Template-Type: ReDIF-Article 1.0 Author-Name: Anoop Kumar S. Author-X-Name-First: Anoop Kumar Author-X-Name-Last: S. Author-Name: R. Rajesh Author-X-Name-First: R. Author-X-Name-Last: Rajesh Title: Investigation on effect of geometric, material and load parameters on strength of composites with cutouts Abstract: Composite applications require presence of multiple holes for mechanical fasteners or cutouts in laminates. Unlike isotropic materials, composite materials experience change in stress values due to different parameters such as geometric, material and loading parameters. The present study is devoted to primarily determine whether geometric or material parameters have dominant influence on strength of composite laminates. Computational study using ABAQUS CAE software is employed for the analyses. Results reveal that geometric parameters have much significant influence on stress concentration factor and thereby the strength of composite laminates, when compared to material parameters. An elliptical cutout is seen to have comparatively more adverse effect on strength of laminate, when compared with other cutout shapes. Further, effect of load parameters - in-plane tension, compression and shear, is also studied. However, no significant effect was evidenced in stress concentration factor due to load parameters. Journal: Int. J. of Enterprise Network Management Pages: 1-22 Issue: 1 Volume: 10 Year: 2019 Keywords: stress concentration factor; composite laminate; open hole tension; geometrical parameters; material parameters; load parameters; edge interaction. File-URL: http://www.inderscience.com/link.php?id=98092 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:1:p:1-22 Template-Type: ReDIF-Article 1.0 Author-Name: R. Gopakumar Author-X-Name-First: R. Author-X-Name-Last: Gopakumar Author-Name: R. Rajesh Author-X-Name-First: R. Author-X-Name-Last: Rajesh Title: Experimental study on the influence of fibre surface treatments and coconut shell powder addition on the compressive strength, hardness and tribological properties of sisal fibre-natural rubber composites Abstract: In the present environment scenario, toxic wastes and their disposal is a major issue. Use of natural materials is the viable solution for this problem. This work aims to design and develop an elastomer composite using natural materials - natural rubber composite reinforced with sisal fibres. Since rubber components are essentials in industrial products, the developed material has lot significance. Six composites made with sisal fibres with various surface modifications and a 10%w/w coconut shell filler powder in natural rubber matrix. Sisal fibres used are raw fibre, alkalised fibres, rubber pre-impregnated raw fibres and rubber pre-impregnated alkalised fibre. The specimens tested for wear resistance, compressive strength and hardness. Maximum wear resistance exhibited by alkalised pre-impregnated sisal-rubber composite, followed by raw pre-impregnated-coconut shell powder-rubber composite. The hardness of raw sisal-rubber and raw pre-impregnated fibre composites improved by 228% than pure rubber (25 Shore A). Compressive strengths also showed improvements. Journal: Int. J. of Enterprise Network Management Pages: 23-31 Issue: 1 Volume: 10 Year: 2019 Keywords: natural rubber; sisal fibres; elastomer composite; hardness; tribology; compressive strength; bushes. File-URL: http://www.inderscience.com/link.php?id=98100 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:1:p:23-31 Template-Type: ReDIF-Article 1.0 Author-Name: C.K. Faseela Author-X-Name-First: C.K. Author-X-Name-Last: Faseela Author-Name: H. Vennila Author-X-Name-First: H. Author-X-Name-Last: Vennila Title: Combined economic and emission dispatch using whale optimisation algorithm Abstract: This paper highlight the use of latest whale optimisation meta heuristic algorithm for solving economic dispatch problem efficiently. This is used to solve the combined economic and emission dispatch problems for standard three generators system and 30 bus IEEE system. The whale optimisation algorithm was found to provide optimum results with easy convergence in comparison with other algorithms like PSO algorithm. Fuel cost and emission costs are combined to derive better result for economic dispatch. For checking the effectiveness of the algorithm, the results obtained using the same are compared with the results of particle swarm optimisation (PSO) and analysed the same against minimum generation cost and easy convergence. The results are found to be excellent for the systems considered. Journal: Int. J. of Enterprise Network Management Pages: 32-43 Issue: 1 Volume: 10 Year: 2019 Keywords: particle swan optimisation; PSO; whale optimisation algorithm; WOA; economic and emission dispatch; EED; optimum; solution; fuel cost; emission cost; optimisation methodology. File-URL: http://www.inderscience.com/link.php?id=98101 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:1:p:32-43 Template-Type: ReDIF-Article 1.0 Author-Name: G. Ganapathy Author-X-Name-First: