Pub Date : 2020-12-30DOI: 10.5013/ijssst.a.21.01.08
Thabit Sultan Mohammed, M. Rasheed, M. Al-Ani, Qeethara Al-Shayea, F. Alnaimi
An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. Condition indicators are derived from sound signals, and used to arrive at a decision about the performance state of the machine. Sound signals are recorded by microphones and processed using time-frequency domain analysis. In this study, number of statistical features; such as mean, standard deviation, skewness, and kurtosis are considered. These statistical features were proven to be effective and simple to interpret. Healthy, about to be faulty, and faulty performance states of the machine are considered, and audio signals are recorded for each state. The five main steps comprising the implemented approach are data acquisition, preprocessing, feature extraction, time and frequency domain analysis, and the decision making. Based on the adopted statistical measures, the experimental results indicate that an excellent recognition of machine performance states is obtained, leading to an efficient fault detection and diagnosis.
{"title":"Fault Diagnosis of Rotating Machine Based on Audio Signal Recognition System: An Efficient Approach","authors":"Thabit Sultan Mohammed, M. Rasheed, M. Al-Ani, Qeethara Al-Shayea, F. Alnaimi","doi":"10.5013/ijssst.a.21.01.08","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.01.08","url":null,"abstract":"An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. Condition indicators are derived from sound signals, and used to arrive at a decision about the performance state of the machine. Sound signals are recorded by microphones and processed using time-frequency domain analysis. In this study, number of statistical features; such as mean, standard deviation, skewness, and kurtosis are considered. These statistical features were proven to be effective and simple to interpret. Healthy, about to be faulty, and faulty performance states of the machine are considered, and audio signals are recorded for each state. The five main steps comprising the implemented approach are data acquisition, preprocessing, feature extraction, time and frequency domain analysis, and the decision making. Based on the adopted statistical measures, the experimental results indicate that an excellent recognition of machine performance states is obtained, leading to an efficient fault detection and diagnosis.","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75252918","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 : 2020-12-30DOI: 10.5013/ijssst.a.21.03.04
L. Angeline, R. Chin, Liau Chung Fan, I. Saad, K. Teo
Countless hours are lost in traffic jam every year. In the efforts to save time, drivers tend to speed up in traffic jam. However there is a traffic paradox suggests that speeding up in traffic jam may not necessarily time saving. Traffic flow is fundamentally dynamic in nature, where the flow formed is greatly subjected to the interaction amongst the drivers. As such, this paper aims to investigate how different speed weightage between the drivers instigating the jam clusters and to assess possible corrective action to reverse jam clusters formation. Based on the identified jam clusters, several properties such as cluster lengths and average speed within the clusters are analysed for corrective action. Traffic simulation with 300 samples on a 5 km length of road shows the proposed algorithm does improve travel time with improvement range from 1.96 % to 7.96 %.
{"title":"Traffic Jam Clustering Analysis with Countermeasure Strategies During Traffic Congestion","authors":"L. Angeline, R. Chin, Liau Chung Fan, I. Saad, K. Teo","doi":"10.5013/ijssst.a.21.03.04","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.03.04","url":null,"abstract":"Countless hours are lost in traffic jam every year. In the efforts to save time, drivers tend to speed up in traffic jam. However there is a traffic paradox suggests that speeding up in traffic jam may not necessarily time saving. Traffic flow is fundamentally dynamic in nature, where the flow formed is greatly subjected to the interaction amongst the drivers. As such, this paper aims to investigate how different speed weightage between the drivers instigating the jam clusters and to assess possible corrective action to reverse jam clusters formation. Based on the identified jam clusters, several properties such as cluster lengths and average speed within the clusters are analysed for corrective action. Traffic simulation with 300 samples on a 5 km length of road shows the proposed algorithm does improve travel time with improvement range from 1.96 % to 7.96 %.","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88792270","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 : 2020-12-30DOI: 10.5013/ijssst.a.21.03.05
Eko Wahyu Utomo, F. Ramadhan, A. Imran
{"title":"VISSIM Simulation-Based Analysis for Improving Traffic Conditions in Bandung Indonesia","authors":"Eko Wahyu Utomo, F. Ramadhan, A. Imran","doi":"10.5013/ijssst.a.21.03.05","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.03.05","url":null,"abstract":"","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84347710","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 : 2020-12-30DOI: 10.5013/ijssst.a.21.03.06
Tang Nyiak Tien, Kit Guan Lim, M. K. Tan, Soo Siang Yang, K. Teo
This paper focuses on improving an optimization process for swarm robots using Particle Swarm Optimization (PSO) by altering the acceleration coefficient from static to dynamic. In swarm robotic, motion coordination addresses the issue of avoiding a group of robots interfere with each other in a limited workspace, while achieving the global motion objective. PSO is commonly suggested in the literature to optimize path trajectory in robotic field. However, the typical PSO tends to be trapped in local optima. Therefore, a dynamic acceleration coefficient is proposed to optimize the cognitive and social coefficients of PSO in order to improve its exploration ability in seeking the global optimum solution. With this novel feature, PSO becomes less dependent on the chain of its past experience that it had explored in a certain region within the solution space. The effectiveness of the proposed method is tested on a simulated swarm robotic platform. Results show the proposed PSO with Dynamic Coefficient (DCPSO) is 1.09 seconds and 3.58 seconds faster than the typical PSO under dynamic and extreme conditions respectively.
