2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)最新文献_第10页

Early Detection of Autism by Extracting Features: A Case Study in Bangladesh 通过提取特征来早期发现自闭症:孟加拉国的一个案例研究

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644357

Md. Shahriare Satu, Farha Farida Sathi, Md. Sadrul Arifen, Md. Hanif Ali, M. Moni

{"title":"Early Detection of Autism by Extracting Features: A Case Study in Bangladesh","authors":"Md. Shahriare Satu, Farha Farida Sathi, Md. Sadrul Arifen, Md. Hanif Ali, M. Moni","doi":"10.1109/ICREST.2019.8644357","DOIUrl":"https://doi.org/10.1109/ICREST.2019.8644357","url":null,"abstract":"Autism Spectrum Disorder (ASD) is a neurobehavioral disorder that begins at childhood and exists this whole life. The objective of this work is that to explore significant features of normal and autism of divisional regions in Bangladesh. We collected individual samples of various children from their parents between 16 to 30 months of different residents using Autism Barta apps by web and fieldwork at Savar, Bangladesh. Then, we preprocessed our data and categorized frequent features based on their individual regions. Different tree based techniques such as J48, Logistic Model Tree, Random Forest, Reduced Error Pruned Tree, and Decision Stump were analyzed to find out the best classifier of them. From these classifiers, J48 showed the best outcomes than other classifiers. We extracted 9 rules and associated conditions from J48 decision tree and gathered frequent instances from our data for extracted rules. Finally, 8 within 23 features were required to classify normal and autism of individual regions in Bangladesh. Besides, 4 rules (10 Conditions) for normal and 5 (12 Conditions) rules for autism out of 9 (16 Conditions) rules were extracted from decision tree. This outcomes assist us to find out significant features of autism in Bangladesh. We expect that our work will be helpful things to improve their condition that leads them to a normal life.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125536195","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: 24

Domicile - An IoT Based Smart Home Automation System 住所-基于物联网的智能家居自动化系统

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644349

Md. Sadad Mahamud, Md. Saniat Rahman Zishan, Syed Ishmam Ahmad, Ahmed Rezaur Rahman, Md.Mehedi Hasan, Md. Lutfur Rahman

引用次数: 22

Water Heating System Using Solar Concentration and Temperature Feedback: A Aost Efficient Approach 利用太阳能集中和温度反馈的热水系统:一种最有效的方法

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644169

Md. Arif Abdulla Samy, Md. Abdullah Al Rakib Hassan, Md. Humayun Kabir Chy, Md. Naimul Hoque, Abdullah Al-Imran, Md. Nahian Al Subri Ivan

{"title":"Water Heating System Using Solar Concentration and Temperature Feedback: A Aost Efficient Approach","authors":"Md. Arif Abdulla Samy, Md. Abdullah Al Rakib Hassan, Md. Humayun Kabir Chy, Md. Naimul Hoque, Abdullah Al-Imran, Md. Nahian Al Subri Ivan","doi":"10.1109/ICREST.2019.8644169","DOIUrl":"https://doi.org/10.1109/ICREST.2019.8644169","url":null,"abstract":"Hot water is a very essential component to be utilized for residential, business and mechanical purposes. Different assets i.e. coal, diesel, gas, power and so forth, are utilized to warm water, which is very costly process. Sunlight based water warming framework is one of them and more affordable than others. The extent of the frameworks relies upon accessibility of sun-oriented radiation, temperature necessity of client, topographical condition and game plan of the nearby planetary group and so forth. The primary target of this research was converting the solar energy into thermal energy and controlling the desired hot water temperature for water heating purposes. In this paper, closed loop solar water heating system was used. A solenoid valve was used to control the supply water which will be going to the user. To control the hot water, temperature feedback control system was used which can sense the water temperature using temperature sensor. The temperature of condenser was sensed by using LM35 temperature sensor also. To increase the efficiency of the collector an additional dual-axis concentrator was used. The research was successful to increase water temperature up to 19°C and stable it.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116216899","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 Smart Sensor Network for an Automated Urban Greenhouse 用于城市温室自动化的智能传感器网络

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644079

K. Meah, Jason Forsyth, J. Moscola

引用次数: 7

Design of a Biosignal Based Stress Detection System Using Machine Learning Techniques 基于生物信号的机器学习应力检测系统设计

