2019 IEEE Conference on Information and Communication Technology最新文献

Investigations on Equal Cost Multi-Path Feature in Dynamic Routing Protocols in IPv6 Networks IPv6网络中动态路由协议等代价多路径特性研究

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066199

S. Tomar, A. Rawat, S. Tokekar, P. Vyavahare

{"title":"Investigations on Equal Cost Multi-Path Feature in Dynamic Routing Protocols in IPv6 Networks","authors":"S. Tomar, A. Rawat, S. Tokekar, P. Vyavahare","doi":"10.1109/CICT48419.2019.9066199","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066199","url":null,"abstract":"Worldwide, organizations are gearing up to implement IPv6 in their networks. The main concern of the network architects is the selection of interior gateway dynamic routing protocol for ensuring the best Quality of Service (QoS) support to the users. The available options are RIPng, OSPFv3, EIGRP, and IS-IS. Intelligent routing of packets over multiple paths is performed by ISPs to satisfy guaranteed Service Level Agreement (SLA) imposed network uptimes and QoS. All these protocols support the Equal Cost Multi-Path (ECMP) feature for achieving these objectives. With the ECMP feature providing re-routing in case of link/node failures in multiple path cases, it is worth to investigate its coupling with dynamic routing protocols. Past research work was focused on carrying out performance analysis of the dynamic routing protocols based on QoS and convergence metrics of simple IPv6 networks. In this paper, we present the performance analysis of the IS-IS and OSPFv3 protocols, specifically probing the performance of the ECMP feature in IPv6 networks. 02, 04 and 08 numbers of equal-cost paths between source and destination, are investigated for QoS parameters, using the OPNET simulator. We conclude that IS-IS is the best among the two, supporting ECMP in IPv6 networks with less than 1%, 27%, 43% packet loss ratios in 02, 04, 08 path networks respectively as compared to 7%, 40%, 55% respectively in ECMP coupled with OSPFv3 routing protocol for video traffic, with similar trends for voice traffic, in the discussed scenarios.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121270923","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

Flash Translation Layer and its functionalities Flash翻译层及其功能

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066266

Madan Mohan Malaviya, P. Singh

引用次数: 0

Quality-of-Service based Reliable Route Discovery using Ant Colony Optimization for VANET 基于蚁群优化的服务质量可靠路由发现

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066182

Ankita Srivastava, A. Prakash, R. Tripathi

引用次数: 5

2019 IEEE Conference on Information and Communication Technology (CICT) 2019 IEEE信息与通信技术会议

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/cict48419.2019.9066175

引用次数: 0

Model Independent Method for Acceptor Splice Sites Prediction in DNA Sequences DNA序列中受体剪接位点预测的模型独立方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066217

S. Sharma, S. N. Sharma, Rajiv K. Saxena

引用次数: 0

Mitosis Detection Using Image Segmentation and Object Detection 利用图像分割和目标检测进行有丝分裂检测

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066180

Nairit Banerjee, Anmol Singh Sethi, Manavdeep Singh, G. S. Anagh, Badnena Svvr Upendra, A. Krohn-Grimberghe, Ranjana Vyas

引用次数: 2

Performance Evaluation of Non-orthogonal Multiple Access in V2V communications Over Double-Rayleigh Fading Channels 双瑞利衰落信道下V2V通信非正交多址性能评价

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066141

Neha Jaiswal, N. Purohit

引用次数: 4

Reinforcement Learning Based Energy Management in Wireless Body Area Network: A Survey 基于强化学习的无线体域网络能量管理研究进展

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066260

Arti Gupta, V. Chaurasiya

引用次数: 11

Development Of An Improved Tomato Leaf Disease Detection And Classification Method 一种改良番茄叶病检测与分类方法的建立

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066230

M. Kaur, R. Bhatia

{"title":"Development Of An Improved Tomato Leaf Disease Detection And Classification Method","authors":"M. Kaur, R. Bhatia","doi":"10.1109/CICT48419.2019.9066230","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066230","url":null,"abstract":"Detection of the plant leaf diseases in earlier stage is beneficial for Indian Economy. The study shows the 10-30% of crops are damaged due to diseases, which is not detected in curing stage. Different leaf disease detection methods are used for different crops. The pretrained Deep Learning Model is used to detect and classify the Tomato Leaf diseases. Dataset of the Tomato Leaf Images is collected from plant village repository. It is divided into categories, six diseased and one healthy. The implementation is done in MATLAB®. Features are extracted from the Feature Layer of the Pre-trained model of ResNet i.e. Fully Connected Layer. It is used to train the model for tomato leaf dataset. The training and testing are defined in a separate phase. The classification is done by the linear learner of the ECOC. It returns a pool trained multiclass error correcting model. To evaluate the trained model various parameters are calculated. The proposed model is able to classify the diseases has a higher Accuracy, Precision, F -Score, Specificity and False Positive Rate. The results of trained model are found to be more accurate than base article.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124317586","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: 26

A Language-independent gender classifier for Online Social Networks 在线社交网络的独立于语言的性别分类器

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066196

Nancy Agarwal, M. A. Wani, Patrick A. H. Bours, S. Jabin, S. Z. Hussain

{"title":"A Language-independent gender classifier for Online Social Networks","authors":"Nancy Agarwal, M. A. Wani, Patrick A. H. Bours, S. Jabin, S. Z. Hussain","doi":"10.1109/CICT48419.2019.9066196","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066196","url":null,"abstract":"Designing gender predictor for the Online Social Network (OSN) is receiving considerable attention from the research communities of different domains. However, the gender classifiers proposed by earlier studies for social media content so far, highly rely on the language used by the users for writing the content. It implies that the prediction model trained on one language (say English) will likely fail in identifying the gender of users with other languages (for example, Spanish). The study conducted in this paper aims to identify the features from user content on an OSN, which will assist in devising a Language-Independent Gender Classifier (LIGC). The experiments are performed on the Facebook networking site. The site provides the users with the list of various personal attributes that they may or may not reveal to other users on the network. The presented work collects such information of the Facebook users and carries out rigorous feature analysis to know whether this information varies between men and women on Facebook. Furthermore, several machine learning algorithms including Random Forest, SVM, Naïve Bayes, and kNN have been employed to determine the potential of the proposed feature set. Random forest approach achieves the highest value (70%) of performance metric, AUROC (Area under the Receiver Operating Characteristic). The current study is the first attempt to utilize information revelation for designing a gender identifier for OSN that is independent of the language used by the members.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132409358","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