Tourism industry in Malaysia has been customarily thought and advanced towards universal markets since its early stages arrange in 1960s. Currently, study about tourism knowledge discovery is very little being addressed. The previous studies are still insufficient to extract important insights from tourism data within Malaysia context. Therefore, this paper aims to analyze profiles of tourists using data mining decision tree techniques where several combinations of the number of branches (2 and 3 branches) and different target splitting rules (Entropy, Gini, and Probability Chi-square) have been applied on comprehensive survey data and to find out the best performing algorithm among the six models for tourism knowledge discovery. Results show that there are a various type of tourists with each group having different patterns or rules. This research study can be very helpful for tourist association, hospitality and hotel managers.Tourism industry in Malaysia has been customarily thought and advanced towards universal markets since its early stages arrange in 1960s. Currently, study about tourism knowledge discovery is very little being addressed. The previous studies are still insufficient to extract important insights from tourism data within Malaysia context. Therefore, this paper aims to analyze profiles of tourists using data mining decision tree techniques where several combinations of the number of branches (2 and 3 branches) and different target splitting rules (Entropy, Gini, and Probability Chi-square) have been applied on comprehensive survey data and to find out the best performing algorithm among the six models for tourism knowledge discovery. Results show that there are a various type of tourists with each group having different patterns or rules. This research study can be very helpful for tourist association, hospitality and hotel managers.
{"title":"Tourism knowledge discovery through data mining techniques","authors":"J. Jamil, I. Shaharanee","doi":"10.1063/1.5121092","DOIUrl":"https://doi.org/10.1063/1.5121092","url":null,"abstract":"Tourism industry in Malaysia has been customarily thought and advanced towards universal markets since its early stages arrange in 1960s. Currently, study about tourism knowledge discovery is very little being addressed. The previous studies are still insufficient to extract important insights from tourism data within Malaysia context. Therefore, this paper aims to analyze profiles of tourists using data mining decision tree techniques where several combinations of the number of branches (2 and 3 branches) and different target splitting rules (Entropy, Gini, and Probability Chi-square) have been applied on comprehensive survey data and to find out the best performing algorithm among the six models for tourism knowledge discovery. Results show that there are a various type of tourists with each group having different patterns or rules. This research study can be very helpful for tourist association, hospitality and hotel managers.Tourism industry in Malaysia has been customarily thought and advanced towards universal markets since its early stages arrange in 1960s. Currently, study about tourism knowledge discovery is very little being addressed. The previous studies are still insufficient to extract important insights from tourism data within Malaysia context. Therefore, this paper aims to analyze profiles of tourists using data mining decision tree techniques where several combinations of the number of branches (2 and 3 branches) and different target splitting rules (Entropy, Gini, and Probability Chi-square) have been applied on comprehensive survey data and to find out the best performing algorithm among the six models for tourism knowledge discovery. Results show that there are a various type of tourists with each group having different patterns or rules. This research study can be very helpful for tourist association, hospitality and hotel managers.","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"54 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114981505","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}
Rahma Zuhra, H. Akhadkulov, T. Y. Ying, M. Noorani
{"title":"A υ-fixed point under (ψ, θ, ϕ)-weak contraction conditions in partially ordered quasi metric space","authors":"Rahma Zuhra, H. Akhadkulov, T. Y. Ying, M. Noorani","doi":"10.1063/1.5121077","DOIUrl":"https://doi.org/10.1063/1.5121077","url":null,"abstract":"","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439052","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}
Indoor cycling was commonly examined from the riding posture, saddle height or pedal force to analyze the muscular activity on cyclists’ lower limbs. While strong muscular strength and proper riding posture are important to minimize strain, the significances of these attributes on cycling fatigue were unclear. An attempt was made to identify significant attributing features for indoor cycling fatigue classification based on an experimental study involving twenty healthy postgraduates. The participants were tasked to perform an indoor cycling fatigue experiment at 6km/h with gradual speed increment till fatigue level achieved. The accelerometry, sacral trajectory and the lower limb kinematic changes were measured. Significant feature subset selection was determined using the wrapper approach with IBk algorithm. The featured data were later classified on IBk, SMO, ZeroR, J48 and Vote followed by subsequent discriminant analysis. The results demonstrated that the significant attributes yielded 95.0% and 75% ...