G. Author-X-Name-Last: Ganapathy Author-Name: N. Sivakumaran Author-X-Name-First: N. Author-X-Name-Last: Sivakumaran Author-Name: Murugesan Punniyamoorthy Author-X-Name-First: Murugesan Author-X-Name-Last: Punniyamoorthy Author-Name: R. Surendheran Author-X-Name-First: R. Author-X-Name-Last: Surendheran Author-Name: Srijan Thokala Author-X-Name-First: Srijan Author-X-Name-Last: Thokala Title: Comparative study of machine learning techniques for breast cancer identification/diagnosis Abstract: The number of new cases of female breast cancer was 124.9 per 100,000 women per year. Similarly, deaths were 21.2 per 100,000 women per year. It calls for an urge to increase the awareness of breast cancer and very accurately analyse the causes which may differ in minute variations. This is why the application of computation techniques are widely increasing to support the diagnostic results. In this paper, we present the application of several machine learning techniques and models like neural network, SVM is used to quantify the classifications. The techniques that are most reliable, accurate and robust are emphasised. It gives a plethora of explorations into the research field for developing predictive models. To achieve higher reliability on the data, we present the comparison of various Machine Learning techniques on a dataset that is available on the website Kaggle. Journal: Int. J. of Enterprise Network Management Pages: 44-63 Issue: 1 Volume: 10 Year: 2019 Keywords: breast cancer; machine learning; neural network; FNA; SVM; kernel; KNN; naive Bayes. File-URL: http://www.inderscience.com/link.php?id=98102 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:1:p:44-63 Template-Type: ReDIF-Article 1.0 Author-Name: Narayanan Hema Rajini Author-X-Name-First: Narayanan Hema Author-X-Name-Last: Rajini Author-Name: Rajaram Bhavani Author-X-Name-First: Rajaram Author-X-Name-Last: Bhavani Title: Automatic detection and classification of brain tumours using k-means clustering with classifiers Abstract: A brain tumour detection and classification system has been designed and developed. This work presents a new approach to the automated detection and classification of astrocytoma, medulloblastoma, glioma, glioblastoma multiforme and craniopharyngioma type of brain tumours based on k-means clustering and texture features, which separate brain tumour from healthy tissues in magnetic resonance images. The magnetic resonance feature image used for the tumour detection consists of T2-weighted magnetic resonance images for each axial slice through the head. The application of the proposed method for tracking tumour is demonstrated to help pathologists distinguish exactly tumour region and its type of tumour. The results are quantitatively evaluated by a human expert. The average overlap metric, average precision and the average recall between the results obtained using the proposed approach and ground truth are 0.92, 0.97 and 0.92, respectively. A classification with accuracy of 100%, 99% and 98% has been obtained by SVM, ANN and decision tree. Journal: Int. J. of Enterprise Network Management Pages: 64-77 Issue: 1 Volume: 10 Year: 2019 Keywords: magnetic resonance imaging; MRI; k-means clustering; segmentation; grey level co-occurrence matrix; GLCM; tumour. File-URL: http://www.inderscience.com/link.php?id=98103 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:1:p:64-77 Template-Type: ReDIF-Article 1.0 Author-Name: R. Kamalakannan Author-X-Name-First: R. Author-X-Name-Last: Kamalakannan Author-Name: R. Sudhakara Pandian Author-X-Name-First: R. Sudhakara Author-X-Name-Last: Pandian Author-Name: P. Sivakumar Author-X-Name-First: P. Author-X-Name-Last: Sivakumar Title: A simulated annealing for the cell formation problem with ratio level data Abstract: In this paper, the cell formation problem is considered with ratio level data with an objective of minimising the cell load variation. The attempt has been made to propose a simulated annealing (SA) based on the perturbation scheme as random insertion perturbation scheme (RIPS). The ratio level data is distinguished by utilising the workload information gathered from process times, production quantity of parts and also from the capacity of the machines. A modified grouping efficiency (MGE) is used to measure the performance of the system. From the results it is observed that the simulated annealing produces the solution does not differ significantly from the optimal solutions for the benchmark problems. The algorithms which we have chosen the benchmark problems are K-means, modified ART1 and genetic algorithm taken from the literature. Journal: Int. J. of Enterprise Network Management Pages: 78-90 Issue: 1 Volume: 10 Year: 2019 Keywords: simulated annealing; cell formation problem; ratio level data. File-URL: http://www.inderscience.com/link.php?id=98107 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:1:p:78-90 Template-Type: ReDIF-Article 1.0 Author-Name: Chidambaranathan Bibin Author-X-Name-First: Chidambaranathan Author-X-Name-Last: