International Journal of Intelligent Enterprise (72 papers in press)
A Formal Design in Generation of Array PIN Using Petri Net Model and Implementation for Secure Transactions
by Vaithyasubramanian S, Lalitha D, Christy A
Abstract: Online banking and ATM transaction are being used by many people for it is easy to process and it is also very fast. Being highly customer-oriented, the two keys to any transaction is the users identity and the PIN. Increasing threats and frauds are major concern in the security of banking transaction. Though several measures are being taken, yet there is a necessity for a Mathematical and Contemporary model for transaction security. A novel PIN validation technique for online and ATM operation based on Array Password has been proposed in this paper. For the formal design and generation of Array Password, Petri Net the Mathematical Modeling Languages has been utilized. Due to its feasibility and clarity this scheme can used to improve the security flaws in e-banking and e-commerce. The implementation process, advantage and usability of the proposed method are presented in this paper.
Keywords: ATM – PIN – Transaction - Security – Array Password – Mathematical Modeling – Petri net.
THE IMPACT OF CORPORATE GOVERNANCE ON BANKS EARNINGS MANAGEMENT
by Binh Nguyen T.Thanh, Min-Ru Tsai
Abstract: Loan loss provisions and realized fixed assets gains and losses are useful information for analysts and investors because they indicate a bank's sense of how stable its lending base and assets are. They are also used as forms of earnings management at banks as a higher level of loan loss provisions decrease earnings while a higher level of realized fixed assets gains and losses increase earnings. This study examines how corporate governance mechanisms affect earnings management at 25 publicly traded banks in Taiwan over the period of Jun. 2003 to Jun. 2018. The empirical results show that the discretionary use of loan loss provisions and realized fixed assets gains and losses play an important role in a banks earnings management. In particular, we find that banks of financial holding companies prefer the discretionary use of loan loss provisions in earnings management that is not influenced by the power of CEOs but by the independent board and the board size. Besides, banks that do not belong to financial holding companies prefer the discretionary use of realized fixed assets gains and losses and their earnings performance are affected by the power of CEOs.
Keywords: Earnings management; Banks; Loan loss provision; Corporate governance.
Management accounting insight via a new perspective on the risk Managementcompanies profitability relationship
by Tariq Tawfeeq Yousif Alabdullah
Abstract: The current study aims at introducing a new insight to be added to the previous studies in the literature review in the field of management accounting through creating some new insight as a new contemporary trend to be compared with the previous in the literature review. To be a new research, including new thoughts compared to existing literature, it investigates the link between predictor and predicted variables; independent managers in the board of directors and risk management committee, and their impact on companies profitability represented by management accounting measurements ROE and ROA, and companys profitability represented by market share. The present work utilized the multiple regression method to analyze available data for Jordanian industrial firms that listed in Amman Stock Exchange for the ended year 2017. Unlike prior studies, the present work unexpectedly could find an insignificant link in the relationship between independent managers and companys profitability represented by ROE and market share. Furthermore, risk management committee has a significant relationship with ROE and market share. Therefore, Jordan government with other related parties should take in their consideration formulation of policies for the importance of risk management existence. The originality of this study is the matter of concerned of the previous studies with the effect of different factors on companies profitability remaining somewhat under-researched in developing countries and Jordan in particular. Thus, from developed and developing nations viewpoint, the current research is the first of its kind that solely chose predictor (independent) variables in their relationship with companies profitability represented by market share, where there is no prior work that investigated risk management as a predictor (independent) variable in this link with market share. In this regard, it probably might be said that no other studies especially in developing countries have examined this link particularly from the risk management perspective in its link with companies profitability. This new insight of this relationship created by the current study offers helpful evidence that introduces outstanding value to several parties, for instance scholars, academics, policy makers, government, and other stakeholders.
Keywords: Independent manager; Risk management committee; companies’ profitability; developing countries.
The Peak-to-Average Power Ratio Reduction using hybrid scheme with Companding and Discrete Hartley Transform for Orthogonal Frequency Division Multiplexing System
by Rashmi N, Mrinal Sarvagya
Abstract: Orthogonal frequency division multiplexing is a multicarrier and high data rate system. Increasing data rate through higher modulation techniques increases peak to average power ratio(PAPR) in OFDM systems. In this paper, we propose a novel hybrid scheme, combined with companding and Discrete Hartley Transform (DHT) spread, in order to reduce high PAPR in superposition coded modulated OFDM system. The experimental results demonstrated that hybrid scheme can reduce the PAPR to 1.749dB. The simulation results of proposed technique is compared with Clipping technique, Partial transmit sequence, Selective mapping and original OFDM system. Further computational complexity is reduced by half by applying hybrid scheme.
Keywords: Orthogonal frequency division multiplexing (OFDM); Peak-to-Average Power Ratio (PAPR); Cumulative Complementary Distribution Function (CCDF); Discrete Hartley Transform (DHT); Superposition Coded Modulation (SCM)-OFDM; Modified µ law Companding (MMC).
Text Content Analysis using Semantic Similarity and Keyword Extraction for Automatic File Name Generation
by Janani Balakumar, S. Vijayarani, J. Ilamathi
Abstract: Tremendous growth in internet technology and the advanced developments in the hardware industry has created a new platform which helps the users to download and store huge quantity of information in the form of word documents, PDFs, text files, images, audio files, and so on. Normally, most of these downloaded files whose names are not giving any proper meaning. These file names may be a combination of numbers or numbers with special symbols or only alphabets with no meaning or alphabets with special symbols or combination of these. This may happen continuously, at some later stage, the computer system contains many different categories of files, and the name of the files does not provide proper meaning. This situation has created a problem for the users, if they are searching for particular information or content from these files, it is very difficult for them to get and this process has become tedious and time consuming one. It is very difficult for the users for renaming the file names after reviewing the content of each and every file. The main aim of this paper is to develop a new tool which provides the appropriate, meaningful and accurate file names automatically, after verifying and analyzing the content. This tool also suggests different combinations of filenames which are related to the content exist in the files. There are three important steps are carried out in this research work; in the first step, classification is performed based on file names, to find whether the file name is meaningful or meaningless. To do this task, the file names are compared using a proposed CNO (Character Numeric Other) algorithm. During the second step, it classifies only the meaningless filenames by using the proposed search techniques. In the third step, it performs the keyword extraction and title extraction. In this step, there are two new algorithms KWE (Keyword Extraction) algorithm and AFNG (Automatic File Name Generator) algorithms are proposed to generate the new file names automatically, from this, most appropriate file name is selected by the users.
Keywords: Text Mining; Content Analysis; Automatic File Name Generator; Keyword Extraction; CNO; File Classification; Search; Indexed Search; KWE; AFNG.
Profound Feature Extraction and Classification of Hyperspectral Images Using Deep Learning
by R. Venkatesan Rudhrakoti, S. Prabu
Abstract: A Hyperspectral image provides an assets of information. It is used to tackle diversity of problems that occur in remote sensing the earth. These hyperspectral images are used in various applications such as research in geology, research in global changes, mapping of environment, mapping of wetlands, traffic capability estimation, identification of minerals and plants and profusion estimation, analysis of crops. The persistent issue, recurrent problem in remote sensing is classifying the spectral images, in which each pixels of the spectral image are being aimed to assign a label. In progression of hyperspectral images, classification process is done to identify distinct spectral pixel holding materials specified by user. Many steps are followed in hyper-spectral image classification such as preprocessing, features extraction with dimensionality reduction and classification. The preprocessing is used to reduce the noises using Median filtering with Anisotropic diffusion (AD) approach. Dimensionality Reduction technique is often used to reduce the large volume of data. Discriminative local metric learning approach is applied to reduce the hyper spectral cube image dimension, thus retaining the significant components for further processing. Finally Recurrent Neural Network (RNN) algorithm is implemented to classify the features with improved accuracy. The proposed work outperforms the existing approaches in terms of accuracy and error rate measurements.
Keywords: Hyper spectral imaging; Diffusion approach; Classification; Features extraction; Neural networks; Class labels.
A Theoretical Study on Managing the Intangible component of the Knowledge base of an Organization
by Srinivas Kolachina, K. Bhavana Raj
Abstract: Any organization employing human resources must be very focused and strategic in preserving the intangible component, called, knowledge of the intellectual sources with the best care. Inevitably this can be one of the significant responsibilities for Human Resource professionals. Knowledge Management originates from the objective of creating support, transferring and applying knowledge in the organization. Acquiring knowledge sources, identifying their core expertise and deploying them into a well- structured knowledge management system makes an organization to have an innovative and potential intellectual database built within. The theoretical study aims at exploring various dynamics of knowledge management vide elucidating the meaning and significance, thereby understanding the pros and cons of managing the same. The Skill web and Peer to Peer Learning are two crucial aspects to be borne in mind for effective and efficient implementation of Knowledge Management. The Success story of Siemens value adds the significance of managing the intangible component of intellectual resources.
Keywords: Intellect; Knowledge; Manage; Learning; Resource.
A PRIVATIZED APPROACH IN ENHANCED SPAM FILTERING TECHNIQUES USING TSAS OVER CLOUD NETWORKS
by P. Mano Paul, I. Diana Jeba Jingle
Abstract: Major problem over cloud networks is the effect of malicious code that protrudes its own activity without intend of network user in resource sharing. One such activity is the spam-filtering techniques which assumes the data with training and testing sets and also rely on fundamental classification through distribution. A privatised spam filtering approach is a classic problem which automatically recognises user context and incoming mail information relevance. To filter mail contents learning based methods, probabilistic based method trying to improve their accuracy but they cannot attain an improvement in identifying suspicious contents and also in segregating legitimate mail entries. Here a novel representation of structured abstraction scheme (SAS) used to generate abstraction in e-mail process using HTML tag content in email and its algorithm for filtering such process of spam filtering is depicted. In this SAS methodology near duplicate matching process with HTML tag
ordering will be processed and newly assigned position ordering were deliberated. The experimental setup shows that there will be a great improvement while filtering spam in accuracy of e-mail content while sharing in cloud networks
Keywords: spam detection; abstraction scheme; spam ontology; privatised e-mail spam filtering; cloud networks.