{"title":"Significant attributes identification for indoor cycling fatigue classification","authors":"S. Tang, W. P. Loh, M. Tamagawa","doi":"10.1063/1.5121137","DOIUrl":"https://doi.org/10.1063/1.5121137","url":null,"abstract":"Indoor cycling was commonly examined from the riding posture, saddle height or pedal force to analyze the muscular activity on cyclists’ lower limbs. While strong muscular strength and proper riding posture are important to minimize strain, the significances of these attributes on cycling fatigue were unclear. An attempt was made to identify significant attributing features for indoor cycling fatigue classification based on an experimental study involving twenty healthy postgraduates. The participants were tasked to perform an indoor cycling fatigue experiment at 6km/h with gradual speed increment till fatigue level achieved. The accelerometry, sacral trajectory and the lower limb kinematic changes were measured. Significant feature subset selection was determined using the wrapper approach with IBk algorithm. The featured data were later classified on IBk, SMO, ZeroR, J48 and Vote followed by subsequent discriminant analysis. The results demonstrated that the significant attributes yielded 95.0% and 75% ...","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116502919","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}
Nur Izyan Mustafa Khalid, Nur Farah Najeeha Najdi, Nurul Faziera Khairul Adlee, M. Misiran, Hasimah Sapiri
Railway safety is an important issue since the safety of passengers, employees, road users and residents in the area of railway can be affected when railway accidents happen. However in Malaysia, the risk management for railway safety is still new, thus few studies available in the literature. In this study, measurement models involving descriptive analysis and event tree analysis for Keretapi Tanah Melayu Berhad (KTMB)’s railway accident risk are developed by considering the primary and secondary data from KTMB. The finding shows collective risk of 0.2406, in which a strong 0.217 is influenced by human error of not following the predetermined standard operating procedures, and only 0.0232 of this risk is caused by the systematic failure. The determinant factors of such accidents include carelessness, conductor’s effect, mechanical failure, high speed, human negligence, and track’s obstruction.Railway safety is an important issue since the safety of passengers, employees, road users and residents in the area of railway can be affected when railway accidents happen. However in Malaysia, the risk management for railway safety is still new, thus few studies available in the literature. In this study, measurement models involving descriptive analysis and event tree analysis for Keretapi Tanah Melayu Berhad (KTMB)’s railway accident risk are developed by considering the primary and secondary data from KTMB. The finding shows collective risk of 0.2406, in which a strong 0.217 is influenced by human error of not following the predetermined standard operating procedures, and only 0.0232 of this risk is caused by the systematic failure. The determinant factors of such accidents include carelessness, conductor’s effect, mechanical failure, high speed, human negligence, and track’s obstruction.