{"title":"Dynamic Acceleration Coefficient of Particle Swarm Optimization in Robotics Motion Coordination","authors":"Tang Nyiak Tien, Kit Guan Lim, M. K. Tan, Soo Siang Yang, K. Teo","doi":"10.5013/ijssst.a.21.03.06","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.03.06","url":null,"abstract":"This paper focuses on improving an optimization process for swarm robots using Particle Swarm Optimization (PSO) by altering the acceleration coefficient from static to dynamic. In swarm robotic, motion coordination addresses the issue of avoiding a group of robots interfere with each other in a limited workspace, while achieving the global motion objective. PSO is commonly suggested in the literature to optimize path trajectory in robotic field. However, the typical PSO tends to be trapped in local optima. Therefore, a dynamic acceleration coefficient is proposed to optimize the cognitive and social coefficients of PSO in order to improve its exploration ability in seeking the global optimum solution. With this novel feature, PSO becomes less dependent on the chain of its past experience that it had explored in a certain region within the solution space. The effectiveness of the proposed method is tested on a simulated swarm robotic platform. Results show the proposed PSO with Dynamic Coefficient (DCPSO) is 1.09 seconds and 3.58 seconds faster than the typical PSO under dynamic and extreme conditions respectively.","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85453256","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 : 2020-12-30DOI: 10.5013/ijssst.a.21.03.07
Prasitchai Veerayuttwilai, S. Thanawastien
{"title":"Simulation Model of Roadside Service for Smart Travel in Congested Zones","authors":"Prasitchai Veerayuttwilai, S. Thanawastien","doi":"10.5013/ijssst.a.21.03.07","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.03.07","url":null,"abstract":"","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"66 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85502262","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 : 2020-12-30DOI: 10.5013/IJSSST.A.21.04.10
Preecha Prasansri, S. Thanawastien, P. Tantaswadi
{"title":"Services Recommendation on Intercity Motorway","authors":"Preecha Prasansri, S. Thanawastien, P. Tantaswadi","doi":"10.5013/IJSSST.A.21.04.10","DOIUrl":"https://doi.org/10.5013/IJSSST.A.21.04.10","url":null,"abstract":"","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83249686","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 : 2020-12-30DOI: 10.5013/IJSSST.A.21.04.01
Hari Adianto, D. Darwin, Alfian Tan, S. Susanto
{"title":"Determining a Satisfying Process Configuration of Yarn Dying Process Using Response Surface Methodology","authors":"Hari Adianto, D. Darwin, Alfian Tan, S. Susanto","doi":"10.5013/IJSSST.A.21.04.01","DOIUrl":"https://doi.org/10.5013/IJSSST.A.21.04.01","url":null,"abstract":"","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76465997","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 : 2020-12-30DOI: 10.5013/ijssst.a.21.03.10
Pisanu Kumeechai, S. Jiriwibhakorn
{"title":"Detection and Tracking of Pedestrians at Zebra Crossings Using a Hybrid Combination of SIFT and Kalman Filter","authors":"Pisanu Kumeechai, S. Jiriwibhakorn","doi":"10.5013/ijssst.a.21.03.10","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.03.10","url":null,"abstract":"","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73643317","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 : 2020-12-30DOI: 10.5013/ijssst.a.21.03.01
Piyada Phosri, N. Pochai
{"title":"Explicit Finite Difference Techniques for a One-Dimensional Water Pollutant Dispersion Model in a Stream","authors":"Piyada Phosri, N. Pochai","doi":"10.5013/ijssst.a.21.03.01","DOIUrl":"https://doi.org/10.5013/ijssst.a.21.03.01","url":null,"abstract":"","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89127736","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 : 2020-12-30DOI: 10.5013/IJSSST.A.21.04.03
Nakul Sharma, P. Yalla
This paper summarizes various states of art literature in the field of mapping and visualizations in a programming language. The main focus is the design and analysis phase of Software Development Life Cycle. Mapping and visualization in software artifact is essential component for better understanding of the software. It also helps developers and maintenance professionals to visualize the effect of changes conducted in source code. In this work, a summary of literature review in of major tools developed for visualization and mapping of source code is provided.
{"title":"Mapping and Visualization of Source Code: A Survey","authors":"Nakul Sharma, P. Yalla","doi":"10.5013/IJSSST.A.21.04.03","DOIUrl":"https://doi.org/10.5013/IJSSST.A.21.04.03","url":null,"abstract":"This paper summarizes various states of art literature in the field of mapping and visualizations in a programming language. The main focus is the design and analysis phase of Software Development Life Cycle. Mapping and visualization in software artifact is essential component for better understanding of the software. It also helps developers and maintenance professionals to visualize the effect of changes conducted in source code. In this work, a summary of literature review in of major tools developed for visualization and mapping of source code is provided.","PeriodicalId":14286,"journal":{"name":"International journal of simulation: systems, science & technology","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84314548","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}
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