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Comparative analysis between theoretical and simulatory learning methods by data science methodology approach

Journal of Physics: Conference Series 2021年第1期1767卷

作者： Patani Rucha Sharadkumar S Shankar Narayan Final year student Department of Computer Science Engineering CMR Institute of Technology Bengaluru- 560 037 India Assistant Professor Department of Mathematics CMR Institute of Technology Bengaluru- 560 037 India

Data science is the most trending interdisciplinary science that integrates the steps of data collection, preprocessing data, transforming data, storing data, data visualization, and hence extracting the insights from the data to serve stakeholder's purposes. Python is commonly used and, along with being a versatile and open-source language, is a favorite tool in Data science studies. The vast libraries are being used to manipulate data and are very simple for even a beginner data scientist to understand. In the present work, we intend to apply the data science methodology to decision making and predictive analysis using the python programming language. We consider the problem of selecting the better mode of study concerning some of the impractical phenomena from physics for the exact understanding of the process. Data collection has been from an educational institute and the comparison has been made between theoretical learning and simulatory learning for selected topics from the vast fields like mechanics, thermodynamics, fluid dynamics, and radioactivity. The steps of data science methodology are germinated to achieve the insights into the data procured and the results are wangled concerning the teaching methodology that could be employed. In the present work, we undertake a comparative study between the theoretical and simulatory modes of teaching by exploring the modes individually through evaluating the responses imparted by a class of high school students. The analysis reported the more inclination of the student's responses towards the simulatory methods when compared to the theoretical method of learning.

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The Influence of Using Responsive Façade as a Tool for Improving the Built Environment: Case study: Attaba – Opera square

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IOP Conference Series: Earth and Environmental science 2022年第1期992卷

作者： M F Eltanboly M M Afify Architecture Department Teaching Assistant Cairo Higher Institute for Engineering Computer Science and Management No.2 Banafseg Center2 first Settlement Cairo Postcode 11477 Egypt and PhD. Student Environmental Design and Energy Efficiency Department Cairo University Faculty of Engineering Giza Architecture department Professor in Environmental Design and Energy Efficiency Department Cairo University Faculty of Engineering Giza

The path we are currently following to improve the physics of construction due to the destruction of our environment through the negative impact of the built environment around us. Current efforts to decrease carbon and energy are noted by modifying and improving modern 'layered' envelopes and improving a misunderstanding of thermal comfort that has become much less effective than expected. Understanding construction physics is an important factor in improving the quality of life indoor and outdoor, relying primarily on theoretical and computational aspects, then applying the practical part to reduce excessive use of carbon and energy and hinder the elaboration of a sustainable and built environment. This paper shows how the problem stems from neglecting to think about the first principles and basic construction physics. Similarly, we show how combining good construction physics with reassessing old methodologies to construction and structure use provides some powerful and effective tools to address the climate emergency. The use of construction physics methods supports the search for new solutions to express the most important factors affecting thermal conduction and minimum surface temperatures. However, buildings have integrated concepts in which advanced systems work together to optimize energy, comfort, and health performance. Convergence between various engineering fields and the overlapping field of construction techniques and services has great potential in the future to achieve the next step in energy saving. As a result, the research highlights new methods that make our buildings interact with the external environment using climate data, responsive envelope design, simulation software, thereby achieving architectural response to surrounding variables, improving building physics to reduce environmental pollution, thermal comfort, and achieving the highest energy efficiency and performance in buildings. This is illustrated by the presentation of a case study

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Performance evaluation of Energy Efficient algorithm using Spatial Trusted and Energy Aware Trusted Distance routing in WSN

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IOP Conference Series: Materials science and engineering 2020年第1期993卷

作者： M. Rajasekaran A. Ayyasamy R. Jebakumar Research Scholar Department of Computer Science and Engineering Annamalai University Chidambaram Tamilnadu India Assistant Professor Department of Computer Science and Engineering Annamalai University Chidambaram Tamilnadu India Associate Professor Department of Computer Science and Engineering SRMIST Kattankulathur Tamilnadu India

Energy efficient routing is the most important design criterion for WSN (Wireless Sensor Network) as the nodes are either powered by batteries, or by other external power sources. In a Sensor network, the nodes communicate with each other in a multi-hop fashion. The availability of each node is equally important to the proper functioning of the network. The power failure of nodes greatly affects the overall performance of the network. The Quality of Service (QoS) has been measured using the parameters of data quality, energy utilization and position of the sensor nodes. In this paper Energy efficient routing algorithm called Location and Energy Aware Trusted distance source routing (LEATDSR), Energy-aware Spatial Trusted Routing algorithm (ESTR) and Intelligent Weighted Fuzzy Cluster based Secure Routing Algorithm (IWFCSRA) were analyzed in term of energy efficiency performance. This paper implements LEATDSR, ESTR and IWFCSRA by using NS2 simulator. Energy Consumption and Security Analysis are used to evaluate LEATDSR, ESTR and IWFCSRA routing protocols performance analysis in WSN.

