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International Journal of Computer Science and Engineering最新文献

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IOT Based Hybrid Artificial Tree For Solar/Wind Power Generation With Pollution Control And Monitoring 基于物联网的太阳能/风力发电混合人工树,具有污染控制和监测功能
Pub Date : 2021-04-25 DOI: 10.14445/23488387/ijcse-v8i4p101
S. Priyanka, P. Dhivya, S. Vigneswari, M Mangaleshwari, G. Sathya
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引用次数: 1
Iot Based Power Monitoring System 基于物联网的电力监控系统
Pub Date : 2021-04-25 DOI: 10.14445/23488387/ijcse-v8i4p102
M JaiganeshP, B. Meenakshisundaram
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引用次数: 2
CCA: A Methodical Vendee Vendor Carbon Copy Algorithm for Data Trading CCA:一种用于数据交易的系统化卖主复写算法
Pub Date : 2021-03-25 DOI: 10.14445/23488387/ijcse-v6i3p105
M AyishaSiddhiqua, T Arivulagarasi, M. Kanmani, Lakshmi, B Ezhilarasi
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引用次数: 0
Brightness Based Password Authentication to Avoid Shoulder Surfing in Banking Applications 基于亮度的密码认证避免银行应用中的肩部冲浪
Pub Date : 2021-03-25 DOI: 10.14445/23488387/ijcse-v6i3p106
R. Kanimozhi, D. Swetha, S. Kowsalya, J. NasrathBanu, R. Sowmiya
This project deals with problems on providing security Bright Pass is a user authentication scheme for secure ATM application. Shoulder surfing refers to eavesdropping one’s personal information like PIN or passwords by observing it from a considerable distance. we address this issue by introducing Bright Pass, a novel authentication mechanism based on screen brightness. Bright Pass allows users to authenticate safely with a PIN-based confirmation in the presence of specific operations on sensitive data. In this approach user can enter their PIN regarding the brightness value displayed to the user.
Bright Pass是一种用于安全ATM应用的用户认证方案。“肩膀冲浪”指的是隔着相当远的距离观察个人识别码或密码等个人信息,并进行窃听的行为。我们通过引入一种基于屏幕亮度的新型认证机制Bright Pass来解决这个问题。Bright Pass允许用户在对敏感数据进行特定操作的情况下,通过基于pin的确认安全地进行身份验证。在这种方法中,用户可以输入有关显示给用户的亮度值的PIN。
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引用次数: 0
An Iot Based Home Automation For Physically Challenged And Elderly People 基于物联网的残疾人和老年人家庭自动化
Pub Date : 2021-03-25 DOI: 10.14445/23488387/ijcse-v8i3p102
M Aashikha, N AbishekaPuvan, B Gowsalya, D. Vijayakumar
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引用次数: 0
A Review: Recruitment Prediction Analysis Of Undergraduate Engineering Students Using Data Mining Techniques 基于数据挖掘技术的工科本科生招生预测分析综述
Pub Date : 2021-03-25 DOI: 10.14445/23488387/ijcse-v8i3p101
Vandana Mulye, Atul D. Newase
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引用次数: 1
Maximizing Ad Revenue by Optimal Scheduling of Web Advertising 通过优化网络广告调度实现广告收益最大化
Pub Date : 2021-03-25 DOI: 10.14445/23488387/ijcse-v6i3p101
J GaneshME
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引用次数: 0
IOT Smart Mirror with News & Temperature 具有新闻和温度的物联网智能镜子
Pub Date : 2021-01-25 DOI: 10.14445/23488387/ijcse-v6i1p104
M. Ramya, R. Ramya, A Sandhiya, K. Raghunath
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引用次数: 1
Image Sampling Using Q-Learning 使用Q-Learning进行图像采样
Pub Date : 2021-01-25 DOI: 10.14445/23488387/IJCSE-V8I1P102
Ning He
: With the advent of the digital information age and multimedia technology development, the amount of image data is increasing day by day. The method of image sampling has been paid much attention to. The traditional triangular mesh sampling method needs to initialize the sampling set and the metric tensor before sampling, which is prone to problems such as unreasonable specification. Therefore, an intelligent image sampling method based on the Q-Learning reinforcement learning algorithm is proposed. Built on the interaction between reinforcement learning agents and the environment, an adaptive sampling method is designed to update agents' characteristics constantly. The experimental results show that this method can achieve the same effect as the traditional triangular mesh sampling method and is more intelligent.
随着数字信息时代的到来和多媒体技术的发展,图像数据量日益增加。图像的采样方法一直受到人们的关注。传统的三角网格采样方法需要在采样前对采样集和度量张量进行初始化,容易出现规格不合理等问题。为此,提出了一种基于Q-Learning强化学习算法的智能图像采样方法。基于强化学习智能体与环境的相互作用,设计了一种自适应采样方法来不断更新智能体的特征。实验结果表明,该方法可以达到与传统三角网格采样方法相同的效果,并且更加智能。
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引用次数: 0
Human and Animal Movement Detection in Agricultural Fields 农业领域的人与动物运动检测
Pub Date : 2021-01-25 DOI: 10.14445/23488387/ijcse-v6i1p103
D. Geetha, P MonishaS, J. Oviya, G. Sonia
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引用次数: 1
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International Journal of Computer Science and Engineering
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