2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)最新文献_第7页

Prediction of Thyroid Disease(Hypothyroid) in Early Stage Using Feature Selection and Classification Techniques 使用特征选择和分类技术预测甲状腺疾病(甲状腺功能减退)的早期

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9397052

Md Riajuliislam, Khandakar Zahidur Rahim, Antara Mahmud

{"title":"Prediction of Thyroid Disease(Hypothyroid) in Early Stage Using Feature Selection and Classification Techniques","authors":"Md Riajuliislam, Khandakar Zahidur Rahim, Antara Mahmud","doi":"10.1109/ICICT4SD50815.2021.9397052","DOIUrl":"https://doi.org/10.1109/ICICT4SD50815.2021.9397052","url":null,"abstract":"Thyroid disease is one of the most common diseases among the female mass in Bangladesh. Hypothyroid is a common variation of thyroid disease. It is clearly visible that hypothyroid disease is mostly seen in female patients. Most people are not aware of that disease as a result of which, it is rapidly turning into a critical disease. It is very much important to detect it in the primary stage so that doctors can provide better medication to keep itself turning into a serious matter. Predicting disease in machine learning is a difficult task. Machine learning plays an important role in predicting diseases. Again distinct feature selection techniques have facilitated this process prediction and assumption of diseases. There are two types of thyroid diseases namely 1. Hyperthyroid and 2.Hypothyroid. Here, in this paper, we have attempted to predict hypothyroid in the primary stage. To do so, we have mainly used three feature selection techniques along with diverse classification techniques. Feature selection techniques used by us are Recursive Feature Selection(RFE), Univariate Feature Selection(UFS) and Principal Component Analysis(PCA) along with classification algorithms named Support Vector Machine(SVM), Decision Tree(DT), Random Forest(RF), Logistic Regression(LR) and Naive Bayes(NB). By observing the results, we could extrapolate that the RFE feature selection technique helps us to provide constant 99.35% accuracy for all four classification algorithms. Thus it's deduced from our research that RFE helps each classifier to attain better accuracy than all the other feature selection methods used.","PeriodicalId":239251,"journal":{"name":"2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126720475","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: 13

Tolerating Soft Errors using Enhanced Matrix Code 使用增强矩阵代码容忍软错误

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396840

Md. Mizanur Rahman Khan, M. S. Sadi, S. M. Al-Zihadi, Jyotirmoy Saha

引用次数: 0

A Hybrid MCDM Approach based on AHP, and TOPSIS to select an ERP system in Bangladesh 基于AHP和TOPSIS的混合MCDM方法选择孟加拉国ERP系统

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396932

Mohd. Raihan Uddin, A. Al Noman, Farzana Tasnim, Nuren Nafisa, Saddam Hossain

引用次数: 2

Social Group Optimized Machine-Learning Based Elderly Fall detection Approach Using Interdisciplinary Time-Series Features 基于跨学科时间序列特征的社会群体优化机器学习老年人跌倒检测方法

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396919

Md. Jaber Al Nahian, Tapotosh Ghosh, Md. Hasan Al Banna, M.N. Uddin, M. Islam, K. A. Taher, M. S. Kaiser

引用次数: 1

Clusterization of Different Vulnerable Countries for Immigrants Due to Covid-19 Using Mean Probabilistic Likelihood Score and Unsupervised Mining Algorithms 基于平均概率似然评分和无监督挖掘算法的Covid-19移民不同脆弱国家聚类

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396950

Shovan Bhowmik, Saha Reno, S. Sultana, Mamun Ahmed

{"title":"Clusterization of Different Vulnerable Countries for Immigrants Due to Covid-19 Using Mean Probabilistic Likelihood Score and Unsupervised Mining Algorithms","authors":"Shovan Bhowmik, Saha Reno, S. Sultana, Mamun Ahmed","doi":"10.1109/ICICT4SD50815.2021.9396950","DOIUrl":"https://doi.org/10.1109/ICICT4SD50815.2021.9396950","url":null,"abstract":"In many developing and poor countries, people often migrate to suitable countries to earn their livelihood and support their families. Due to the ongoing pecuniary disaster that ensued because of COVID-19, many immigrants are coming back to their ancestry from different migrant-friendly countries for several reasons. In this paper, a novel approach has been proposed to segregate these countries into five vulnerability labels based on probabilistic likelihood score (LHS) and unsupervised clustering algorithms (CA). A survey dataset of returnee people including various information has been collected and leveraged as attributes in this study. Depending on the dissemination of attributes, LHS has been generated using Bayes' Theorem for each vulnerable country and three unsupervised mining algorithms (KMeans++, Agglomerative and BIRCH) have been applied to the LHS for categorization. Output labels obtained from CA are then evaluated appropriating the average LHS. Multiple performance measurement metrics (Adjusted Rand Index, Mutual Information based Score) have been consolidated to get an incisive comparison of vulnerability labels resulting from CA and expected LHS. The highest value of 0.74 has been attained as Normalized Mutual Information based Score for BIRCH clustering accompanying ample results for the remaining algorithms. The result has shown that the combined application of probabilistic LHS and unsupervised CA can be a reliable method to identify the vulnerability of different countries generally chosen by migrant people.","PeriodicalId":239251,"journal":{"name":"2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133982248","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

A Belief Rule-Based Expert System to Assess Multiple Human Reaction in the Context of Facebook Posts under Uncertainty 基于信念规则的专家系统在不确定性下评估Facebook帖子背景下的多重人类反应

