2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)最新文献_第7页

Time Series with Sentiment Analysis for Stock Price Prediction 基于情绪分析的时间序列股票价格预测

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8969060

Vrishabh Sharma, R. Khemnar, R. Kumari, B. Mohan

引用次数: 13

Implementation of Three Dimensional Model for Flying Ad Hoc Network 飞行Ad Hoc网络三维模型的实现

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8969063

Sunil Kr. Maakar, Y. Singh, Rajeshwar Singh

引用次数: 1

Rumor Propagation: A State-of-the-art Survey of Current Challenges and Opportunities 谣言传播:当前挑战与机遇的最新研究

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8969023

Roohani, Tushar Rana, P. Meel

引用次数: 5

A Pragmatic Evaluation of 4G and 5G Wireless Networks in the Current Scenario 当前场景下4G和5G无线网络的实用评估

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8968780

Er. Kailash Aseri

{"title":"A Pragmatic Evaluation of 4G and 5G Wireless Networks in the Current Scenario","authors":"Er. Kailash Aseri","doi":"10.1109/ICCT46177.2019.8968780","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8968780","url":null,"abstract":"In the current scenario, most of the services are deployed on web based services and these can be accessed using wireless technologies. The greater part of the corporate or business driven organizations is conveyed on web or cloud based condition. For such usage, the sites, versatile applications and cloud put together administrations are propelled with respect to the internet so that the whenever anyplace access to the administrations can be accessible. India is one of the greatest markets of cell phones and a worthwhile spot for the global organizations associated with the assembling of cell phones. From the examination investigation and reports from Statista.com, it is introduced that India is one of the key nations with tremendous market of versatile clients. In year 2017, around 134 millions cell phones were sold in India that is the enormous figure. From another exploration report, it is anticipated that the cell phone clients in India will increment to around 450 Millions by year 2022. To adapt up to the huge heap of cell phone remote systems, there is have to hoist the execution in current 4G and emerging 5G Networks advancements with the goal that the higher level of execution can be accomplished in the system condition. This original copy is having the emphasis on the delineation of the result from cutting edge remote systems of 4G and 5G with the reproduction utilizing the development execution apparatuses of cupcarbon.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134574033","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: 2

Power Allocation Schemes for Implant Nodes in Cooperative Wireless Body Area Networks 无线协作体域网络中植入节点功率分配方案

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8968787

G. Kumar, U. Prashanthi, K. Tejaswini, T. Gayathri

引用次数: 0

Machine Learning Based Comparative Analysis of Methods for Enhancer Prediction in Genomic Data 基于机器学习的基因组数据增强子预测方法比较分析

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8969054

Amandeep Kaur, A. Chauhan, A. Aggarwal

引用次数: 3

Analysis of the Security Problems of Robotic Systems 机器人系统安全问题分析

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8969055

A. Basan, E. Basan, Anton Gritsynin

引用次数: 1

Application of Natural Language Processing and IoTCloud in Smart Homes 自然语言处理和物联网云在智能家居中的应用

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-09-01 DOI: 10.1109/ICCT46177.2019.8969066

Shubham Kumar, S. Benedict, Srilakshmi Ajith

{"title":"Application of Natural Language Processing and IoTCloud in Smart Homes","authors":"Shubham Kumar, S. Benedict, Srilakshmi Ajith","doi":"10.1109/ICCT46177.2019.8969066","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969066","url":null,"abstract":"Internet of Things (IoT) based systems, most predominantly, the machine to machine communication based systems, have evolved in the recent past which helped to increase the efficiency of services offered without much necessity of human interaction. In general, IoT cloud-assisted solutions could serve several applications, including the Smart Home Automation, due to the availability of high-speed mobile networks coupled with cost effective, accessible and fast embedded hardware. In fact, there exists a few smart home solutions in the market that aim at automating the basic operations of home appliances. However, most of these systems focus on mimicking the basic operations of the electrical switches. This paper attempts to unfold a Smart Home Automation system using Natural Language Processing (NLP) and IoT cloud solutions. The proposed system was able to remotely control smart homes in a secure and in a customized manner; the approach could precisely monitor home devices with the application of GoogleAPI for integrating devices. Experiments were carried out at the IoT Cloud research lab of IIIT Kottayam such that a mini-Smart Home environment was setup to remotely control the sensors such as humidity and temperatures of Smart Homes. The paper described a method to create an end user product using 3D modeling and 3D printing facilities. In addition, the paper has unfolded the state-of-the-art research works carried out in the field of smart home automation using NLPs.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115156943","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

