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Real Time Fire detection and Localization in Video sequences using Deep Learning framework for Smart Building

Journal of Physics: Conference Series 2021年第1期1916卷

作者： P Sridhar R R Sathiya Assistant Professor Ece Sri Ramakrishna Engineering College Coimbatore Assistant Professor Department of Computer Science and Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

This work presents autonomous electrical fire-detection and localization using computer vision based techniques. The proposed work uses YOLO v2 to extract the electrical fire features more effectively than other conventional and machine learning approaches. This working model is tested on commercial and residential building as well as indoor and outdoor environments. This framework has achieved high detection accuracy and low false alarm rate. Besides, the proposed frame work can be used for early real-time electrical fire detection in surveillance videos and we present experimental results for electrical fire localization in CCTV footage using the deep learning architecture proposed in this work.

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computer Vision based Early Electrical Fire-detection in Video Surveillance oriented for Building environment

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Journal of Physics: Conference Series 2021年第1期1916卷

作者： P Sridhar R R Sathiya Assistant Professor ECE Sri Ramakrishna Engineering College Coimbatore Assistant Professor Department of Computer Science and Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

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Machine learning approach for detection of keratoconus

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IOP Conference Series: Materials science and engineering 2021年第1期1055卷

作者： S Shanthi K Nirmaladevi M Pyingkodi K Dharanesh T Gowthaman B Harsavardan Associate Professor Department of Computer Science and Engineering Kongu Engineering College Erode India Assistant Professor Department of Computer Applications Kongu Engineering College Erode India UG Student Department of Computer Science and Engineering Kongu Engineering College Erode India

Keratoconus is a progressive eye disease and it should be detected in early stage, to avert probable refractive surgery that could develop ecstasies. In this the authors proposes a new computer aided diagnosis model based on Support Vector Machine (SVM) learning to detect the early stage of keratoconus using the available topographic, pachymetric and aberrometry parameters of patients with keratoconus, subclinical keratoconus and normal corneas. The proposed SVM produces 91.8% accuracy with 94.2% sensitivity, 97.5% specificity for classification of early keratoconus from normal; 100% accuracy with 100%, 100% of sensitivity and specificity respectively for classification of early keratoconus from subclinical keratoconus.

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Analyzing ELearning platform reviews using Sentimental Evaluation with SVM Classifier

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

作者： R Muralidharan T Kanagasabapathy R P Vijai Ganesh Assistant Professor Department of Computer Science and Engineering Dr. Mahalingam College of Engineering and Technology Coimbatore India

In today's scenario, the participation of eLearning courses is rapidly increasing among users, especially during post-pandemic situation. Due to a hike in the need of eLearning, there is a sharp increase in emerging of online courses. Not only the academic people (students and teachers), but others also interested in the online courses, irrespective of their ages. Since numerous eLearning platforms are mushrooming, it is mandatory to follow various standard techniques to evaluate the quality of these courses. It would be more adaptable, if the evaluation techniques are made based on the Course users feedback. These feedback of the users contain more valuable information which helps in constructive decision making. The satisfactions and criticisms of the courses are shared through opinion of the registered user. Due to enormous amount of web reviews available for a course, it is extremely time-consuming and difficult to manually analyze the review and come to a conclusive decision. Reviews contain course feature specific factual information along with the opinion statements which may be positive or negative. The text reviews obtained from most of the webpages of the online courses feedback or comments section, are found to be unstructured and inconclusive. Analyzing and extracting the actual opinion throughout the reviews manually is very difficult. So, an automated technique is needed to evaluate the course based on the features of the courses, which results in attaining a decision. The Aspect based opinion mining is such a methodology which describes the important aspects of each opinion and classify them on their polarity.

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Privacy Preserving On Remote Sensing Data Using Reversible Data Hiding

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Journal of Physics: Conference Series 2021年第1期1979卷

作者： K Saravanan K Suganthi R Kalaiselvi B Divya S Dilip Kumar PG Scholar Department of Computer Science and Engineering Arasu Engineering College Kumbakonam Tamilnadu India Assistant Professor

The method of steganography covers message in the cover file and forms a stego file. Imagery needs a method that will boost protection, minimise distortion in the stego file and recover data without failure. There is a need for reducing transmitting time in the age of multimedia and the Internet. The main purpose of this project is to create safe contact between the sender and the recipient through emails and other modes of communication. A reversible data hiding algorithm was proposed in the integer wavelet transformation (IWT) domain to resolve the image distortion problem. This strategy aims to incorporate data into IWT coefficients of higher frequencies. After wavelet coefficients are collected by converting the integer wavelet data into high-frequency subbands HL, LH and HH, the human eyes would have fewer recognisable objects. After data is incorporated in such IWT coefficients, reverse integral wavelet transformation can occur following application. The stegno image was further encrypted by using Elliptic Curve Cryptography (ECC). The process of encryption enhances the image security during data transmission. In our proposed work inverse wavelet transformation (IWT) and Elliptic Curve Cryptography (ECC) algorithms are effectively utilized to achieve highly secure communication.