Optimal Power Flow with Renewable Energy resources using Static VAR Compensator and Grey-Wolf Optimization
by M. Rambabu, Nagesh Kumar G.V, Sobhan P.V.S.
Abstract: The technical and economic performance of electrical power system networks is being improved by interconnecting renewable energy sources like solar, wind to the conventional power systems. In this paper, a Composite Bus utilization index is proposed for the placing of static VAR compensator (SVC) and further sized using Grey wolf algorithm(GWO) for reduction of fuel cost with valve-point effect, real power losses, and carbon emissions in a power system with renewable energy sources. Composite Bus utilization index (CBUI) is a blend of L-index and Vi /Vo index and determines the weak bus of the modern electrical system. The deliverable power of wind and solar generation is determined by the Weibull probability density function (PDF) and Lognormal PDF and interconnected to the power system network. The SVC is placed at the maximum value of CBUI,and the tuning of SVC at the proposed location is done with Grey Wolf algorithm. This methodology is applied to IEEE 57 bus systems to check the effectiveness of the approach under various loading conditions
Keywords: Static VAR Compensator; Optimal Reallocation; Grey wolf algorithm; Lognormal; Weibull PDF; carbon emission; Valve point effect.
Identifying Relation, Problem, and IT Approach of Design and Planning in Engineer-To-Order (ETO)
by Pandu Dwi Luhur Pambudi, Mahendrawathi ER
Abstract: The primary driver of the complexity of planning in an engineer-to-order (ETO) project is the uncertainty of design deep into the engineering and production process. There are no studies that explicitly identify and analyze systematic literature review (SLR) results using a content analysis approach on the topics related the relation between design and planning; the problems appeared during the design and planning phase, and the IT approach in ETO company. This paper presented the systematic literature review results using a content analysis on a comprehensively and systematically generated survey samples. The results confirmed if the design has strongly associated with planning. The dynamic and deterministic problems widely discussed in the planning problems. On the other side, uncertainty and variability become the broad topics discussed in the design problem. The findings showed that the IT approach using ERP and CAD were the most attractive approach discussed by several previous studies in the field of ETO Company.
Keywords: engineer-to-order (ETO); Design; Planning; IT Approach; Systematic Literature Review.
An Efficient Diabetes Prediction System for Better
by Satyanarayana Murthy T
Abstract: An unreasonable increase of glucose in blood results in Diabetes. In recent times this problem is often seen in many people around the world. Having an efficient medical diagnosis of diabetic prevention is essential. So in this context, health care professionals have come up with different solutions, but none of them have taken shape. Considering these facts we have proposed an integrated diabetic prediction system with the inclusions of Un-supervised k-means clustering and Navie Bayes classification. In this context, random attribute selection is used as the initial centroid selection method for k-means Clustering. Significant work is compared with traditional classification algorithms in terms of accuracy along with additional performance parameters like sensitivity, specificity, precision, and F-measure and as a result, it is determined that the proposed algorithm is achieving 99.42%, which is higher than any other recently proposed classification technique.
Keywords: Diabetes Mellitus; Metabolic; Knowledgebase DSS; PIMA Indian Heritage; WEKA.
Analysis of Error Rate for Various Attributes to obtain the Optimal Decision Tree
by K. Maheswari, S. Ramkumar
Abstract: The competitive and computational intelligence is required to increase the gross profit of the product in a market. The classification algorithm rpart is applied on retail market data set. The regression rpart decision tree algorithm is implemented with principal component analysis to impute data in the missing part of the dataset. The objective is to obtain an optimal tree by analyzing cross validation error, standard deviation error, and number of splits and relative error of various attributes. The results of various attributes by anova method are compared to choose the best optimal tree. The tree with minimum error rate is considered for the optimal tree.
Keywords: Decision Tree; Error rate; Data mining and Pruning.
Technological Innovation: Classification Model and Future Research Agenda
by Alaa M. Ubaid, Refaat Hassan Abdel-Razek
Abstract: Previous innovation classification models suffer from duplications, gaps, and overlaps. A comprehensive innovation classification model was proposed in this paper. The proposed model present and explain the concept of multidimensional innovations, fill the gaps in the previous classification models, integrate the classical and the modern innovations types, explain the relationships between innovations types, and help to propose future research directions. The overlaps between innovations types were identified and unified. For classical innovations' types, four-dimensional innovations levels analyzed and presented in the model. The analysis showed that the higher innovations levels stem from the combination of the lower innovations levels with decreased numbers of innovations as we move to the higher innovations levels. The proposed model incorporates innovations types that have been ignored in the previous models, which maximize the benefits of this model. SLR methodology adopted in this research reveals the identification of many future research directions.
Keywords: innovation; types; classification; typology; sustainability; eco; resources-constrained.
Information Security Protection for eHealth records using Temporal Hash Signature
by Charanya R
Abstract: Patient Health record information management becomes an important and challenging task through different practices are followed by hospitals. Also, the risks associated with securing the data from cyber-attacks and data breaches become inevitable. Ransomware is the biggest cyber-attack in the history of National Health Service (NHS) which has affected nearly 100 countries worldwide in 2017. In the healthcare system, loss of sensitive data leads to embarrassment whereas loss of integrity leads to loss of the patients life. Though many technical solutions exist to store the Electronic Health Record (EHR) information in a secure way, still it is not sufficient to satisfy the security requirements such as clear attributes for role-based access, common regulations that protect patients privacy and specific guidelines to control the data. This paper provides a brief discussion on existing security mechanisms with a proposal based on the temporal shadow in the cloud. The integrity of the patients document is modeled with linked records and verified by a temporal signature.
Keywords: eHealth; EHR; Temporal Hash Signature; Binary merkle tree.
Ensuring prompt cloud service provider based on service level agreement (SLA) using Fuzzy Logics and Decision Support System
by Karthikeyan P, E. Sathiyamoorthy
Abstract: Cloud services are subscribed by the Cloud service Users (CSU) from specific Cloud Service Provider (CSP). Several Cloud Service Providers may offer the same as well as different services. Hence various factors have to be considered while selecting a CSP which offers the same type of services. An Intelligent Third Party (ITP) helps the CSU in choosing a best suited CSP. Requirements of the CSU are captured and processed using Fuzzy Logics. These are matched with service offerings of the CSPs using a multi criteria decision making process called the Analytic Hierarchy process (AHP). Using this Decision Support System, the ITP suggests the best suited CSP among the registered CSPs to the CSU. A negotiation process follows where the CSU can make their choice in choosing the suggested CSPs. A partial SLA is generated between the CSU and chosen CSP defining the various services selected, attributes provided by the CSP, other requirements of CSU and violation details.
Keywords: Cloud service provider; service level agreement; Fuzzy logic; Decision support system\r\n\r\n.
Analysis of dependence of grade point average over psychological factors incorporating advanced data mining
by Leena Khanna, Shailendra Narayan Singh, Mansaf Alam, Ritu Kumar
Abstract: Academic performance of any individual is dependent upon numerous aspects regarding the day to day life of the individual under consideration. Academic performance is measured in terms of the grade point average or GPA as it is called. Grade point average is dependent not only on the faculty but also on various cognitive and non-cognitive factors. The non-cognitive or the psychological parameters includes factors like study habits, social anxiety, extraversion and allied. In this study, a detail analysis of numerous psychological factors that can impact the grade point is studied. Bases on the various psychological factors studied, the performance of an individual is classified and in forthcoming examination can be forecasted.
Keywords: Forecasting; Grade Point Average; Achievement Motivation Scale; Study Habits; extraversion; conscientiousness; social anxiety; emotional competence; self-efficacy for children.
Feature Selection for Stock Price Prediction: A Critical Review
by Binita Kumari, Srikanta Patnaik, Tripti Swarnkar
Abstract: Stock price prediction has drawn huge attention due to its impact on economic stability. Accurate stock price prediction is highly essential to reduce the risk associated with it so as to decide good investment strategies. There are various factors influencing the prediction of stock indices namely gross margin, exchange rate, inflation rate, relative index and so on. Feature selection plays a vital role in effective and accurate prediction of stock indices. This paper aims to provide a clear review of widely used features affecting the stock price fluctuations, feature selection techniques and prediction models from the recent literature.The study also highlights the future directions in this domain focusing the enhancement of the prediction performance.
Keywords: features; feature selection; stock price prediction.
FUSION OF MULTIMODAL BIOMETRIC AUTHENTICATION USING GRADIENT PYRAMID , PCA AND DWT
by Devi R, Sujatha P Dr
Abstract: The current development in the information technology requires executing authentication and security resources available for the techniques in authorization. The authentication based on the biometric, which may overcome all other techniques. By using the , physiological or behavioral traits , the biometric techniques can improve the authenticity or authorization for a human being. The users such as unauthorized persons cannot able to access the resources. The biometric trait processes for the multimodal biometric system can process its information separately. The fusion scheme combines the processed information. The proposed model consists of identification method with the Multimodal biometric process, which is based on the two parameters such as the Iris with fingerprint. These parameters focused on the classification on support vector machine (SVM) makes fusion with the gradient pyramid (GP). Comparison made for the proposed method with discrete wavelet transformation (DWT) with the principle component analysis (PCA).sift. The feature extraction process uses the matrices composed of gray level co-occurance matrix. The individual accuracy for the authentication process undergoes the step of comparison with the iris fused with the standard procedure and accuracy related with fingerprint. A result indicates the fusion biometric images can provide the better results in the compared with the individual images in the biometric pattern.
Keywords: biometric authentication; GP; SVM; DWT; PCA; iris and fingerprint; fusion.
