Template-Type: ReDIF-Article 1.0
Author-Name: Kai Sun
Author-X-Name-First: Kai
Author-X-Name-Last: Sun
Author-Name: Naidi Liu
Author-X-Name-First: Naidi
Author-X-Name-Last: Liu
Author-Name: Xinghua Sun
Author-X-Name-First: Xinghua
Author-X-Name-Last: Sun
Author-Name: Yuxin Zhang
Author-X-Name-First: Yuxin
Author-X-Name-Last: Zhang
Title: Design and implementation of big data analysis and visualisation platform for the smart city
Abstract:
Through the construction of smart cities, the modernisation of urban governance systems and governance capacities can be improved. However, the constructions of smart cities face the challenges of data failure, lack of relevance, information fragmentation, fundamental data without accepting new data and innovative concepts. Business big data are extracted, and converted from different departments, and then these structured, semi-structured, and non-structured data are extracted and transformed to load in data warehouse by ETL through the data sharing and exchange platforms. Then joint databases and element searches were used to create multi-department data business views to support specific applications in smart cities. This research realises the smart city big data visual analysis system. The system architecture includes data access layer, data management layer, data analysis layer and release management layer. The system mainly includes four modules: people's livelihood service, citizen big data, urban operation and big data map. This system helps break data barriers, connect data islands, and digitise many municipal businesses, so as to perform data analysis and data visualisation, and provide support for refined governance decision making. The system realises the access, integration, transformation, visualisation and interactive decision analysis of various data of urban life.
Journal: Int. J. of Information Technology and Management
Pages: 373-385
Issue: 3/4
Volume: 22
Year: 2023
Keywords: smart city; big data; urban governance; data visualisation.
File-URL: http://www.inderscience.com/link.php?id=131842
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:373-385

Template-Type: ReDIF-Article 1.0
Author-Name: Yibing Ma
Author-X-Name-First: Yibing
Author-X-Name-Last: Ma
Author-Name: Hongyu Guo
Author-X-Name-First: Hongyu
Author-X-Name-Last: Guo
Author-Name: Yuqi Sun
Author-X-Name-First: Yuqi
Author-X-Name-Last: Sun
Author-Name: Fang Liu
Author-X-Name-First: Fang
Author-X-Name-Last: Liu
Title: Real-time prediction algorithm and simulation of sports results based on internet of things and machine learning
Abstract:
Machine learning is an intelligent technology that plays an important role in classification and prediction. In the field of sports prediction, the prediction results must be processed, because many events in large-scale sports events are linked to funds. Through inquiries on the internet, more and more sports-related data can be obtained. Using these data, people continue to develop intelligent models and prediction systems, optimise and innovate these models and systems, and then more accurately predict the results of the game. Sports event prediction can capture various attributes, including team game video, game results, and player data. Different stakeholders use different methods to predict the outcome of the game. This article is mainly based on basketball technical time series statistics, using a three-layer feedforward back-propagation neural network, and adopting a rotation prediction method to predict the most important technical and statistical indicators of the team. According to the team's forecast data, the average field goal percentage is 46.03%, the 3-point field goal percentage is 37.48%, the assists are 12.95, and the backcourt rebounds are 25.4.
Journal: Int. J. of Information Technology and Management
Pages: 386-406
Issue: 3/4
Volume: 22
Year: 2023
Keywords: machine learning; exercise results; real-time prediction; internet of things; IoT.
File-URL: http://www.inderscience.com/link.php?id=131845
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:386-406