{"title":"Assessing railway accident risk through event tree analysis","authors":"Nur Izyan Mustafa Khalid, Nur Farah Najeeha Najdi, Nurul Faziera Khairul Adlee, M. Misiran, Hasimah Sapiri","doi":"10.1063/1.5121060","DOIUrl":"https://doi.org/10.1063/1.5121060","url":null,"abstract":"Railway safety is an important issue since the safety of passengers, employees, road users and residents in the area of railway can be affected when railway accidents happen. However in Malaysia, the risk management for railway safety is still new, thus few studies available in the literature. In this study, measurement models involving descriptive analysis and event tree analysis for Keretapi Tanah Melayu Berhad (KTMB)’s railway accident risk are developed by considering the primary and secondary data from KTMB. The finding shows collective risk of 0.2406, in which a strong 0.217 is influenced by human error of not following the predetermined standard operating procedures, and only 0.0232 of this risk is caused by the systematic failure. The determinant factors of such accidents include carelessness, conductor’s effect, mechanical failure, high speed, human negligence, and track’s obstruction.Railway safety is an important issue since the safety of passengers, employees, road users and residents in the area of railway can be affected when railway accidents happen. However in Malaysia, the risk management for railway safety is still new, thus few studies available in the literature. In this study, measurement models involving descriptive analysis and event tree analysis for Keretapi Tanah Melayu Berhad (KTMB)’s railway accident risk are developed by considering the primary and secondary data from KTMB. The finding shows collective risk of 0.2406, in which a strong 0.217 is influenced by human error of not following the predetermined standard operating procedures, and only 0.0232 of this risk is caused by the systematic failure. The determinant factors of such accidents include carelessness, conductor’s effect, mechanical failure, high speed, human negligence, and track’s obstruction.","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127125073","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}
University Service Centre (USC) is a one-stop centre for students to acquire all services regarding their studies at a university. It is observed that the waiting time for students to get the services is quite long for some counters. This scenario will give negative feedback and bad reputation to the USC performance. Thus, the purpose of this study is to develop assignment models of counters to services for staff utilization in order to minimize total service time by using Hungarian method. The waiting time of students being served during one-month period is collected and the record shows that there were 7043 students have attended to the services within 17 operation days. The assignment models have been developed to minimize the total service time by considering few scenarios of assigning services to counters. The results show that the total service time can be reduced by having several alternative scenarios. This research has suggested the minimum time of services that can be a guideline for policy making in order to improve the service performance and students’ satisfaction.University Service Centre (USC) is a one-stop centre for students to acquire all services regarding their studies at a university. It is observed that the waiting time for students to get the services is quite long for some counters. This scenario will give negative feedback and bad reputation to the USC performance. Thus, the purpose of this study is to develop assignment models of counters to services for staff utilization in order to minimize total service time by using Hungarian method. The waiting time of students being served during one-month period is collected and the record shows that there were 7043 students have attended to the services within 17 operation days. The assignment models have been developed to minimize the total service time by considering few scenarios of assigning services to counters. The results show that the total service time can be reduced by having several alternative scenarios. This research has suggested the minimum time of services that can be a guideline for policy maki...
{"title":"Application of assignment model in resources utilization of University Service Centre","authors":"Teoh Siew Chin, M. Shokri, Nerda Z. Zaibidi","doi":"10.1063/1.5121087","DOIUrl":"https://doi.org/10.1063/1.5121087","url":null,"abstract":"University Service Centre (USC) is a one-stop centre for students to acquire all services regarding their studies at a university. It is observed that the waiting time for students to get the services is quite long for some counters. This scenario will give negative feedback and bad reputation to the USC performance. Thus, the purpose of this study is to develop assignment models of counters to services for staff utilization in order to minimize total service time by using Hungarian method. The waiting time of students being served during one-month period is collected and the record shows that there were 7043 students have attended to the services within 17 operation days. The assignment models have been developed to minimize the total service time by considering few scenarios of assigning services to counters. The results show that the total service time can be reduced by having several alternative scenarios. This research has suggested the minimum time of services that can be a guideline for policy making in order to improve the service performance and students’ satisfaction.University Service Centre (USC) is a one-stop centre for students to acquire all services regarding their studies at a university. It is observed that the waiting time for students to get the services is quite long for some counters. This scenario will give negative feedback and bad reputation to the USC performance. Thus, the purpose of this study is to develop assignment models of counters to services for staff utilization in order to minimize total service time by using Hungarian method. The waiting time of students being served during one-month period is collected and the record shows that there were 7043 students have attended to the services within 17 operation days. The assignment models have been developed to minimize the total service time by considering few scenarios of assigning services to counters. The results show that the total service time can be reduced by having several alternative scenarios. This research has suggested the minimum time of services that can be a guideline for policy maki...","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129091009","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}