Bibin Author-Name: P. Seeni Kannan Author-X-Name-First: P. Seeni Author-X-Name-Last: Kannan Author-Name: P.K. Devan Author-X-Name-First: P.K. Author-X-Name-Last: Devan Author-Name: R. Rajesh Author-X-Name-First: R. Author-X-Name-Last: Rajesh Title: Performance and emission characteristics of a DI diesel engine using diestrol blends and diesel as fuel Abstract: Biofuels, namely, biodiesel and ethanol produced from renewable energy sources are used as fuels in the blended form along with diesel to investigate the performance and emission characteristics of a DI diesel engine. Diestrol blend consists of diesel, biodiesel/methyl ester and ethanol. In diestrol blends, ethanol percentage is steadily elevated with an incremental factor of 5% culminating into three blends with a maximum percentage of 15% by volume and named as EB5, EB10 and EB15 respectively. A comprehensive analysis of engine performance characteristics such as brake thermal efficiency, brake specific fuel consumption, exhaust gas temperature and emission characteristics such as carbon monoxide, carbon dioxide, unburned hydrocarbon, oxides of nitrogen and smoke opacity were carried out. From the above investigation, it was found that brake thermal efficiency increased by 3%, 5% and oxides of nitrogen emission decreased by 23%, 24.5% when compared to diesel and B20 respectively. Journal: Int. J. of Enterprise Network Management Pages: 91-108 Issue: 2 Volume: 10 Year: 2019 Keywords: diesel engines; diestrol; ethanol; emissions; methyl esters; punnai oil; performance; ternary blends. File-URL: http://www.inderscience.com/link.php?id=100485 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:91-108 Template-Type: ReDIF-Article 1.0 Author-Name: A. Maruthamuthu Author-X-Name-First: A. Author-X-Name-Last: Maruthamuthu Author-Name: Murugesan Punniyamoorthy Author-X-Name-First: Murugesan Author-X-Name-Last: Punniyamoorthy Author-Name: Swetha Manasa Paluru Author-X-Name-First: Swetha Manasa Author-X-Name-Last: Paluru Author-Name: Sindhura Tammuluri Author-X-Name-First: Sindhura Author-X-Name-Last: Tammuluri Title: Prediction of carotid atherosclerosis in patients with impaired glucose tolerance - a performance analysis of machine learning techniques Abstract: The focus of this paper is to examine factors associated with carotid atherosclerosis in patients with impaired glucose tolerance (IGT), and to predict the rapid progression of carotid intima-media thickness (IMT). The proposed machine learning methods performed well and accurately predicted the progression of carotid IMT. The linear support vector machine, nonlinear support vector machine with a radial basis kernel function, multilayer perceptron (MLP), and the Naive Bayes method were employed. A comparison of these methods was conducted using the Brier score, and the accuracy was tested using a confusion matrix. Journal: Int. J. of Enterprise Network Management Pages: 109-117 Issue: 2 Volume: 10 Year: 2019 Keywords: multilayer perceptron; MLP; support vector machine; SVM; radial basis kernel function; impaired glucose tolerance; IGT; carotid atherosclerosis; Naive Bayesian model; Brier score. File-URL: http://www.inderscience.com/link.php?id=100528 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:109-117 Template-Type: ReDIF-Article 1.0 Author-Name: A.S. Balakrishnan Author-X-Name-First: A.S. Author-X-Name-Last: Balakrishnan Author-Name: Jayshree Suresh Author-X-Name-First: Jayshree Author-X-Name-Last: Suresh Title: Do you gain by green supply chain management? Abstract: The importance of green has increased due to the environmental change. The burning of oil and other fossil fuels releases carbon dioxide, which rises, blankets the earth and traps heat. On environmental issues, there are intensive studies which have been dealt with extensively by practitioners and academicians. There is an increasing pressure on businesses to improve economic and environmental performance. Green supply chain management (GSCM) is an emerging approach for economic and ecological benefit to manufacturers. This paper presents the case study on how GSCM practiced in Ford India in the areas of logistics, packaging and manufacturing processes, how GSCM influence with firm performance and its gain by extending across firms in developing markets such as India. Journal: Int. J. of Enterprise Network Management Pages: 118-132 Issue: 2 Volume: 10 Year: 2019 Keywords: green supply chain management; GSCM; logistics; manufacturing; packaging; India. File-URL: http://www.inderscience.com/link.php?id=100539 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:118-132 Template-Type: ReDIF-Article 1.0 Author-Name: M. Mohan Prasad Author-X-Name-First: M. Mohan Author-X-Name-Last: Prasad Author-Name: K. Ganesan Author-X-Name-First: K. Author-X-Name-Last: Ganesan Author-Name: K.P. Paranitharan Author-X-Name-First: K.P. Author-X-Name-Last: Paranitharan Author-Name: R. Rajesh Author-X-Name-First: R. Author-X-Name-Last: Rajesh Title: An analytical study of lean implementation measures in pump industries