Improving the Competitiveness of Traditional Mar-kets in Martapura Riverside, Banjarmasin, South Kalimantan for Raising the Local Economy
by Tinik Sugiati, Zakhyadi Ariffin, Dian Masita Dewi, Freddy Zul Pribadi
Abstract: Any regions economic growth and development is affected by a number of system activi-ties and one such activity is trade. Progress in the economic filed can be measured by the frequency of activity in the trade sector. Trading needs sufficient facilities such as infra-structure, market etc. Traditional markets have an important role in improving the local economy. However, the existence of modern market imposes a threat to the traditional market development. To survive in competition with the modern market, traditional market needs to focus on customer need. This paper focuses on obtaining information about priori-ties to improve the survivability of traditional markets in competition. The object for this study is Ujung Murung Market which is one of the traditional markets in the Martapura riverside, Banjarmasin City, South Kalimantan. Respondents are categorized as seller and buyer in the traditional market and servants Civil of Management Market Office. Data are analyzed by using AHP (Analytical Hierarchy Process) with PriEst Software. The novelty of this study is consideration of customer value as sources of competitive advantage in tradi-tional market. The data analysis shows that traditional market in Martapura riverside has competition-based customer value perspective such as: function value, emotional value, social value, seller service value, convenience value, added value, and reasonableness of the price. This study shows that the strategy of considering perspective of customers signifi-cantly improve traditional market competitiveness.
Keywords: Competitive advantage; customer value; traditional markets; Analytical Hierarchy Process; function value; emotional value; social value; seller service value; convenience value; added value; reasonableness; traditional markets; market competitiveness; Merchants and prod-ucts; public transportation.
Determining the Firm Innovativeness by Organizational Innovation and Knowledge Capacity in ASEAN Pharmaceutical Industry: A Comparative study with Mediating Role of Innovation Capability
by Thanaporn Sriyakul, Kittisak Jermsittiparsert, Jutamat Sutduean, Siridech Kumsuprom
Abstract: The study presents the phenomenon of firm innovativeness, organizational innovation, and knowledge capacity and innovation capability in pharmaceutical firms of ASEAN region. The research framework and links of variables are supported by resource based view theory that innovation capabilities of firms assist to gain competitive advantages and enhance performance. The purpose of the paper is to determine the influence of organizational innovation and knowledge capacity on innovation capability, further innovation capability influences the firm innovativeness. The study determines the mediating role of innovative capability between organizational innovation and firm innovativeness, mediating role of innovation capability between knowledge capacity and firm innovativeness. The study obtained the data from two different samples of ASEAN region and comparative analysis and results have been presented. SMART-PLS was used to determine the relationship and testing the direct and in-direct hypothesis of the study. Measurement model and structural equation modeling technique was utilized to determine the relationship between variables of proposed research framework. The results show that innovation capability influenced positively by organizational innovation and knowledge capacity, similarly innovation capability influence firm innovativeness.
Keywords: Organizational Innovation; Knowledge Capacity; Innovation Capability; Firm Innovativenessrnrn.
Movable barcode scanning system using IOT smart glasstechnology
by AKASH AWASTHI, Deeplakshmi P, NAGARAJ P, Madhu Vamsi Amarakota
Abstract: Nowadays everything is getting digitalized in India according to
the Digital India programme. Lot of manual work has been replaced by
Digital and IoT-based technologies. Now, the trend of using smart glasses
for managing the warehouses is increasing, these glasses need manual
interaction, which may lead to manual error. This study can develop a
technology to reduce the manual interaction that further reduces theft,
manual errors and it will be helpful for an organization to save the
cost, which has been spent on workers every month. So, there exists a
need for a technology, which can make the inventory management in
the warehouse totally digitalized and automatic. Considering the need for
industrial automation, the present study provides an idea of movable barcode
scanning system to measure the inventories and send a notification to supplier
and the company employee for order placement as well as display currently
scanned inventories on web page hosted by our system. It can make the
industry advanced, fast and digitalized especially in warehouse management.
Keywords: Barcode Scanning; Automation; smart glasses; manual interaction; Inventory Management.
A Critical Analysis of the Earnings Management Strategies in Politically Influenced Firms
by Muhammad Sadiq, Zaleha Othman, Ooi Chee Keong
Abstract: The purpose of this paper is to investigate whether politically influenced firms employ income-decreasing accrual-based earnings management strategy to report less taxable income. The current study also investigates whether politically influenced firms substitute one of the earnings management strategies with the other. The study used a sample of non-financial listed firms in Pakistan over the period of 20072016. The results envisaged that politically influenced firms manipulate earnings downwards with the objective to report less taxable income, pursuant to which the regulators must keep political factors in mind during regulatory reforms. Moreover, this study shows that politically influenced firms substitute one earnings management strategy with the other. This study contributes to the field of earnings management where it integrates Agency Theory with Political Economy Theory. Apart from that, this study provides deep insight to policy makers who are interested in improving corporate governance in transnational economies.
Keywords: Political influences; accruals-based earnings management; real earnings management; corporate governance.
A Modified Fuzzy C Means Approach for segmenting the input Flood images captured by Synthetic Aperture Radar
by NATTESHAN N V S, SURESHKUMAR NAGARAJAN
Abstract: Image segmentation is a process of separating a homogenous area into a heterogeneous area. There are lots of interesting applications of segmentation in the areas of flooding, change detection in Synthetic aperture radar images. In this work the Fuzzy C means algorithm is utilized for segmenting the flooded areas in the given input image based on the details of the intensity pixels in the given input images. But there is a problem of speckle noise occurring in the images due to backscattered echo from earth surface. Hence a Fuzzy Discontinuity adaptive weight based non-local means filtering is being used to eliminate the speckle noise. In the fuzzy c means segmentation algorithm a modification is proposed which is done as two steps namely the Quantization and aggregation. These two steps alone are modification which utilizes the mean of the pixels rather than segmenting each pixel by pixel pattern. So, this modified FCM performs better and there is a reduction in running time of the algorithm in performing the segmentation. One of the main drawbacks in the Fuzzy C means conventional algorithm is that the time taken for the algorithm to converge will be more. Hence a modified fuzzy C Means algorithm is required in order to reduce the convergence rate of the algorithm. There is various application of clustering algorithms in various domains of image processing. This research work particularly focuses on the application of the Fuzzy C Means clustering algorithm for segmenting the flood occurred regions and further processing of the flood occurred regions will be carried out.
Keywords: Fuzzy C means; de-speckling; Clustering; segmentation; quantization; aggregation.
How strategic intelligence impact marketing strategy effectiveness in SMEs context: using structural equation modeling
by Mona Jami Pour, Fateme Ebrahimi Delavar, Atefe Khaleghi
Abstract: Despite the increasing investment in marketing activities, the many business expectations have not been satisfied yet. How to invest in marketing strategies depends on the capabilities and intelligence of marketing managers in the analysis of the conditions and one of the key intelligence is strategic intelligence. Strategic intelligence pertains to provision the critical information to achieve competitive advantage and is an essential part of the competition in today's economy. In spite of the important strategic intelligence of marketing managers, few studies empirically investigated the impact of it on marketing effectiveness. Therefore, the main aim of this study is to evaluate empirically the relationship between strategic intelligence and marketing strategy effectiveness in small and medium-sized enterprises (SME) context. Data from 186 SMEs provide empirical support for the critical role of strategic intelligence on marketing strategy effectiveness. The study also found that all of the strategic intelligence components, including foresight, systematic thinking, partnering and motivating and empowering with the exception of the visioning component, had a positive and significant effect on marketing strategy effectiveness.
Keywords: Strategic intelligence; marketing strategy effectiveness; SME; structural equation modeling.
A modified un-realization approach for effective data perturbation
by Gopalan N.P, Satyanarayana Murthy T
Abstract: In recent times data has been evolving from multiple sources like
social media, face book, twitter etc. in large volumes and acquiring in multiple
forms.These data have multi-dimensional sensitive features from different
resources entail that privacy preserving is a significant research issue. In this
context, un-realization algorithms have evolved to hide the collected data with
the addition of noise to them to generate a distorted dataset while attempting
privacy preservation. In this paper, a novel modified un-realization algorithm has
been proposed to generate a distorted dataset by removing duplicate elements in
the dataset decreasing computational time of decision tree construction process.
These techniques add noise to the original data and generate a distorted dataset
by using a un-realization algorithm. This novel approach converts the original
sample data sets into different perturbed data sets by inducing the noise through
set theory. It experimentally produces better results than un-realization algorithm
in terms of CPU execution time and space complexity.
Keywords: privacy; un-realization; distortion; perturb.
Sustainable Development Goals through Public Sector Social Responsibility of Indian Energy Firms A Qualitative Analysis
by Parul Rishi, Suchitra Pandey
Abstract: Public sectors have been regulated by Department of Public Enterprises (DPE) CSR guidelines since 2010, and thus have the experience and expertise of formally carrying out Corporate Social Responsibility (CSR). CSR activities of these organizations are under constant monitoring by both the DPE-CSR guidelines and the CSR law. Understanding the potential of these organizations to contribute to CSR, the government aims to achieve Sustainable Development Goals (SDGs) through CSR. Consequently, the country has linked the SDGs with its national development goals and has set ambitious plans for implementation of these SDGs. This study analyzes and documents the CSR practices of the Indian public sectors concerning the CSR law and the SDGs for sustainable growth in a holistic manner for the people and the planet. Further, the interviews from the key functionaries have helped understand the policy-level changes that need to be introduced for successful CSR implementation and achievement of the goals.
Keywords: Corporate Social Responsibility(CSR); Sustainable Development Goals(SDG); Department of Public Enterprises(DPE),Schedule VII,Environment.
Special Issue on: ICACB'18 Advanced Intelligent and Communication Systems
Product recommendation system using optimal switching hybrid algorithm
by P. Bhuvaneshwari, A. Nagaraja Rao
Abstract: The recommendation system works as a heart in the business strategy of e-commerce. By employing various techniques and methods it recommends the desirable items to the user. Recent studies suggest by applying proper methods the accuracy of the recommendation can be improved. Traditional techniques like collaborative filtering face the cold start problem, so in this paper, we propose an optimal switching hybrid approach (OSHA) to overcome the issue. Here, K-nearest neighbour algorithm is used to predict the similar kind of users and the experimental results show that the proposed algorithm performs better than the standalone technique.
Keywords: e-commerce; collaborative filtering; cold start problem; optimal switching hybrid approach; OSHA; K-nearest neighbour.
