SKIT Research Journal最新文献

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An Impression on Over Modulation Strategy in Inverter 逆变器中过调制策略的研究
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.40-49
Raghuraj Kumar, Bharat Modi, Baibhav Bishal, M. Lalwani
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引用次数: 0
Use of Demolished Recycled Aggregate for Pavement Construction: A Review 废旧再生骨料在路面施工中的应用综述
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.22-26
Dikshant Sharma, P. Kushwaha, Nishant Sachdeva
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引用次数: 1
A Review on Techniques of Recommendation System 推荐系统技术综述
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.31-36
Palika Jajoo, Dolly Mittal
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引用次数: 0
Comparative study of Physical Properties on Conventional and Modified Binder 常规粘结剂与改性粘结剂物理性能的比较研究
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.27-30
Apoorva Dwivedi, P. Kushwaha, Anirudh Mathur
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引用次数: 0
Effect of SiO2 Thickness Variation on Threshold Voltage and Trans-Conductance of TFT SiO2厚度变化对TFT阈值电压和跨电导的影响
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.37-39
A. Jain, Lalit Kumar Lata, Abhinandan Jain, P. K. Jain
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引用次数: 1
Digital Education in India: Future Perspective and Challenges 印度数字教育:未来展望与挑战
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.87-92
Atul Gupta, Ona Ladiwal
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引用次数: 0
The COVID 19 Era's Emerging Business Trends 新冠肺炎时代的新兴商业趋势
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.93-96
Savita Choudhary, Priyanka Bhaskar
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引用次数: 0
Evaluation of Existing Pedestrian Facilities and Its Potential Improvements 现有行人设施的评估及其可能改善之处
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.16-21
P. Pandey, Anirudh Mathur, Nikhil Sharma
{"title":"Evaluation of Existing Pedestrian Facilities and Its Potential Improvements","authors":"P. Pandey, Anirudh Mathur, Nikhil Sharma","doi":"10.47904/ijskit.11.2.2021.16-21","DOIUrl":"https://doi.org/10.47904/ijskit.11.2.2021.16-21","url":null,"abstract":"","PeriodicalId":424149,"journal":{"name":"SKIT Research Journal","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124627475","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
Some Unified Integrals Pertaining to Srivastava Polynomials 关于斯里瓦斯塔瓦多项式的一些统一积分
SKIT Research Journal Pub Date : 2021-01-11 DOI: 10.47904/ijskit.11.2.2021.81-84
V. Singhal, Nawal Kishor Jangid, Amber Srivastava
{"title":"Some Unified Integrals Pertaining to Srivastava Polynomials","authors":"V. Singhal, Nawal Kishor Jangid, Amber Srivastava","doi":"10.47904/ijskit.11.2.2021.81-84","DOIUrl":"https://doi.org/10.47904/ijskit.11.2.2021.81-84","url":null,"abstract":"","PeriodicalId":424149,"journal":{"name":"SKIT Research Journal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121982051","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
Analysis of Android Malware Detection Techniques in Deep Learning 基于深度学习的Android恶意软件检测技术分析
SKIT Research Journal Pub Date : 2020-10-30 DOI: 10.47904/ijskit.10.2.2020.21-26
Neetu Agarwal, Vipin Jain, Raju Ranjan
{"title":"Analysis of Android Malware Detection Techniques in Deep Learning","authors":"Neetu Agarwal, Vipin Jain, Raju Ranjan","doi":"10.47904/ijskit.10.2.2020.21-26","DOIUrl":"https://doi.org/10.47904/ijskit.10.2.2020.21-26","url":null,"abstract":"Over the years, developments in smart phone technology has boost up their use among users. This has captivated malware authors’ attention. Malware attacks in various forms has troubled users by stealing their personal information, banking information and much more. Android users have been strained most because of Android’s open nature. Throughout this time, efforts have been made to devise software and methods to detect android malwares. Starting from anti-virus software to Machine Learning and now Deep Learning, researchers have put forward various techniques to get to grips with the problem. Many Deep Learning Techniques have been put forward like Deep Neural Network, Convolutional Neural Network, Recurrent Neural Network, Deep Belief Network and Autoencoders. This paper looks at and analyzes supervised Deep Learning classifiers to detect Android malware. Keywords– Deep Learning, Android Malware, CNN, Neural Network.","PeriodicalId":424149,"journal":{"name":"SKIT Research Journal","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114931149","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
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