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Performing Experimentation with Physics Model to Predict Statistical Weather Condition

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Journal of Physics: Conference Series 2020年第1期1712卷

作者： A. Jayanthiladevi V. Nagaraju L. Devi N. Padmavathi P. Sailaja M.S Minu B R Tapas Bapu Professor-Computer Science & Information Science Srinivas University Karnataka India Professor / Department of ECE Rajalakshmi institute of technology Assistant professor in computer application Muthayammal College of arts and science Rasipuram Tamilnadu India Assistant Professor / Department Of Technology Velammal Institute Of Technology Assistant professor Dept of CSE SRM Institute of Science and Technology Ramapuram Campus Professor / Dept of ECE S. A. engineering college

Ice in wind turbines may cause a tremendous reduction in energy conservation. As, ice over turbines are not considered to be a traditional weather prediction data, prediction towards power can leads to higher error. This work anticipates a statistical approach dependent on Niave bayes regression to identify production loss has to be analyzed. It measures input of regional weather condition and various other conditions, and identify power production loss for 48 hours to enhance prediction of next generation energy loss. This can be trained with various prediction measurements and drastically enhances other conventional approaches for longer period. It may diminish absolute production error by ~100kW and it computes its skill with other models. Prediction of weather data is considered to be one of the effectual data for diverse statistical prediction and some calculations are not so absolute. This method can be computational less cost and may be trained again for next prediction.

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Smart Gas Monitoring System for Home and Industries

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IOP Conference Series: Materials science and engineering 2020年第2期981卷

作者： Modepalli Kavitha Dr. S. Hrushikesava Raju Saiyed Faiayaz Waris Dr. Ashok Koulagaji Assistant Professor Department of computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Associate Professor Department of computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India

Nowadays, gas industries or gas cylinders in a home will experience gas leakages because of human negligence or other external conditions and lack of patience. Due to disaster to be raised by such cases, the demolition happened is unpredictable. To predict the disaster in advance, then alternatives could be taken to avoid such cases. In this paper, an IoT device is designed that will detect gas leakages and the status of the gas to be known whenever cut off is specified by the user. The proposed IoT methodology for knowing the status of the gas summary is demonstrated using the specific use cases. The proposed IoT to be installed through a manual approach or virtual approach is depending on the consumer interest. There were many instances experiencing the many people to become victims of this and also the environment to be also spoiled and it takes more time to purify the infected environment or to bring the affected environment to a normal level. It is demanded nowadays to predict future disasters using G-IoT. In G-IoT, the components whenever meet less than the cut off values, will notify the report to the main center and authorized user. The V-IoT is also used to monitor outer environments like gas pipeline and its conditions. If the resources are supplied at the time of installation of setup and detected whenever a specific component becomes shortage, the automatic approach takes place and will start filling that specific component with required according to manual recording.

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An Efficient Privacy-Preserving Ranked Keyword Search Method

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IOP Conference Series: Materials science and engineering 2021年第1期1084卷

作者： E. Nirmala S. Muthurajkumar D. Subitha Research Scholar Department of Computer Technology Madras Institute of Technology (MIT) Campus Anna University Chennai India Assistant Professor Department of Computer Technology Madras Institute of Technology (MIT) Campus Anna University Chennai India Assistant Professor Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Vel Nagar Chennai

The keyword searching algorithm plays a vital role in cloud computing Architecture. Here, the searching technique is applied as a tool to encrypted data set which is outsourced. This technique works well, by either directed on multi keyword findings with exact match or one keyword search with fuzzy logic with a result of true or false. Though the existing techniques come across sensible difficultyin execution upon the encrypted data set, in the execution of multiple keyword based searching, keyword correction is difficult to achieve. To overcome with this problem, we construct a highly efficient, multiple corrections in keyword searching algorithm using ranking scheme. Multiple corrections like spell checks and errors. In the existing system of Author Wang and others scheme, they were unable to address the aforementioned problems, But in our method of multiple keyword searching technique, the Fuzzy Gramm algorithm helps to detect and handle the spelling errors by making a function call. Additionally the keywords with similar ancestry can be found by making use of stemming procedure. Alongside with thatrank keyword is used to achieve accurate checking with matched text file content. Thus the proposed approach enhances security and reliability to the maximum extent compared to the existing system.

