2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)最新文献_第2页

Jack-knifing in small samples of survival data: when bias meets variance to increase estimate precision 小样本生存数据的jack- knife:当偏差满足方差以提高估计精度

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00030

Lubomír Štěpánek, Filip Habarta, I. Malá, L. Marek

引用次数: 0

Prediction of Telecommunication Network Outage Time Using Multilayer Perceptron Modelling Approach 基于多层感知机模型的电信网络中断时间预测

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00025

F. Oduro-Gyimah, K. Boateng, Prince Boahen Adu, Kester Quist-Aphetsi

{"title":"Prediction of Telecommunication Network Outage Time Using Multilayer Perceptron Modelling Approach","authors":"F. Oduro-Gyimah, K. Boateng, Prince Boahen Adu, Kester Quist-Aphetsi","doi":"10.1109/ICCMA53594.2021.00025","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00025","url":null,"abstract":"As the demand in communication traffic grows; there should be the provision of reliable telecommunication network to users. Operators however, face a myriad of challenges in fulfilling their part of the contract such as network outage. The phenomenon of network outage has been a challenge that every network operator is consistently trying to avoid. In this study, a multilayer feedforward neural network also called multilayer perceptron (MLP) was adopted to model network outage time of network elements or systems. The MLP network was trained on a 150 samples of daily network outage time data obtained from the Network Operating Centre of an operator in Ghana. The data covered a period of 1st January to 30th May 2018 and was analysed with Matlab software. In developing the model, the input and output layers were kept constant, while the number of neurons were varied from 1 to 20 to obtain a good prediction. The performance of the models were measured by the Mean Squared Error (MSE), Root Mean Squared Error (RMSE) and the Correlation Coefficient (R). After careful and extensive training, validation and testing, 20 models were developed. The MLP selected was 1-4-1 which produced MSE, RMSE, and an R-value of 0.0000024321, 0.00160 and 0.99993 respectively with a prediction accuracy of 97.5%. The study concludes that downtime prediction can be improved by feed forward neural network optimized using Levenberg-Marquardt with sigmoid function in the hidden and linear activation function in the output layer.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132556696","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: 4

An alternative to Cox’s regression for multiple survival curves comparison: A random forest-based approach using covariate structure 多生存曲线比较的Cox回归的替代方法:使用协变量结构的随机森林方法

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00029

Lubomír Štěpánek, Filip Habarta, I. Malá, L. Marek

{"title":"An alternative to Cox’s regression for multiple survival curves comparison: A random forest-based approach using covariate structure","authors":"Lubomír Štěpánek, Filip Habarta, I. Malá, L. Marek","doi":"10.1109/ICCMA53594.2021.00029","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00029","url":null,"abstract":"There are several established methods for comparing more than two survival curves, namely the scale-rank test or Cox’s proportional hazard model. However, when their statistical assumptions are not met, their results’ validity is affected.In this study, we address the mentioned issue and propose a new statistical approach on how to compare more than two survival curves using a random forest algorithm, which is practically assumption-free. The repetitive generating of many decision trees covered by one random forest model enables to calculate of a proportion of trees with sufficient complexity classifying into all groups (depicted by their survival curves), which is the p-value estimate as an analogy of the classical Wald’s t-test output of the Cox’s regression. Furthermore, a level of the pruning of decision trees the random forest model is built with, can modify both the robustness and statistical power of the random forest alternative. The discussed results are confirmed using COVID-19 survival data with varying the tree pruning level.The introduced method for survival curves comparison, based on random forest algorithm, seems to be a valid alternative to Cox’s regression; however, it has no statistical assumptions and tends to reach higher statistical power.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133401986","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

Smart model of accessibility and mobility of health care 医疗保健可及性和流动性的智能模式

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00032

Mêtowanou H. Ahouandjinou, D. Medenou, R. Houessouvo, M.A. Godwind Houdji

{"title":"Smart model of accessibility and mobility of health care","authors":"Mêtowanou H. Ahouandjinou, D. Medenou, R. Houessouvo, M.A. Godwind Houdji","doi":"10.1109/ICCMA53594.2021.00032","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00032","url":null,"abstract":"Benin’s health system, like all health systems, is faced with the challenge of providing quality, safe and affordable health care. The problems of understaffing of health care personnel compared to the WHO recommendation on the one hand, and the problems of poor distribution of these health care personnel over the extent of the health care system on the other hand, lead us to think about a model of mobility and accessibility of health care in Benin. This work aims at setting up an intelligent algorithm of accessibility and mobility of health care and will allow any patient embarked at any point of the health system to be taken care of automatically by a doctor and a nurse. To achieve this, we have (i) studied the state of the art of healthcare accessibility and mobility, (ii) modeled the healthcare trajectory, (iii) developed an algorithm for the automatic assignment and management of a patient in a healthcare system and simulated it using operations research and graph tools. The work allowed to set up a dynamic algorithm of accessibility to health care and to answer the challenges of the health care systems.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124032167","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

Machine Learning: Challenges, Limitations, and Compatibility for Audio Restoration Processes 机器学习:音频恢复过程的挑战、限制和兼容性

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00013

Owen Casey, Rushit Dave, Naeem Seliya, E. S. Boone

引用次数: 0

Exploration of Endogenous Constraints Leading to Failure of Micro Small and Medium Enterprises (MSMEs) in Developing Countries (A Case Study of Mallam, Greater Accra Region of Ghana) 发展中国家中小微企业失败的内生约束探析(以加纳大阿克拉地区马拉姆为例)