in India Abstract: The manufacturing industries in India are gearing up to face the challenges namely the quality, timely delivery and satisfying customer need. This prompted some large manufacturing industries to implement lean thinking in their manufacturing process. Most of the manufacturing companies are yet to take up this task. Particularly, the pump industries which are mostly occupied by SMEs are still to follow the suit. In this context, this study has made sincere attempt to survey the implementation of lean in pump manufacturing industries in India through an instrument consisting of seven lean implementation measures namely, RILP, lean tools employed in the company, RLPTLI, MBLP, evaluation of level of waste in the company, success factors of lean practicing in the company and lean performance indicators. A survey type research was conducted and the results indicated that identified lean implementation measures were found to be significant in achieving lean implementation in pump industries. Journal: Int. J. of Enterprise Network Management Pages: 133-151 Issue: 2 Volume: 10 Year: 2019 Keywords: lean practice; lean implementation measures; pump manufacturing; India. File-URL: http://www.inderscience.com/link.php?id=100540 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:133-151 Template-Type: ReDIF-Article 1.0 Author-Name: H. Vennila Author-X-Name-First: H. Author-X-Name-Last: Vennila Author-Name: R. Rajesh Author-X-Name-First: R. Author-X-Name-Last: Rajesh Title: Combined static economic and emission dispatch by improved moth optimisation with valve point loading Abstract: This paper aims to find an optimum solution for the problem by the use of an algorithm inspired by the flight pattern of moths. Like a moth drawn to a flame, this algorithm zones in on the optimal solution, to minimise fuel cost as well as shrink emission of harmful gases. Moth flame optimisation is a simple and robust method to discover the optimal solution in a vast search space. Thus, by implementing a heuristic algorithm like improved moth flame optimisation, the complex problem of finding the power to be generated by each generator in a power system can be vastly simplified and the optimal result can be easily and efficiently obtained. Journal: Int. J. of Enterprise Network Management Pages: 152-161 Issue: 2 Volume: 10 Year: 2019 Keywords: economic dispatch; emission dispatch; improved moth flame; heuristic algorithm. File-URL: http://www.inderscience.com/link.php?id=100542 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:152-161 Template-Type: ReDIF-Article 1.0 Author-Name: M.K. Marichelvam Author-X-Name-First: M.K. Author-X-Name-Last: Marichelvam Author-Name: M. Geetha Author-X-Name-First: M. Author-X-Name-Last: Geetha Title: A hybrid algorithm to solve the stochastic flow shop scheduling problems with machine break down Abstract: A flow shop scheduling problem with uncertain processing times and machine break down is considered in this paper. The objective is to minimise the maximum completion time (makespan). As the problem is non-deterministic polynomial-time hard (NP-hard), a hybrid algorithm (HA) is proposed to solve the problem. The firefly algorithm (FA) is hybridised with the variable neighbourhood search (VNS) algorithm in the proposed HA. Extensive computational experiments are carried out with random problem instances to validate the performance of the proposed algorithm. Journal: Int. J. of Enterprise Network Management Pages: 162-175 Issue: 2 Volume: 10 Year: 2019 Keywords: scheduling; NP-hard; flow shop; makespan; firefly algorithm; variable neighbourhood search; VNS. File-URL: http://www.inderscience.com/link.php?id=100544 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:162-175 Template-Type: ReDIF-Article 1.0 Author-Name: Sanjay Mohapatra Author-X-Name-First: Sanjay Author-X-Name-Last: Mohapatra Title: Critical review of literature and development of a framework for application of artificial intelligence in business Abstract: Artificial intelligence has the ability to predict outcomes accurately and with reliability. The techniques have been used in several industries and domains. However, documenting results from different research that were conducted have not been documented. Also, most of the research has been carried out in developed countries and not much work has been published from other economies. As a result, there is a need to develop proper research background so that application of AIs can be sustainable and effective. The purpose of this study is to critically review different studies that have adopted AI in several domains, so that a theoretical framework guide for researchers and practitioners can be developed. This framework will also establish future trends in the said research area. From online databases, relevant articles and extracts were retrieved and were systematically analysed. Using these inputs, a framework was developed. The findings of this study show that there is a gap between research work done and documentation available. The