Levy distribution in scheduling the WSN to enhance its lifespan
by Nagarathna Pattari, Manjula R
Abstract: Recent advancement in Nanotechnologies, communication technologies, hardware, software and low-cost mass production have given rise to enormous applications of Wireless Sensor Networks (WSNs) to be part and partial of our day to day lives. Right from home security, environmental monitoring, industrial manufacturing and monitoring and building latest smart cities, hardly there is any field left that does not use sensors. Either deployed randomly or systematically a WSN collects information from its surroundings within its sensing range, it may process the information or just pass on to other ends of the network for further processing. They communicate information collected through a wireless communication network to the sink node where all the information collected from all sensors nodes get collected. Some nodes in the network will have the ability to preprocess the data before transmission. WSN are widely varying characteristics and applications, almost all the sensors collect the information, preprocess, and transmit. A Reliable WSN must serve its purpose for long-duration since the sensor nodes are very tiny in size and powered by small batteries mounted onto them. Recharging or changing batteries may be next to impossible thing in some applications. For example, charging batteries of sensor nodes of WSN working in battlefields, enemy territories, and a volcano erupted areas is often impractical. Therefore energy constraint in WSN is the very serious issue in WSN as well as in research. In this paper, we present a mechanism to schedule WSN sensor nodes such that improves its lifespan for longer duration of time. We divide the available sensors to $k$ Disjoint Set Covers (DSCs) by applying a hybrid evolutionary algorithm which uses Levy distribution.
Keywords: Wireless Sensor Network; Disjoint Cover Set; hybrid evolutionary algorithm.
An Incremental Approach for Hierarchical Community Mining in Evolving Social Graphs
by Keshab Nath, Swarup Roy, Sukumar Nandi
Abstract: Community members which are highly connected with each other inside a community tends to create sub-communities, commonly termed as intrinsic or hierarchical communities. Finding intrinsic communities help us to reach out specific user needs, understanding the network dynamics and unveiling the functional and hidden aspects in the network, which is difficult without unveiling intra and inter-community all kinds of relationship. With the passage of time, members of a community may acquire different interests, leads to movement of members within different communities. Frequent changes in the relationship of members towards a community make the task of community
detection even more challenging. In this work, we propose a new community detection method, embedded communities from evolving networks (ECEnet), for handling intrinsic communities in evolving networks. We adopt a density variation concept to detect the intrinsic communities in growing networks. We use a new membership function to measure the contiguity of a member towards a community. We use both synthetic and real-world social networks for our experimentation. Experimental results reveal that ECEnet is successful in detecting intrinsic or hierarchical communities in a dynamic scenario.
Keywords: intrinsic communities; hierarchical communities; evolving networks; dynamic communities; incremental clustering; embedded cluster; density variation.
OBJECT CATEGORIZATION AND FLAME APPREHENSION
by Santhosh Kumar B, Velliangiri S, Ajayan J
Abstract: Object categorization is a customary errand of PC observation which includes deciding if a picture contains some particular class of question. The thought is firmly related with acknowledgment, arrangement, and misgiving. There are numerous techniques to speak to a division of articles, from shape investigation, or neighbourhood inscriptions, for example, SIFT, and so forth. The possible point is to extricate semantics from video to be utilized as a part of larger amount action examination undertakings. Arranging the kind of an uncovered video question is a significant advance in accomplishing this objective. Nonetheless, late research has demonstrated that question groups and their areas in pictures can be found in a freely way too. Our contemporary question arrangement calculation influences utilization of the closer view pixel to delineate to every individual associated area to make a blueprint for the protest. Customarily fire sensors which sense the nearness of specific particles created by smoke and fire by photometry were utilized to recognize fire. Normal sensors mean to detect particles, accordingly, an essential shortcoming of point locators is that they are separate limited and decay in open spaces. In this paper we depict the computational models utilized in our way to deal with achieve the objectives indicated previously
Keywords: Fire identification; FlameColor; Contour Pattern; Object categorization.
Efficient Wideband Filter Using Closed Loop Resonator with coupling lines
by Oudaya Coumar, S. Tamilselvan
Abstract: This paper is about a wideband filter using closed loop resonator with inter-digital coupling lines. The square resonator is used as closed loop structure integrated with inter-digital coupling on both sides which plays a major key role in this filter design. The proposed wideband filter can be employed in UWB receivers since the operating band of UWB is matching with operating bandwidth of this filter. Design and EM Simulation of the UWB filters characteristics are discussed in this work. The proposed UWB filter produces tremendous bandwidth ranges from 2.3 GHz to 8 GHz. The filter evaluation parameters like return loss, insertion loss, phase and group delay are obtained and their responses are analysed. The complete size measurement of the filter is achieved to be 39mm
Keywords: Insertion Loss (IL); Return Loss (RL); square resonator; and ultra-wideband filter (UWB).
AN ANALYSIS OF COMMITMENT AMONG COLLEGE TEACHERS
by Lovelin Auguskani P, Sreedevi V, Jerlin Priya
Abstract: The study An Analysis of Commitment among College Teachers. was carried out Nagercoil at Kanyakumari District. The study helps to understand the commitment level of college teachers. The study was conducted with a sample size of 158 teaching staff, data has been collected through questionnaire. This research paper is through analyzed with primary data which was collected conveyance sampling techniques.This study investigated the commitment among college teachers. The findings from the analysis indicated that the level of organizational commitment is high among the college teachers in Nagercoil at Kanyakumari District. One Way analysis is used to find Variance between the category of appointment and the three commitments level (affective, continuance, and normative) and find variance between the designation and commitment. Majority of government aided respondents are having high level of affective, and normative commitment and self finance respondents having high level of continuance commitment. Assistant professors are having high level of affective, and continuance commitments, Associate Professors are having high level of normative commitment. In order to maintain this level the management should take various initiatives which will motivate the faculty to remain committed towards their job and responsibilities.
Keywords: Affective; Continuance; Normative; Education; Teachers.
LIFI Based Smart Systems for Industrial Monitoring
by Prabakaran N., Naresh K., Kannadasan Rajendran
Abstract: Light Fidelity (Li-Fi) is an unfolding technology which can be used to transfer data through light. It is a complete transformation to the world of wireless data transfer. Harald Haas from the University of Edinburgh, United Kingdom termed and introduced Light Fidelity to world through the global talk show in which he demonstrated of a Li-Fi prototype at the TED Global conference in Edinburgh on 12th July 2011. Challenging the pre-existing data transfer model namely the Wireless Fidelity (Wi-Fi) on various parameters such as speed, safety, reliability eco-friendliness and efficiency. The light emitting diode in a Li-Fi system is the source of data transfer utilizing visible light as medium of communication. This can provide greater download capacity in comparison to the existing wired or wireless networks due to higher bandwidth of light. With such high potential every electronic day to day use commodity that has role of light over it can be thought of to be used as an internet accesses point. Since it can't penetrate through walls they have short range but are highly secure in the confinement of the surrounding in comparison to Wi-Fi and overcome the radio frequency bandwidth availability issues in the near future.
Keywords: Bandwidth Light emitting diode:rn Light Fidelity; Visible light Communication; Wireless Fidelity;.
Comparison of Automated Leaf Recognition Techniques
by Mahmudul Hassan, Arnab Kumar Maji
Abstract: Plant plays an important role in different ways in human life and atmosphere. There are large numbers of plant species in the world. Plant species plays a vital role in many domains such as preventing some the diseases, farming, environment, discovery of new drug and other related areas. Recognition of plant species without expert understanding is a huge task. There has been great demand for applying automatic computer vision technologies to increase botanical knowledge. Using leaf features and traits, the classification and identification of plant is carried out. Leaf features like shape, texture and venation are the features most frequently used to differentiate the plant species. Different methodologies are there to extract the feature and to classify the leaf images using classifier. In this paper we are going to discuss on different leaf recognition approaches along with feature extraction methods and their performances.
Keywords: ANN(Articial Neural Network); CNN(Convolution Neural Network); Deep learning; PNN(Probabilistic Neural Network); SVM(Support Vector Machine).
A Detail Study on Context-Aware Architectures in Internet of Things
by Deeba Kanmani, Saravanaguru RA.K
Abstract: Internet of things is used to get the data around the world at your fingertip. As we move towards IoT the role of sensors has become vital. These sensors generate a vast amount of data. Sensors are used to sense and collects parallel information from the given set. We propose Context-aware for an Internet of things architectures which computerize the task. In this paper, we will discuss about the architecture of context-aware, IoT and context-aware reasoning. The principle objective of this paper is to audit existing architecture identified with context-aware and IoT and to make the comparative analysis table. The principle point is to enable the clients to present the issues and our proposed design enhances and delivers important information.
Keywords: Context aware; Internet of Things; Middleware; Context Reasoning; Nature Inspired Algorithm; Middleware architecture.
ENHANCING SECURITY BY TWO WAY DECRYPTION OF MESSAGE PASSING OF EMR IN PUBLIC CLOUD
by PRATHAP R, MOHANASUNDARAM R
Abstract: Encryption is one of the most critical and mandatory technique to provide security in outsourced data. Message passing is the most unsecure place of transfer of dangerous information's, and this message passing is made the end to end encryption to avoid a centralized security agent to access the data. Existing methods of encryption only provide end to end encryption which is not feasible for certain situations like implementing authentication. When the end to end encryption is made, the messages are always not known to the central authentication agent like CBI, in this paper, we provide a two side decryption algorithm that can be decrypted by two entities (one receiver and the other is the central authentication agent). Thus improving the message passing security by allowing the centralized authentication agent to read the transferring words. We implemented this two-way decryption in trip database dataset, and the experiment results prove that our proposed algorithm improves the security of message passing of Electronic Medical Records in public cloud while comparing with existing encryption algorithms.
Keywords: Cloud; EMR; Encryption; Decryption; Authentication; Authorization.