The Cox Proportional Hazard Model (Cox PHM) is commonly employed in survival analysis. It has proportional hazard assumption which is not always satisfied in real application. In such a case, the survival data can be analyzed using non-parametric approaches, one of them is the Survival Least Square Support Vector Machines (SURLS-SVM) recently developed. This approach does not require the proportional hazard assumption and the distribution of survival time can be unknown. Some papers apply SURLS-SVM on both simulation study and real data without considering feature selection. The performance of statistical methods can be determined by choosing relevant features selected as input. Therefore, the feature selection method is necessary to be applied in SURLS-SVM. In this paper, the Cox PHM and the SURLS-SVM with feature selection are applied on simulated data and clinical data, i.e. survival of cervical cancer patients. These two approaches are compared using prognostic index so-called concordance index (c-index). For both data sets, the c-index obtained from SURLS-SVM, with or without feature selection, is much higher than the one obtained from Cox PHM. On the cervical cancer data, SURLS-SVM with feature selection selects 10 relevant features out of 12 features. This also works for Cox PHM with feature selection.The Cox Proportional Hazard Model (Cox PHM) is commonly employed in survival analysis. It has proportional hazard assumption which is not always satisfied in real application. In such a case, the survival data can be analyzed using non-parametric approaches, one of them is the Survival Least Square Support Vector Machines (SURLS-SVM) recently developed. This approach does not require the proportional hazard assumption and the distribution of survival time can be unknown. Some papers apply SURLS-SVM on both simulation study and real data without considering feature selection. The performance of statistical methods can be determined by choosing relevant features selected as input. Therefore, the feature selection method is necessary to be applied in SURLS-SVM. In this paper, the Cox PHM and the SURLS-SVM with feature selection are applied on simulated data and clinical data, i.e. survival of cervical cancer patients. These two approaches are compared using prognostic index so-called concordance index (c-ind...
{"title":"A simulation study and application of feature selection on survival least square support vector machines","authors":"H. A. Khoiri, D. Prastyo, S. W. Purnami","doi":"10.1063/1.5121121","DOIUrl":"https://doi.org/10.1063/1.5121121","url":null,"abstract":"The Cox Proportional Hazard Model (Cox PHM) is commonly employed in survival analysis. It has proportional hazard assumption which is not always satisfied in real application. In such a case, the survival data can be analyzed using non-parametric approaches, one of them is the Survival Least Square Support Vector Machines (SURLS-SVM) recently developed. This approach does not require the proportional hazard assumption and the distribution of survival time can be unknown. Some papers apply SURLS-SVM on both simulation study and real data without considering feature selection. The performance of statistical methods can be determined by choosing relevant features selected as input. Therefore, the feature selection method is necessary to be applied in SURLS-SVM. In this paper, the Cox PHM and the SURLS-SVM with feature selection are applied on simulated data and clinical data, i.e. survival of cervical cancer patients. These two approaches are compared using prognostic index so-called concordance index (c-index). For both data sets, the c-index obtained from SURLS-SVM, with or without feature selection, is much higher than the one obtained from Cox PHM. On the cervical cancer data, SURLS-SVM with feature selection selects 10 relevant features out of 12 features. This also works for Cox PHM with feature selection.The Cox Proportional Hazard Model (Cox PHM) is commonly employed in survival analysis. It has proportional hazard assumption which is not always satisfied in real application. In such a case, the survival data can be analyzed using non-parametric approaches, one of them is the Survival Least Square Support Vector Machines (SURLS-SVM) recently developed. This approach does not require the proportional hazard assumption and the distribution of survival time can be unknown. Some papers apply SURLS-SVM on both simulation study and real data without considering feature selection. The performance of statistical methods can be determined by choosing relevant features selected as input. Therefore, the feature selection method is necessary to be applied in SURLS-SVM. In this paper, the Cox PHM and the SURLS-SVM with feature selection are applied on simulated data and clinical data, i.e. survival of cervical cancer patients. These two approaches are compared using prognostic index so-called concordance index (c-ind...","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128687918","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}
R. C. Mamat, A. Kasa, Siti Fatin Mohd Razali, A. Samad, A. Ramli, M. Yazid
Ground settlement is the main factor in slope stability. This paper reviews the application of artificial intelligence (AI) in predicting the slope ground settlement. The objective of this paper is to discuss the application of AI in three categories i.e. i) ANN, ii) ANFIS and iii) hybrid model which includes research reports over the last ten years. Additionally, future research proposals are presented. ANN is a predictive tool that is often used instead of ANFIS because of its non-linear behavior.Ground settlement is the main factor in slope stability. This paper reviews the application of artificial intelligence (AI) in predicting the slope ground settlement. The objective of this paper is to discuss the application of AI in three categories i.e. i) ANN, ii) ANFIS and iii) hybrid model which includes research reports over the last ten years. Additionally, future research proposals are presented. ANN is a predictive tool that is often used instead of ANFIS because of its non-linear behavior.
