International Journal of Computer Science and Informatics最新文献

Smart Hospitality and Secure Tourism Management using Blockchain Technology: BESHosTM Approach 使用区块链技术的智能酒店和安全旅游管理:BESHosTM方法

International Journal of Computer Science and Informatics Pub Date : 2022-02-01 DOI: 10.47893/ijcsi.2022.1196

Asik Rahaman Jamader, Puja Das, Biswaranjan Acharya, Sandhya Makkar

引用次数: 0

Tourism Decision Making System & Auto Guidance Technique using Data analytics. 基于数据分析的旅游决策系统与自动引导技术。

International Journal of Computer Science and Informatics Pub Date : 2022-02-01 DOI: 10.47893/ijcsi.2022.1195

Asik Rahaman Jamader, Puja Das, Biswaranjan Acharya, Sandhya Makkar

引用次数: 0

A Study on Privacy of IoT Devices among a Sample of Indians in the U.S- 2021 物联网设备隐私在美国印度人样本中的研究- 2021

International Journal of Computer Science and Informatics Pub Date : 2022-02-01 DOI: 10.47893/ijcsi.2022.1198

S. Prasad, Sharanya Prasad, Vijith Raghavendra, Srishma Sunku

{"title":"A Study on Privacy of IoT Devices among a Sample of Indians in the U.S- 2021","authors":"S. Prasad, Sharanya Prasad, Vijith Raghavendra, Srishma Sunku","doi":"10.47893/ijcsi.2022.1198","DOIUrl":"https://doi.org/10.47893/ijcsi.2022.1198","url":null,"abstract":"The Internet of Things (IoT) has gained immense popularity over the last decade with wide-ranging applications in domains of medicine, science, military as well as domestic use. Despite its tremendous growth, privacy concerns plague IoT applications and have the potential to hamper the benefits derived from its usage. This paper carries out a statistical analysis of empirical data collected from users of IoT to assess the level of awareness among users of IoT. The mode of study was through a questionnaire sent through Google forms to a selection of Indians living across the U.S. The place was chosen as some of the authors were in that country and also because its usage is more in the U.S. Many homes have extensive use of IoT, even if it’s for simple operations like turning on/off electric bulbs. Privacy issues have also been a matter of concern as these devices are linked to the internet. The sample was chosen from judgment /convenience sampling. Only one member per family was asked to respond so that there is no overlap of the collected data. The respondents were asked about the privacy issues of using IOT devices and also if it bothered them to continue usage. The results showed that not only were users aware of the privacy issues related to IoT, but they also expressed concerns over the same. Due to the convenience and ease of usage, it is highly unlikely that people will stop using these devices but definitely, the usage will be more guarded in the future.","PeriodicalId":252777,"journal":{"name":"International Journal of Computer Science and Informatics","volume":"286 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131955070","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

Diabetes Prediction: A Study of Various Classification based Data Mining Techniques 糖尿病预测:基于分类的数据挖掘技术研究

International Journal of Computer Science and Informatics Pub Date : 2022-02-01 DOI: 10.47893/ijcsi.2022.1191

Sipra Sahoo, Tushar Mitra, A. Mohanty, Bharat Jyoti Ranjan Sahoo, Smita Rath

{"title":"Diabetes Prediction: A Study of Various Classification based Data Mining Techniques","authors":"Sipra Sahoo, Tushar Mitra, A. Mohanty, Bharat Jyoti Ranjan Sahoo, Smita Rath","doi":"10.47893/ijcsi.2022.1191","DOIUrl":"https://doi.org/10.47893/ijcsi.2022.1191","url":null,"abstract":"Data Mining is an integral part of KDD (Knowledge Discovery in Databases) process. It deals with discovering unknown patterns and knowledge hidden in data. Classification is a pivotal data mining technique with a very wide range of applications. Now a day’s diabetic has become a major disease which has almost crippled people across the globe. It is a medical condition that causes the metabolism to become dysfunctional and increases the blood sugar level in the body and it becomes a major concern for medical practitioner and people at large. An early diagnosis is the starting point for living well with diabetes. Classification Analysis on diabetic dataset is a part of this diagnosis process which can help to detect a diabetic patient from non-diabetic. In this paper classification algorithms are applied on the Pima Indian Diabetic Database which is collected from UCI Machine Learning Laboratory. Various classification algorithms which are Naïve Bayes Classifier, Logistic Regression, Decision Tree Classifier, Random Forest Classifier, Support Vector Classifier and XGBoost Classifier are analyzed and compared based on the accuracy delivered by the models.","PeriodicalId":252777,"journal":{"name":"International Journal of Computer Science and Informatics","volume":"54 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120815323","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 Study about Unemployment in India – 2004 - 2018 2004 - 2018年印度失业问题研究