Template-Type: ReDIF-Article 1.0
Author-Name: Zhao-quan Jian
Author-X-Name-First: Zhao-quan
Author-X-Name-Last: Jian
Author-Name: Mohamed Ali Osman
Author-X-Name-First: Mohamed Ali
Author-X-Name-Last: Osman
Author-Name: Lei Li
Author-X-Name-First: Lei
Author-X-Name-Last: Li
Title: The effects of relationship quality and knowledge sharing on service innovation performance: organisational learning as a mediator
Abstract:
Drawing on RBV and service dominant logic and using data collected from 243 companies, this paper aims at examining the interplays between relationship quality, knowledge sharing, organisational learning, and service innovation performance. This empirical research found that knowledge sharing and relationship quality were significantly related to organisational learning, and that in turn significantly affected service innovation performance. Moreover, better relationship quality would yield improved knowledge sharing. Furthermore, we propose that organisational learning is a significant mediator through which knowledge sharing influences firm performance, and that relationship quality is also a critical factor that facilitates service innovation.
Journal: Int. J. of Information Technology and Management
Pages: 1-12
Issue: 1/2
Volume: 22
Year: 2023
Keywords: relationship quality; knowledge sharing; organisational learning; service innovation performance.
File-URL: http://www.inderscience.com/link.php?id=130057
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:1-12

Template-Type: ReDIF-Article 1.0
Author-Name: P.G. Saleeshya
Author-X-Name-First: P.G.
Author-X-Name-Last: Saleeshya
Author-Name: R. Rahul
Author-X-Name-First: R.
Author-X-Name-Last: Rahul
Title: Impact of e-commerce on supply chain management
Abstract:
E-commerce is web-enabled technology that brought significant changes in the supply chain activities of an industry. Supply chain management has become a major strategy in manufacturing and service industry. An attempt has made in this paper on identifying the significant factors that affect the e-commerce adoption in the supply chain of a company, identifying the effects of e-commerce on different aspects of supply chain. The study also identifies the major performance parameters of a supply chain and effect of e-commerce adoption on these supply chain variables. An attempt has been made to propose a conceptual model for the study based on the existing literature and field study; the model is validated by academic experts and also experts in industry. Correlation analysis is being carried out to find gap between the ideal and actual situation.
Journal: Int. J. of Information Technology and Management
Pages: 13-31
Issue: 1/2
Volume: 22
Year: 2023
Keywords: supply chain; e-commerce; correlation; conceptual model.
File-URL: http://www.inderscience.com/link.php?id=130058
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:13-31

Template-Type: ReDIF-Article 1.0
Author-Name: Artur Strasser
Author-X-Name-First: Artur
Author-X-Name-Last: Strasser
Author-Name: Susanne Strahringer
Author-X-Name-First: Susanne
Author-X-Name-Last: Strahringer
Author-Name: Markus Westner
Author-X-Name-First: Markus
Author-X-Name-Last: Westner
Title: Determinants of success and failure of knowledge transfer in information systems offshoring: a ranking-type Delphi study
Abstract:
The transfer of knowledge from client to service provider poses major challenges in information systems (IS) offshoring projects. Knowledge transfer directly affects IS offshoring success. Therefore, associated challenges must be overcome. Our study examines the determinants of success and failure of knowledge transfer in IS offshoring projects based on a ranking-type Delphi study. We questioned 32 experts from Germany, each with more than ten years of experience in near- or offshore initiatives to seek a consensus among them. We identified 19 success and 20 failure determinants. These determinants are ranked in order of importance using best-worst scaling. Aspects of closer cooperation are critical for effective knowledge transfer. This includes regular collaboration, willingness to help and support, and mutual trust. In contrast, critical determinants of failure are concerned with fears and fluctuation of human resources. Hidden ambiguities or knowledge gaps, an unwillingness and disability to share knowledge, and high fluctuation of human resources negatively impact knowledge transfer.
Journal: Int. J. of Information Technology and Management
Pages: 32-56
Issue: 1/2
Volume: 22
Year: 2023
Keywords: best-worst scaling; BWS; Delphi; determinants of success; determinants of failure; information systems; IS; information systems offshoring; knowledge transfer; ranking-type Delphi.
File-URL: http://www.inderscience.com/link.php?id=130059
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:32-56