Changed Detection of Landsat 8 Imagery using Object Based Image Analysis with Particle Swarm Optimization
by Amitabha Nath, Amos Bortiew, Goutam Saha
Abstract: This paper addresses the problem of classification of hyperspectral remote sensing image and detection of any changes in the land use pattern using it. Traditional pixel based classification approaches often fail to achieve acceptable accuracy in classifying Landsat images because of its complexity. Therefore, present work aims to apply object based-image analysis (OBIA), which is a concept that combines segmentation and classification together into one unit. We propose a hybrid OBIA architecture, augmented with particle swarm optimisation (PSO) technique to fine tune different hyperparameters involved with it. We present its success on a classification problem where two sets of landsat-8 images captured in the year 2016 and 2017 are considered as input and OBIA is applied for classifying the images into four major land use classes and detect any changes in these classes over the period of time. The results are then compared with best pixel based classification approach known as random forest (RF) classifier to determine its effectiveness in classification of hyperspectral images. Statistical measures like precision, overall accuracy and kappa coefficient are used as a parameter for comparison.
Keywords: Landsat 8 image; RF; object based-image analysis; OBIA; particle swarm optimisation; PSO; changed detection; accuracy assessment.
An Analytical Hierarchical Process based Weighted Assessment of factors contributing Precipitation
by Vaishnavi Balaji, J. Karthikeyan, Kiran Yarrakula
Abstract: The analytical hierarchical process is a prioritising algorithm used in the field of multi-criteria decision making system. AHP has a special capability to handle intangible criteria, this exclusive nature strengthened its popularity. In this work, AHP is exercised to prioritise parameters that contribute to precipitation. Precipitation is any form of water that reaches the earth surface from the atmosphere such as rain, dew, snow, etc. Recent researches consider precipitation as one of the crucial phenomena of climate change and lots of modelling techniques are proposed to predict precipitation using varied parameters. The significance of the study is to address minor fallout of AHP in rank reversal and uncertainty in ranking the given parameters, by attempting to prioritise six basic climatic parameters such as maximum temperature, wind velocity, relative humidity, solar radiation and elevation, which are considered to contribute precipitation.
Keywords: analytical hierarchical processing; AHP; precipitation; climatic factors affecting precipitation; multi-criteria decision making algorithm.
A Hybrid Medical Image Coding Based on Block Truncation Coding and Residual Vector Quantization
by P. Chitra, M. Mary Shanthi Rani
Abstract: The advancement of medical field has witnessed tremendous growth with state of the art imaging technologies for accurate diagnosis, which in turn demands efficient storage of medical images. Further enhance the image quality RVQ is implemented in the proposed method. The proposed work aims at developing an effective algorithm for compressing medical images exploiting the advantages of Block Truncation coding(BTC) and Residual Vector Quantization(RVQ). The advantage of the Block Truncation Coding (BTC) is twofold: 1. It is simple to implement and 2. Involves less computational complexity. RVQ is used to enhance the quality further. In the proposed method, the input image is compressed using BTC in the first phase. The residual error out of first phase is subjected to RVQ in the second phase. The novel feature of the proposed method is the adaptive procedure of RVQ based on the variance of residual vectors. High variant residual vectors are subject to vector quantization and low variant vectors to scalar quantization respectively. Furthermore, the residual values are normalized to positive values, so as to preserve their sign, before quantization. Experimental results show the superior performance of the proposed method in terms of compression metrics.
Keywords: Block Truncation Coding; Residual Vector Quantization; Image Compression.
Near-Zero Computing using NCFET for IoT Applications
by Kishore Sanapala, Satyanarayana S.V.V, Sakthivel R
Abstract: The Internet of Things (IoT) is an emerging application area which is going to become one of the leading electronic hubs in the semiconductor industry. The energy consumption of the devices or circuits built on the IoTs is becoming a significant concern with the Complementary Metal Oxide Semiconductor (CMOS) technology scaling. In the recent times, to reduce energy consumption, supply voltage scaling has proved to be an effective technique with near-threshold/subthreshold computations depicting the endpoint of voltage scaling. This paper discusses how the Near-Zero Computing (NZC) is achieved by scaling the supply voltage (VDD) beyond the subthreshold regime using the Negative Capacitance FET (NCFET) to enable IoT with beyond CMOS features. After characterizing the NCFET for near zero operation, the basic computational circuits: logic gates and 1-bitfull adder circuit are designed using NCFET at near-zero VDD of 0.1V. The circuits were simulated using Intel-45nm technology. Performance parameters such as power, delay, energy, and Energy-Delay Product (EDP) are compared with the CMOS counterparts. From the comparisons, the NCFET logic designs have achieved significant improvements than CMOS designs and is found that the NCFET logic results in more than 54%, 68%, 85%, and 95% savings in power, delay, energy, and EDP respectively for the design of conventional full adder circuit.
Keywords: CMOS; Energy; IoT; NCFET; NZC.
A Key-Escrow Free Identity-Based Signature Scheme Without Requirement of a Secure Channel in the Private Key Issuance Phase
by Subhas Chandra Sahana, Bubu Bhuyan
Abstract: Identity-Based Cryptosystem (IBC) provides us the simplest key management procedures over traditional Public Key Cryptosystem (PKC) as it eliminates the need for certificates of PKC. Hence, no certificate management activities are involved in IBC. However, there are two major drawbacks with the identity-based cryptosystem. One is the key-escrow problem and the other one is the necessity of a channel which is secure for the transmission of the private key, generated by a trusted center called Key Generation Center (KGC). In this work, we propose an identity-based signature scheme, fitted in an existing established variant IBC model. The proposed scheme avoids the necessity of the secure channel as well as it is key-escrow free. The proposed scheme is constructed using bilinear pairings and based on the blinding-binding technique.
Keywords: identity-based cryptosystem; digital signature; key escrow problem;
bilinear pairings; blinding-binding technique; key generation center.
Special Issue on: ERPBSS 2018 Shifting Dynamics in Business
Supply Chain Transparency, Ethical Sourcing, and Synthetic Diamond Alternatives: Exploring the Perspectives of Diamond Retailers
by Meike Schulte, Cody Paris
Abstract: Supply chain transparency is central to sustainable business operations, and consumers are more proactively seeking out socially responsible goods and services. At the same time, the diamond industry has traditionally been opaque. The perception of blood diamonds continues to be a challenge to the industry. The purpose of this paper is to explore the importance and perspectives of supply chain transparency of diamond retailers in the UAE and their perceptions of the importance of transparency and ethical sourcing for consumer diamond purchasing decisions. The research findings suggest that retailers currently perceive the consumers to be indifferent or unaware of the complexity of transparency in the diamond supply chain. However, some consumers did inquire about the origin. Additionally, as they are at the end of the supply chain retailers do not have the means to guarantee that diamonds are ethically sourced.
Keywords: Diamond Industry; Conflict Diamonds; Synthetic Diamonds; Provenance; Sourcing Conditions; Ethical Sourcing; Supply Chain Transparency; Diamond Jewelry Retailers.
SAUDIS PERCEPTION OF MEDICAL INFORMATION PRIVACY:
A POINT-OF-VIEW ON THE USE OF MEDICAL TECHNOLOGY
by Hussein El-Omari
The use of electronic medical technology EMT offers different types of benefits in health care but also pose certain risks. As Saudi Arabia progresses toward the implementation of this type of medical records, a more in-depth understanding of attitudes that influence overall levels of EMT support is required. This article examined the perception of Saudi consumers (patients) regarding the privacy of their electronic medical records. The findings of this study showed that Saudis concerns regarding the privacy of their electronic medical records did not indicate any significant difference regarding the respondents duration of service with current provider, or their gender. On the other hand, significant differences were found regarding Saudis concerns about privacy and their education levels, age groups, and marital status.
The social and cultural of Saudis drives them to care a lot about their personal privacy as their social life restricts revealing sensitive issues to strangers, especially when it comes to females and/or family members. They also still have lack of confidence in electronic issues/devices as many social problems surface every now and then in Saudi society that usually have unfortunate consequences. For example, many social problems have surfaced because of Saudis using social media on their mobiles.
The findings of this study are of great importance to the marketing of health services in Saudi Arabia, which have great deal of importance to Saudi consumers (patients). Therefore, the concept of information privacy must be appreciated as this sector is becoming very competitive. Developing a successful marketing strategy for this type of service requires careful consideration of all social, cultural, and legal issues of the Saudi environment.
Environment of Saudi Arabia
Medical Sector of Saudi Arabia
Special Issue on: Innovative Business and Organisational Transformation Practices
Analysing the Entrepreneurial Intentions through Intellectual Capital: Evidences from India
by Ahmed Musa Khan, Mohd Yasir Arafat, Mohd Anas Raushan
Abstract: Intellectual capital is defined as the knowledge that can be converted into value. Intellectual capital has received a considerable attention from in the field of innovation performance. Still, there is a paucity of research which identifies the role of intellectual capital in creating ventures. This research is an attempt to examine the influence of intellectual capital on start-ups. A large data set of responses from 3360 respondents from India has been provided by the largest entrepreneurship research project Global Entrepreneurship Monitor has been used. A logistic regression technique is employed to measure the influence of intellectual capital on entrepreneurial intentions. The results show that all the components of intellectual capital, human capital, structural capital and relational capital have a positive and significant impact on entrepreneurial intentions. The study suggests that policies should be proposed to develop human capital, structural capital and facilitate interaction between existing and potential entrepreneurs so that new venture creation can be fostered. This research falls among the initial studies investigating the relationship between intellectual capital and entrepreneurial intentions. The review of literature reveals that very few studies based on large data set are conducted in developing countries like India.
Keywords: intellectual capital; entrepreneurial intentions; human capital; structural capital; relational capital; India.
