Pub Date : 2022-10-01DOI: 10.1109/hpcsim.2011.5999799
Copyright and Reprint Permission: Abstracting is permitted with credit to the source. Libraries are permitted to photocopy beyond the limit of U.S. copyright law for private use of patrons those articles in this volume that carry a code at the bottom of the first page, provided the per-copy fee indicated in the code is paid through
{"title":"Copyright page","authors":"","doi":"10.1109/hpcsim.2011.5999799","DOIUrl":"https://doi.org/10.1109/hpcsim.2011.5999799","url":null,"abstract":"Copyright and Reprint Permission: Abstracting is permitted with credit to the source. Libraries are permitted to photocopy beyond the limit of U.S. copyright law for private use of patrons those articles in this volume that carry a code at the bottom of the first page, provided the per-copy fee indicated in the code is paid through","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124552128","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 : 2022-06-01DOI: 10.1109/icimu.2014.7066592
R. Jidin, N. Jamil, S. Yussof, Yunus Yusoff, Roslan Ismail, Azimah Abdul Ghapar
{"title":"Table of content (TOC)","authors":"R. Jidin, N. Jamil, S. Yussof, Yunus Yusoff, Roslan Ismail, Azimah Abdul Ghapar","doi":"10.1109/icimu.2014.7066592","DOIUrl":"https://doi.org/10.1109/icimu.2014.7066592","url":null,"abstract":"","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115019362","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 : 2014-11-18DOI: 10.1109/ICIMU.2014.7066637
S. Shanmuganathan, R. Ibrahim, Siti Halimah Bt Bakori
Exposure to airborne wood (hard and soft) dust can lead to a number of diseases, such as asthma, emphysema, bronchitis and upper respiratory tract cancers, lately even proven to be linked to elevated risks for chromosomal instability in cells of the aerodigestive tract. In this context, the paper investigated the particulate wood dust concentrations in a university environment near a timber mill using a data mining approach consisting of JRip, J48 algorithms and a multilayer perceptron (MLP). The data collected consists of particulate wood concentrations and related atmospheric conditions recorded over a few days at four different locations within the university situated next to the timber mill. The results reveal that ORICC is the location most exposed to high concentrations of wood dust (up to 1.57 MG/M3 at times). This exceeds the recommended exposure limit of 1 MG/M3 for humans if the dust particles were of hardwood hence, more tests are recommended to establish the airborne particulate wood dust composition from the factory.
{"title":"A data mining approach to analysing airborne wood particulate concentration and atmospheric data","authors":"S. Shanmuganathan, R. Ibrahim, Siti Halimah Bt Bakori","doi":"10.1109/ICIMU.2014.7066637","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066637","url":null,"abstract":"Exposure to airborne wood (hard and soft) dust can lead to a number of diseases, such as asthma, emphysema, bronchitis and upper respiratory tract cancers, lately even proven to be linked to elevated risks for chromosomal instability in cells of the aerodigestive tract. In this context, the paper investigated the particulate wood dust concentrations in a university environment near a timber mill using a data mining approach consisting of JRip, J48 algorithms and a multilayer perceptron (MLP). The data collected consists of particulate wood concentrations and related atmospheric conditions recorded over a few days at four different locations within the university situated next to the timber mill. The results reveal that ORICC is the location most exposed to high concentrations of wood dust (up to 1.57 MG/M3 at times). This exceeds the recommended exposure limit of 1 MG/M3 for humans if the dust particles were of hardwood hence, more tests are recommended to establish the airborne particulate wood dust composition from the factory.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124436163","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066643
A. Alsaffar, N. Omar
Online social media is used to show the sentiments of different individuals about various subjects. Sentiment analysis or opinion mining has recently been considered as one of the highly dynamic research fields in natural language processing, Web mining, and machine learning. There has been a very limited amount of research that focuses on sentiment analysis in the Malay language. This study investigates how feature selection methods contribute to the improvement of Malay sentiment classification performance. Three supervised machine-learning classifiers and seven feature selection methods are used to conduct a series of experiments for the effective selection of the appropriate methods for the automatic sentiment classification of online Malay-written reviews. Findings show that the classifications of Malay sentiment improve using feature selections approaches. This work demonstrates that all feature reduction methods generally improve classifier performance. Support Vector Machine (SVM) approach provide the highest accuracy performance of features selection in order to classify Malay sentiment comparing with other classifications approaches such as PCA and CHI square. SVM records 87% as experimental accuracy result of feature selection.