present applications of AI techniques require model-based approach that brings in consistency in research as well as for industry. A paradigm shift in the framework-based approach could lead to achieving a sustainable practice. Journal: Int. J. of Enterprise Network Management Pages: 176-185 Issue: 2 Volume: 10 Year: 2019 Keywords: artificial intelligence; framework; AI applications; theoretical study. File-URL: http://www.inderscience.com/link.php?id=100546 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:2:p:176-185 Template-Type: ReDIF-Article 1.0 Author-Name: Palanisamy Shanthi Devi Author-X-Name-First: Palanisamy Shanthi Author-X-Name-Last: Devi Author-Name: Ramasamy Viswanathan Author-X-Name-First: Ramasamy Author-X-Name-Last: Viswanathan Title: Convergence of partial differential equation using fuzzy linear parabolic derivatives Abstract: Discovering solution for partial differential equations (PDEs) is considered to be difficult task. Exact solution is said to be identified only in certain specified cases. In this paper, convergence of partial differential equation using fuzzy linear parabolic (PDE-FLP) method on a finite domain is designed. The method is based on PDE where coefficients are obtained as fuzzy numbers and solved by linear parabolic derivatives. Firstly, PDE form and fuzzy representation of two independent variables are derived. Secondly, fuzzy linear parabolic (FLP) derivative is provided for numerical convergence. FLP derivatives are employed to describe time dependent aspects. Parabolic derivatives are also due to similar coefficient condition for the analytic solution. Finally, numerical results are given, which demonstrates the effectiveness and convergence of PDE-FLP method. A detailed comparison between approximate solutions obtained is discussed. Also, figurative representation to compare between approximate solutions is also presented. Journal: Int. J. of Enterprise Network Management Pages: 190-210 Issue: 3/4 Volume: 10 Year: 2019 Keywords: partial differential equation; PDE; fuzzy; linear parabolic; domain; numerical solution. File-URL: http://www.inderscience.com/link.php?id=103141 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:190-210 Template-Type: ReDIF-Article 1.0 Author-Name: V. Priya Author-X-Name-First: V. Author-X-Name-Last: Priya Author-Name: K. Umamaheswari Author-X-Name-First: K. Author-X-Name-Last: Umamaheswari Title: A document similarity approach using grammatical linkages with graph databases Abstract: Document similarity had become essential in many applications such as document retrieval, recommendation systems, plagiarism checker, etc. Many similarity evaluation approaches rely on word-based document representation, because it is very fast. But these approaches are not accurate when documents with different language and vocabulary are used. When graph representation is used for documents they use some relational knowledge which is not feasible in many applications because of expensive graph operations. In this work a novel approach for document similarity computation which utilises verbal intent has been developed. This improves the similarity by increasing the number of linkages using verbs between two documents. Graph databases were used for faster performance. The performance of the system is evaluated using various metrics like cosine similarity, jaccard similarity and dice with different review datasets. The verbal intent-based approach has registered promising results based on the links between two documents. Journal: Int. J. of Enterprise Network Management Pages: 211-223 Issue: 3/4 Volume: 10 Year: 2019 Keywords: graph databases; text similarity; grammatical linkages; verbal intent modelling; knowledge graphs. File-URL: http://www.inderscience.com/link.php?id=103143 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:211-223 Template-Type: ReDIF-Article 1.0 Author-Name: T. Anand Author-X-Name-First: T. Author-X-Name-Last: Anand Author-Name: R. Sudhakara Pandian Author-X-Name-First: R. Sudhakara Author-X-Name-Last: Pandian Title: A customer-based supply chain network design Abstract: This study eventually synthesises and proposes a new algorithm for a customer to a customer supply chain management system. Parallely, we consider cost reductions in quantity rebate for inbound and outbound transportation of logistics. It utilises an approximation procedure to simplify distance calculation details and builds up an algorithm to solve supply chain management issues using nonlinear optimisation technique. Numerical studies illustrate the solution procedure and influence of model parameters on supply chain management and total costs. This study will result as a reference for top-level managements and organisations. Journal: Int. J. of Enterprise Network Management Pages: 224-240 Issue: 3/4 Volume: 10 Year: 2019 Keywords: customer to customer network; facility location-allocation; inventory policy; continuous approximation approach. File-URL: http://www.inderscience.com/link.php?id=103153 