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Plithogenic cognitive analysis on instigating spiritual intelligence in smart age youth for humanity redemption 为人类救赎而激发智龄青年精神智能的生成性认知分析
Pub Date : 1900-01-01 DOI: 10.1063/5.0074105
R. Priya, N. Martin, T. E. Kishore
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引用次数: 1
Prediction of disease and suggestion of specialist using big data techniques 利用大数据技术进行疾病预测和专家建议
Pub Date : 1900-01-01 DOI: 10.1063/5.0074128
K. Kanimozhi, R. Jeyavathana, C. S. Hameed
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引用次数: 1
Industrial automation using IoT 使用物联网的工业自动化
Pub Date : 1900-01-01 DOI: 10.1063/5.0074113
R. A. Sekar, T. Prabakaran, A. Sudhakar, R. S. Kumar
Monitoring in Industries is done by sensor with most accuracy and reliability. Internet of things (IOT) is rapidly increasing technology. IOT is the network of physical objects or things embedded with electronic software, sensors, and network connectivity which enables these objects to collect and exchange data. It uses a technology that makes use of control system such as computer to control the physical device over the internet. Here we propose efficient industry automation system that allows user to efficiently control industry appliances/machines over the internet. We use 3 loads as industrial appliances or machines and a motor to demonstrate as an industrial motor. We are developing a system which will automatically monitor the industrial applications and generate Alerts/Alarm or take intelligent decisions using concept of IOT. Safety from leaking of raw gas and fire are the most important requirements of home and industries security system for people. Automation is the current need of industries. There are number of technologies that are growing to achieve the good automation in the plant. Industries have been automated with machines that allow for fully automated tasks without or little manual intervention. Well here we propose an internet based industry automation system that allows a single industry operator to control industry appliances with ease using ARM7 processor and IOT. Our proposed system allows for automation of industrial loads to achieve automation over internet. We use IOT for the web serve interface and ARM7 processor to process and run circuit loads. User is allowed to send commands for machines/ load switching over internet using IOT from anywhere in the world over internet. The ARM7 processor captures these commands by internet over wifi connector. Now the ARM7 processes received data to extract user commands. After getting commands it displays it on LCD display.
工业监测是由最准确和可靠的传感器完成的。物联网(IOT)是一项快速发展的技术。物联网是嵌入电子软件、传感器和网络连接的物理对象或事物的网络,使这些对象能够收集和交换数据。它是一种利用计算机等控制系统通过互联网控制物理设备的技术。在这里,我们提出了高效的工业自动化系统,允许用户通过互联网有效地控制工业设备/机器。我们使用3个负载作为工业设备或机器和一个电机来演示作为工业电机。我们正在开发一个系统,该系统将自动监控工业应用并生成警报/警报或使用物联网概念做出智能决策。防止原料气和火灾的泄漏是人们对家庭和工业安全系统最重要的要求。自动化是当前工业的需要。有许多技术正在发展,以实现工厂的良好自动化。工业已经自动化,机器允许完全自动化的任务,而不需要或很少的人工干预。在这里,我们提出了一个基于互联网的工业自动化系统,允许单个工业运营商使用ARM7处理器和物联网轻松控制工业设备。我们提出的系统允许工业负荷自动化,通过互联网实现自动化。我们使用IOT作为web服务接口和ARM7处理器来处理和运行电路负载。用户可以使用物联网从世界任何地方通过互联网发送机器/负载切换命令。ARM7处理器通过wifi连接器通过互联网捕获这些命令。现在,ARM7处理接收到的数据以提取用户命令。收到命令后,它显示在LCD显示器上。
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引用次数: 10
Predictive analytics on Covid using recurrent neural network 基于递归神经网络的新冠肺炎预测分析
Pub Date : 1900-01-01 DOI: 10.1063/5.0074488
S. Vadivel, R. Jayakarthik
In this paper, we develop a risk based predictive analytics model utilizing the available dataset to train the model. To predict the likelihood of a new strain of Covid-19 syndrome in patients, the researchers used a deep learning classifier called Recurrent Neural Network (RNN). The study considers diabetes patients as the respondents and the data is collected from the diabetes patients. The risk of covid-19 effects on diabetes patients are deeply analyzed using RNN. The collected datasets are initially pre-processed and then the features are extracted with final classification using RNN. The experimental analysis is conducted to validate the efficacy of the predictive analytics using RNN. The findings indicate that the suggested RNN outperforms other approaches for forecasting covid-19 risk in diabetic patients. © 2022 Author(s).
在本文中,我们开发了一个基于风险的预测分析模型,利用可用的数据集来训练模型。为了预测患者感染新型Covid-19综合征的可能性,研究人员使用了一种名为循环神经网络(RNN)的深度学习分类器。本研究以糖尿病患者为调查对象,数据来源于糖尿病患者。采用随机神经网络深入分析新冠肺炎对糖尿病患者的影响。收集到的数据集首先进行预处理,然后使用RNN提取特征并进行最终分类。通过实验分析验证了RNN预测分析的有效性。研究结果表明,建议的RNN在预测糖尿病患者covid-19风险方面优于其他方法。©2022作者。
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引用次数: 1
A study on design of universal gripper for different part handling: Methods, mechanisms, and materials 不同零件处理的通用夹持器设计研究:方法、机构和材料
Pub Date : 1900-01-01 DOI: 10.1063/5.0074452
G. Shanmugasundar, M. Dharanidharan, D. Vishwa, P. Gokul, L. Manojkumar
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引用次数: 2
Evaluation of retention and stability of locator and ball attachment mandibular overdenture retained on a single median implant - An invitro study 评估定位球附着下颌覆盖义齿在单中位种植体上的固位和稳定性-一项体外研究
Pub Date : 1900-01-01 DOI: 10.1063/5.0074184
N. Vidhyasankari, C. Dhineshkumar, S. Shanmugapriya, S. Senthilkumar, R. Ramesh
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引用次数: 0
Genetic based algorithm to improve performance of mobile ad-hoc network 改进移动ad-hoc网络性能的遗传算法
Pub Date : 1900-01-01 DOI: 10.1063/5.0079764
Hamela K., M. Narayanan
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引用次数: 1
Access decision based on trust management in pervasive applications 普及应用中基于信任管理的访问决策
Pub Date : 1900-01-01 DOI: 10.1063/5.0074817
A. Hema, K. Kuppusamy
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引用次数: 0
Predominance and diminishing equivocalness of the images using double filtering – Density algorithm 利用双滤波-密度算法对图像进行优势化和模糊化
Pub Date : 1900-01-01 DOI: 10.1063/5.0074468
B. Mallikeswari, P. Sripriya
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引用次数: 0
Autonomous object recognition and collision avoidance for micro aerial vehicles with effective and cost-efficient sensor 基于高效、低成本传感器的微型飞行器自主目标识别与避碰
Pub Date : 1900-01-01 DOI: 10.1063/5.0074162
S. Shiyamala, G. Bhuvaneshwaran, Chejerla Om Prakash Reddy
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引用次数: 0
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