2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)最新文献_第8页

Reduction of Frequency Disruption During Cyber-Attack in the Power System 减少电力系统网络攻击时的频率中断

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350518

Muhammad Musleh Uddin, M. Kabir

{"title":"Reduction of Frequency Disruption During Cyber-Attack in the Power System","authors":"Muhammad Musleh Uddin, M. Kabir","doi":"10.1109/STI50764.2020.9350518","DOIUrl":"https://doi.org/10.1109/STI50764.2020.9350518","url":null,"abstract":"This paper proposes an effective stable system model, called as ESSM for providing stable frequency in power system during cyber-attack. The proposed ESSM is formulated by four different controllers, such as, LFC, AGC, AGC-PID and LQR that are implemented in a common system model individually. The focusing issue of this work is that a new numerical problem is solved by the implementation of the proposed model that has been run by incorporating the above four different controllers. The purpose of considering the new problem solution in our proposed ESSM is to achieve an effective stable system model. According to our knowledge, nobody has solved such problem before that has been solved in this paper. In this work, to achieve the proposed ESSM, the individual system models with four different controllers have been simulated in MATLAB using SIMULINK tool and the results are compared in terms of frequency deviation and settling time. The simulation results exhibit that, all the system models work well to minimize the frequency disturbance within very short time. The comparisons among the four models show that, LQR performs better compared to the other models in terms of reducing settling time as well as reducing frequency deviation.","PeriodicalId":242439,"journal":{"name":"2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126227396","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

Reliable Identity Management System Using Raspberry Pi 可靠的身份管理系统使用树莓派

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350462

Md. Rakib Hasan, Partha Chakraborty, M. Khatun, Aditi Sarker, Kawshik Banerjee, T. Choudhury, Mohammad Abu Yousuf, Mohammad Zahidur Rahman

{"title":"Reliable Identity Management System Using Raspberry Pi","authors":"Md. Rakib Hasan, Partha Chakraborty, M. Khatun, Aditi Sarker, Kawshik Banerjee, T. Choudhury, Mohammad Abu Yousuf, Mohammad Zahidur Rahman","doi":"10.1109/STI50764.2020.9350462","DOIUrl":"https://doi.org/10.1109/STI50764.2020.9350462","url":null,"abstract":"Biometric authentication, the process of verification using unique biological characteristics, is considered one of the most accurate technologies for authentication. It compares two or more biometric data to identify the differences among them properly. Based on the comparison between individual’s biometric features and stored authorized features, it makes the decision of matched or mismatched. If the given sample of the biometric data matches with the stored one, authorization is confirmed. Nowadays, many real-time applications use biometric authentication to meet security purposes fully. However, it is difficult to implement fingerprint recognition system specially on Linux based computer. A well-known, less costly embedded computer called Raspberry Pi is used to build the entire system. Fingerprint enrollment, fingerprint recognition, photo capture, QR code generation as well as QR code reading were entirely done using python and python associated libraries. For storage management, we have used MySQL as it is convenient and open-source. This paper discusses about a quality authentication model which is highly capable and cost- effective. The authentication process consists of extracting the biometric features with ORB algorithm, matching those features using FLANN matcher, generating and validating QR code based on encrypted personal information accurately. Here, AES algorithm is used for encrypting personal data which is then converted and stored in form of QR code. Final authentication process involves both fingerprint and QR code validation. Performing two factor authentication affixes more reliability to the system.","PeriodicalId":242439,"journal":{"name":"2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114007635","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

Cyber Security Threat Modeling of A Telesurgery System 远程手术系统的网络安全威胁建模

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350452

Md. Rashid Al Asif, R. Khondoker

引用次数: 5

Hand Gesture Recognition for Bangla Sign Language Using Deep Convolution Neural Network 基于深度卷积神经网络的孟加拉手语手势识别

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350484

Dardina Tasmere, Boshir Ahmed

引用次数: 7

NAVIX: A Wearable Navigation System for Visually Impaired Persons NAVIX:视障人士可穿戴导航系统

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350480

Debasish Bal, Md. Munirul Islam Tusher, Mizanur Rahman, Md. Salmanur Rahman Saymon

{"title":"NAVIX: A Wearable Navigation System for Visually Impaired Persons","authors":"Debasish Bal, Md. Munirul Islam Tusher, Mizanur Rahman, Md. Salmanur Rahman Saymon","doi":"10.1109/STI50764.2020.9350480","DOIUrl":"https://doi.org/10.1109/STI50764.2020.9350480","url":null,"abstract":"Visually impaired people meet several difficulties such as freedom of navigation inability, informing location, obstacle or sudden danger, and many more. None can erase this worst feeling. However, our fundamental aim of this project is to introduce a wearable system for blinds under indoor conditions, which can be mounted on a jacket, portable, lightweight, and user friendly as well as the optimum solution. Such behaviours engender a new prototype and a part of nascent technological improvement. The system comprises Raspberry Pi, three ultrasonic sensors, camera module, vibration motor, gyroscope, emergency button, and mobile application for android, namely ‘Blynk’. Raspberry Pi acts as a ‘Central Processing Unit (CPU)’, connected with each part. Among them, ultrasonic sensors detect any blockage within 400 cm and send an alert through the headpiece when it appears within 30 cm. Camera module read frame by frame, identify the person standing in front and recognize pre-trained faces using ‘Haar feature’ algorithm. The gyroscope provides information about the 3D axis of the patient, which acts instantly during an unusual activity such as fall detection. The software has been installed in the cellphone of the guardian to receive an alert automatically. It may occur in the event of an accident or, pushing the ‘Emergency Button’. A wearable blind assistive system-based project installed upon the jacket obviates the needs for a pair of eyes or a helping hand in an oblique manner, which in turn reduces the misery more than a modicum.","PeriodicalId":242439,"journal":{"name":"2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131942308","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: 6

