2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)最新文献_第7页

Fractional Order Sinusoidal Oscillator Using only a Single Operational Trans-resistance Amplifier 分数阶正弦振荡器，仅使用单个运算跨阻放大器

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397101

Manoj Kumar, D. Bhaskar, Pragati Kumar

{"title":"Fractional Order Sinusoidal Oscillator Using only a Single Operational Trans-resistance Amplifier","authors":"Manoj Kumar, D. Bhaskar, Pragati Kumar","doi":"10.1109/ICCCIS51004.2021.9397101","DOIUrl":"https://doi.org/10.1109/ICCCIS51004.2021.9397101","url":null,"abstract":"In this paper a fractional order sinusoidal oscillator (FSO) implemented with two fractional capacitors (FC), four resistors and a single operational trans-resistance amplifier (OTRA) has been presented. The characteristic equation of proposed fractional order oscillator has been derived using nodal analysis and the expressions for frequency of oscillation, condition of oscillation and phase difference between the output voltages are obtained. In one special case, when α = β = 1.0, the circuit behaves as a classical single resistance controlled sinusoidal oscillator (SRCO) in which the frequency of oscillation and the condition of oscillation can be varied through separate resistors. These properties are retained even when the value of α and β lie in the range of 0 < α, β < 1. Since the input terminals of OTRA are at virtually ground, the proposed oscillator circuit is also insensitive to parasitic input capacitances and input resistances. The workability of proposed structure has been verified with PSPICE simulation results using a single OTRA (constructed with CMOS transistors using TMSC 0.18 μm technology) and fractional capacitors realized using the method proposed by Valsa and Dovrak and Friedl.","PeriodicalId":316752,"journal":{"name":"2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121994957","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

Reliability based micro-economic cost model for cloud computing systems 基于可靠性的云计算系统微观经济成本模型

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397210

Rohit Sharma, Raghuraj Singh

引用次数: 0

Convolutional Neural Networks Based Diagnosis of Myocardial Infarction in Electrocardiograms 基于卷积神经网络的心电图心肌梗死诊断

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397193

Samir S. Yadav, Sitaram B. More, S. Jadhav, Sanjay R. Sutar

{"title":"Convolutional Neural Networks Based Diagnosis of Myocardial Infarction in Electrocardiograms","authors":"Samir S. Yadav, Sitaram B. More, S. Jadhav, Sanjay R. Sutar","doi":"10.1109/ICCCIS51004.2021.9397193","DOIUrl":"https://doi.org/10.1109/ICCCIS51004.2021.9397193","url":null,"abstract":"Myocardial infarction also called heart attack, is the most dangerous Coronary heart disease for humans beings. Portable Electrocardiogram(ECG) device is useful for the identification and control of ECG signals for myocardial infarction. These ECG signals record heart electrical activity and reflect the unusual movement of the heart. Visually, it is difficult to identify a variation in ECG due to its small amplitude and period. Therefore in this paper, we implemented a convolutional neural network (CNN) made of two layers of convolution-pooling, two dense layers and one output layer for the diagnosis of myocardial infarction using ECG. For batter performance, this network uses Leaky ReLU neurons with categorical cross-entropy loss function and the ADAM optimizer algorithm. To avoid the problem of overfitting, we used L2 regularisation method for regularization of the dense layer of CNN. For experimentation, we use the Physikalisch-Technische Bundesanstalt (PTB) diagnostic database. In this database, we obtained results of sensitivity, specificity, and accuracy of 100 %, 99.65%, and 99.82%, respectively, for data taken from the training set. And sensitivity, specificity, and accuracy of 99.88 %, 99.65%, and 99.82%, respectively, on patients, it hasn’t seen before which indicating that the model can achieve excellent classification performance.","PeriodicalId":316752,"journal":{"name":"2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126825253","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

Smart Agriculture Using Wireless Sensor Monitoring Network Powered By Solar Energy 利用太阳能无线传感器监测网络的智能农业

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397111

Sutanika Barik, S. Naz

{"title":"Smart Agriculture Using Wireless Sensor Monitoring Network Powered By Solar Energy","authors":"Sutanika Barik, S. Naz","doi":"10.1109/ICCCIS51004.2021.9397111","DOIUrl":"https://doi.org/10.1109/ICCCIS51004.2021.9397111","url":null,"abstract":"Every single life in this world depends on agriculture to reside. People are cultivating plants in a traditional way of agriculture since from thousands of years. In this era of development there is a huge demand to fulfil. So a revolution is clearly needed in the field of agriculture. This paper explores how a smart agriculture can be installed in place of traditional agriculture. Here an agri-tech system is designed to monitor several parameters of the crop field through wireless sensors and also automation is applied to balance those monitored parameters. Wireless sensors are used to monitored the soil moisture level, pH level of the soil, soil temperature etc. After monitoring, these real time data are transferred by zigbeenetwork to a control system (raspberry pi)to balance the parameters of the soil of the crop field according to the requirements. Zigbeeprotocol gives the input of the raspberry pi which analyzes the data properly and according to the requirements it gives the output. This output is able to pump the required amount of the water to the crop field, balanced the pH level by spreading the précised type of fertilizer and also checks the temperature of the soil. Thus the percentage of crop production is effectively increased by this automatic monitoring system. The energy needed to drive the system, will be provided by solar panels in off-grid manner.","PeriodicalId":316752,"journal":{"name":"2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"603 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123231017","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