Template-Type: ReDIF-Article 1.0
Author-Name: Wenlong Zhu
Author-X-Name-First: Wenlong
Author-X-Name-Last: Zhu
Author-Name: Shiye Wang
Author-X-Name-First: Shiye
Author-X-Name-Last: Wang
Title: How to evaluate brand extension in the mobile internet environment
Abstract:
How to successfully implement a brand extension has been a common topic among global enterprises. Mobile internet (M-internet), a new information and communication technology, creates suitable conditions for enterprise brand extension. However, little research related to brand extension evaluation has addressed M-internet. From the perspective of the consumer, this study constructs a brand extension evaluation model based on the task-technology fit (TTF) and the Aaker and Keller model (A&K model), and analyses the influencing mechanism of brand extension evaluation by using the structural equation modelling (SEM). The final results show that technical characteristics of M-internet produce a positive effect on attitude of parent brand. Furthermore, attitude of parent brand positively influences the brand extension evaluation, brand trust and perceived fit. Lastly, brand extension evaluation is subject to the positive impact of brand trust and perceived fit in addition to attitude of parent brand.
Journal: Int. J. of Information Technology and Management
Pages: 57-75
Issue: 1/2
Volume: 22
Year: 2023
Keywords: mobile internet; brand extension evaluation; structural equation modelling; SEM; mediation effect.
File-URL: http://www.inderscience.com/link.php?id=130060
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:57-75

Template-Type: ReDIF-Article 1.0
Author-Name: Luis Guillermo Martinez Ballesteros
Author-X-Name-First: Luis Guillermo Martinez
Author-X-Name-Last: Ballesteros
Author-Name: Per Jonny Nesse
Author-X-Name-First: Per Jonny
Author-X-Name-Last: Nesse
Author-Name: Jan Markendahl
Author-X-Name-First: Jan
Author-X-Name-Last: Markendahl
Title: QoE-based service differentiation: an analysis of the business implications for the mobile services market
Abstract:
Mobile network operators (MNOs) face a future characterised with new challenges, such as growing data consumption, a slowdown in subscriber growth and reduced revenues due to the success of over-the-top providers. MNOs must offer affordable services and provide innovative strategies to retain current customers. Quality of experience (QoE) is a well-established methodology for measuring the overall level of customer satisfaction and has also been presented as a way to improve telecommunication services. However, there is still a lack of knowledge on how the MNOs can take advantage of QoE and its potential benefits. In this paper, we explored the implications of the incorporation of QoE feedback in mobile networks at the business level. The analysis shows that value-added offers of differentiated and personalised services can be seen as alternatives to generate new revenue streams in the mobile service market.
Journal: Int. J. of Information Technology and Management
Pages: 76-109
Issue: 1/2
Volume: 22
Year: 2023
Keywords: quality of experience; QoE; business models; mobile networks; service differentiation.
File-URL: http://www.inderscience.com/link.php?id=130061
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:76-109

Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Xie
Author-X-Name-First: Xiang
Author-X-Name-Last: Xie
Author-Name: Yingte Wang
Author-X-Name-First: Yingte
Author-X-Name-Last: Wang
Author-Name: Ying Cui
Author-X-Name-First: Ying
Author-X-Name-Last: Cui
Title: Research on evaluation of network payment security
Abstract:
This paper collects data about network payment fraud through a questionnaire and then analyses the data. We propose a prediction model based on the hybrid support degree apriori algorithm. First, is to find out the factors that are closely related to the success of cheating. Then, we find for the nodes of the decision tree and their importance by using the ID3 algorithm to construct the decision tree. We then construct and verify the evaluation index system of the network payment from the user's point of view while considering the results of association rules and decision tree, and combined with principal component analysis and text mining results. Finally, we determine the weight using entropy method. With the proposed model, we can determine the probability of being deceived according to the situation of different people. This not only reminds people to be vigilant but also provides a reference for the community.
Journal: Int. J. of Information Technology and Management
Pages: 110-126
Issue: 1/2
Volume: 22
Year: 2023
Keywords: apriori algorithm; ID3 algorithm; internet payment security; styling; evaluation system; principal component analysis; entropy method.
File-URL: http://www.inderscience.com/link.php?id=130062
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:110-126