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644259

Md Fahim Rizwan, Rayed Farhad, Farhan Mashuk, Fakhrul Islam, M. H. Imam

{"title":"Design of a Biosignal Based Stress Detection System Using Machine Learning Techniques","authors":"Md Fahim Rizwan, Rayed Farhad, Farhan Mashuk, Fakhrul Islam, M. H. Imam","doi":"10.1109/ICREST.2019.8644259","DOIUrl":"https://doi.org/10.1109/ICREST.2019.8644259","url":null,"abstract":"This study represents a design of a detection system of stress through machine learning using some available bio signals in human body. Stress can be commonly defined as the disturbance in psychological equilibrium. Stress detection is one of the major research areas in biomedical engineering as proper detection of stress can conveniently prevent many psychological and physiological problems like cardiac rhythm abnormalities or arrhythmia. There are several bio-signals available (i.e. ECG, EMG, Respiration, GSR etc.) which are helpful in detecting stress levels as these signals shows characteristic changes with stress induction. In this paper, ECG was selected as the primary candidate because of the easily available recording (i.e. several mobile clinical grade recorders are available now in the market) and ECG feature extraction techniques. Another advantage of ECG is that respiratory signal information can also be detected form ECG which is known as EDR (ECG derived Respiration) without having separate sensor system for respiration measurement. Features of ECG signals are distinctive and collection of the signals is cost-efficient. From ECG we derived RR interval, QT interval, and EDR features for the development of the model. For the implementation of a supervised machine learning (SVM) method in MATLAB, Physionet’s \"drivedb\" database was used as the training dataset and validation. SVM was chosen for classification, as there are two classes of labeled data; ‘stressed’ or ‘non-stressed’. Several SVM model types were verified by changing the feature number and Kernel type. Our results showed an accuracy level of 98.6% with Gaussian Kernel function and using all available features (RR, QT and EDR), which also emphasizes the importance of respiratory information in stress detection through Machine Learning.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125669717","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: 32

Early Detection of Kidney Disease Using ECG Signals Through Machine Learning Based Modelling 基于机器学习建模的心电图信号早期检测肾脏疾病

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644354

Tahsin M. Rahman, Saima Siddiqua, Siam E. Rabby, Nahid Hasan, M. H. Imam

{"title":"Early Detection of Kidney Disease Using ECG Signals Through Machine Learning Based Modelling","authors":"Tahsin M. Rahman, Saima Siddiqua, Siam E. Rabby, Nahid Hasan, M. H. Imam","doi":"10.1109/ICREST.2019.8644354","DOIUrl":"https://doi.org/10.1109/ICREST.2019.8644354","url":null,"abstract":"This paper introduces the idea of detecting the presence of kidney disease through machine learning based classification modelling, by processing the patient’s ECG signal. Recent studies and ongoing researches have showed that patients undergoing kidney problems start developing cardiac problems- scientifically known as the Cardio Renal Syndrome (CRS) which can lead to a sudden cardiac arrest in the last stages of their disease. Since cardio-vascular diseases and the chronic kidney disease is inter-related, this model can be used for patients undergoing cardio-vascular problems to determine whether their kidneys have been effected or not. If the Chronic Kidney Disease (CKD) can be diagnosed at an earlier stage, it may give the patient some time to help reverse the disease or at least slow its progression by taking necessary medical steps. For this model, digitized ECG data was collected from open access databases such as PTB (for kidney patients) and Fantasia (for healthy people) from Physionet Database (www.physionet.org) and the model was later validated using different data from the same online database. The validation process gave satisfactory results, as the model could successfully classify the users from being healthy or a kidney patient. In our study, we found an accuracy level of 97.6% which was the highest using both features QT and RR interval, in comparison to the accuracy that was found when either one of the features was used.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131755348","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: 10

Power Generation from Waste in Chittagong City, Bangladesh- A Sustainable Approach to Mitigate The Energy Crisis 孟加拉国吉大港废物发电——缓解能源危机的可持续方法

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644306

M. Abrar, A. Hasan

引用次数: 3

Concentrated Solar Power Dish Stirling Technology in Prospect of Energy Crisis in Bangladesh 集中太阳能发电碟斯特林技术在孟加拉能源危机的前景

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644477

Md. Mamun Hossain, T. Ahmed, Zahid Ahsan, Shuvra Saha, K. Firoz

{"title":"Concentrated Solar Power Dish Stirling Technology in Prospect of Energy Crisis in Bangladesh","authors":"Md. Mamun Hossain, T. Ahmed, Zahid Ahsan, Shuvra Saha, K. Firoz","doi":"10.1109/ICREST.2019.8644477","DOIUrl":"https://doi.org/10.1109/ICREST.2019.8644477","url":null,"abstract":"With the exponential increase in demand of power all over the world, the limited natural fuel resources are being stressed every hour. No matter the abundance, these resources are bound to deplete completely in far future. Humankind is now moving onto such methods for electricity generation which can meet our demand and preserve the nature’s reserves simultaneously. Concentrated Solar Power (CSP) uses the heat from the Sun to produce mechanical thus electrical power. It was chosen a preexisting method (Euro Dish) and modified it to a level suitable for small-scale/personal use. This is an obstacle in the way of making this technology and method popular and usable on a mass scale, let alone on a personal scale. In this paper, stirling engine was used as a heat engine with concentrated solar power. It also shows the comparison between concentrated solar power (CSP) and photovoltaic (PV) system. The primary objective, to generate mechanical power from Stirling engine and converting it into electrical power through a dc generator of low r.p.m., was completed with minor inefficiencies and discrepancies.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116911681","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

Camera Model Identification using Deep CNN and Transfer Learning Approach 使用深度CNN和迁移学习方法识别相机模型

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644194

Md. Hasan Al Banna, Md Ali Haider, Md. Jaber Al Nahian, M. Islam, K. A. Taher, M. S. Kaiser

引用次数: 21

Construction and Interpolation of a Multi-frequency Radio Map 多频无线电地图的构造与插值

2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pub Date : 1900-01-01 DOI: 10.1109/ICREST.2019.8644474

Azril Haniz, G. Tran, K. Sakaguchi, J. Takada, Toshihiro Yamaguchi, T. Mitsui, S. Arata

引用次数: 1