International Journal of Computer Science and Informatics Pub Date : 2022-02-01 DOI: 10.47893/ijcsi.2022.1194

S. Prasad, Harshini N, A. N, Aishwarya Hr

引用次数: 0

Valuation of Software Exposures using Visualization, Best-Worst Method and Artificial Neural Network 基于可视化、最佳-最差法和人工神经网络的软件风险评估

International Journal of Computer Science and Informatics Pub Date : 2022-02-01 DOI: 10.47893/ijcsi.2022.1193

S. Dwivedi, R. Tripathi

{"title":"Valuation of Software Exposures using Visualization, Best-Worst Method and Artificial Neural Network","authors":"S. Dwivedi, R. Tripathi","doi":"10.47893/ijcsi.2022.1193","DOIUrl":"https://doi.org/10.47893/ijcsi.2022.1193","url":null,"abstract":"Software is one of the most important part in today’s world, with its requirements in every industry be it automotive, avionics, telecommunication, banking, pharmaceutical and many more. Software systems are generally a bit complicated and created by distinct programmers. Usually any mistake in the code by a programmer in the developing stage of a software can lead to loopholes that cause Exposure. Exposure is a software flaw that an assaulter can exploit to conduct unlawful activities within a computer system. Despite the understanding of Exposure by the academia and industry, the amount of Exposure is growing exponentially as fresh characteristics are added to the software frequently. Developers and testers are faced with the challenge of fixing large amounts of exposure within limited resources and time. Thus, prioritizing software exposures is essential to reduce the usage of corporate assets and time, which is the motivation behind the present study. In the present paper, the issue of software exposure prioritization is addressed by utilizing a new multi-criterion decision-making (MCDM) technique known as the Best Worst method (BWM). Further, to assess the vulnerabilities in terms of their critical nature, we have applied Two-Way assessment technique. The BWM utilizes two pairwise comparison vectors to determine the weights of criteria. The two- way assessment framework takes into account the perspectives of both managers/developers and stakeholders/testers to highlight the severity of software vulnerabilities. This can act as a significant measure of efficiency and effectiveness for the prioritization and evaluation of vulnerability. The findings are validated with a software testing firm from North India.","PeriodicalId":252777,"journal":{"name":"International Journal of Computer Science and Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130811249","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 Optimized Machine Learing Framework For Extracting Suicide Factors Using K-Means++ Clustering 基于k - means++聚类的自杀因素提取优化机器学习框架

International Journal of Computer Science and Informatics Pub Date : 2022-01-01 DOI: 10.47893/ijcsi.2022.1197

Naren S R, Thirumal P C, Sudharson D

引用次数: 0

NLP CHALLENGES FOR MACHINE TRANSLATION FROM ENGLISH TO INDIAN LANGUAGES 从英语到印度语言的机器翻译的NLP挑战

International Journal of Computer Science and Informatics Pub Date : 2014-07-01 DOI: 10.47893/ijcsi.2014.1169

V. R. Mallamma, M. Hanumanthappa

{"title":"NLP CHALLENGES FOR MACHINE TRANSLATION FROM ENGLISH TO INDIAN LANGUAGES","authors":"V. R. Mallamma, M. Hanumanthappa","doi":"10.47893/ijcsi.2014.1169","DOIUrl":"https://doi.org/10.47893/ijcsi.2014.1169","url":null,"abstract":"This Natural Langauge processing is carried particularly on English-Kannada/Telugu. Kannada is a language of India. The Kannada language has a classification of Dravidian, Southern, Tamil-Kannada, and Kannada. Regions Spoken: Kannada is also spoken in Karnataka, Andhra Pradesh, Tamil Nadu, and Maharashtra. Population: The total population of people who speak Kannada is 35,346,000, as of 1997. Alternate Name: Other names for Kannada are Kanarese, Canarese, Banglori, and Madrassi. Dialects: Some dialects of Kannada are Bijapur, Jeinu Kuruba, and Aine Kuruba. There are about 20 dialects and Badaga may be one. Kannada is the state language of Karnataka. About 9,000,000 people speak Kannada as a second language. The literacy rate for people who speak Kannada as a first language is about 60%, which is the same for those who speak Kannada as a second language (in India). Kannada was used in the Bible from 1831-2000. Statistical machine translation (SMT) is a machine translation paradigm where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The statistical approach contrasts with the rule-based approaches to machine translation as well as with example-based machine translation.","PeriodicalId":252777,"journal":{"name":"International Journal of Computer Science and Informatics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129753078","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: 7