Workplace Spirituality and Employees Readiness for Change as Precursors to Innovative Work Behaviour: an Empirical Examination
by Nimitha Aboobaker, K.A. Zakkariya, Manoj Edward
Abstract: Organisational performance and sustainability in the contemporary technological world is largely driven by the relentless change and continuous innovations brought about by employees. In this context, this paper investigates the relationship between workplace spirituality and innovative work behaviour, based on an empirical research conducted among 208 employees working in information technology sector. The study also examined the mediating role of individual readiness for change in the aforementioned relationship. The three dimensions of workplace spirituality had varying influences on outcome variables. Employees with higher experiences of meaningful work and alignment with organisational values had higher readiness for change and innovative work behaviour. Findings of this study revealed no significant direct effect of sense of community on innovative work behaviour of the employees. Nevertheless, sense of community had an indirect effect on innovative work behaviour, through the mediating role of readiness to change. Implications for employees experience of workplace spirituality and outcomes, so as to meet the challenges of a volatile, uncertain, complex and ambiguous (VUCA) business environment are elaborated.
Keywords: alignment with organisational values; innovative work behaviour; job design; meaningful work; organisational culture; readiness for change; sense of community; teamwork; workplace spirituality.
Impact of Organisational Justice on Perception of Ability-Job-Fit in Changing Environment
by MRINALI Tikare
Abstract: This quantitative study aims to investigate the relationship among procedural justice (PJ), distributive justice (DJ) and perceived-ability-job-fit. data were collected by using multi-stage sampling from 274 Class-I government employees. The scales developed by Sweeney and MaFarlin (1997) for Procedural-distributive justice (IV) and Abdel-Halim (1981) for ability-job-fit (DV) were selected. The respondents have positive perception about their ability to perform the job and they are optimistic about the fairness of prevailing procedures and distribution of rewards followed by their organisation which is indicated by high mean scores. The positive DJ and PJ perceptions proportionately increase the perception of ability-job-fit. multiple-regression analysis indicated that two independent variables (DJ-PJ) explained the variance in perceived-ability-job-fit. The perception of PJ is making a statistically significant unique contribution to the prediction of the perceived-ability-job-fit. The employees can reduce the stress by understanding the fit-concepts. The HR can predict the behavior of their employees by executing the fairness practices in the system. The top-management can win trust and thereby expect support from their employees, even during dynamic/volatile business environments by implementing appropriate PJ in the organisation. However, there are several concerns while generalising the findings of this study.
Keywords: distributive/procedural justice; experienced government employees; perceived-ability-job-fit.
Economic, Political and Institutional Determinants of Foreign Direct Investment Inflow in Emerging and Developing Asia
by Anil Kumar Goyal
Abstract: This study investigates the role of economic, political and institutional factors in attracting foreign direct investment (FDI) inflow in top five host economies of emerging and developing Asia consisting of China, Hong Kong, Singapore, India, and Viet Nam for a period of 20062016. The study is based on determinants, identified from literature review on the basis of their relevance and significance, of FDI inflow. The study uses fixed effects panel regression in order to measures the significance of determinants of FDI inflows in top five host economies of developing Asia. Findings of panel regression model reveal that most of the economic variables seem to be statistically significant and determinants FDI inflow as compared to institutional and political variables of FDI. After imputing variables into economic, political and institutional, multiple regression estimates indicate that the coefficients of economic and institutional factors are significant as determinants of FDI inflow in developing Asia.
Keywords: determinants of FDI inflow; economic; political and institutional factors; emerging Asia; developing Asia; FDI host economies; China; Hong Kong; Singapore; India; Viet Nam; panel data; fixed effect; multiple regression.
Price Discovery and Volatility Transmission in the Spot and Futures Market of Pepper: An Empirical Analysis
by Asha Nadig, T. Viswanathan
Abstract: Pepper, the king of spices, is one of the oldest and widely traded spices across the world over many centuries. As a commodity traded in the spot, futures and export market, global demand and supply play a crucial role in shaping pepper price and volatility. As price risks are integral to farmers and traders, forecasting successive prices will be of great help to them. The price risk can be minimised through effective hedging. The futures market provides a platform for both hedging and speculation. Hence understanding the relationship between spot and future market is essential for the traders of commodities. This paper examines the price discovery mechanism and volatility transmission between the spot and futures prices of pepper. Applying the statistical, seasonal variation and econometric models for forecasting, forecasting accuracy is tested. The Holt-Winters model gives biased estimate of future prices. The ARIMA model is the appropriate model to forecast the price of pepper.
Keywords: forecasting; price discovery; co-integration; volatility spill over.
Special Issue on: Advances in Approaches and Methods for Decision Making Using Optimisation and Artificial Intelligence Techniques
Gender differences in the perception of the Quality of College Life in Spanish University
by Juan Jose Blazquez-Resino, Edyta Gołąb-Andrzejak, Santiago Gutierrez-Broncano
Abstract: Through the current research, we intend to analyse how students differ in their levels of quality of college life (QCL) according to gender, and how this relates to overall quality of life (QoL) and loyalty [measured by Identification and word of mouth (WoM)] to their specific university. The survey included 243 students attending public university in Spain. The results obtained through the analysis of data allow affirming that there are differences between women and men both in the configuration of the quality of their college life and in its effect on the loyalty shown towards the college. This paper contributes towards an improved comprehension regarding the differences between the students according to their gender, so that managers can develop strategies better adapted to students.
Keywords: quality of college life; QCL; student satisfaction; installations satisfaction; education satisfaction; social satisfaction; quality of life; QoL; positive word of mouth; WoM; identification; gender differences; effect of gender; university; Spain.
Grey based decision making approach for the selection of distributor in supply chain
by Peeyush Vats, Gunjan Soni, Ajay Pal Singh Rathore, Om Ji Shukla
Abstract: The objective of this research article is to select the most appropriate distributor in a supply chain by applying a grey approach. This approach is based on the selection criteria of a distributor. This approach may be very much helpful to select the most suitable distributor in a supply chain among all alternatives of distributors available in the existing supply chain. This approach may be used as a tool to solve the multi-criteria decision-making problem by supply chain managers in different aspects. For implementing this approach, a case study has been carried out from a large-sized bearing manufacturing company for deciding the best alternative of distributor available existing in the supply chain. In this case study, eight selection criteria for the selection of a distributor and four distributors have been considered. A grey approach is implemented for selecting the most suitable distributor based on eight selection criteria among all the four distributors available in the existing supply chain. There is a significant amount of literature available on grey-based decision-making methods for solving multi-criteria decision-making problems. In this article grey-based, decision-making approach has been discussed in a very detailed manner for the selection of the best alternative of distributor by providing the comparative ranking to the alternatives and some specific weights to the selection criteria of the distributor.
Keywords: Grey approach; Supply Chain; Distributor; Multi-criteria decision making problem.
Customer experience evaluation of the car rental industry in Delhi NCR
by Pankaj Deshwal, Ankit Kumar, Umang Soni, Roshil Verma
Abstract: This paper is aimed extracting the key dimensions of customer experience in the self-drive car rental industry in India and studying their impact on users satisfaction, users loyalty, word of mouth and social perceptions. The study was carried out using a 31 items questionnaire which was responded by 155 participants. The principal component analysis was performed followed by linear regression. The results indicated that the four components-application functioning, operational convenience, transaction convenience and variety of choice- had a positive impact on loyalty, satisfaction and word of mouth and negligible influence on social perceptions.
Keywords: : Car rental industry; satisfaction; loyalty; word of mouth; social perception; customer experience.
The Effect of Travel Safety Experience on Passenger Satisfaction
by Pankaj Deshwal
Abstract: Purpose The aim of the study is to ascertain the dimensions of safety experience of the female passengers as regards to metro rail services provided by the Delhi metro rail in India. The impact of these dimensions on satisfaction is to be assessed.rnDesign/methodology/approach The female safety experience dimensions are obtained by performing an exploratory factor analysis. The research was conducted using survey method. A structured instrument was used to collect responses from the female passengers. Further, the reliability of the dimensions is ascertained followed by multiple linear regression analysis using SPSS s/w.rnFindings As a major output of the present research, nine dimensions viz. experience with other passengers, teasing experience, feeling towards metro rail, staff experience, outside metro station experience, compartment experience, behaviour experience, entry experience and recovery experience emerged as dimensions that lead to female passenger satisfaction as regards Delhi metro rail services. Further, the outputs of multiple linear regression revealed out of these nine dimensions, five dimensions, namely, feeling towards metro rail, experience with other passengers, recovery experience and staff experience are found to be statistically significant at 1 or 5 percent significance level.rnOriginality/value Authors believe this is the first effort that ascertains the dimensions that lead to female safety experience as regards to Delhi metro rail services and explore the impact of these dimensions on female passenger overall satisfaction. rn
Keywords: Female; safety experience; satisfaction; metro rail; regression; factor analysis.
Sustainable Supply Chain Risk Mitigation: A mixed method approach
by Madhukar Chhimwal, Saurabh Agrawal, Girish Kumar
Abstract: The objective of this research is to find a way to minimize risk in the supply chain by identifying the critical success factors and analyzing the relationship between sundry critical success factors. Proposed study construct a model of the critical success factors using the Interpretive Structural Modeling approach and test the model using regression analysis technique. Analysis of the results indicates that there are some critical success factors which have high driving power and low dependence that require utmost attention and are of great paramount while other cluster consists of those critical success factors which are highly dependent and need futuristic actions. In this work, only regression analysis technique is used to validate the model that is developed using Interpretive Structural Modeling approach. This type of relegation will help the supply chain managers to distinguish between independent and dependent critical success factors and how the relationships among the critical success factors will efficaciously minimize the risk in a supply chain. This study can be considered as a base study for the practitioners and academicians who are working in the area of risk management for achieving sustainability in the supply chain.
Keywords: Sustainable supply chain management; Interpretive Structural Modeling; Regression analysis; Risk Mitigation.
Performance Measurement of various AI techniques for Energy Estimation and its Optimization using Sensitivity Analysis
by Yashish Swami, Navjot Singh, Umang Soni
Abstract: The objective of this project is to predict Energy Performance of a Building (EPB) in terms of heating and cooling load by using various Artificial Intelligence (AI) techniques then measuring the corresponding strength of each input and its effect on the output in order to identify the most significant input from the lot by using Sensitivity Analysis. EPB can help in efficient construction of buildings as well as put a leash on dwindling Natural Resources and Global Warming. The various intelligent techniques used in this project are Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), ANFIS-GA (Genetic Algorithm) and ANFIS-PSO (Particle Swarm Optimization. In order to identify the most significant input, we are using a technique based on Sensitivity Analysis, which is called the Connection Weight Algorithm. In the end, performance of the AI techniques is compared to select the best performing model.rn
Keywords: Energy Performance of Building; Artificial Neural Network; Adaptive Neuro-Fuzzy Inference System; ANFIS-GA; ANFIS-PSO; Sensitivity Analysis; Heating Load; Cooling Load.