地面沉降是影响边坡稳定的主要因素。本文综述了人工智能在边坡地面沉降预测中的应用。本文的目的是讨论人工智能在三类中的应用，即i) ANN, ii) ANFIS和iii)混合模型，其中包括过去十年的研究报告。最后，对今后的研究提出了建议。人工神经网络是一种预测工具，由于其非线性特性，经常被用来代替人工神经网络。地面沉降是影响边坡稳定的主要因素。本文综述了人工智能在边坡地面沉降预测中的应用。本文的目的是讨论人工智能在三类中的应用，即i) ANN, ii) ANFIS和iii)混合模型，其中包括过去十年的研究报告。最后，对今后的研究提出了建议。人工神经网络是一种预测工具，由于其非线性特性，经常被用来代替人工神经网络。
{"title":"Application of artificial intelligence in predicting ground settlement on earth slope","authors":"R. C. Mamat, A. Kasa, Siti Fatin Mohd Razali, A. Samad, A. Ramli, M. Yazid","doi":"10.1063/1.5121094","DOIUrl":"https://doi.org/10.1063/1.5121094","url":null,"abstract":"Ground settlement is the main factor in slope stability. This paper reviews the application of artificial intelligence (AI) in predicting the slope ground settlement. The objective of this paper is to discuss the application of AI in three categories i.e. i) ANN, ii) ANFIS and iii) hybrid model which includes research reports over the last ten years. Additionally, future research proposals are presented. ANN is a predictive tool that is often used instead of ANFIS because of its non-linear behavior.Ground settlement is the main factor in slope stability. This paper reviews the application of artificial intelligence (AI) in predicting the slope ground settlement. The objective of this paper is to discuss the application of AI in three categories i.e. i) ANN, ii) ANFIS and iii) hybrid model which includes research reports over the last ten years. Additionally, future research proposals are presented. ANN is a predictive tool that is often used instead of ANFIS because of its non-linear behavior.","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114143540","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}
Husam Jasim Mohammed, Ihsan Ali Mubarak Al-Jubori, M. M. Kasim
Project management is one of the most important issues to fulfil organizational objectives. The project management criteria are playing a vital role for completion of any project. The aim of this paper is to evaluate five main project criteria (time, cost, quality, risk, and safety) mathematically by using a multi-criteria method in order to assist stakeholders or project managers in decision-making. The fuzzy Analytic Hierarchy Process (AHP) is selected with the use of triangular fuzzy numbers for pairwise comparison scales in prioritizing the criteria in managing projects. Utilizing the fuzzy AHP technique can facilitate uncertainty in doing evaluation. In this study, one expert who is a project manager with many years of experience was asked to carry out the evaluation. The results show that the expert’s main concern in managing project is time, and cost is the second important. The study demonstrates how uncertainty in making evaluation of multiple criteria can be solved by using fuzzy method such as fuzzy AHP, in contrary to the crisp or the traditional AHP which is based on specific values, the evaluator(s) are always ambiguous and vague to give exact judgment. Hence, the application of this fuzzy method can make the assessment outcomes more accurate, scientific, and objective. It is anticipated that this work may serve as a support tool for stakeholders in improving the project management quality level.Project management is one of the most important issues to fulfil organizational objectives. The project management criteria are playing a vital role for completion of any project. The aim of this paper is to evaluate five main project criteria (time, cost, quality, risk, and safety) mathematically by using a multi-criteria method in order to assist stakeholders or project managers in decision-making. The fuzzy Analytic Hierarchy Process (AHP) is selected with the use of triangular fuzzy numbers for pairwise comparison scales in prioritizing the criteria in managing projects. Utilizing the fuzzy AHP technique can facilitate uncertainty in doing evaluation. In this study, one expert who is a project manager with many years of experience was asked to carry out the evaluation. The results show that the expert’s main concern in managing project is time, and cost is the second important. The study demonstrates how uncertainty in making evaluation of multiple criteria can be solved by using fuzzy method such as ...
