2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS)最新文献

Radio aeronomy in Nigeria: First results from very low frequency (VLF) radio waves receiving station at Anchor University, Lagos 尼日利亚的无线电航空学:第一个结果来自拉各斯Anchor大学的甚低频(VLF)无线电波接收站

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.247002

V. Nwankwo, S. Chakrabarti, S. Sasmal, W. Denig, M. P. Ajakaiye, Timothy Akinsola, Muyiwa Adeyanju, Paul I. Anekwe, K. Iluore, M. Olátúnjí, D. Bhowmick, J. Fatokun, M. Ayoola, O. Soneye, Joel Ajamu

{"title":"Radio aeronomy in Nigeria: First results from very low frequency (VLF) radio waves receiving station at Anchor University, Lagos","authors":"V. Nwankwo, S. Chakrabarti, S. Sasmal, W. Denig, M. P. Ajakaiye, Timothy Akinsola, Muyiwa Adeyanju, Paul I. Anekwe, K. Iluore, M. Olátúnjí, D. Bhowmick, J. Fatokun, M. Ayoola, O. Soneye, Joel Ajamu","doi":"10.1109/ICMCECS47690.2020.247002","DOIUrl":"https://doi.org/10.1109/ICMCECS47690.2020.247002","url":null,"abstract":"The study of the Earth’s atmosphere and the space environment is important because of the role played by the medium in the activities that affect the Earth and its inhabitants directly or indirectly. A robust capability to monitor, model and predict the happenings in the atmospheric space through deployment of both space- and ground-based observational systems for data acquisition, is key to result-oriented scientific research in atmospheric and space sciences. In this paper, we highlight the importance of regional deployment of observational facilities for data acquisition to complement current observational tools. We briefly review the capabilities of very low frequency (VLF) radio waves (in monitoring and studying changes in the atmosphere and ionosphere), and also present data obtained from our newly deployed VLF radio waves receiver at Anchor University, Lagos (AUL). We show that the diurnal signature characterised by VLF radio signal reflected in the data of three of four propagation paths (AUL-HWU, AUL-JJI, AUL-NWC and AUL-VTX) received at AUL. This outcome shows that operational condition of the VLF radio wave receiver is good. We anticipate interesting findings as we exploit this institution-based dataset to probe ionospheric irregularities in our region for the first time. In the light of some identified ionospheric changes in the equatorial region, we anticipate that our research effort using this regional VLF dataset will yield new results that will be resourceful for better understanding and characterisation of the dynamics of the equatorial D-layer ionosphere, since our region of reception (Lagos) lies close to the equator.","PeriodicalId":347202,"journal":{"name":"2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951404","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}

引用次数: 1

An Overview Of Smart Garden Automation 智能园林自动化概述

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240892

Samuel Olawepo, A. Adebiyi, M. Adebiyi, O. Okesola

引用次数: 7

Performance Evaluation Of Machine Learning Techniques For Prediction Of Graduating Students In Tertiary Institution 机器学习技术在高校毕业生预测中的性能评价

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240888

Ajinaja Micheal Olalekan, O. Egwuche, Sy Olatunji

{"title":"Performance Evaluation Of Machine Learning Techniques For Prediction Of Graduating Students In Tertiary Institution","authors":"Ajinaja Micheal Olalekan, O. Egwuche, Sy Olatunji","doi":"10.1109/ICMCECS47690.2020.240888","DOIUrl":"https://doi.org/10.1109/ICMCECS47690.2020.240888","url":null,"abstract":"Near accurate prediction of students’ future performance based on their historical academic records is important for effective pedagogical interventions. It is imperative to provide an enhanced prediction system that can assist educational institutions to identify and monitor students at different threshold and to focus on improving students that their threshold is less than graduation at early stage. Studies on the prediction of graduating students using data mining techniques have been widely carried out in the existing literature. The paper applied Baye’s theorem and Artificial Neural Networks (ANN) to build a predictive model for the likelihood of students’ graduation in a tertiary institution. The prediction was performed on four variables- Unified Tertiary Matriculation Examination (UTME), Number of sittings for O’level (NOS), Grade Points of O’level (Grade) and Mode of Entry (PreND). The implementation was carried out in Rstudio environment. The results showed that ANN had higher accuracy compared to Bayesian Classification. ANN performed better because of the learning rules it contains.","PeriodicalId":347202,"journal":{"name":"2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125039458","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}

引用次数: 11

Modeling Infectious Diseases in Jos, Nigeria using PAR and PEWMA Models 利用PAR和PEWMA模型在尼日利亚乔斯建立传染病模型