Optimization of Software Release Time using Adaptive Neuro Fuzzy Approach
by Shubhra Gautam, Deepak Kumar, L.M. Patnaik
Abstract: In this research study, the optimal release time of the software to be released is determined by using adapative neuro fuzzy optimization method. Adaptive neuro fuzzy optimization method has the advantage of fuzzy logic and neural network both. Different input criteria are taken in the paper based on which the optimal release time of the software is determined. The two important factors that govern the release time of any software are Cost and Reliability. Cost and reliability are estimated with respect to mean number of failures. Software reliability growth models are used to find the mean number of failures in any software. First, a software release time growth model is discussed which gives us the mean number of failures, these will be used to determine the cost and reliability. Second, an adaptive neuro fuzzy method is discussed for optimization by which the optimal time of release of spftware is obtained. Numerical examples are taken and results obtained are compared with different other optimization methods. From the results of numerical example, we can conclude that neuro fuzzy optimization method is best for software release time optimization.
Keywords: Software testing; Optimal release time,reliability,cost ; fuzzy logic; neuro fuzzy.
Special Issue on: Big Intelligent Enterprise For Sustainable Computing
Role of advertising and promotional strategies in shaping consumer brand attitude regarding consumer durable retailers in Vietnam
by Cuong Hung Pham
Abstract: Marketing communication is changing day by day along with the changing customer touch points, buying points, preferences and stores choices. As a result of this, advertising and promotional strategies are also changing. The purpose of this paper is the find the role of advertising and promotional strategies in shaping consumer brand attitude in the area of consumer durables in Vietnam. The present paper is exploratory cum descriptive in nature. The study uses primary data collected with the help of structured questionnaire from 638 respondents. The scale development and scale validation has been done through confirmatory factor analysis and validity and reliability analysis testing respectively. Structural equation modelling has been applied to establish the relationship between advertising and promotional strategies and brand attitude. It has been found from the study that there are four constructs of advertising and promotional strategies namely advertising, sales promotion, direct marketing and word of mouth. All these constructs have significant role in
shaping brand attitude. The study establishes the relationship among advertising and promotional strategies and brand attitude. Such a comprehensive relationship was not found in the extant literature in the context of consumer durable retailing.
Keywords: advertising; promotional strategies; structural equation modelling; brand attitude.
Optimising time in cloud using multi-hold inherited maximisation algorithm to reduce computational time
by D.S. Manoj Kumar, P. Sriramya
Abstract: The analysis in cloud computing is gaining momentum. In cloud computing, the allotment of resources assumes a significant job in choosing the performance, resource usage, and power consumption of the information that is focused. The provision of virtual machines in the cloud-primarily focuses on fundamental enhancement issues in distributed computing, specifically once the cloud foundation is made for accessing the resources from portable and handled devices. Resource arranging upheld service level agreement in distributed computing is an NP-hard drawback. An improved calculation multi-hold inherited maximisation (MHIM) algorithm has been introduced which is dependent on hereditary calculation-based advancement has predicted that placing a variety of resources on demand by assessing the entire group of undertakings inside the activity line can reduce the computational time. The simulation results demonstrate that there is an extinct degree of difference in
execution time and the response time of MHIM algorithm compared with different scheduling algorithms.
Keywords: scheduling algorithms; genetic algorithms; response time; VM allocation.
A hybrid artificial bee colony algorithmic approach for classification using neural networks
by C. Mala, Vishnu Deepak, Sidharth Prakash, Surya Lashmi Srinivasan
Abstract: Artificial neural networks are an integral component of most corporate and research functions across different platforms. However, depending upon the nature of the problem and quality of initialisation values, the usage of standard stochastic gradient descent always risks the possibility of getting trapped in local minima and saddle points for smaller neural networks in particular. One way to overcome this is by using algorithms with proven global search capabilities to train the network. This allows the neural net to reach the optimum values for weights regardless of the initialisation parameters used during training. Two algorithms are proposed based on modifications to the original artificial bee colony algorithm and their performances are analysed extensively on three benchmark datasets of increasing complexity. The first (NMABC) employs neural network appropriate initialisation and linear search
space expansion. This is integrated into the second (LHABC) incorporates stochastic gradient descent into the employed phase of the bees for faster convergence. It is found that the proposed algorithms consistently outperform standard approaches in all cases.
Keywords: artificial bee colony algorithm; neural network; meta-heuristic; hyperparamter.
Combination of audiovisual message design on prevention technique of cocoa pest attack using video medium as extension media
by Anna Gustina Zainal
Abstract: The main purpose of this paper is to determine the improvement in farmers knowledge about cocoa pests using video and the influence of knowledge improvement of cocoa farmers. An experiment is conducted involving 80 respondents selected randomly from farmer groups in Way Jepara Subdistrict, Mataram Baru Subdistrict, East Lampung District, Lampung Province and Indonesia where respondents were divided into two groups and each group received two treatments. Data related to respondents knowledge level is obtained through pre-test and post-test method. Analysis of variance (ANOVA) technique is used to analyse relationship between variables. This paper highlighted the result related to differences in farmers knowledge before and after the experiment. It is found that the type of narrative language used in video did not affect in farmers knowledge improvement. The experiment also found that the message presentation through video medium and the form of used narrative presentation was in direct narration form.
Keywords: communication; prevention technique; message; audio visual; relationship between variables; circular e-learning workware; public e-learning; response audience; effective tools; visual message; namely language; pre-test; treatment; post-test.
Special Issue on: Computational Intelligence in Sustainable Informatics Systems
Energy-Aware hybrid optimization algorithm for wireless sensor networks
by Swapna B. Sasi, Santhosh R
Abstract: The wireless sensor networks, incorporated with very minute, autonomous, highly mobile senor nodes that are powered by battery, has greatly influenced the researchers and has become a promising network in gathering information through sensing in a wide spread range of applications and the areas that are inaccessible to the humans. The framing of routing as a counter measure for the challenges incurred in the WSN is once again more arduous and strenuous. The stochastic and the discrete algorithm developed for the cluster head selection with the aim of minimizing the energy consumption, resulted with the maximization of the delay and losses caused by the minimized network life time as they faced difficulties in the selection of the head that is optimal, so the paper puts forward an hybrid optimization algorithm, clubbing the glow-worm and the fruit-fly for selection of the cluster head and further proceeds with the routing using the simple fuzzy rule based system for enhancing the network lifetime and energy consumption, further improving the quality of the service. The Result analysis is performed in the network simulator to evince the performance and the QOS enhancements attained through the proposed system.
Keywords: Cluster framing; Glow-worm; Fruity-fly; simple fuzzy rule system; network lifetime; optimization; Energy Consumption.
Demand-Side Management in Smart Electricity Grids: A Review
by Shwetha B N, Jasma Balasangameshwara
Abstract: Smart grids are enabling technologies for the functioning of electrical grids and the countrys economy. A smart grid is a technology which supplies electricity to consumers and provides bidirectional communication halfway with power utility and consumer. In smart grid networks, managing energy efficiency is an upcoming challenge. The energy is consumed by appliances in the residential sector, even during peak times. It results in wastage of energy up to some extent. Thus, Energy efficiency can be fulfilled by deploying the infrastructure of smart meters along with advanced metering infrastructure and policies for managing demand. Demand-Side Management (DSM) is a primary concept in the emerging smart grid. Thus, DSM balances vitality utilization every day utilizing various procedures, as it influences every customer's unit cost. This survey highlights different types of DSM and briefs about different approaches of DSM in the residential area. The individual approach of DSM may use a load scheduling algorithm it can be optimized technique or load shifting algorithm to achieve reduced electricity cost and optimal electricity energy consumption. The advantages of each approach are specified using energy parameters like energy cost, peak load, peak to average ratio, research gap is highlighted with delay, user comfortability. The focus is on exploring load scheduling algorithms used for smart appliances in a residential area and the impact of load scheduling on optimizing energy consumption.
Keywords: Demand Side Management,Load Scheduling,Residential,Smart Electricity Grid.
MagnetOnto: Modeling and Evaluation of Standardized Domain Ontologies for Magnetic Materials as a Prospective Domain
by Lucky Donald Lyngdoh Kynshi, Gerard Deepak, A. Santhanavijayan
Abstract: Ontologies are information processing entities that are used for modeling, representing, and reasoning domain knowledge Owing to the complexity in the relationship between different terms within a domain, there needs to be a logic in which they are pragmatically related. Ontology Modeling is the best strategy to represent conceptual and domain-specific knowledge which makes it feasible for information systems to understand and interpret the relationship between various terms. In this paper, a detailed investigation of magnetic materials as a domain is carried out and the relationship between terms in the domain is represented as machine-interpretable ontological entities. A detailed OWL ontological model that comprises of 123 classes with six distinct levels has been proposed. A detailed qualitative analysis using a semiotic approach using several parameters and quantitative analysis has been carried out. MagnetOnto is strictly a concept-oriented ontology with minimum deviations from the parent domain. An overall reuse ratio of 95.1% has been achieved by MagnetOnto, which makes this a best-in-class and also the first ontology to model magnetic materials.
Keywords: Antiferromagnetic; Conceptual Modeling; Diamagnetic; Dipole Moment; Domain Ontologies; Informatics physics; Magnetization.