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00027

Emmanuel Kwabla Ocloo, Ebenezer Malcalm, G. Kumar

{"title":"Exploration of Endogenous Constraints Leading to Failure of Micro Small and Medium Enterprises (MSMEs) in Developing Countries (A Case Study of Mallam, Greater Accra Region of Ghana)","authors":"Emmanuel Kwabla Ocloo, Ebenezer Malcalm, G. Kumar","doi":"10.1109/ICCMA53594.2021.00027","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00027","url":null,"abstract":"Micro Small and Medium Enterprises (MSMEs) are considered the most enterprises that create jobs in the country when running consistently and very well leading to the achievement of high Gross Domestic Product (GDP) reflecting in the macro economy. However, this inheritance and dreams of MSMEs are not realized due to some endogenous (internal) metrics or factors. The study seeks to investigate the underlying internal factors leading to failure of selected MSMEs in Mallam in Greater Accra Region of Ghana. However, the entire population targeted for this research was 85 while 70 respondents were randomly drawn out of the total population. The 70 selected respondents assisted in proper flow of information required for the success of the research.The research has employed descriptive research design since it portrays accurate responses from owners that are targeted, MSMEs’ managers in the targeted population. Structured questionnaires were used to collect primary data through direct interview of entrepreneurs. Both qualitative and quantitative methods of data collection were applied in this study. The collected data was analyzed using Statistical Package for Social Sciences (SPSS). The findings unraveled two set of endogenous constraints such as entrepreneurial constraints and business or enterprise constraints that lead selected MSMEs to fail in their businesses. Some of the entrepreneurial constraints are poor skills in management, gender and age of entrepreneur, lack of education, and lack of experience. On the other hand, the business challenges are lack of capital, lack of recording accounting data, poor business plan, age and size of company.The study would assist industry players to apply the various constraints identified in their decision-making process. In addition, the research would contribute to existing literature.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123560500","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

Selective Blocking Approach of User Equipment in Restricted Communication Zones 限制通信区内用户设备的选择性阻塞方法

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00026

Michael Agyare, J. J. Kponyo, F. Oduro-Gyimah

引用次数: 0

Cyber Threat Ontology and Adversarial Machine Learning Attacks: Analysis and Prediction Perturbance 网络威胁本体和对抗性机器学习攻击:分析和预测扰动

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00020

Abel Yeboah-Ofori, Umar Mukhtar Ismail, Tymoteusz Swidurski, F. Opoku-Boateng

{"title":"Cyber Threat Ontology and Adversarial Machine Learning Attacks: Analysis and Prediction Perturbance","authors":"Abel Yeboah-Ofori, Umar Mukhtar Ismail, Tymoteusz Swidurski, F. Opoku-Boateng","doi":"10.1109/ICCMA53594.2021.00020","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00020","url":null,"abstract":"Machine learning has been used in the cybersecurity domain to predict cyberattack trends. However, adversaries can inject malicious data into the dataset during training and testing to cause perturbance and predict false narratives. It has become challenging to analyse and predicate cyberattack correlations due to their fuzzy nature and lack of understanding of the threat landscape. Thus, it is imperative to use cyber threat ontology (CTO) concepts to extract relevant attack instances in CSC security for knowledge representation. This paper explores the challenges of CTO and adversarial machine learning (AML) attacks for threat prediction to improve cybersecurity. The novelty contributions are threefold. First, CTO concepts are considered for semantic mapping and definition of relationships for explicit knowledge of threat indicators. Secondly, AML techniques are deployed maliciously to manipulate algorithms during training and testing to predict false classifications models. Finally, we discuss the performance analysis of the classification models and how CTO provides automated means. The result shows that analysis of AML attacks and CTO concepts could be used for validating a mediated schema for specific vulnerabilities.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114497787","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: 2

A DSS-based Comparator for Facial Race Age Estimation 基于 DSS 的面部种族年龄估计比较器

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/ICCMA53594.2021.00017

Ebenezer Nii Ayi Hammond, Shijie Zhou, Qihe Liu

{"title":"A DSS-based Comparator for Facial Race Age Estimation","authors":"Ebenezer Nii Ayi Hammond, Shijie Zhou, Qihe Liu","doi":"10.1109/ICCMA53594.2021.00017","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00017","url":null,"abstract":"Facial age estimation is an essential feature in many applications satisfying the need to provide users with content that corresponds to their ages. However, providing an inclusive facial age estimation solution that is also high-performing is challenging due to the many different factors that influence the face. This article leverages DeepSets for Symmetric Elements (DSS) to propose an approach that aims to extract a reliable set of rich feature vectors for age estimation. It combines a DSS feature extractor, ternary classifier, and a race determiner. Precisely, the extractor consists of a siamese-like layer that applies a regular convolutional neural network to input images and an aggregation module that sums up all of the images and then adds them to the output from the siamese layer. To estimate the age, the ternary classifier obtains the feature vectors seeking to classify them into three possible outcomes that correspond to younger than, similar to, or older than. The correlation is achieved using identical pairs of input and reference images that belong to the same race. The result indicates the similarity between the images: the higher the score, the closer the similarity. With an accuracy of 94.8%, 95.2%, and 90.5% on the MORPH II, a race-inclusive dataset, and the FG-NET, we demonstrate that our proposal exemplifies facial age estimation particularly when the race factor is considered in the estimation.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127028188","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

[Title page iii] [标题页iii]

2021 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2021-07-01 DOI: 10.1109/iccma53594.2021.00002

引用次数: 0