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9397016

Shazzad Hossain Mazumder, Mohammad Shahadat Hossain, Karl Andersson

{"title":"A Belief Rule-Based Expert System to Assess Multiple Human Reaction in the Context of Facebook Posts under Uncertainty","authors":"Shazzad Hossain Mazumder, Mohammad Shahadat Hossain, Karl Andersson","doi":"10.1109/ICICT4SD50815.2021.9397016","DOIUrl":"https://doi.org/10.1109/ICICT4SD50815.2021.9397016","url":null,"abstract":"Human may have multiple reactions at a time. Social media is a real-life example where people can express their reactions or opinions. For example, Facebook has become a widely used social media where users express their opinion on different posts such as status or photo post. Therefore, user opinions can easily be achieved through social media and then analyzed and applied in different practical fields. Reaction assessment of Social media can be an excellent source of information. Therefore, an accurate assessment of human reaction is a must. Facebook provides six emoticons for each of the posts of its users. The six emoticons define six types of reactions. The user, who wants to react to any post, have to choose only one of the six emoticons. There is no scope for a user to express multiple reactions at a time. Moreover, if a user selects an emoticon, then the system takes that input as 100% of that corresponding reaction, or 0% if not selected, thus the reaction assessment system becomes a Boolean system. Therefore, the assessment of multiple reactions of the user cannot be measured with 100% certainty due to the existence of various types of uncertainties such as vagueness, imprecision, randomness, ignorance, incompleteness, and ambiguity in the system. Therefore, to assess multiple human reactions, an expert system is needed to handle all these uncertainties. The system design, development process, and applications of an expert system to assess multiple human reactions are described in this paper. For the development of the expert system, the Belief Rule-Based Inference Methodology using the Evidential Reasoning (RIMER) approach has been used and the system is named as a Belief Rule-Based Expert System (BRBES). The developed BRBES can mitigate all the uncertainties mentioned above.","PeriodicalId":239251,"journal":{"name":"2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130075291","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

JCVirusNEntamoebaNET (JCENET): A Deep Neural Network for John Cunningham Virus and Entamoeba Parasite Detection JCVirusNEntamoebaNET (JCENET):一种检测约翰坎宁安病毒和内阿米巴寄生虫的深度神经网络

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396771

M. Hasan, Muhammad Usama Islam

{"title":"JCVirusNEntamoebaNET (JCENET): A Deep Neural Network for John Cunningham Virus and Entamoeba Parasite Detection","authors":"M. Hasan, Muhammad Usama Islam","doi":"10.1109/ICICT4SD50815.2021.9396771","DOIUrl":"https://doi.org/10.1109/ICICT4SD50815.2021.9396771","url":null,"abstract":"Parasites and viruses are responsible for attacking the immune system of human body and destroying it in the process which makes detection of parasites and virus a penultimate task in modern medical analysis. The detection process is often characterized with symptoms, microscopic tests. However, little research work has been carried out to exploit and garner the capability of deep learning to classify and detect the parasites and virus. In our research work, we propose a new deep neural network based image processing approach to classify the parasites, germs and virus for the case of Entamoeba parasite which leads to Amebiasis disease and John Cunningham virus which is responsible for Progressive multifocal leukoencephalopathy (PML). We have applied our own deep convolutional neural network to classify the JC virus and entamoeba using immunohistochemistry(IHC) images and microscope images from a dataset that We have collected from various neuropathology laboratories, and researchers. Our model achieved overall classification accuracy of 77% and F1-score of 76% with a strong narrative of rationale for utilization of batch normalization and dropout layer in deep learning model.","PeriodicalId":239251,"journal":{"name":"2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115316431","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

Prospects of Internet of Things for Bangladesh 孟加拉物联网的前景

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396818

Nasim Parvez, Tamjidul Haque Chowdhury, Shahina Sultana Urmi, K. A. Taher

{"title":"Prospects of Internet of Things for Bangladesh","authors":"Nasim Parvez, Tamjidul Haque Chowdhury, Shahina Sultana Urmi, K. A. Taher","doi":"10.1109/ICICT4SD50815.2021.9396818","DOIUrl":"https://doi.org/10.1109/ICICT4SD50815.2021.9396818","url":null,"abstract":"This paper represents a conceptual framework model for the Prospects of Internet of Things (IoT) for Bangladesh. IoT is an enhancement of the internet that can be described as things or objects being connected anytime and anywhere with anything, so as to give seamless communications and external services. Bangladesh has recently formulated ‘National IoT Strategy’ in March 2020, mentioning that IoT is an enabler to the development and contributor to economic growth of a country. The prospects of IoT depends on its applications for improving agriculture, manufacturing, healthcare, transportation, education delivery, business process optimization, smart governance with public utility services, smart cities etc. Similarly, IoT is likely to have huge opportunities and positive impacts for the socio-economic development of Bangladesh. The conceptual model of the study shows that in order to implement the ‘National IoT Strategy’ Bangladesh, she needs to develop a set of policy ‘Guidelines for the adoption of IoT. This research will primarily explore the prospects of IoT in the socio-economic development sectors. The likely outcome of this study is the introduction of IoT enabled socioeconomic development of Bangladesh.","PeriodicalId":239251,"journal":{"name":"2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115519558","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

Municipal Solid Waste Based Power Generation: A Case Study in Chittagong City 城市固体废物发电:以吉大港为例

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396817

S. Alam, F. S. Hossain

引用次数: 0

Solar Energy based Net Metered Easy-Bike Charging Station in Bangladesh 孟加拉国的太阳能净计量简易自行车充电站

2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) Pub Date : 2021-02-27 DOI: 10.1109/ICICT4SD50815.2021.9396847

Mohammad Mahinur Rahman, M. R. Khan

引用次数: 2