{"title":"Study on feature selection and machine learning algorithms for Malay sentiment classification","authors":"A. Alsaffar, N. Omar","doi":"10.1109/ICIMU.2014.7066643","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066643","url":null,"abstract":"Online social media is used to show the sentiments of different individuals about various subjects. Sentiment analysis or opinion mining has recently been considered as one of the highly dynamic research fields in natural language processing, Web mining, and machine learning. There has been a very limited amount of research that focuses on sentiment analysis in the Malay language. This study investigates how feature selection methods contribute to the improvement of Malay sentiment classification performance. Three supervised machine-learning classifiers and seven feature selection methods are used to conduct a series of experiments for the effective selection of the appropriate methods for the automatic sentiment classification of online Malay-written reviews. Findings show that the classifications of Malay sentiment improve using feature selections approaches. This work demonstrates that all feature reduction methods generally improve classifier performance. Support Vector Machine (SVM) approach provide the highest accuracy performance of features selection in order to classify Malay sentiment comparing with other classifications approaches such as PCA and CHI square. SVM records 87% as experimental accuracy result of feature selection.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122651523","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066641
Mohd Izhan Mohd Yusoff, Ibrahim Mohamed, M. A. Abu Bakar
Hidden Markov models (HMM) is a probabilistic model consisting of variables representing observations, variables that are hidden, the initial state distribution, transition matrix, and parameters for all observation distributions. The said model is commonly used in speech recognition field and it has seen an increase in terms of usage, which include user profiling in mobile communication networks, and energy disaggregation. This paper shows, via numerical example, the computation of HMM's forward procedure will exceed the precision range of essentially any machine (even in double precision). It also extends the procedure to include Gaussian mixture hidden Markov models (GMHMM), the procedure that can be used as both a generator of observations, and as a model for how a given observation sequence was generated by an appropriate HMM.
{"title":"Hidden Markov models: An insight","authors":"Mohd Izhan Mohd Yusoff, Ibrahim Mohamed, M. A. Abu Bakar","doi":"10.1109/ICIMU.2014.7066641","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066641","url":null,"abstract":"Hidden Markov models (HMM) is a probabilistic model consisting of variables representing observations, variables that are hidden, the initial state distribution, transition matrix, and parameters for all observation distributions. The said model is commonly used in speech recognition field and it has seen an increase in terms of usage, which include user profiling in mobile communication networks, and energy disaggregation. This paper shows, via numerical example, the computation of HMM's forward procedure will exceed the precision range of essentially any machine (even in double precision). It also extends the procedure to include Gaussian mixture hidden Markov models (GMHMM), the procedure that can be used as both a generator of observations, and as a model for how a given observation sequence was generated by an appropriate HMM.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122052683","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066606
F. Masoumiyan, Zuriati Binti Ahmad Zukarnain, S. Subramaniam, Z. Hanapi
Orthogonal Frequency Division Multiplexing Access (OFDMA) technology along with cooperative relay networks are generally described as an appropriate applicant for developed cellular networks because of the improvements to system performance through flexible resource allocation schemes. In these networks interference-aware resource allocation or interference coordination, represents an important role in raising resource utilization as well as enhancing cell throughput. This paper focuses on existing co-channel interference mitigation methods in multi-cell OFDMA Relay Based Cellular Networks (RBCNs). It aims to utilize the advantages of relay stations while reducing the negative effects of introduced interference. This research first presents the general system model scenarios of interference in RBCNs and provides an overview of the problem. It then compares the potential interference scenarios in these systems. Our study examines the techniques based on the frequency reuse factor they use and shows that even by maintaining the frequency reuse at one; we can maximize the system throughput.