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:224-240 Template-Type: ReDIF-Article 1.0 Author-Name: T. Vairam Author-X-Name-First: T. Author-X-Name-Last: Vairam Author-Name: S. Sarathambekai Author-X-Name-First: S. Author-X-Name-Last: Sarathambekai Title: Proficient smart trash can management using internet of things and SDN architecture approach Abstract: Most of the metropolitan cities facing the problem of collecting garbage on time. Due to the inadequacy of garbage collection, the trash bin gets overflow and causes various risk such as spreading diseases, unpleasant aroma, ugliness, etc. To evade all these circumstances, this paper addresses the efficient collection of garbage's by implementing IoT based smart trash can system. This system monitor the overall status of all trash cans around the city. Whenever the trash level of bin reaches the threshold level it sends the alert message to the truck driver. It also helps the garbage truck driver by providing him with the shortest path to attend all trash cans in city. IoT based smart trashcan is implemented using Raspberry Pi board with HC SR04 ultrasonic sensor for measuring trash level. Amazon Web Services (AWS) helps in storage of data and sending notifications to the concerned people who are involved in the process of collecting garbage. Managing data traffic in IoT network is difficult task, we also addressed this issue by designing the software defined networking (SDN) for smart trash can system. SDN will further help to improve the performance of our system. Journal: Int. J. of Enterprise Network Management Pages: 241-252 Issue: 3/4 Volume: 10 Year: 2019 Keywords: software defined networking; SDN; internet of things; IoT; trash bin; Amazon Web Services; AWS. File-URL: http://www.inderscience.com/link.php?id=103154 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:241-252 Template-Type: ReDIF-Article 1.0 Author-Name: K. Naveen Durai Author-X-Name-First: K. Naveen Author-X-Name-Last: Durai Author-Name: K. Baskaran Author-X-Name-First: K. Author-X-Name-Last: Baskaran Title: Decision tree classification - N tier solution for preventing SQL injection attack on websites Abstract: The current situation has dragged everyone into the contiguous usage of web applications. As every task is performed based on web applications, it is very important that we will have to think and secure the web applications to the most out of it. What is SQLIA? It could be defined as the one that is implemented by the users who actually does not possess any of the access permissions though they want to abuse the access rights in the database and steal the data or edit them or delete as desired. To achieve SQL injection attacks, malicious query is written to leak out the data that is highly confidential. Interference of the SQL injection attack shall be well executed through the public interface as that is the existing source that an application provides when the case is that the host-level entry point and the network are secured enough. Some the suspicions that a SQLIA pretend to expose is that it cannot be applied without single quotes, space or double dashes. Journal: Int. J. of Enterprise Network Management Pages: 253-271 Issue: 3/4 Volume: 10 Year: 2019 Keywords: SQLIA-SQL; injection attacks; hyper text transfer protocol; HTTP; OWASP; WEBSSARI. File-URL: http://www.inderscience.com/link.php?id=103155 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:253-271 Template-Type: ReDIF-Article 1.0 Author-Name: R. Subha Author-X-Name-First: R. Author-X-Name-Last: Subha Title: P-tree oriented association rule mining of multiple data sources Abstract: A prominent research area in data mining field is (ARM). As distributed databases emerged, need to mine different patterns across them become necessary and hence distributed ARM algorithms were desired. But these algorithms increased communication complexity and overhead. This paper proposes a new algorithm P-tree oriented distributed association rule mining (PDAM) for mining association rules from distributed databases. This algorithm enables a quicker computation of support counts of item sets. P-tree, a special kind of data structure is used in the algorithm which holds the transactional data. These tree data structures do effective storage of data by employing lossless compression techniques. Message exchange optimisation is proposed in this paper. Both the database scans as well as message exchanges are reduced by the proposed method. It would also reduce the size of average transactions, data sets and message exchanges. Journal: Int. J. of Enterprise Network Management Pages: 272-279 Issue: 3/4 Volume: 10 Year: 2019 Keywords: association rule mining; ARM; P-tree; distributed association rule mining; DARM. File-URL: http://www.inderscience.com/link.php?id=103156 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:272-279 Template-Type: ReDIF-Article 1.0 Author-Name: G. Gokilakrishnan Author-X-Name-First: G. Author-X-Name-Last: Gokilakrishnan Author-Name: P. Ashoka Varthanan Author-X-Name-First: P. Ashoka