{"title":"Evaluating project management criteria using fuzzy analytic hierarchy Process","authors":"Husam Jasim Mohammed, Ihsan Ali Mubarak Al-Jubori, M. M. Kasim","doi":"10.1063/1.5121097","DOIUrl":"https://doi.org/10.1063/1.5121097","url":null,"abstract":"Project management is one of the most important issues to fulfil organizational objectives. The project management criteria are playing a vital role for completion of any project. The aim of this paper is to evaluate five main project criteria (time, cost, quality, risk, and safety) mathematically by using a multi-criteria method in order to assist stakeholders or project managers in decision-making. The fuzzy Analytic Hierarchy Process (AHP) is selected with the use of triangular fuzzy numbers for pairwise comparison scales in prioritizing the criteria in managing projects. Utilizing the fuzzy AHP technique can facilitate uncertainty in doing evaluation. In this study, one expert who is a project manager with many years of experience was asked to carry out the evaluation. The results show that the expert’s main concern in managing project is time, and cost is the second important. The study demonstrates how uncertainty in making evaluation of multiple criteria can be solved by using fuzzy method such as fuzzy AHP, in contrary to the crisp or the traditional AHP which is based on specific values, the evaluator(s) are always ambiguous and vague to give exact judgment. Hence, the application of this fuzzy method can make the assessment outcomes more accurate, scientific, and objective. It is anticipated that this work may serve as a support tool for stakeholders in improving the project management quality level.Project management is one of the most important issues to fulfil organizational objectives. The project management criteria are playing a vital role for completion of any project. The aim of this paper is to evaluate five main project criteria (time, cost, quality, risk, and safety) mathematically by using a multi-criteria method in order to assist stakeholders or project managers in decision-making. The fuzzy Analytic Hierarchy Process (AHP) is selected with the use of triangular fuzzy numbers for pairwise comparison scales in prioritizing the criteria in managing projects. Utilizing the fuzzy AHP technique can facilitate uncertainty in doing evaluation. In this study, one expert who is a project manager with many years of experience was asked to carry out the evaluation. The results show that the expert’s main concern in managing project is time, and cost is the second important. The study demonstrates how uncertainty in making evaluation of multiple criteria can be solved by using fuzzy method such as ...","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115813449","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}
H. S. Zulkafli, George Steftaris, G. Gibson, N. Zammitt
This study is motivated by the issue that arises when modelling the consistency of symptoms reporting by individual patients during hypoglycaemic episodes. It is argued that any episode occurring within 24 hours from a previous episode may reduce the intensity of subsequent hypoglycaemic episodes. Such episodes were excluded from further consideration because they could potentially affect our model given that it is based on the patient’s inherent propensity to report a given symptom and the intensity of that symptom in a given episode. The aim of this study is to investigate the effect of adding data from episodes that occurred within 24 hours from their preceding episode. We develop a permutation testing to investigate whether episodes’ intensity exhibits change that goes beyond random variation when episodes are in temporal proximity. Further analysis consists of comparison between the two cases i.e. excluding episodes within 24 hours and including those episodes with regards to their correlations between the intensity of the episodes. The analysis shows that adding these new episodes does not have a significant impact on the intensity of episodes.This study is motivated by the issue that arises when modelling the consistency of symptoms reporting by individual patients during hypoglycaemic episodes. It is argued that any episode occurring within 24 hours from a previous episode may reduce the intensity of subsequent hypoglycaemic episodes. Such episodes were excluded from further consideration because they could potentially affect our model given that it is based on the patient’s inherent propensity to report a given symptom and the intensity of that symptom in a given episode. The aim of this study is to investigate the effect of adding data from episodes that occurred within 24 hours from their preceding episode. We develop a permutation testing to investigate whether episodes’ intensity exhibits change that goes beyond random variation when episodes are in temporal proximity. Further analysis consists of comparison between the two cases i.e. excluding episodes within 24 hours and including those episodes with regards to their correlations betwe...