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Educational Assistance Bot

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Journal of Physics: Conference Series 2021年第1期1797卷

作者： Arindam Roy Dharmpal Singh Sudipta Sahana PG Student Department of Computer Science & Engineering JIS College of Engineering Kalyani Nadia-741235 Associate Professor Department of Computer Science & Engineering JIS College of Engineering Kalyani Nadia-741235 Assistant Professor Department of Computer Science & Engineering JIS College of Engineering Kalyani Nadia-741235

An Internet bot performs automated tasks over the Internet. This software application is also known as a web robot or robot or simply bot, Typically, bots runs simple and structurally repetitive tasks, at a much higher rate than would be possible for a human alone. This effort is to help the users by providing all the basic student's academic details like subjects, faculty names, books, notes and routine according to their need using bot. Users can also get other information like fees structure, library inventory list, calendar etc. Additional information like top educational sites, most trending educational videos etc will be regularly updated by the admin. This is an all-in-one application which can also be used to fetch and update information which is purely related to COVID-19.

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Applications of Flying Ad-hoc Network During COVID-19 Pandemic

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IOP Conference Series: Materials science and engineering 2021年第1期1099卷

作者： Manisha Devi Sunil Kumar Maakar Deepak Sinwar Mahesh Jangid Poonam Sangwan Scholar Department of Computer Science and Engineering BRCM College of Engineering and Technology Bahal Haryana India Assistant Professor Department of Computer Science and Engineering BRCM College of Engineering and Technology Bahal Haryana India Assistant Professor Department of Computer and Communication Engineering Manipal University Jaipur Dehmi Kalan Jaipur Rajasthan India Associate Professor Department of Computer Science and Engineering Manipal University Jaipur Dehmi Kalan Jaipur Rajasthan India Assistant Professor Department of Chemistry Government College Hisar Haryana India

The 2019 novel coronavirus (2019-nCoV), with a beginning stage in Wuhan (China), has spread quickly among people living in different nations and has affected more than 6 million lives. Researchers around the globe are trying to device a solution in the form of the vaccine but unfortunately, till date, there is no full-proof vaccine for 2019-nCoV. Most of the countries are adopting prolonged lockdown and social distancing strategies to counter this pandemic. Flying Ad-hoc Network (FANET) on the other hand, can provide several services such as the delivery of essential items, disinfecting common areas, surveillance, traffic monitoring, communication, temperature monitoring, etc. Availing such services using FANETs during Corona Virus Disease (COVID-19) outbreak is like a boon that can minimize the general problems of mankind to some extent during lockdowns. Nowadays, it is foremost required to deploy solutions that can automate the process of availing several services using FANETs and the same is attracting researchers in great demand. This paper has presented a brief survey of several applications of FANETs (especially UAVs and Drones) that can facilitate mankind in coping with the general problems during COVDI-19 outbreak and subsequent lockdowns. We hope that this survey has covered most of the applications of UAVs and can provide new insights into the research community.

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SAMS: Smart Agriculture Management System Using Emerging Technologies IoT, AI -A Study

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IOP Conference Series: Materials science and engineering 2021年第1期1074卷

作者： B. Srinivas Kumar S.G. Santhi K. Kranthi Kumar Research Scholar Department of Computer Science and Engineering Annamalai University. Associate Professor Department of Computer Science and Engineering Annamalai University. Assistant Professor Department of Information Technology Gudlavalleru Engineering College Gudlavalleru

Farming or Agriculture is the science and art of cultivating plants. It is the vital enrichment in the growth of human living. It creates food and the other related things by farming with domestic animals and will enable people to live long and healthy life. There are two agricultural categories, one is traditional Agriculture and the second one is Modern Agriculture. In Traditional Agriculture Farmers had faced many difficulties to Farm, but with the modern Agriculture Farmers can be able to see many improvements in Framing due to the agronomy, use of agricultural chemicals such as pesticides and fertilizers, Plant breeding and technological growth, these enrichments in Farming would yield good crop.(IoT)Internet of Things very often called as a system it can able to connect real physical Things, Implanted sensors, Embedded software's along with different technologies to connect and to transfer data amongst various diverse devices over the Internet. It is the hopeful expertise or technology which gives accurate and most reliable solutions on the way to too many domains. There is an extensive set of wide range of real time applications of IoT devices such as Industrial, Consumer, Commercial, Infrastructure may made IoT is the one of the best Technology to see enhancements in many domains. Solutions which are given by IoT would reduce human efforts in Farming and may provide sound of crop. In this paper a small survey will be presented to see how Internet of Things and its equivalent or other represent technologies AI, Cloud Computing would be useful to provide SMART AGRICULTURE along with Modern agricultural improvements will also be presented.