Author-X-Name-Last: Varthanan Title: Development of manufacturing - distribution plan considering quality cost Abstract: In the current complex business world, making decisions on the manufacturing-distribution problem is a tedious task to the supply chain managers. Solving mathematical model with many entities requires a suitable algorithm for optimum results which increase the profitability of any industrial activity. Any model without considering the percentage of rejection in a particular plant, will not supply the right quality and quantity of products to the customers. Here, a mathematical model is developed by considering the quality cost in addition to normal time manufacturing cost, subcontracting cost, transportation cost, overtime manufacturing cost, holding cost, cost of hiring, and cost of firing. Mixed integer linear programming (MILP) model is developed and solved using a modified heuristic based discrete particle swarm algorithm (DPSA) which generates the manufacturing-distribution plan in order to bring the total cost minimum for the bearing industry under study. The normal time manufacturing loss and the overtime loss in terms of product quantity and cost are calculated and manufactured. Journal: Int. J. of Enterprise Network Management Pages: 280-304 Issue: 3/4 Volume: 10 Year: 2019 Keywords: quality cost; optimisation; manufacturing-distribution plan; supply chain. File-URL: http://www.inderscience.com/link.php?id=103157 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:280-304 Template-Type: ReDIF-Article 1.0 Author-Name: R. Sandhiya Author-X-Name-First: R. Author-X-Name-Last: Sandhiya Author-Name: M. Sundarambal Author-X-Name-First: M. Author-X-Name-Last: Sundarambal Title: Chicken swarm optimisation based clustering of biomedical documents and health records to improve telemedicine applications Abstract: The aim of this paper is to develop an efficient ontology enabled chicken swarm optimisation (CSO) based clustering algorithm with dynamic dimension reduction (DDR) to efficiently cluster biomedical documents and health records to facilitate telemedicine applications. A total of 350 documents and health records are collected from PubMed repository for telemedicine applications. First, the documents are pre-processed via semantic annotation and concept mapping while term frequency and inverse gravity moment (TF-IGM) factor is used to improve document representation and the modified n-gram resolves the substitution and deletion malpractices. DDR technique reduces feature space dimension and prunes non-useful text features to increase the clustering accuracy by tackling the high dimensionality problem. Finally, the clusters are formed by CSO clustering. Experimental simulations prove that the CSO-DDR clustering model is significantly efficient than the traditional algorithms and ensures reliable and adaptive telemedicine applications with better clustering of biomedical documents and health records. Journal: Int. J. of Enterprise Network Management Pages: 305-328 Issue: 3/4 Volume: 10 Year: 2019 Keywords: telemedicine; health records; biomedical document clustering; semantic smoothing; TF-IGM; chicken swarm optimisation; CSO; dimension reduction; ontology; concept mapping; modified n-grams; PubMed. File-URL: http://www.inderscience.com/link.php?id=103158 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:305-328 Template-Type: ReDIF-Article 1.0 Author-Name: P. Damodharan Author-X-Name-First: P. Author-X-Name-Last: Damodharan Author-Name: C.S. Ravichandran Author-X-Name-First: C.S. Author-X-Name-Last: Ravichandran Title: Inclusive strategic techno-economic framework to incorporate essential aspects of web mining for the perspective of business success Abstract: The competing nature among the web mining industries is observed to be its capability to drive business success. Therefore the classification of web mining using online business reliance as a factor has been considered. According to the classification, if the net effect of every click stream from a potential customer during an online session is expected to culminate in the 'buy' then it is exhaustive promote. Otherwise it is partial promote. Moreover intention behind modelling partial promote and exhaustive promote using Cournot game theory is to have a techno-economic framework which helps in mapping web mining uncertainties with business performance. The results show that the developed techno-economic web mining framework performs mining operations from the perspective of business success. Hence it can help the management professionals in making appropriate choice while choosing, fine tuning, upgrading the web mining techniques. Journal: Int. J. of Enterprise Network Management Pages: 329-349 Issue: 3/4 Volume: 10 Year: 2019 Keywords: web mining; e-commerce; web content mining; WCM web structure mining; WSM; decision making; knowledge management. File-URL: http://www.inderscience.com/link.php?id=103159 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:329-349 Template-Type: ReDIF-Article 