Template-Type: ReDIF-Article 1.0
Author-Name: Arushi Jain
Author-X-Name-First: Arushi
Author-X-Name-Last: Jain
Author-Name: Vishal Bhatnagar
Author-X-Name-First: Vishal
Author-X-Name-Last: Bhatnagar
Author-Name: Nilanjan Dey
Author-X-Name-First: Nilanjan
Author-X-Name-Last: Dey
Author-Name: Amira S. Ashour
Author-X-Name-First: Amira S.
Author-X-Name-Last: Ashour
Author-Name: Fuqian Shi
Author-X-Name-First: Fuqian
Author-X-Name-Last: Shi
Title: Scrutinising medical practitioners' Twitter feeds: an analysis
Abstract:
Mining of social media data has found widespread applications in recent times. Twitter feeds and Facebook posts are being used to device product marketing strategies, sentiment analysis, financial predictions and forebode alarming situations. Twitter feeds analysis can be applied for analysing the behaviour and experiences of medical practitioners. Doctors' informal conversations on Twitter can provide deep insights about their work experiences, their concerns about the profession, their feelings - pathos or excitement they feel - and the affecting conditions. In the present work, Twitter feed of doctors along with the Twitter hashtags are used to collect data from tweets with hashtags such as #DoctorProblems. Afterward, data analysis was performed to determine the major problems faced by the members of the medical fraternity. These problems were categorised into five main categories. The multi-label na
Journal: Int. J. of Information Technology and Management
Pages: 127-139
Issue: 1/2
Volume: 22
Year: 2023
Keywords: big data; Hadoop distributed file system; HDFS; MapReduce; naïve Bayes multi-label classifier; Tweets; evaluation-based measure; label-based measure.
File-URL: http://www.inderscience.com/link.php?id=130063
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:127-139

Template-Type: ReDIF-Article 1.0
Author-Name: Ron Ziv
Author-X-Name-First: Ron
Author-X-Name-Last: Ziv
Author-Name: Oded Koren
Author-X-Name-First: Oded
Author-X-Name-Last: Koren
Author-Name: Nir Perel
Author-X-Name-First: Nir
Author-X-Name-Last: Perel
Title: Big data block impact within big data environment
Abstract:
Handling data is becoming more and more complex. A higher velocity of data is created as more people have access to data generating devices such as computers, mobile phones, medical devices, home appliances, etc. Data files, such as user activity logs, system logs and so on, are stored in HDFS big data platform in various sizes, which takes into consideration the business requirements, infrastructure parameters, administration decisions, and other factors. Dividing the data files (in various volumes) without taking into consideration the HDFS™ predefined block size, may create performance issues that can affect the system's activity. This paper presents how HDFS™ block design affects the performance of Apache™ Hadoop® big data environment by testing different architectures for reading, writing, and querying identical datasets. We designed three scenarios to illustrate different file divisions on the big data platform. The findings present a significant impact on the performance of a system in accordance with the architecture deployed.
Journal: Int. J. of Information Technology and Management
Pages: 140-159
Issue: 1/2
Volume: 22
Year: 2023
Keywords: information management; architecture; HDFS; performance; big data; block partition.
File-URL: http://www.inderscience.com/link.php?id=130064
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:140-159

Template-Type: ReDIF-Article 1.0
Author-Name: Peng Xiao
Author-X-Name-First: Peng
Author-X-Name-Last: Xiao
Title: A reliability and security enhanced framework for cloud-based storage systems
Abstract:
In cloud computing environments, reliable and secure data storage service plays a more and more important role in many data-intensive applications. However, existing storage systems either fail to provide them or provide them in a cost-ineffective manner. To provide better storage service in nowadays cloud environments, we propose a novel framework called reliability and security enhanced cloud storage (RSCS), which consists of several well-designed components to improve low-level data reliability as well as guarantee up-level data accessing security. In the RSCS framework, a simple yet effective file system scheme is proposed, which can duplicate stripped data in different storage nodes so as to increase the data reliability and aggregated throughput. We also introduce a centralised leasing mechanism, which allows accessing different portions of a file based on the multiple-reader-single-writer principle. Finally, we provide a secure data accessing tunnel technology, which allows the RSCS to establish secure communication channels between users and storage nodes without introducing too many extra costs. In a real-world cloud platform, we conduct sets of experiments and the results show that the proposed RSCS framework is able to meet the requirements for most of cloud-based storage platforms.
Journal: Int. J. of Information Technology and Management
Pages: 160-174
Issue: 1/2
Volume: 22
Year: 2023
Keywords: cloud storage; data security; replication service; file system.
File-URL: http://www.inderscience.com/link.php?id=130065
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:1/2:p:160-174