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Garbage Waste Segregation Using Deep Learning Techniques

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IOP Conference Series: Materials science and engineering 2021年第1期1012卷

作者： G Sai Susanth L M Jenila Livingston L G X Agnel Livingston School of Computer Science and Engineering Vellore Institute of Technology Chennai Tamil Nadu India - 600127 Assistant Professor CSE Department St. Xavier's Catholic College of Engineering Chunkankadai Nagercoil Kanyakumari District Tamil Nadu India - 629003

Waste segregation is one of the primary challenges to recycling systems in major cities in our country. In India, 62 million tons of garbage is generated annually. Of this 5.6 million tons of wastes consist of plastic materials. About 60 percent of this is recycled every year. In addition, 11.9 million tons are recycled from 43 million tons of solid waste produced. Though the numbers sound good, a serious problem in the recycling industry is the segregation of waste before recycling or any other waste treatment processes. In India, at present situation waste is not segregated when collected from households. So a lot of workforce and effort are needed to separate this waste. In addition to this people working in this industry are prone to various infections caused due to toxic materials present in the waste. So the idea is to decrease the human intervention and make this waste segregation process more productive. The proposed work is aimed to build an image classifier that identifies the object and detects the type of waste material using Convolutional Neural Network. In this work, four different models of the CNN, such as ResNet50, DenseNet169, VGG16, and AlexNet, trained on ImageNet, are used to extract features from images and feed them into a classifier to make predictions and distinguish a type of waste from its corresponding category. The experimental results showed that the performance of DenseNet169 was significantly greater than all four models and the performance of ResNet50 is closer to DenseNet169.

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Real Time Emotion Analysis Usingbrainwavesin Comparison to Facial Expression

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IOP Conference Series: Materials science and engineering 2020年第1期994卷

作者： S. Devi Dr. M. Rajalakshmi S. Saranya B. Jeevanandan A. Ramya Assistant Professor Department of Information Technology Associate Professor Department of Information Technology Assistant Professor Department of Computer Science and Engineering B. E Student Department of Information Technology Coimbatore Institute of Technology

Emotions play a vital role in human living and are correlated with every single word which is being spoken, without them life will be saturated and irrelevant. Understanding of the real apparent facial expressions might be difficult because part of the emotion might not be revealed outside by everyone. In the proposed method, the emotions of the human are analyzed in two different ways so that the real hidden emotion of the subject can be detected. Every human has unique brain waves, which gives better accuracy than other techniques. It ensures that the facial expression exhibited outside is real or not. The emotion analyzed will be useful in treating the person with high mental stress and also infinding the emotion of differently abled person who requires medical treatment.

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Secured payment system using face recognition technique

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AIP Conference Proceedings 2020年第1期2282卷

作者： Arun Misra Rahul Kumar Dev Mr. M. Rajasekaran 1B. Tech Computer Science and Engineering SRM Institute of Science and Technology Chennai India 2Assistant Professor Computer Science and Engineering SRM Institute of Science and Technology Chennai India

This paper describes the process through which “Secured payment system using face recognition technique”- project has been made. It describes the main objective of the project which is to be able to develop a secured and robust payment system using face recognition in python programming language with the help of OpenCV. It uses confidence value which can be described as the value generated by the system informing us about the accuracy of prediction. This project was made by combining various detection modules and pattern recognizer. In this project various existing methods are combined together to give us the result. Pin and one time password (OTP) are used for security measures to make safe and successful transaction. OTP will be sent to the registered phone number of the user.

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Monitoring and control of temperature, humidity using machine learning

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AIP Conference Proceedings 2021年第1期2378卷

作者： Arvind Kumar Shukla Ashish Gupta A. Arunraja C. Arunkumar Madhuvappan 1Associate professor School of Computer Science and Applications IFTM University Lodhipur Rajput Moradabad India 2Professor & Head Department of English Govt. Girls College Sadar Betul. (M.P) 460001 India 3Assistant Professor Department of ECE Sri Ramakrishna Engineering College Coimbatore India 4Assistant Professor/ECE Vinayaka Mission’s Kirupananda Variyar Engineering College Vinayaka Mission’s Research Foundation - Deemed to be University (VMRFDU) Salem India

In this paper, In Recent Year Machine learning plays important role in analyzing the various time of weather condition all around the world especially Indian Subcontinent. Data is available in the government website to analyze the data for few long years. This should be matched with UCI technique for the machine learning and obtain the condition of different level of data repository. Temperature and humidity level condition of different parameters were analyzed and taken as example of weather condition to monitor the weather condition. We need to design a model to fit the different condition and need to extrapolating the needs of information, and optimize the technique using some algorithm and variation should be targeted and value should be analyzed.

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