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240842

Moday Osagie Adenomon, Esther Temidayo Fagbemi

{"title":"Modeling Infectious Diseases in Jos, Nigeria using PAR and PEWMA Models","authors":"Moday Osagie Adenomon, Esther Temidayo Fagbemi","doi":"10.1109/ICMCECS47690.2020.240842","DOIUrl":"https://doi.org/10.1109/ICMCECS47690.2020.240842","url":null,"abstract":"this research work examined the interrelationship among HIV/AIDS, Tuberculosis, and Hepatitis diseases in Plateau state. To achieve this, annual data for the period from 2003 to 2018 was collected from the department of biostatistics at the Plateau State Specialist Hospital (PSSH), Jos, Nigeria. The methods of analysis employed are the Poisson Autoregressive (PAR(1)) and the Poisson Exponentially Weighted Moving Average (PEWMA) Models. The results suggested significant annual decrease of about 23.9% and 4% in Tuberculosis and HIV/AIDS respectively. Furthermore, the results suggested significant annual increase of about 46% in Hepatitis. In addition, the PEWMA model suggested that TB increased by about 0.02% when HIV increase, but Hepatitis significantly increased TB by at least 0.24%. in addition, HIV increase by about 0.85% when TB increases but Hepatitis has no such effect on HIV cases. Lastly, PEWMA model suggested a rise of 0.5% in Hepatitis cases when there TB increase, but increase in HIV has no significant effect on Hepatitis cases in Jos. Therefore this study recommended that campaign against TB should be improved because TB cases significantly affect HIV and Hepatitis in Jos, Nigeria.","PeriodicalId":347202,"journal":{"name":"2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125532295","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}

引用次数: 0

Comparative Analysis of Machine Learning Techniques in Health System 机器学习技术在卫生系统中的比较分析

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240861

Olubukola Emmanuel Olawade, S. Onashoga, O. Arogundade

引用次数: 1

On the Boundedness Analysis of the State Variables for a Loaded DC Servo Motor System 负载直流伺服电机系统状态变量的有界性分析

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240899

L. A. Olutimo, O. Oni, I. D. Omoko

引用次数: 0

An Improved Customer Relationship Management Model for Business-to-Business E-commerce Using Genetic-Based Data Mining Process 基于遗传数据挖掘的企业对企业电子商务客户关系管理模型

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240875

A. Makinde, O. R. Vincent, A. Akinwale, Adebayo Oguntuase, Ijegwa David Acheme

{"title":"An Improved Customer Relationship Management Model for Business-to-Business E-commerce Using Genetic-Based Data Mining Process","authors":"A. Makinde, O. R. Vincent, A. Akinwale, Adebayo Oguntuase, Ijegwa David Acheme","doi":"10.1109/ICMCECS47690.2020.240875","DOIUrl":"https://doi.org/10.1109/ICMCECS47690.2020.240875","url":null,"abstract":"Customer Relationship Management (CRM) empowers the employees and takes customers’ satisfaction to a higher level. However, CRM faces some challenges in Business-to-Business (B2B) e-commerce because CRM data are rarely analyzed across market segments or customer categories and customer–firm relationship is also complex. Therefore, making appropriate decisions in CRM model is difficult. This paper presents a combined model for B2B CRM using Genetic algorithm and Data Mining Techniques to improve decision making. The model classifies the customers into Repeat and Shop-and-Go customers. A modified Data mining – C5.0 was used for customer classification and Genetic algorithm was used to optimize the rules generated by the decision tree algorithm. The results showed that the proposed model effectively allocates resources to the most profitable group of customers. The proposed model has higher accuracy and outperforms others when compared to the conversional C5.0, k-means, and Support Vector Machine (SVM) algorithm.","PeriodicalId":347202,"journal":{"name":"2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS)","volume":"387 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120878156","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}

引用次数: 3

An Ontology-based Knowledge Acquisition Model for Software Anomalies Systems 基于本体的软件异常系统知识获取模型

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240896

T. Adetunji, O. R. Vincent, C. Ugwunna, Lateefat Adeola Odeniyi, O. Folorunso

{"title":"An Ontology-based Knowledge Acquisition Model for Software Anomalies Systems","authors":"T. Adetunji, O. R. Vincent, C. Ugwunna, Lateefat Adeola Odeniyi, O. Folorunso","doi":"10.1109/ICMCECS47690.2020.240896","DOIUrl":"https://doi.org/10.1109/ICMCECS47690.2020.240896","url":null,"abstract":"Vast knowledge abounds in the field of anomalies in software systems, especially when these anomalies are rightly and wholly classified. However, it has been hard to find this knowledge in a single repository to yield potentially useful insights into understanding the types of errors inherent in a system to correct them to yield robust software systems ultimately. The few earlier studies geared towards this direction could not adequately address this issue due to the inadequacy of the techniques employed. This paper aims to correct this phenomenon by using the Protégé knowledge acquisition tool to build a prototype ontology-based knowledge system. Ontologies— consensual machine-readable resources—are designed to promote the sharing, interoperability, and reuse of knowledge. The ontology built is integrated with the inference rule of an expert system to produce the knowledge system where both elicitation and validation of domain facts are done. This will, therefore, lead to the effortless building of seamless, robust, and integrity-filled systems whose knowledge is reusable and sharable.","PeriodicalId":347202,"journal":{"name":"2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124063324","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}

引用次数: 1

Swarm Intelligence Algorithm and its Application:A Critical Review 群智能算法及其应用综述

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.246996

Akintayo Oyebanji Kumoye, R. Prasad, M. Fonkam

引用次数: 5

PCA Model For RNA-Seq Malaria Vector Data Classification Using KNN And Decision Tree Algorithm 基于KNN和决策树算法的RNA-Seq疟疾病媒数据PCA分类模型

2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) Pub Date : 2020-03-01 DOI: 10.1109/ICMCECS47690.2020.240881

M. Arowolo, M. Adebiyi, A. Adebiyi, O. Okesola

引用次数: 23