A Novel method for IDC Prediction in Breast Cancer Histopathology images using Deep Residual Neural Networks 基于深度残差神经网络的乳腺癌组织病理学图像IDC预测新方法

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 2019-08-20 DOI: 10.1109/ICCT46177.2019.8969037

Chandra Churh Chatterjee, G. Krishna

{"title":"A Novel method for IDC Prediction in Breast Cancer Histopathology images using Deep Residual Neural Networks","authors":"Chandra Churh Chatterjee, G. Krishna","doi":"10.1109/ICCT46177.2019.8969037","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969037","url":null,"abstract":"Invasive ductal carcinoma (IDC), which is also sometimes known as the infiltrating ductal carcinoma, is the most regular form of breast cancer. It accounts to about 80% of all breast cancers. According to American Cancer Society [1], more than 180, 000 women in the United States are diagnosed with invasive breast cancer each year. The survival rate associated with this form of cancer is about 77% to 93% depending on the stage at which they are being diagnosed. The invasiveness and the frequency of the occurrence of these disease makes it one of the difficult cancers to be diagnosed. Our proposed methodology involves diagnosing the invasive ductal carcinoma with a deep residual convolution network to classify the IDC affected histopathological images from the normal images. The dataset for the purpose used is a benchmark dataset known as the Breast Histopathology Images [2]. The microscopic RGB images are converted into a seven channel image matrix, which are then fed to the network. The proposed model produces a 99.29% accurate approach towards prediction of IDC in the histopathology images with an AUROC score of 0.9996. Classification ability of the model is tested using standard performance metrics. The following methodology has been described in the next sections. Index Terms–Residual learning, CIELAB color space, Grad-CAM, Contrast adaptive histogram equalization (CLAHE), Gaussian filtering","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127705041","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

Forecasting the Trends and Patterns of Crime in Bangladesh using Machine Learning Model 使用机器学习模型预测孟加拉国犯罪的趋势和模式

2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) Pub Date : 1900-01-01 DOI: 10.1109/ICCT46177.2019.8969031

A. Biswas, Sarnali Basak

{"title":"Forecasting the Trends and Patterns of Crime in Bangladesh using Machine Learning Model","authors":"A. Biswas, Sarnali Basak","doi":"10.1109/ICCT46177.2019.8969031","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969031","url":null,"abstract":"Last few years in Bangladesh, the crime rate has increased rapidly. Hence it is an essential task to analyze and predict the crime so that the authority can minimize or prevent the crimes easily. In this situation, machine learning can perform a notable role to reveal the crime trends and patterns of Bangladesh. Here, various machine learning regression models i.e. linear regression, polynomial regression, and random forest regression are used to forecast the trends and patterns of crime in Bangladesh. Dataset used in this research is available for the public which is gathered from the Bangladesh police’s website. The dataset comprises record about various crime types i.e. dacoity, robbery, kidnapping, murder, women & child repression, theft, burglary, arms act, explosive, narcotics, and smuggling of Bangladesh. Firstly, training of regression models is done on the training dataset. After completion of the training, forecasting of crime is performed on the test data by the different regression models. Then we compare the forecasting results with the actual results and calculate the model evaluation metrics for the different applied regression models. After comparing the result, it is possible to find out the best-suited regression model for the crime-related data among all the applied regression models. Finally, it is observed that polynomial and random forest regression are better to predict the crime trends and patterns than the linear regression.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"16 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":"114358901","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: 12