Pub Date : 2019-03-01DOI: 10.1109/ICCMA.2019.00012
A. Acakpovi, Haruna Mohammed, N. Nwulu, Francois-Xawier Nicolas Fifatin, Télesphore Cossi Nounangnonhou, R. Abubakar
Power Line Communication (PLC) is a means of communication that uses the power line network medium to transmit data and signals. The PLC system is basically divided into Narrowband and Broadband PLC system. The PLC is considered to be one of the most favourable candidates for Advanced Metering Infrastructure (AMI). In the past Electricity Company of Ghana (ECG) used PLC (Narrowband-PLC) as a medium of Communication for smart prepaid metering but was unsuccessful due to hostile nature of the power line characteristics like electrical noise and interferences. Noise characterization of the power lines channel is very important for PLC systems design. In this paper, the measurements of noise properties injected by various loads in the Narrowband frequency 1-500 KHz and Broadband frequency 2-12 MHz spectrum are presented and discussed. The outcome of the study suggests that the Narrowband frequency region 1 - 500 KHz is marked with noise and therefore noise will have a negative impact on PLC categories operating under this region of frequency band. On the other hand, noise level on the Broadband frequency region 2-12 MHz was found to be minimal and therefore noise will have very little or no impact on the PLC Category operating under the Broadband frequency band (BB-PLC).
电力线通信(Power Line Communication, PLC)是利用电力线网络介质传输数据和信号的一种通信手段。PLC系统基本上分为窄带和宽带PLC系统。PLC被认为是先进计量基础设施(AMI)最有利的候选者之一。过去，加纳电力公司(ECG)使用PLC(窄带PLC)作为智能预付费计量的通信媒介，但由于电力线的电气噪声和干扰等敌对性质而失败。电力线通道的噪声特性对PLC系统设计非常重要。本文介绍并讨论了在窄带频率1- 500khz和宽带频率2- 12mhz频谱中各种负载注入的噪声特性的测量。研究结果表明，窄带频率区域1 - 500khz被标记为噪声，因此噪声将对在该频段区域下运行的PLC类别产生负面影响。另一方面，宽带频率区域2-12 MHz的噪声水平被发现是最小的，因此噪声对在宽带频段(BB-PLC)下运行的PLC类别的影响很小或没有影响。
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Pub Date : 2019-03-01DOI: 10.1109/iccma.2019.00002
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Pub Date : 2019-03-01DOI: 10.1109/ICCMA.2019.00017
Nabare Williams Kwame, Emmanuel Freeman
The need for an effective network for business operation have been the driving force for most institutes globally. It is however noted that most networks face different levels of poor performance. An aspect is network congestion that hinders the smooth flow of data or information anticipated by users of a network. The ability to predict the quality of experience in our network performance to avoid congestion so as to render quality services to a client is very paramount. This paper investigates an innovative approach to analyze the performance of a network using an appropriate techniques. The methodology used a simulation tool IxChariot version 7.10 SP4 simulator for this study which allowed for the emulation of key performance metrics, such as throughput, packet loss, jitter, delay etc. within a hybrid network topology of 35 nodes. The congestion that occurred leading to packet loss during the test run was curtailed by the application of Quality of Service (QoS) techniques such as the increase in bandwidth, the use of playout buffers as well as prioritizing certain packets.
对商业运作的有效网络的需求一直是全球大多数研究所的推动力。然而，值得注意的是，大多数网络都面临不同程度的性能差。一个方面是网络拥塞，它阻碍了网络用户所期望的数据或信息的顺畅流动。预测网络性能体验质量以避免拥塞从而为客户提供高质量服务的能力是非常重要的。本文研究了一种利用适当的技术来分析网络性能的创新方法。该方法使用了模拟工具IxChariot version 7.10 SP4模拟器进行研究，该模拟器允许在35个节点的混合网络拓扑中模拟关键性能指标，如吞吐量、数据包丢失、抖动、延迟等。通过应用服务质量(QoS)技术(如带宽的增加、播放缓冲区的使用以及对某些数据包进行优先级排序)，减少了在测试运行期间导致数据包丢失的拥塞。
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Pub Date : 2019-03-01DOI: 10.1109/iccma.2019.00001
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Pub Date : 2019-03-01DOI: 10.1109/ICCMA.2019.00014
E. Peters, G. Aggrey
The technological advancements over the years have greatly influenced processes and functions of higher education institutions (HEIs) worldwide. For that matter, various governments have called on all universities worldwide to improve their processes and activities. The massive investment in Enterprise Resource Planning (ERP) systems by higher education institutions need to be assessed based on the effectiveness of their application. However, there is no suitable analytic framework that would evaluate systematically the effectiveness of ERP systems in higher education institutions. Therefore, this study presents an analytic framework for ERP systems effectiveness evaluation in HEIs. A proposed analytic framework has been developed by integrating two well-known models: Balanced scorecard (BSC) and ISO 25010 models. The framework has been developed to analyze systematically the effectiveness of ERP. Five perspectives and twenty-six measuring indicators are suggested for evaluating the effectiveness of ERP systems in HEIs. The five perspectives suggested include financial, customer/stakeholder, internal business process, learning and growth and system quality perspectives.