{"title":"Permutation testing in analyzing the changes in the intensity of hypoglycaemic episodes occuring within 24 hours from previous episodes","authors":"H. S. Zulkafli, George Steftaris, G. Gibson, N. Zammitt","doi":"10.1063/1.5121078","DOIUrl":"https://doi.org/10.1063/1.5121078","url":null,"abstract":"This study is motivated by the issue that arises when modelling the consistency of symptoms reporting by individual patients during hypoglycaemic episodes. It is argued that any episode occurring within 24 hours from a previous episode may reduce the intensity of subsequent hypoglycaemic episodes. Such episodes were excluded from further consideration because they could potentially affect our model given that it is based on the patient’s inherent propensity to report a given symptom and the intensity of that symptom in a given episode. The aim of this study is to investigate the effect of adding data from episodes that occurred within 24 hours from their preceding episode. We develop a permutation testing to investigate whether episodes’ intensity exhibits change that goes beyond random variation when episodes are in temporal proximity. Further analysis consists of comparison between the two cases i.e. excluding episodes within 24 hours and including those episodes with regards to their correlations between the intensity of the episodes. The analysis shows that adding these new episodes does not have a significant impact on the intensity of episodes.This study is motivated by the issue that arises when modelling the consistency of symptoms reporting by individual patients during hypoglycaemic episodes. It is argued that any episode occurring within 24 hours from a previous episode may reduce the intensity of subsequent hypoglycaemic episodes. Such episodes were excluded from further consideration because they could potentially affect our model given that it is based on the patient’s inherent propensity to report a given symptom and the intensity of that symptom in a given episode. The aim of this study is to investigate the effect of adding data from episodes that occurred within 24 hours from their preceding episode. We develop a permutation testing to investigate whether episodes’ intensity exhibits change that goes beyond random variation when episodes are in temporal proximity. Further analysis consists of comparison between the two cases i.e. excluding episodes within 24 hours and including those episodes with regards to their correlations betwe...","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127388816","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}
Nurul Syafiqa Mohd Sapri, Maduri Ruchhi Bedi a, P. D. S. Bedi, Syariza Abdul-Rahman, Aida Mauziah Benjamin
The rapid changes of lifestyles especially eating habits of fast-food and convenience food which are usually rich in sodium and sugar or carbohydrate lead to other chronic diseases especially for diabetics. Diet practice is one of the very important steps that the diabetic patients can take care of in order to avoid to other complications. The diet planning of a diabetic patient aims to balance up the nutrients and to control the level of blood glucose in the body with minimal cost. This paper aims to provide a combination of food menu that satisfies the daily nutrient requirements of a diabetic person at a minimum cost. An integer programming model of a diabetic diet problem is developed to determine the food combination that satisfies the standard daily nutritional requirements for two days and repetition of menu is prohibited. In this study, a sensitivity analysis is performed by substituting meals. It is found that the best combination of menu for two days for a diabetic patient is at the cost of RM49.10. The optimal solution for the two days menu plan fulfils the standard nutritional requirements for diabetic patients. It is suggested that the findings can be used as a guideline for the diabetic patients themselves or for hospital management to suggest meal planning for diabetic patients.The rapid changes of lifestyles especially eating habits of fast-food and convenience food which are usually rich in sodium and sugar or carbohydrate lead to other chronic diseases especially for diabetics. Diet practice is one of the very important steps that the diabetic patients can take care of in order to avoid to other complications. The diet planning of a diabetic patient aims to balance up the nutrients and to control the level of blood glucose in the body with minimal cost. This paper aims to provide a combination of food menu that satisfies the daily nutrient requirements of a diabetic person at a minimum cost. An integer programming model of a diabetic diet problem is developed to determine the food combination that satisfies the standard daily nutritional requirements for two days and repetition of menu is prohibited. In this study, a sensitivity analysis is performed by substituting meals. It is found that the best combination of menu for two days for a diabetic patient is at the cost of RM49...
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