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}
Lubomír Štěpánek, Filip Habarta, I. Malá, L. Marek
{"title":"Jack-knifing in small samples of survival data: when bias meets variance to increase estimate precision","authors":"Lubomír Štěpánek, Filip Habarta, I. Malá, L. Marek","doi":"10.1109/ICCMA53594.2021.00030","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00030","url":null,"abstract":"Estimates performed particularly using small samples are a priori inaccurate. Furthermore, estimations of m-year survival rates, especially for large m ≫ 0, are inevitable of low precision because they are calculated as fractions with both low numerators and denominators. In this study, we use different degrees of jack-knifing of the original dataset used for m-year survival rates estimations to optimize the trade-off between decreasing variance (and increasing accuracy) and increasing bias of the estimates. Assuming the jack-knife enriches the original data in an allowed way since it does not generate new, non-existing observations, the results could suggest overcoming the small sample issue.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"77 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":"120963654","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}
{"title":"An Enhanced approach of the K-means clustering for Anomaly-based intrusion detection systems*","authors":"Meriem Kherbache, D. Espès, Kamal Amroun","doi":"10.1109/ICCMA53594.2021.00021","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00021","url":null,"abstract":"The development of an anomaly-based Intrusion Detection System (IDS) is of primary importance in networks because it reinforces security. Unlike supervised methods, unsupervised methods are not widely used although they are fast and efficient. In this paper, we propose an unsupervised approach based on the K-means method to show the efficacy of these models over the supervised methods. The proposed model improves the K-means method using the Caliniski Harabasz indicator to find the appropriate number of clusters required for clustering by computing the intra-cluster to inter-cluster ratio. Above all, the proposed model is applied to two datasets, the well-known NSL-KDD and the newest CICIDS2017. The experimental results show that the proposed model exceeds largely the traditional K-means method. Additionally, it is also very efficient both in detection and time consuming compared to the SVM classifier that is a supervised classifier.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"2 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":"126747145","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}
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}
Owen Casey, Rushit Dave, Naeem Seliya, E. S. Boone
{"title":"Machine Learning: Challenges, Limitations, and Compatibility for Audio Restoration Processes","authors":"Owen Casey, Rushit Dave, Naeem Seliya, E. S. Boone","doi":"10.1109/ICCMA53594.2021.00013","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00013","url":null,"abstract":"In this paper, machines learning networks are explored for their use in restoring degraded and compressed speech audio. The project intent is to build a new trained model from voice data to learn features of compression artifacting (distortion introduced by data loss from lossy compression) and resolution loss with an existing algorithm presented in ‘SEGAN: Speech Enhancement Generative Adversarial Network’. The resulting generator from the model was then to be used to restore degraded speech audio. This paper details an examination of the subsequent compatibility and operational issues presented by working with deprecated code, which obstructed the trained model from successfully being developed. This paper further serves as an examination of the challenges, limitations, and compatibility in the current state of machine learning.","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":"128049409","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}
{"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}
{"title":"Selective Blocking Approach of User Equipment in Restricted Communication Zones","authors":"Michael Agyare, J. J. Kponyo, F. Oduro-Gyimah","doi":"10.1109/ICCMA53594.2021.00026","DOIUrl":"https://doi.org/10.1109/ICCMA53594.2021.00026","url":null,"abstract":"A selective mobile phone communication blocking active interceptor system for specific mobile phone restricted zones is designed. The system provides eligibility of communication based on the type of communication service permitted for the specific restricted locations. The designed system was simulated using a Fuzzy Inference System (FIS) toolbox with a set of IF-THEN rules and membership functions (MFs) for the input and output of the system. The eligibility for communication services was designed to suit specific user locations. These locations were converted into input triangular MFs. The output is the decision (“allow” and “not allow”) for each of the inputs. S-shape and Z-shape MFs were used as the output decision variables. The results indicate selective blocking of communication services according to the type of communication service permitted for a specific location. In addition, privileged users were given total access to all communication services for each specific location.","PeriodicalId":131082,"journal":{"name":"2021 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"169 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":"123366400","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}
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}
{"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}
{"title":"[Title page iii]","authors":"","doi":"10.1109/iccma53594.2021.00002","DOIUrl":"https://doi.org/10.1109/iccma53594.2021.00002","url":null,"abstract":"","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":"134197715","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}