Template-Type: ReDIF-Article 1.0
Author-Name: Yizhi Li
Author-X-Name-First: Yizhi
Author-X-Name-Last: Li
Author-Name: Xiangming Zhou
Author-X-Name-First: Xiangming
Author-X-Name-Last: Zhou
Title: Optimisation of outlier data mining algorithm for large datasets based on unit
Abstract:
This article aims to study the cell-based outlier data mining algorithm for large datasets, and to further improve the profit group data mining algorithm. This experiment first uses mathematical statistical analysis methods to study the optimisation of large data sets based on the unit-based outlier data mining algorithm and the proportion of data mining in various categories of the internet of things; then uses data statistics methods to classify and analyse large data sets, and test normal data mining optimisation algorithms. Finally, the experimental data shows that data mining has been significantly improved in terms of speed, intelligent internet of things, intelligent transportation, big data, genetic algorithms, etc. Experimental data testing shows that the algorithm can quickly and efficiently mine outliers in the dataset, and increase the detection speed of outliers by about 32%, which has guiding significance for outlier data mining in large datasets.
Journal: Int. J. of Information Technology and Management
Pages: 175-189
Issue: 3/4
Volume: 22
Year: 2023
Keywords: outlier data; algorithm optimisation; big dataset; intelligent internet of things; IoT; mining speed.
File-URL: http://www.inderscience.com/link.php?id=131804
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:175-189

Template-Type: ReDIF-Article 1.0
Author-Name: Li Wan
Author-X-Name-First: Li
Author-X-Name-Last: Wan
Author-Name: Xiao Hu
Author-X-Name-First: Xiao
Author-X-Name-Last: Hu
Title: Scheduling and monitoring on engineering vehicles based on IoT
Abstract:
With the development of information technology, the traditional logistics industry is given an opportunity to improve the time to process information. In this paper, we design an intelligent logistics platform based on internet of things (IoT). The locations and dynamic data of vehicles are collected using intelligent equipment on the platform. Moreover, we build a mathematical model based on collected data for a transportation problem, which is solved by Lingo to obtain an intelligent schedule. Our solution of scheduling and monitoring of engineering vehicles based on IoT can help enterprises reduce operational costs and improve service quality.
Journal: Int. J. of Information Technology and Management
Pages: 190-202
Issue: 3/4
Volume: 22
Year: 2023
Keywords: scheduling; monitoring; engineering vehicles; IoT; intelligent logistics.
File-URL: http://www.inderscience.com/link.php?id=131805
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:190-202

Template-Type: ReDIF-Article 1.0
Author-Name: Hailan Pan
Author-X-Name-First: Hailan
Author-X-Name-Last: Pan
Author-Name: Shi Yin
Author-X-Name-First: Shi
Author-X-Name-Last: Yin
Title: Precision advertising and optimisation strategy based on big data algorithms
Abstract:
This article aims to study the precise placement and optimisation strategies of advertisements based on big data algorithms. This article first proposes four different methods to estimate and approximate the quantitative analysis of the placement of high-precision data advertisements. Secondly, the advertising platform discussed in this article is an independent B/S system, the entire platform includes a back-end system that maintains advertising materials and advertising, a user behaviour collection system, user behaviour analysis, and recommendations for advertising based on interest. Results of the experiment showed that the application of the algorithms to enable large data transmission process of advertising content could reasonably resolve diiklanake, ad interaction that is not good, data manipulation and data burning, and problems of data manipulation and data leakage. Additionally, the accuracy of advertising has increased by 25.2%.
Journal: Int. J. of Information Technology and Management
Pages: 203-212
Issue: 3/4
Volume: 22
Year: 2023
Keywords: big data algorithm; accurate advertising; optimisation strategy; collaborative filtering algorithm.
File-URL: http://www.inderscience.com/link.php?id=131806
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:203-212