{"title":"Co-channel interference mitigation techniques in multi-cell OFDMA Relay-Based Cellular Networks: A survey","authors":"F. Masoumiyan, Zuriati Binti Ahmad Zukarnain, S. Subramaniam, Z. Hanapi","doi":"10.1109/ICIMU.2014.7066606","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066606","url":null,"abstract":"Orthogonal Frequency Division Multiplexing Access (OFDMA) technology along with cooperative relay networks are generally described as an appropriate applicant for developed cellular networks because of the improvements to system performance through flexible resource allocation schemes. In these networks interference-aware resource allocation or interference coordination, represents an important role in raising resource utilization as well as enhancing cell throughput. This paper focuses on existing co-channel interference mitigation methods in multi-cell OFDMA Relay Based Cellular Networks (RBCNs). It aims to utilize the advantages of relay stations while reducing the negative effects of introduced interference. This research first presents the general system model scenarios of interference in RBCNs and provides an overview of the problem. It then compares the potential interference scenarios in these systems. Our study examines the techniques based on the frequency reuse factor they use and shows that even by maintaining the frequency reuse at one; we can maximize the system throughput.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129501753","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066598
Z. Moghaddasi, H. Jalab, R. M. Noor
Digital image forgery is becoming easier to perform because of the rapid development of various manipulation tools. Image splicing is one of the most common image forgery techniques. To detect the spliced images several methods proposed utilizing the statistical features of the digital images. In this paper, a new image splicing detection approach proposed based on singular value decomposition (SVD) feature extraction method applied in steganalysis. SVD-based features are merged with discrete cosine transform (DCT) for image splicing detection. Support vector machine is used to distinguish between authentic and spliced images. The results show a detection accuracy of 78.82% is achieved for the proposed method with only 50 dimensional feature vector. Furthermore the performance of SVD-based features needs more improvement in image splicing detection area of work.
{"title":"SVD-based image splicing detection","authors":"Z. Moghaddasi, H. Jalab, R. M. Noor","doi":"10.1109/ICIMU.2014.7066598","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066598","url":null,"abstract":"Digital image forgery is becoming easier to perform because of the rapid development of various manipulation tools. Image splicing is one of the most common image forgery techniques. To detect the spliced images several methods proposed utilizing the statistical features of the digital images. In this paper, a new image splicing detection approach proposed based on singular value decomposition (SVD) feature extraction method applied in steganalysis. SVD-based features are merged with discrete cosine transform (DCT) for image splicing detection. Support vector machine is used to distinguish between authentic and spliced images. The results show a detection accuracy of 78.82% is achieved for the proposed method with only 50 dimensional feature vector. Furthermore the performance of SVD-based features needs more improvement in image splicing detection area of work.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129100013","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066639
Khmael Rahem, N. Omar
Although valuable crime information is available in human-readable form in online newspapers and electronic archives, software systems that can extract and present relevant information are limited and are of significant interest to researchers in the field of information extraction. This work aims to extract available drug crime information from online newspaper articles. This work has the following subtasks: assess where and how drug traffickers hide drugs, identify the nationalities of drug dealers, identify the types (names) of drugs, and assess the quantity and prices of drugs in the local market. This paper presents a rule-based approach to extract information on the basis of a set of drug crime gazetteers and on a set of grammatical and heuristic rules. This work is validated through experiments. Results show that the technique developed here are promising.