{"title":"Evaluating the Effectiveness of ERP Systems in HEIs: A Proposed Analytic Framework","authors":"E. Peters, G. Aggrey","doi":"10.1109/ICCMA.2019.00014","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00014","url":null,"abstract":"The technological advancements over the years have greatly influenced processes and functions of higher education institutions (HEIs) worldwide. For that matter, various governments have called on all universities worldwide to improve their processes and activities. The massive investment in Enterprise Resource Planning (ERP) systems by higher education institutions need to be assessed based on the effectiveness of their application. However, there is no suitable analytic framework that would evaluate systematically the effectiveness of ERP systems in higher education institutions. Therefore, this study presents an analytic framework for ERP systems effectiveness evaluation in HEIs. A proposed analytic framework has been developed by integrating two well-known models: Balanced scorecard (BSC) and ISO 25010 models. The framework has been developed to analyze systematically the effectiveness of ERP. Five perspectives and twenty-six measuring indicators are suggested for evaluating the effectiveness of ERP systems in HEIs. The five perspectives suggested include financial, customer/stakeholder, internal business process, learning and growth and system quality perspectives.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115955952","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 : 2019-03-01DOI: 10.1109/ICCMA.2019.00016
Thierry Blaise Taih Coffi Aka, A. Acakpovi, Kester Quist-Aphetsi
This paper evaluates the performances of FBMC as compared to OFDM in a simulation environment. Multicarrier techniques have been very influential in the development of wireless communication technologies especially Orthogonal Frequency-Division Multiplexing (OFDM), mainly deployed in new networks generation such as 4G, 802.11x, and DVB. Even though OFDM is more widespread than the other multiple sharing techniques, the technology presents some shortcomings in some special applications that are more efficiently addressed with the use of Filter Bank Multicarrier (FBMC). This paper performs a comparative analysis of OFDM and FBMC based on power spectral density, prototype filter, bandwidth efficiency and latency through simulation with Matlab software. Results showed that FBMC outperformed OFDM in many capacities and it should therefore be perceived as a promising technology for future emerging networks.
{"title":"Performance Evaluation of FBMC Compared to OFDM by Simulation with Matlab","authors":"Thierry Blaise Taih Coffi Aka, A. Acakpovi, Kester Quist-Aphetsi","doi":"10.1109/ICCMA.2019.00016","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00016","url":null,"abstract":"This paper evaluates the performances of FBMC as compared to OFDM in a simulation environment. Multicarrier techniques have been very influential in the development of wireless communication technologies especially Orthogonal Frequency-Division Multiplexing (OFDM), mainly deployed in new networks generation such as 4G, 802.11x, and DVB. Even though OFDM is more widespread than the other multiple sharing techniques, the technology presents some shortcomings in some special applications that are more efficiently addressed with the use of Filter Bank Multicarrier (FBMC). This paper performs a comparative analysis of OFDM and FBMC based on power spectral density, prototype filter, bandwidth efficiency and latency through simulation with Matlab software. Results showed that FBMC outperformed OFDM in many capacities and it should therefore be perceived as a promising technology for future emerging networks.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121967540","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 : 2019-03-01DOI: 10.1109/ICCMA.2019.00026
Ephraim Nii Kpakpo Waller, Pamela Delali Adablah, Q. Kester
The Economy is affected by dynamic and unstable variables. Therefore, it is very necessary to recognize the variations of the economic variables in order to make better decisions in the future via forecasting. In our work, a Markov Chain model, which is a mathematical tool in the stochastic Process, to forecasting some vital economic variables in making a critical decision was engaged. We proposed a forecasting model, based on Markov chains.
{"title":"Markov Chain: Forecasting Economic Variables","authors":"Ephraim Nii Kpakpo Waller, Pamela Delali Adablah, Q. Kester","doi":"10.1109/ICCMA.2019.00026","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00026","url":null,"abstract":"The Economy is affected by dynamic and unstable variables. Therefore, it is very necessary to recognize the variations of the economic variables in order to make better decisions in the future via forecasting. In our work, a Markov Chain model, which is a mathematical tool in the stochastic Process, to forecasting some vital economic variables in making a critical decision was engaged. We proposed a forecasting model, based on Markov chains.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115747700","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 : 2019-03-01DOI: 10.1109/ICCMA.2019.00019
Joseph Kweku
A visitor, who arrives in the city of Accra today, will see huge tall metallic slender structures (towers or mast) going as high as 50 meters, being used for the purpose of cell sites for telecommunication companies. Currently there are six mobile operators in Ghana (VODAFONE, TIGO, AIRTEL, GLO, EXPRESSO and MTN not neglecting the LTE providers, Surfline, BLU and BUSY). The indiscriminate installation of towers in Ghana has however congested the skyline of the city. This research is aimed at analysing the extent of infrastructure sharing, develop a model that can be followed by these Telecos and lastly analyse the cost benefits of engaging in tower sharing. MTN Ghana was used as the case study of this research. The extent of infrastructure sharing was investigated and found out that only passive type of sharing was practiced in Ghana and these Telecos were using a joint venture agreement. A cell site model, of ground space area of 25m x 25m and a tower height of 60m was proposed for use by new Telecos and old in reducing mast congestion. On the average about 44.61% of capital expenditure can be saved if all the eight Telecos in the country share a common tower.