Template-Type: ReDIF-Article 1.0
Author-Name: Li-Jun Yang
Author-X-Name-First: Li-Jun
Author-X-Name-Last: Yang
Title: Parallel machine scheduling optimisation based on an improved multi-objective artificial bee colony algorithm
Abstract:
Aiming at the scheduling model of the same kind of machine, considering that low carbon emission is an urgent problem to be solved in the manufacturing industry, a mathematical model containing the maximum completion time and maximum processing energy consumption was established. In order to balance the local development ability and global search ability of an artificial bee colony algorithm, and improve the convergence speed of the algorithm, a scheduling optimisation method of parallel machine based on improved multi-objective ABC algorithm was proposed. Firstly, a chaotic image initialisation method is proposed to ensure the diversity and excellence of the initial population. Then, the individual threshold is used to dynamically adjust the search radius to improve the search accuracy and convergence speed. Finally, considering the development times of the external archive solution, the evolution is guided by selecting the elite solution reasonably. In order to verify the effectiveness of the algorithm, comparative experiments and performance analysis of the algorithm are carried out on several examples. The results show that the proposed algorithm can solve the scheduling problem of the same kind of machine effectively in practical scenarios.
Journal: Int. J. of Information Technology and Management
Pages: 213-225
Issue: 3/4
Volume: 22
Year: 2023
Keywords: parallel machine; artificial bee colony; scheduling optimisation; multi-objective.
File-URL: http://www.inderscience.com/link.php?id=131807
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:213-225

Template-Type: ReDIF-Article 1.0
Author-Name: Weixian Wang
Author-X-Name-First: Weixian
Author-X-Name-Last: Wang
Title: Application of a multi-channel attention mechanism in text classification of new media
Abstract:
Sentiment analysis of new media text has become a research hotspot in recent years. In order to more effectively analyse the emotional polarity of new media text, this paper proposes a text classification algorithm based on a multi-channel attention mechanism. First, channels based on bidirectional gating recurrent unit (BiGRU) neural network are used to extract semantic features, while channels based on fully connected neural network are used to extract emotional features. In order to extract the key information better, the attention mechanism is introduced into the two channels respectively, and the bidirectional encoder representation technology based on converter is used to provide the word vectors. Then, the real emotional semantics are embedded into the model through the dynamic adjustment of the word vector by the context. Finally, the semantic features and emotional features of the double channels are fused to obtain the final semantic expression. In the experiment part, NLPCC2014 dataset and microblog data captured by crawler are used for comparative experiment. The experimental results show that the proposed multi-channel attention mechanism method can enhance the ability of emotion semantic capture, and improve the performance of emotion classification.
Journal: Int. J. of Information Technology and Management
Pages: 226-239
Issue: 3/4
Volume: 22
Year: 2023
Keywords: new media; sentiment analysis; multi-channel; attention mechanism.
File-URL: http://www.inderscience.com/link.php?id=131808
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:226-239

Template-Type: ReDIF-Article 1.0
Author-Name: Hongjun Jia
Author-X-Name-First: Hongjun
Author-X-Name-Last: Jia
Title: Innovation and entrepreneurship orientation and suggestions for new engineering computer majors under the background of artificial intelligence
Abstract:
With the advent of the era of artificial intelligence, Chinese universities are also shouldering the heavy responsibility of cultivating innovative talents. In this paper, a variety of methods such as literature, questionnaire, and mathematical statistics are used to design a new engineering computer innovation and entrepreneurship education experiment. This paper analyses the problems existing in the current training programs of computer majors in colleges and universities, and grasps the understanding, difficulties and needs of computer majors on innovation and entrepreneurship. The survey results show that among the respondents, 51.63% of the students believe that entrepreneurship is a good choice, and 23.48% of the students are starting or have experienced entrepreneurship. In the requirements of computer professional employ ability; the frequency of selection of practical ability and innovation ability is as high as 97.59% and 95.58%, which is enough to show the importance of practical ability and innovation ability.
Journal: Int. J. of Information Technology and Management
Pages: 240-261
Issue: 3/4
Volume: 22
Year: 2023
Keywords: artificial intelligence; new engineering; computer science; innovation and entrepreneurship.
File-URL: http://www.inderscience.com/link.php?id=131809
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:240-261

