2019 4th International Conference on Information Systems and Computer Networks (ISCON)最新文献_第6页

Coalescing Artificial Intelligence with Augmented Reality to vitalize Smart-Glasses 结合人工智能与增强现实，激活智能眼镜

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036274

Naman Sharma, R. Bathla

引用次数: 3

Reconfigurable Antenna Design with Air Substrate for S and C bands S波段和C波段空气基板可重构天线设计

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036224

Farha, R. S. Yadav

引用次数: 0

Performance Analysis of Umbrella based Cognitive Environment Map in Uplink Cellular Networks 基于伞形认知环境映射的上行蜂窝网络性能分析

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036191

Astha Sharma

{"title":"Performance Analysis of Umbrella based Cognitive Environment Map in Uplink Cellular Networks","authors":"Astha Sharma","doi":"10.1109/ISCON47742.2019.9036191","DOIUrl":"https://doi.org/10.1109/ISCON47742.2019.9036191","url":null,"abstract":"Future devices are envisioned to be ‘Super Smart’ empowered by convergence of diverse advanced hardware and software technologies such as Cloud Computing, Cognitive Radio, Big Data, Machine Learning and Artificial Intelligence. These devices armed with cognitive intelligence will use perception capability to interact and learn from the environment and make the decisions instantly. It is challenging to accurately determine spatial spectrum opportunities available in uplink bands of cellular network due to varied primary user locations. This paper has laid a framework for spectrum opportunity detection wherein the future devices embedded with cognitive intelligence will have a potential to build a ‘Cognitive Environment Map (CEM)’. A CEM that can be viewed as a sort of internal neural representation of the geographical space in which the device operates to effectively detect spectrum opportunities. The performance improvement provided by the CEM, constructed using an efficient computational geometry technique named ‘Umbrella-based algorithm’ over traditional circular ranges is analyzed in an uplink cellular network. Results show that CEM are able to solve the hidden and exposed nodes problem considerably and performance of the opportunity detector is analyzed. Further, the impact of varying detection range, interference ranges of primary and secondary users as well as effect of propagation environment in terms of operational SNR and SINR is also discussed.","PeriodicalId":124412,"journal":{"name":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116860498","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

Spam SMS Filtering using Recurrent Neural Network and Long Short Term Memory 基于递归神经网络和长短期记忆的垃圾短信过滤

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036269

A. Chandra, S. Khatri

{"title":"Spam SMS Filtering using Recurrent Neural Network and Long Short Term Memory","authors":"A. Chandra, S. Khatri","doi":"10.1109/ISCON47742.2019.9036269","DOIUrl":"https://doi.org/10.1109/ISCON47742.2019.9036269","url":null,"abstract":"SMS is the abbreviation for Short Messaging Service which uses standard protocols for mobile devices to exchange information via short text messages. Today SMS's are an easy, inexpensive and widely accepted way to communicate rather than phone calls. Spam can be described as random unsolicited messages sent at large without any authorization from the receiver. People still deal with spammer's misusing SMS's to advertise false claims and can gain access to private information of users. Emails, social media sites, review, and even Twitter has seen spammers trying to intrude everywhere with the advent of Internet. Spam appears in many forms like comments, emails, search results and personal messages where spammers tend to gain revenues. Various Machine Learning algorithms like Neural Networks have tried to detect spam messages and normal messages or ham from SMS's. These techniques can learn high level features automatically using raw data unlike traditional ways where features are selected after analysis for classification. In this research paper, we propose a new method utilizing Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) using Keras models and Tensorflow backend to detect Spam and Ham from ‘SpamSMSCollection’ dataset available at UCI machine learning repository. Crucial preprocessing of dataset included tokenization, TF-IDF Vectorization and removal of stopwords. Overall accuracy of 98% is achieved and shows improvement from other machine learning algorithms for spam detection.","PeriodicalId":124412,"journal":{"name":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115628122","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: 15

Employee Turnover Prediction System 员工离职预测系统

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036180

Mehul Jhaver, Yogesh Gupta, A. Mishra

{"title":"Employee Turnover Prediction System","authors":"Mehul Jhaver, Yogesh Gupta, A. Mishra","doi":"10.1109/ISCON47742.2019.9036180","DOIUrl":"https://doi.org/10.1109/ISCON47742.2019.9036180","url":null,"abstract":"Employee turnover has been recognized as a main problem for industries due to its contrary influence on work place throughput and long term development tactics. To resolve this issue, officialdoms use machine learning techniques to guess employee turnover. Precise predictions qualify administrations to take action for holding of employees. Nonetheless, the data for this type of issue comes from HR Information Systems. This leads to the supremacy of noise in the data that extracts predictive models disposed to over-fitting and hence imprecise. This is the main problem that is the motivation of this study, and one that has not been handled earlier. The innovative contribution of this study is to reconnoiter the application of Gradient Boosting technique which is more robust because of its regularization formulation. The global retailer data is used to compare Gradient Boosting against three traditionally used supervised classifiers like Logistic Regression, Support Vector Machine, Random Forest and reveal its suggestively higher accuracy for predicting employee turnover. In this study I have also implemented Artificial Neural Network to study how to the neural network helps in classification of different classes. This paper is aimed at developing models which can predict employee turnover and it can help the organization to take necessary steps to retain these employees.","PeriodicalId":124412,"journal":{"name":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122035259","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

Implementation of Restrictions in Smart Home Devices for Safety of Children 智能家居设备对儿童安全的限制实施

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036218

Sparsh Sangal, R. Bathla

引用次数: 3

A Model to Implement and Secure Online Documentation using Blockchain 使用区块链实现和保护在线文档的模型

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036245

Paras Pant, R. Bathla, S. Khatri

{"title":"A Model to Implement and Secure Online Documentation using Blockchain","authors":"Paras Pant, R. Bathla, S. Khatri","doi":"10.1109/ISCON47742.2019.9036245","DOIUrl":"https://doi.org/10.1109/ISCON47742.2019.9036245","url":null,"abstract":"The past decade has seen a tremendous rise in the use of blockchains for facilitating a trust based decentralized financial framework, in hope of eliminating dependency on core institutions such as banks. A blockchain stores a chronological record for a document detailing all the alterations that have been made to it since its inception. This data contained within this document may be anything, e.g. a lease document, personal files, etc. Smart documents can be used everywhere within the industry or an enterprise. Although blockchain based structures are much less eco-friendly in comparison to the ones with a database-based approach. Inter Planetary File System can be used to remotely store massive quantities of statistical data that may be involved in a blockchain transaction and address it in the actual chain by an absolute, everlasting link. Each report and all the blocks in a chain are assigned a unique fingerprint known as a cryptographic hash. This virtual cryptographic signature is used to verify legitimacy of each block. In this paper with the help of IPFS, along with other encryption methods we propose a secure and tamper proof model for blockchain based financial transactions.","PeriodicalId":124412,"journal":{"name":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126702807","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

An Intruder Monitoring System for Improving the Network Security 一种提高网络安全的入侵者监控系统

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036195

Sourav Thapliyal, Himanshu Gupta, S. Khatri

引用次数: 0

Comparison of target detection techniques for hyperspectral images 高光谱图像目标检测技术的比较

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036193

Dharambhai Shah, Madhumita Tripathy, T. Zaveri

引用次数: 5

A Novel Approach for Classification of Microblog Tweets 一种新的微博Tweets分类方法

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI: 10.1109/ISCON47742.2019.9036264

Varsha Tiwari, Himani Sikarwar

引用次数: 0