{"title":"Analysis of Co-Location of Telecommunication Infrastructure In Ghana","authors":"Joseph Kweku","doi":"10.1109/ICCMA.2019.00019","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00019","url":null,"abstract":"A visitor, who arrives in the city of Accra today, will see huge tall metallic slender structures (towers or mast) going as high as 50 meters, being used for the purpose of cell sites for telecommunication companies. Currently there are six mobile operators in Ghana (VODAFONE, TIGO, AIRTEL, GLO, EXPRESSO and MTN not neglecting the LTE providers, Surfline, BLU and BUSY). The indiscriminate installation of towers in Ghana has however congested the skyline of the city. This research is aimed at analysing the extent of infrastructure sharing, develop a model that can be followed by these Telecos and lastly analyse the cost benefits of engaging in tower sharing. MTN Ghana was used as the case study of this research. The extent of infrastructure sharing was investigated and found out that only passive type of sharing was practiced in Ghana and these Telecos were using a joint venture agreement. A cell site model, of ground space area of 25m x 25m and a tower height of 60m was proposed for use by new Telecos and old in reducing mast congestion. On the average about 44.61% of capital expenditure can be saved if all the eight Telecos in the country share a common tower.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128192394","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 : 2019-03-01DOI: 10.1109/ICCMA.2019.00015
Michael Christopher Xenya, Crentsil Kwayie, Kester Quist-Aphesti
In this paper, an intruder detection system has been built with an implementation of convolutional neural network (CNN) using raspberry pi, Microsoft’s Azure and Twilio cloud systems. The CNN algorithm which is stored in the cloud is implemented to basically classify input data as either intruder or user. By using the raspberry pi as the middleware and raspberry pi camera for image acquisition, efficient execution of the learning and classification operations are performed using higher resources that cloud computing offers. The cloud system is also programmed to alert designated users via multimedia messaging services (MMS) when intruders or users are detected. Furthermore, our work has demonstrated that, though convolutional neural network could impose high computing demands on a processor, the input data could be obtained with low-cost modules and middleware which are of low processing power while subjecting the actual learning algorithm execution to the cloud system.
{"title":"Intruder Detection with Alert Using Cloud Based Convolutional Neural Network and Raspberry Pi","authors":"Michael Christopher Xenya, Crentsil Kwayie, Kester Quist-Aphesti","doi":"10.1109/ICCMA.2019.00015","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00015","url":null,"abstract":"In this paper, an intruder detection system has been built with an implementation of convolutional neural network (CNN) using raspberry pi, Microsoft’s Azure and Twilio cloud systems. The CNN algorithm which is stored in the cloud is implemented to basically classify input data as either intruder or user. By using the raspberry pi as the middleware and raspberry pi camera for image acquisition, efficient execution of the learning and classification operations are performed using higher resources that cloud computing offers. The cloud system is also programmed to alert designated users via multimedia messaging services (MMS) when intruders or users are detected. Furthermore, our work has demonstrated that, though convolutional neural network could impose high computing demands on a processor, the input data could be obtained with low-cost modules and middleware which are of low processing power while subjecting the actual learning algorithm execution to the cloud system.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133229673","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}
In recent years, technology has evolved exponentially therefore allowing for research into newer areas. The legal system has expressed significant growth in the area of Information Systems adoption and use forthe storage of cases, making information retrieval easy and old cases accessible. But there has been little work on decision support systems for validation of fairness of a judgement.In our work we proposed theBayesian network probability that was used to determine whether a case judged at the court was fair or not. We tested the system on cases and had promising results that could be improved and integrated into future legal information systems.
{"title":"Using Bayesian Networks In Analysing Judgement","authors":"Loretta Pinamang Asamoah, Edwin Worlawoe Amaglo, Q. Kester","doi":"10.1109/ICCMA.2019.00025","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00025","url":null,"abstract":"In recent years, technology has evolved exponentially therefore allowing for research into newer areas. The legal system has expressed significant growth in the area of Information Systems adoption and use forthe storage of cases, making information retrieval easy and old cases accessible. But there has been little work on decision support systems for validation of fairness of a judgement.In our work we proposed theBayesian network probability that was used to determine whether a case judged at the court was fair or not. We tested the system on cases and had promising results that could be improved and integrated into future legal information systems.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129547313","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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