Template-Type: ReDIF-Article 1.0
Author-Name: Aiju Wang
Author-X-Name-First: Aiju
Author-X-Name-Last: Wang
Title: Embedded system architecture-computer embedded software defect prediction based on genetic optimisation algorithms
Abstract:
With the rapid development of electronic measurement technology, people have put forward higher requirements for the diversity of oscilloscope functions and abundant peripheral interfaces. This paper aims to use genetic optimisation algorithms to detect embedded software defects, provide users with prepared defect information, and improve the efficiency and accuracy of detection. This paper proposes popular algorithms for moving target video detection, selection operator, crossover operator and mutation operator, and establishes a complete system, deepening a virtual simulation environment for embedded software development model. In addition, from hardware simulation to the detection of software defects such as memory leaks and uninitialised variables, they are all included in the system and run through the entire process of embedded software development. The experimental results in this paper show that the complete simulation technology has realised a multi-architecture emulator Emu, combined with the defect detection software Valgrind, has realised a complete lack of phase detection system, and the detection rate is as high as 96.7%.
Journal: Int. J. of Information Technology and Management
Pages: 262-280
Issue: 3/4
Volume: 22
Year: 2023
Keywords: embedded system architecture; genetic optimisation algorithm; computer embedded; software defect.
File-URL: http://www.inderscience.com/link.php?id=131814
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:262-280

Template-Type: ReDIF-Article 1.0
Author-Name: Fan Zhang
Author-X-Name-First: Fan
Author-X-Name-Last: Zhang
Author-Name: Yu Su
Author-X-Name-First: Yu
Author-X-Name-Last: Su
Title: O2O customer big data analysis system based on embedded technology
Abstract:
In modern production and control, the application of data acquisition system is extremely common. In order to study the operability of embedded new technology applied to big data analysis, this paper adopts big data query method, system construction method and data export method to collect samples and analyse the data acquisition system. In the introduction to the data acquisition method, the absolute error of a single measurement is first calculated. Analysis of the two gauge blocks, 1.0 mm and 1.1 mm, showed that the absolute error of the results was less than 0.5 microns when four measurements were taken. The experimental results show that the system has high data acquisition accuracy and stable and reliable data output.
Journal: Int. J. of Information Technology and Management
Pages: 281-300
Issue: 3/4
Volume: 22
Year: 2023
Keywords: embedded technology; O2O customers' introduction; big data technology; data mining; analysis system.
File-URL: http://www.inderscience.com/link.php?id=131815
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:281-300

Template-Type: ReDIF-Article 1.0
Author-Name: Xianyu Wang
Author-X-Name-First: Xianyu
Author-X-Name-Last: Wang
Title: Research on application of optimal particle swarm optimisation algorithm in logistics route improvement
Abstract:
Aiming at the logistics path optimisation model, the author converts the logistics path optimisation problem into a classical travelling salesman problem in the field of mathematics. The adaptive particle swarm optimisation algorithm is used to dispose of the model problem. In the algorithm, each particle has four behaviour evolution strategies, and the individual speed and position are updated by selecting the strategy with the highest probability. An adaptive particle swarm optimisation algorithm is proposed. The algorithm improves the speed of individual optimisation by using probabilistic mutation algorithm of policy behaviour, which avoids falling into local optimal solution. For the purpose of demonstrating the effectiveness and performance of the method, comparative experiments are conducted on the open source Oliver30 dataset. Experimental results show that the average path length achieved by the proposed method is closer to the optimal value, and the convergence speed is fast.
Journal: Int. J. of Information Technology and Management
Pages: 301-314
Issue: 3/4
Volume: 22
Year: 2023
Keywords: convergence; particle; swarm; optimisation; multi-strategy; adaptive.
File-URL: http://www.inderscience.com/link.php?id=131816
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:301-314