AttentionBuildNet for Building Extraction from Aerial Imagery 从航空图像中提取建筑物的AttentionBuildNet

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397178

P. Das, S. Chand

引用次数: 7

ASTITVA: Assistive Special Tools and Technologies for Inclusion of Visually Challenged ASTITVA:辅助特殊工具和技术，包括视觉障碍

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/icccis51004.2021.9397168

Apala Pramanik, R. Johari, Nitesh Kumar Gaurav, Sapna Chaudhary, Rohan Tripathi

引用次数: 0

Monitoring Driver’s Drowsiness Status at Night Based on Computer Vision 基于计算机视觉的驾驶员夜间困倦状态监测

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397180

Vidhu Valsan A, Paul P. Mathai, Ierin Babu

{"title":"Monitoring Driver’s Drowsiness Status at Night Based on Computer Vision","authors":"Vidhu Valsan A, Paul P. Mathai, Ierin Babu","doi":"10.1109/ICCCIS51004.2021.9397180","DOIUrl":"https://doi.org/10.1109/ICCCIS51004.2021.9397180","url":null,"abstract":"Drivers drowsiness and fatigue decreases the vehicle management skills of a driver. The operator driving vehicle in night has become a significant downside today. Driver in a drowsiness state is the one among the important reason of increasing amount of road accidents and death. Hence the drowsiness detection of driver is considering as most active research field. Many ways are created recently to detect the drowsiness of driver. Existing methods can be classified in three categories based on physiological measures, performance measures of vehicles and ocular measures. Few ways are intrusive and distract the driver from comfortable driving. Some of the methods need expensive sensors for information handling. Therefore, a low cost, real time system to detect the driver’s drowsiness is developed in this paper. In this proposed system, real time video of driver records using a digital camera. Using some image processing techniques, face of the driver is detected in each frame of video. Facial landmarks points on the driver’s face is localized using one shape predictor and calculating eye aspect ratio, mouth opening ratio, yawning frequency subsequently. Drowsiness is detected based on the values of these parameters. Adaptive thresholding method is used to set the thresholds. Machine learning algorithms were also implemented in an offline manner. Proposed system tested on the Face Dataset and also tested in real-time. The experimental results shows that the system is accurate and robust.","PeriodicalId":316752,"journal":{"name":"2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"39 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120907104","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: 5

Effectuating Supervised Machine Learning Techniques for Multiclass Classification of Problematic Internet and Mobile Usage 实现有监督机器学习技术对有问题的互联网和移动使用的多类分类

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397062

S. Sarkar, Samanyu Bhandary, Arti Arya

{"title":"Effectuating Supervised Machine Learning Techniques for Multiclass Classification of Problematic Internet and Mobile Usage","authors":"S. Sarkar, Samanyu Bhandary, Arti Arya","doi":"10.1109/ICCCIS51004.2021.9397062","DOIUrl":"https://doi.org/10.1109/ICCCIS51004.2021.9397062","url":null,"abstract":"The internet has slowly become an inevitable part of every facet of our lives. With the power of the world wide web available at the touch of our fingertips, anything seems possible. But mental health disorders due to prolonged usage of the ever-evolving internet and mobile are also on the rise. Studies show there is a strong correlation between excessive internet usage and depression, lower self-esteem, Attention-Deficit Disorder (ADHD), impulsivity, hyperactivity and so on. In this paper, a system is proposed that classifies a persons’ internet/mobile usage into four classes (multi class) which are- Normal, Borderline, Critical and Severe. In collaboration with our institutions’ Counsellor and considering previous studies, a non-invasive questionnaire was developed to collect the data. The collected data was used to train some efficient and state-of-the-art machine learning models such as Logistic Regression, Decision Trees, Support Vector Machines (SVM), Xtreme Gradient Boosting (XGBoost), Random Forests and Light Gradient Boosting (LightGBM). The model with the highest accuracy was taken forward to deliver the best possible classification of a user into one of four categories. With thorough training and testing linear SVM with radial basis kernel returned the best accuracy and thus it was chosen to move forward with.","PeriodicalId":316752,"journal":{"name":"2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121069665","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

[ICCCIS 2021 Front cover] [ICCCIS 2021封面]

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/icccis51004.2021.9397122

引用次数: 0

A Review on E-waste: Fostering the Need for Green Electronics 电子废物检讨:促进绿色电子的需要

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2021-02-19 DOI: 10.1109/ICCCIS51004.2021.9397191

N. Misra, Sandeep Kumar, Arpit Jain

引用次数: 16