1.0 Author-Name: V. Navya Author-X-Name-First: V. Author-X-Name-Last: Navya Author-Name: P. Deepalakshmi Author-X-Name-First: P. Author-X-Name-Last: Deepalakshmi Title: Effective transmission of critical parameters in heterogeneous wireless body area sensor networks Abstract: Wireless body area networks have great potential to change the future of remote and personalised healthcare technology by embedding smart devices to provide real-time feedback. In this article, proposed a threshold-based routing concept to route only the critical data of bio-sensors during an emergency condition of a patient. Sensor nodes attached to the body, sense and forwards patient's vital sign's data based on the standard thresholds applied during the routing process. Depending on variations in the sensed data, the energy parameters are calculated and data are routed to the coordinator node for further communication. An efficient node is selected based on the least cost value that depends on high residual energy and less distance to sink. From the results obtained, the proposed technique provides improvements in terms of energy, stability period, network lifetime, throughput, path loss and packet delivery ratio compared to existing multi-hop routing techniques. Journal: Int. J. of Enterprise Network Management Pages: 350-370 Issue: 3/4 Volume: 10 Year: 2019 Keywords: wireless body area network; WBAN; real-time feedback; bio-sensors; threshold-based routing; personalised healthcare; emergency condition; vital sign's data; effective transmission; smart devices; critical parameters; standard thresholds; network lifetime; energy parameters; multihop routing. File-URL: http://www.inderscience.com/link.php?id=103161 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:350-370 Template-Type: ReDIF-Article 1.0 Author-Name: Gowri Thangam Jeyaraj Author-X-Name-First: Gowri Thangam Author-X-Name-Last: Jeyaraj Author-Name: A. Sankar Author-X-Name-First: A. Author-X-Name-Last: Sankar Title: Extreme learning machine and K-means clustering for the improvement of link prediction in social networks using analytic hierarchy process Abstract: The rapid growth of the availability of healthcare related data raises a challenge of extracting useful information. Thus there is an urgent need for the healthcare industry to predict the disease, that reduces the amount of cumbersome tests on patients The aim of this paper is to employ a combination of machine learning algorithms namely extreme learning machine algorithm with k-means clustering and analytic hierarchy process, for the prediction of disease in a patient through the extraction of different patterns from the dataset based on the relationships that exists among the attributes. It would help the physician and the medical scientists to predict the possibility of the disease. In today's era, the percentage of females getting affected by diabetes has increased exponentially. So, the experiments are carried over PIMA diabetes data set that focuses on females are extracted from UCI repository and the results are found to be significant. Journal: Int. J. of Enterprise Network Management Pages: 371-388 Issue: 3/4 Volume: 10 Year: 2019 Keywords: analytic hierarchy process; extreme learning machine; K-means clustering; social networks; link prediction; network management. File-URL: http://www.inderscience.com/link.php?id=103162 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:371-388 Template-Type: ReDIF-Article 1.0 Author-Name: P. Prakash Author-X-Name-First: P. Author-X-Name-Last: Prakash Author-Name: Raghavi Suresh Author-X-Name-First: Raghavi Author-X-Name-Last: Suresh Author-Name: Dhinesh Kumar PN Author-X-Name-First: Dhinesh Kumar Author-X-Name-Last: PN Title: Smart city video surveillance using fog computing Abstract: Conventional video surveillance systems require infrastructure including expensive servers with capability to process images and store video recordings. These surveillance systems produce and need to store a huge amount of data and to execute in real time to detect safety events. The problems of the anti-social activities which gradually increasing across the country especially in the urban areas in recent times which lead to the need for technological innovations in the security and surveillance system. The proposed system is based on cloud computing. In this paper the application has been modelled and simulated using iFogSim. The results predicts that the fog-based model is more secured and efficient compared to cloud computing parameter energy consumption. The proposed system helps to increase the effectiveness of the intelligent agencies and thereby increase crime safety at public places. Journal: Int. J. of Enterprise Network Management Pages: 389-399 Issue: 3/4 Volume: 10 Year: 2019 Keywords: cameras; Internet of Things; IoT; fog computing; cloud computing; surveillance system; ifogsim; smart city. File-URL: http://www.inderscience.com/link.php?id=103165 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijenma:v:10:y:2019:i:3/4:p:389-399