Neural Network Compression by Filter Similarity Detection and Visualization 基于滤波器相似度检测和可视化的神经网络压缩

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350412

Mayesha Mukarrama, Abul Kalam al Azad, Khan Raqib Mahmud

引用次数: 0

Prognostic Biomarkers Identification for Diabetes Prediction by Utilizing Machine Learning Classifiers 利用机器学习分类器识别糖尿病预测的预后生物标志物

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350498

Utsha Das, Azmain Yakin Srizon, Md. Ansarul Islam, Dhiman Sikder Tonmoy, Md. Al Mehedi Hasan

{"title":"Prognostic Biomarkers Identification for Diabetes Prediction by Utilizing Machine Learning Classifiers","authors":"Utsha Das, Azmain Yakin Srizon, Md. Ansarul Islam, Dhiman Sikder Tonmoy, Md. Al Mehedi Hasan","doi":"10.1109/STI50764.2020.9350498","DOIUrl":"https://doi.org/10.1109/STI50764.2020.9350498","url":null,"abstract":"Diabetes caused 4.2 million deaths in 2019 alone which makes it the seventh leading cause of death worldwide. Although diabetes can be treated, late treatment can be fatal and may result in early death. Moreover, diabetes is a costly disease to maintain, hence, early detection of diabetes can facilitate the patients by indicating the time to seek treatment and to get prepared mentally and financially. Previously, various studies suggested and proposed different approaches for achieving near-perfect accuracy but not many works focused on finding the appropriate attributes which can predict the disease at the early stage. In this study, we focused on finding those significant features and our experimental analysis showed the findings of 10 significant features that can achieve a near-perfect recognition of 98.08%. The feature selection approaches used in this research are the Chi-Square test, the Minimum Redundancy Maximum Relevance (mRMR) test, and the Recursive Feature Elimination test based on Random Forest (RFE-RF). Also, the seven classifiers utilized in this research are Decision Tree (DT), K-Nearest Neighbors (KNN), Logistic Regression (LR), Naïve Bayes (NB), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM).","PeriodicalId":242439,"journal":{"name":"2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126977840","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 cost analysis of VSC-HVDC and HVAC as transmission system for a 50 MW offshore wind farm in Hatiya Island Hatiya岛50mw海上风电场VSC-HVDC与HVAC输电系统成本比较分析

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350463

Md. Sarower Jahan, S. Hamim, Md. Tasrif Imran Bhuiyan, Md. Jaynal Abeadin, Md. Nabid Chowdhury

引用次数: 2

A Computer Based Image Processing Approach to Identify Rice Blast 基于计算机图像处理的稻瘟病识别方法

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350507

T. M. Shahriar Sazzad, A. Anwar, Sabrin Islam, Sumaiya Afroz Mila, Sahrima Jannat Oishwee, Afia Anjum

{"title":"A Computer Based Image Processing Approach to Identify Rice Blast","authors":"T. M. Shahriar Sazzad, A. Anwar, Sabrin Islam, Sumaiya Afroz Mila, Sahrima Jannat Oishwee, Afia Anjum","doi":"10.1109/STI50764.2020.9350507","DOIUrl":"https://doi.org/10.1109/STI50764.2020.9350507","url":null,"abstract":"Fungus and bacteria are the main cause of rice plant diseases. Among all fungal diseases rice blast is considered as one of the most common and fatal rice plant disease. Without proper care and use of pesticides this deadly plant disease can cause huge damage for rice crops. Detection of rice blast disease at the early stage can help farmers to use proper pesticides and can save their crops and hence a computerized approach is necessary. Currently a good number of approaches available but none of them seems to provide a suitable solution in terms of identification accuracy. A suitable approach has been presented in this study where both input and output images are color images. Various image processing steps were considered in this study which includes enhancement, noise reduction, color image segmentation, and color features for identification. CNN classifier was applied for validation purpose. In compare to existing available approaches this study proposed approach is capable of providing better results in terms of accuracy which is 97.50%.","PeriodicalId":242439,"journal":{"name":"2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128582498","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

Network Lifetime Aware Routing Algorithm for Energy Harvesting Wireless Sensor Networks 能量收集无线传感器网络的网络寿命感知路由算法

2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) Pub Date : 2020-12-19 DOI: 10.1109/STI50764.2020.9350422

Amena Zahan Prithibi, Syeda Kanij Faria, Palash Roy, M. Razzaque

引用次数: 2