{"title":"Drug-related crime information extraction and analysis","authors":"Khmael Rahem, N. Omar","doi":"10.1109/ICIMU.2014.7066639","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066639","url":null,"abstract":"Although valuable crime information is available in human-readable form in online newspapers and electronic archives, software systems that can extract and present relevant information are limited and are of significant interest to researchers in the field of information extraction. This work aims to extract available drug crime information from online newspaper articles. This work has the following subtasks: assess where and how drug traffickers hide drugs, identify the nationalities of drug dealers, identify the types (names) of drugs, and assess the quantity and prices of drugs in the local market. This paper presents a rule-based approach to extract information on the basis of a set of drug crime gazetteers and on a set of grammatical and heuristic rules. This work is validated through experiments. Results show that the technique developed here are promising.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123453487","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066665
Nellmondee Julius, E. E. Mustapha
Take-A-Break Notification is a software which runs on Windows operating system designed for office workers who have the highest tendency on prolonged computer screens use, in order to reduce Computer Vision Syndrome (CVS). The purpose of this study is to prevent computer users from looking in front of a computer screen for a long period of time. Rapid Application Development (RAD) methodology has been used for the project development phase. The software will dim the computer, disabling the mouse and keyboard functions which will force the employees to take a 5 minutes break after 2 hours working in front of the computer screens. This software will encourage office workers to apply the ergonomic practices and to be able to reduce the increasing rate of Computer Vision Syndrome (CVS).
{"title":"Take-A-Break Notification: An ergonomic application","authors":"Nellmondee Julius, E. E. Mustapha","doi":"10.1109/ICIMU.2014.7066665","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066665","url":null,"abstract":"Take-A-Break Notification is a software which runs on Windows operating system designed for office workers who have the highest tendency on prolonged computer screens use, in order to reduce Computer Vision Syndrome (CVS). The purpose of this study is to prevent computer users from looking in front of a computer screen for a long period of time. Rapid Application Development (RAD) methodology has been used for the project development phase. The software will dim the computer, disabling the mouse and keyboard functions which will force the employees to take a 5 minutes break after 2 hours working in front of the computer screens. This software will encourage office workers to apply the ergonomic practices and to be able to reduce the increasing rate of Computer Vision Syndrome (CVS).","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"566 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116243493","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 : 2014-11-01DOI: 10.1109/ICIMU.2014.7066654
B. Solemon, Izyana Ariffin, Nor Nashrah Azmi
The advancement of mobile communication technologies nowadays, such as Global Positioning Systems (GPS) and Radio Frequency Identification (RFID), has enables participation by volunteers (often non-professional) to produce, share, and consume geographic information. Such participation is termed as Volunteered Geographic Information (VGI), which is loosely known as crowdsourcing. This paper describes a proposed mobile platform that explores the potential of exploiting volunteers to produce geographic information related to stationary assets of an electricity utility company in the country. The paper begins with a brief discussion on the principles of crowdsourcing and VGI. This is followed by reviews of four commonly cited applications, which rely on volunteers for their geographic information. The design, development and future work of the proposed mobile application are elaborated in this paper.
{"title":"Mobile platform for exploring the potential of volunteered geographic information for asset register","authors":"B. Solemon, Izyana Ariffin, Nor Nashrah Azmi","doi":"10.1109/ICIMU.2014.7066654","DOIUrl":"https://doi.org/10.1109/ICIMU.2014.7066654","url":null,"abstract":"The advancement of mobile communication technologies nowadays, such as Global Positioning Systems (GPS) and Radio Frequency Identification (RFID), has enables participation by volunteers (often non-professional) to produce, share, and consume geographic information. Such participation is termed as Volunteered Geographic Information (VGI), which is loosely known as crowdsourcing. This paper describes a proposed mobile platform that explores the potential of exploiting volunteers to produce geographic information related to stationary assets of an electricity utility company in the country. The paper begins with a brief discussion on the principles of crowdsourcing and VGI. This is followed by reviews of four commonly cited applications, which rely on volunteers for their geographic information. The design, development and future work of the proposed mobile application are elaborated in this paper.","PeriodicalId":408534,"journal":{"name":"Proceedings of the 6th International Conference on Information Technology and Multimedia","volume":"79 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113964221","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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