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Multiple Watermarking Scheme for Video & Image for Authentication & Copyright Protection

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IOP Conference Series: Materials science and engineering 2021年第1期1131卷

作者： Neha Janu Ankit Kumar Pankaj Dadheech Gajanand Sharma Ashutosh Kumar Linesh Raja Associate Professor Department of Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan Jaipur Rajasthan India Assistant Professor Department of Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan Jaipur Rajasthan India Assistant Professor Department of Computer Science & Engineering JECRC University Jaipur Rajasthan India Assistant Professor Department of Computer Applications Manipal University Jaipur Rajasthan India

Watermarking has been used frequently to authenticate the accuracy and security of the image and video files. In the world of computer technology, several watermarking strategies have developed during the past 20 years. Integrate a picture of identity that is not always concealed, such that no detail is not possible to delete. A monitoring code can also be used to deter unauthorized recording equipment. Another application is the watermark copyright control, which works at stopping the creator of the image from stealing photos unlawfully. A watermark is a promising option for the copyright transcendence of multi-media files, as embedded messages are still included. Due to the limits of fidelity, a watermark may be implemented in a small multimedia data space. There is no proof that Automated Watermarking technologies will fulfil the ultimate purpose of the cleaners of all sorts of copyright security operations to gather knowledge from the data they obtain. Relevant situations may be deemed more fairly expected with the usage of automated copyright marking technologies. A perfect device will not be able to add a digital watermark without the limit, which does not supply the whole object with details. In this work, a modern technique for watermarking includes injecting two or more messages or photographs into a single picture for protection purposes and repeating a similar procedure for N-frames for authentication in the film.

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IMPROVED RESOURCE MANAGEMENT AND UTILIZATION BASED ON A FOG-CLOUD COMPUTING SYSTEM WITH IOT INCORPORATED WITH CLASSIFIER SYSTEMS

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Microprocessors and Microsystems 2021年

作者： M. Buvana K. Loheswaran Karanam Madhavi Sivakumar Ponnusamy Aradhana Behura R. Jayavadivel Assistant Professor Department of Computer Science and Engineering PSNA College of Engineering and Technology Dindigul India Associate Professor Department of Computer Science and Engineering CMR College of Engineering &Technology Kandlakoya Medchal Road Hyderabad - 501 401 Telangana India Professor Computer Science and Engineering Department Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad 500090 Telangana state India Associate Professor Department of Computer Science and Engineering SRM Institute of Science &Technology Delhi NCR Campus Modinagar Ghaziabad Uttar Pradesh-201204 India Assistant Professor Department of Computer Science and Engineering GITA Engineering College Road Badaraghunathpur Janla Bhubaneswar Odisha-752054 India Associate Professor Department Computer Science and Engineering Vivekanandha College of Engineering for Women Tiruchengode Namakkal Tamilnadu-– 637205 India

With the rapid rise of computing devices-linked networks, the Internet of Things (IoT) has increased proportionally and speedily. After that, the size of the data generated and significantly increased computational effort. A solution for a very large workload is cloud computing significantly slowed and continues to be a problem in a distributed computer network. Addressing the workload at the network edge can enchase time feedback, and delaying the data load management task imposes performance constraints from the power source to the edge of the network, which does not support only limited battery power. Therefore, the workload must be distributed equally to the clouds and across the network. This document presents the XCS Classification System (LCS), by XCS and BCM-XCS, to ensure energy consumption at the end of the project which decreases the workloads of the processing time. Our test outcome showed the dominance of BCM-XCS XCS according to standard methods. A distributed method of allocating responsibility for reducing the processing time between node cloud and fog. In addition to the significant benefits of handling fluctuating turnaround times, the proposed procedures can simultaneously decrease 42% response times utilizing an average consumption of energy in the grid edge. With the propounded method, rechargeable batteries are used on the edge of the grid also can load approximately 18% more than the best method of the prior art.

关键词： Learning classification systems (LCS) Extended Classification System (XCS) Internet of Things (IoT) fog computing best classifier memory (BCM)

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