Template-Type: ReDIF-Article 1.0
Author-Name: Wenlong Jin
Author-X-Name-First: Wenlong
Author-X-Name-Last: Jin
Author-Name: Liujing Wang
Author-X-Name-First: Liujing
Author-X-Name-Last: Wang
Author-Name: Chengting Zhang
Author-X-Name-First: Chengting
Author-X-Name-Last: Zhang
Title: Artificial intelligence and big data in the production process to optimise the parameters of the cut tobacco-making process
Abstract:
With the development of industrial control technology and the acceleration of informatisation construction, the tobacco industry has higher and higher requirements for the scheduling, quality, craftsmanship, and consumption of tobacco production lines. This article aims to use big data and artificial intelligence energy systems to optimise the parameters in the cut tobacco-making process. This paper designs a making process detection system based on artificial intelligence, and uses a database to store big data. It analyses the data through the database, selects an important step in the cut tobacco-making process, and optimises the parameters of threshing and redrying. The speed of beater, hot air temperature and moisture regain temperature in the threshing and redrying process were compared and analysed. Finally, the leaf emergence rate and stem emergence rate are compared between the tobacco shreds with optimised parameters and the unoptimised shredded tobacco. The results show that the optimised parameters are 550, hot air temperature 90°C, and moisture regain temperature 65°C. Additionally, the optimised shredded tobacco has stronger performance than the unoptimised shredded tobacco.
Journal: Int. J. of Information Technology and Management
Pages: 315-334
Issue: 3/4
Volume: 22
Year: 2023
Keywords: artificial intelligence and big data; cut tobacco-making process; parameter optimisation; optimisation process.
File-URL: http://www.inderscience.com/link.php?id=131823
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:315-334

Template-Type: ReDIF-Article 1.0
Author-Name: Qiang Ma
Author-X-Name-First: Qiang
Author-X-Name-Last: Ma
Title: Design and implementation of corporate governance automated decision model based on web data
Abstract:
As a global, dynamic interactive and cross platform distributed graphic information system based on the hypertext and HTTP, the web provides a graphical and easy to access intuitive interface for users to find information, and organises the information nodes into an interrelated network structure. In corporate governance, information mining and processing is particularly important. Web data can provide a large amount of high-dimensional structured and unstructured data for corporate decision makers to make more effective management decisions. Therefore, this paper attempts to build a model to help managers improve their decision-making ability and corporate governance. Through the integration of web data, this paper tests the impact of executives' ME on perks. The results show that the background characteristics of executives could affect their decision making, and the model can be established under certain constraints. This paper enriches the application of decision-making model to improve the level of corporate governance.
Journal: Int. J. of Information Technology and Management
Pages: 335-353
Issue: 3/4
Volume: 22
Year: 2023
Keywords: web; automated decision; corporate governance; decision support system; marketisation.
File-URL: http://www.inderscience.com/link.php?id=131825
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:335-353

Template-Type: ReDIF-Article 1.0
Author-Name: Bahao Li
Author-X-Name-First: Bahao
Author-X-Name-Last: Li
Title: Development of regional agricultural e-commerce in China based on CAS
Abstract:
The paper makes an exploration of the mode of agricultural production and operation. Based on the analysis of the demand of farmers for e-commerce, and with the intelligent sensor connected to the internet of things, an attempt to propose the solution of 'internet plus agricultural business' is put forward. The main regional agricultural products in China are aquatic products. In 2016, the total output of aquatic products was 2.853 million tons, of which the output of pelagic fishery and mariculture were 449,000 tons and 167,000 tons respectively. The total agricultural output value of crops ranked second, including 152,000 tons of grain, 37,000 tons of vegetables and 24,000 tons of fruits. The e-commerce of agricultural products effectively introduces e-commerce into the traditional trade of agricultural products and realises the organic combination of the two. It avoids the shortcomings of the traditional agricultural products trading system.
Journal: Int. J. of Information Technology and Management
Pages: 354-372
Issue: 3/4
Volume: 22
Year: 2023
Keywords: intelligent systems; regional agricultural products; e-commerce development; intelligent sensors.
File-URL: http://www.inderscience.com/link.php?id=131827
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Handle: RePEc:ids:ijitma:v:22:y:2023:i:3/4:p:354-372