Pub Date : 2019-10-17DOI: 10.1504/ijenm.2019.10024736
M. Sundarambal, Raman Sandhiya
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.
{"title":"Chicken swarm optimisation based clustering of biomedical documents and health records to improve telemedicine applications","authors":"M. Sundarambal, Raman Sandhiya","doi":"10.1504/ijenm.2019.10024736","DOIUrl":"https://doi.org/10.1504/ijenm.2019.10024736","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42879593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-17DOI: 10.1504/IJENM.2019.10022915
G. Gokilakrishnan, P. Varthanan
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.
{"title":"Development of manufacturing - distribution plan considering quality cost","authors":"G. Gokilakrishnan, P. Varthanan","doi":"10.1504/IJENM.2019.10022915","DOIUrl":"https://doi.org/10.1504/IJENM.2019.10022915","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46155761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-17DOI: 10.1504/ijenm.2019.10024740
Gowri Thangam Jeyaraj, A. Sankar
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.
{"title":"Extreme learning machine and K-means clustering for the improvement of link prediction in social networks using analytic hierarchy process","authors":"Gowri Thangam Jeyaraj, A. Sankar","doi":"10.1504/ijenm.2019.10024740","DOIUrl":"https://doi.org/10.1504/ijenm.2019.10024740","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47881992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-17DOI: 10.1504/IJENM.2019.10023275
P. Damodharan, C. Ravichandran
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.
{"title":"Inclusive strategic techno-economic framework to incorporate essential aspects of web mining for the perspective of business success","authors":"P. Damodharan, C. Ravichandran","doi":"10.1504/IJENM.2019.10023275","DOIUrl":"https://doi.org/10.1504/IJENM.2019.10023275","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49563306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-17DOI: 10.1504/ijenm.2019.103153
T. Anand, R. Pandian
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.
{"title":"A customer-based supply chain network design","authors":"T. Anand, R. Pandian","doi":"10.1504/ijenm.2019.103153","DOIUrl":"https://doi.org/10.1504/ijenm.2019.103153","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/ijenm.2019.103153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45635322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-17DOI: 10.1504/ijenm.2019.10024738
V. Navya, P. Deepalakshmi
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.
{"title":"Effective transmission of critical parameters in heterogeneous wireless body area sensor networks","authors":"V. Navya, P. Deepalakshmi","doi":"10.1504/ijenm.2019.10024738","DOIUrl":"https://doi.org/10.1504/ijenm.2019.10024738","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43080922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-27DOI: 10.1504/IJENM.2019.10022250
M. Prasad, K. Ganesan, K. Paranitharan, R. Rajesh
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.
{"title":"An analytical study of lean implementation measures in pump industries in India","authors":"M. Prasad, K. Ganesan, K. Paranitharan, R. Rajesh","doi":"10.1504/IJENM.2019.10022250","DOIUrl":"https://doi.org/10.1504/IJENM.2019.10022250","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45062626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-27DOI: 10.1504/IJENM.2019.10022256
S. Mohapatra
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.
{"title":"Critical review of literature and development of a framework for application of artificial intelligence in business","authors":"S. Mohapatra","doi":"10.1504/IJENM.2019.10022256","DOIUrl":"https://doi.org/10.1504/IJENM.2019.10022256","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46725258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-27DOI: 10.1504/IJENM.2019.10022245
A. Maruthamuthu, M. Punniyamoorthy, S. Paluru, Sindhura Tammuluri
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.
{"title":"Prediction of carotid atherosclerosis in patients with impaired glucose tolerance - a performance analysis of machine learning techniques","authors":"A. Maruthamuthu, M. Punniyamoorthy, S. Paluru, Sindhura Tammuluri","doi":"10.1504/IJENM.2019.10022245","DOIUrl":"https://doi.org/10.1504/IJENM.2019.10022245","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46891095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-27DOI: 10.1504/IJENM.2019.10022254
M. K. Marichelvam, M. Geetha
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.
{"title":"A hybrid algorithm to solve the stochastic flow shop scheduling problems with machine break down","authors":"M. K. Marichelvam, M. Geetha","doi":"10.1504/IJENM.2019.10022254","DOIUrl":"https://doi.org/10.1504/IJENM.2019.10022254","url":null,"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.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44094559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：