Multi-Level Security Model for Privacy Preserving in the Cloud Work Flow Scheduling
by Shahul S., Arunkumar B
Abstract: The traditional security provisionings concentrating on the authentication of the all the data that are critical or no critical results in the increase in the computational time and the cost. Further the methods of security provisioning focusing the sensitive data alone, evinced minimization of the computational cost and time ,but were liable to the unauthorized attacks, as the single level of security were not enough due to the evolving counter technologies. So the paper proffers the single level security provisioning of the sensitive datas, by providing a multilevel security that uses the multiple number of cryptographic process for the privacy preserving in the cloud work-flow scheduling, by allowing the multi-level cryptographic process without affecting the quality of service, the computational cost and the time. The proffered method is validated in the work NS-2 to evidence the quality of service and the minimization in the computational cost and the execution time.
Keywords: Work-Flow; privacy preserving; cloud computing; multi-level cryptographic process; quality of service; computational cost and execution time.
High Performance Inventive System for Gait Automation and Detection of Physically Disabled Persons
by Vinothkanna Rajendran, Vijayakumar Thangavel, Prabakaran Narayanasamy
Abstract: Physically challenged persons may face many difficulties in the present modern environment as most of the commercial facilities and utilities for a day to day life is designed for normal people to lead a sophisticated life. Particularly people physically disabled face struggles in escalators in malls and public transportation places. It is very difficult for the disabled individual to be identified as one among in a large crowd and they normally feel unconformable to step inside in a running escalator. This research work proposes a novel method to identify the physically challenged persons from a large crowd by their nature of legs, walking pattern and hand sticks and provide necessary preference for them to get inside the escalators. Gait automation and detection mechanism is used for person identification for all gait events and deep learning based neural network (DLNN) is used for learning the patterns and making the system to automatically identify the physically challenged. Experimental results shows that the proposed system automatically measures all the angle of gait events with an accuracy level of 95.4% and thus offers a cost effective solution for gait kinematic analysis for disabled peoples.
Keywords: Physically disabled; Gait; Deep learning neural network (DLNN),.
Optimizing QoS with Load Balancing in Cloud Computing applying Dual Fuzzy Technique
by Chintureena Thingom, Ganesh Kumar R
Abstract: Cloud computing has become a necessity when the internet usage has increased drastically. This research paper objective is to optimise quality of service in cloud computing using dual fuzzy technique. With the competition to provide the best quality service at cloud data centre, we are analysing the parameters of average response time, average completion time, average CPU utilisation and job success. Cloud-sim simulator along with the mathematical model is used to provide reliable and valid result. To achieve the best result, the load in datacentre needs to be efficiently distributed, so that it is managed to process maximum service requests with the best service response time and very few failures. In this paper, we applied dual fuzzy technique for the load balancing in the cloud data centre and the findings were extensive and supports the proposed technique. With this technique, cloud computing service provider can provide better quality service.
Keywords: cloud computing; dual fuzzy; quality of service; cloud-sim; load balancing.
Design of Master Controller Test Kit for the Railway Diesel Locomotives
by KISHORE KUMAR KAMARAJUGADDA, Movva Pavani
Abstract: In the present paper, a master controller test kit for the diesel locomotives is designed, developed and the prototype is tested. Master controller test kit is used by the locomotive driver to drive the engine which is a human-machine interface which primarily performs three essential functions such as controlling the regression, progression, and locomotive braking. Stick type master controller is a modular based compact design which is a crew friendly for smooth operation and comfort. In the proposed model, the operation of solenoids is indicated by LEDs, and dynamic braking is shown by Digital Voltmeter for measuring the drop across braking control pot (BKCP)
coil. By using this test stand a layman can also check the master controller in the section itself which saves staff-hours and most significant loco downtime. The tested prototype is economical, and its performance is comparable with the existing microcontroller based master controllers.
Keywords: diesel locomotive; throttle handle; reverser handle; master controller testing kit; directional handle; dynamic brake handle.
Study paper on Internet of Things and its utilized protocols with application
by Roopa Jayasingh, Remus Dominic D’mello, Abhishek Soren, Ankit Alex Hansdak, Bidyut Mondal
Abstract: The people of the 21st century have now entered a new era of computing technology which is known by a very common name: the internet of things (IoT). Although it is also known by certain other names like machine to machine, Internet of Everything and many more, one thing common in this technology is that it is happening in real and has got quite a potential to shape the future of computer technology in the coming days. IoT is basically a paradigm which generally consists of interactive smart machines which communicate with other smart machines, resulting into generation of
informative data which are used to produce necessary actions that controls and command things hence making our day-to-day life a lot simpler. The following thesis is an extensive reference to the utilities, applications and possibilities of the IoT.
Keywords: internet of things; IoT; message queuing telemetry transport; constrained application protocol; XMPP; asynchronous messaging; open system intercommunication; OSI.
A Systematic Analysis of Defects, Incidents, Tickets and Service Effort Estimation
by Sharon Christa, SUMA V
Abstract: The delivery of quality software will always remain the primary focus of any software industry and in order to retain the quality, different measures are undertaken since customers can be retained only by providing quality product and services. Quality can be achieved by reducing defects in the software system during pre-deployment. Issues and requests raised by customer on the delivered software is addressed in different ways and is considered as a service provided to the customer. This paper gives an analysis of software maintenance from the service perspective and presents a detailed survey on the research currently undertaken by researchers in the area of ticket analytics, its scope in different scenarios. It is followed by an analysis on the impact of effort estimation on service request. Further, the paper presents a case study on incidents logged by different clients in an IT industry under different domains. The resolution time, priority, severity and volume of tickets are considered and its relationships are analyzed. This paper therefore enables in sampling the data which in turn enables the project personnel for further prediction activities.
Keywords: Defect Detection; Software Maintenance as a Service; Incident; Ticket Analytics; Service Request Effort; Application Management Service; Time to Resolve; IT Service Management.
Prediction of Disease Using Fuzzy Random Forest
by Balaji Bodkhe, SANJAY SOOD
Abstract: In this research work, eight health care clinical datasets from the internet including UCI machine learning repository have been experimented for validating the proposed classification and recommendation framework. These dataset contains the different attributes which the specific information like symptoms, cure, prevention, treatment, age, gender etc. Basically most of data available in semi structured format like CSV, .arff, XML etc. This process system can automatically download the dataset once and store it into data node. In pre-process phase all attributes has read from dataset and select any (t) out of n, for creating the training data. If the data is belongs with text format, we must need to convert into text. First blended dataset is partitioned into numeric dataset and distinct dataset and assembled devouring both traditional clustering algorithms and fuzzy clustering algorithms. The classification has done with FRF algorithm
Keywords: Machine Learning; FRF; fuzzy clustering algorithms.
Multi-Kernel Learning based Recommender System using Adaptive Neuro-Fuzzy Inference System
by A. Salman Ayaz, A. Jaya, Zameer Gulzar
Abstract: Nowadays, the personalized recommendations for a user is mainly build based on users rating. The drawback of online websites is that it presents many choices that result in consuming more time.Also it becomes strenuous for the user to find the the right information or product from numerous search results. In this work, a new Multi-Kernel Learning (MKL) is developed for providing the relevant information based on current user behavior through his/her click stream data without explicitly asking for these data. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is used for detecting the victors stream of data in on-line sites. This method recommends a browsing option and matches the data to a specific user group that meet the requirements of a particular user at the required time. The experimental results showed that the proposed MKL-ANFIS Recommendation System (RS) improved the accuracy and coverage values approximately 3-4% compared to the traditional methods such as Fuzzy C Means (FCM), Enhanced Graph Based Partitioning algorithm (EGBP) and C-Means and Center of Gravity (CM & COG).
Keywords: Adaptive Neuro-Fuzzy Inference System; Data mining; Multi-Kernel Learning; Recommender System.
A New Training Approach Based on ECOC-SVM for SAR Image Retrievals
by G. Sivakrishna, N. Prakash
Abstract: Synthetic Aperture Rader (SAR) is a side looking radar system and this SAR uses the flight path of the platform for simulating an extremely large antenna or aperture electronically. SAR is utilized for creating the high-resolution remote sensing imagery which used in various applications such as has environment monitoring, earth-resource mapping and military systems. SAR image processing receiving a massive attention in nowadays, because of the development of sensors.Here, a huge amount of SAR images is produced with the help of the earth observation satellites. There are two main objectives are considered in this paper. One is Image Retrieval (IR) on the SAR images and another one is denoising of SAR images. The SAR image retrieval is a way of identifying pre-defined images in the reference images. The aim of the paper is to perform the image retrieval of the SAR images by using the error correcting code based Support Vector Machine (ECOC-SVM). The retrieving process of the IR is mainly depends on the features from the respective satellite images. The features from the SAR images are extracted by using four different techniques such as Texture Spectrum (TS), Gray level Difference Method (GLDM), Scale-Invariant Feature Transform (SIFT) and Hue, Saturation, Value (HSV) model. From these techniques three different features such as texture, colour and shape are extracted. The image denoising at the SAR images are performed by the bi orthogonal wavelet transform (BWT) with Particle Swarm Optimization (PSO). PSO is used for optimizing the soft threshold for denoising the SAR images. The performance of the proposed methodology is analysed in terms of Average precision and average standard deviation and peak signal to noise ratio. Then it is evaluated with one existing method named IIRM. The average accuracy of the SAR image retrieval is 98.438 %. The average precision of the proposed methodology is 70.31% for ocean image, it is high when compared to the ocean image average precision of IIRM method that is 63.5%.
Keywords: SARImage Retrieval; Synthetic Aperture Rader; error correcting code based SVM; feature extraction; soft threshold; Particle Swarm Optimization (PSO); desnoising.
Special Issue on: ERPBSS 2018 Shifting Dynamics in Business
Brand preferences for consumer electronics in the United Arab Emirates
by Anand Haridas, Alun Epps
Abstract: The global consumer electronics industry has recently seen intense rivalry between a few major players. This research focuses on consumer behaviour, brand preferences and the relationship between socio-demographic factors and brands in the United Arab Emirates (UAE). A quantitative study of data collected through a web based questionnaire concludes that quality and brand equity are the major determinants of a consumers decision and identifies Sony and Apple as the preferred electronics and smart phone brands. Age, gender and income do not influence brand preference within the UAE market.
Keywords: consumer behaviour; brand preference; quality; brand equity; consumer electronics; smart phones; the United Arab Emirates.