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Machine learning approach for detection of keratoconus

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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Discernment and Diminution of Black Hole Attack in Mobile Ad-Hoc Network using Artificial Intelligence

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Journal of Physics: Conference Series 2021年第1期2040卷

作者： K Srinivas V Harsha Shastri Vinay Kumar Nassa Gudapati Syam Prasad Prathipati Ratna Kumar Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Hyderabad - 500075. Assistant Professor Department of Computer Science and EngineeringLoyola Academy Secunderabad-500010 Telangana. Principal/Professor Department of Computer Science & Engineering South Point Group of Institutions Sonepat-131001(Hr.) Professor & HOD Department of IT Narasaraopeta Engineering College Narasaraopeta Guntur District. Assistant Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Hyderabad – 500075.

The MANET is an interesting research topic that has movable nodes. The mobile ad hoc system is an important research area. The nodes are connected by wireless connections. Thus it is vital to have a stable network because information and interaction are crucial in diverse fields such as security and catastrophe emergency response. Because of the decentralized system's vibrant existence, these channels are vulnerable to various threats, including BHA, GHA, SHA. One of the well-known security issues in MANET is the black hole assault. Each node has a routing table containing information from the target node. The number of assaults in MANET is usually protocol networking assaults. The study focused on black hole attacks for discernment and decrease. A black hole attack node wrongly picks up all packet and collects them without passing them to an endpoint by taking a fresh path to the destination nodes. This paper presents BHA defence from assaults with the principle of Artificial Neural Network and calculates its efficiency according to the set of elements, such as efficiency, PDR and delay and energy utilization. This paper aims to devise an artificial neural network method for black hole discernment and reduction in MANET.

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Detecting Bone Fracture in Medical Images

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Journal of Physics: Conference Series 2021年第1期1770卷

作者： N Satya Sriveni K Hema Latha A Viji Amutha Mary Mercy Paul Selvan UG Student Department of Computer Science and Engineering Sathyabama Insititute of Science and Technology Chennai India Associate Professor Department of Computer Science and Engineering Sathyabama Instititute of Science and Technology Chennai India Assistant Professor Department of Computer Science and Engineering Sathyabama Insititute of Science and Technology Chennai India

Bone fracture is one of the most ordinary problems in mortals because of accidents or other causes. Breaking bones can occur in our body, such as the wrist, heel, ankle, hip, rib, leg, chest, etc. Fractures cannot be seen with the naked eye, so X-ray/CT images are used to detect them. But sometimes these images lack sufficient detail for diagnosis. Today image processing plays an important role in detecting bone fractures. Image processing is important for the archiving and transmission of modern data, in particular for image transmission, video encoding, digital libraries, image databases, and remote sensing. This research paper presents detailed research on image processing methods for detecting bone fractures. The following research will help in studying various techniques that can be used to detect fractures in boned through the process of image processing and also includes updating of some new techniques as an improvement.

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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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Detecting Cardiac Arrest Based on Image Processing

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Journal of Physics: Conference Series 2021年第1期1770卷

作者： Veeranna Chowdary Muthamreddy A Viji Amutha Mary Mercy Paul Selvan Jancy UG Student Department of Computer Science and Engineering Sathyabama Insititute of Science and Technology Chennai India Associate Professor Department of Computer Science and Engineering Sathyabama Instititute of Science and Technology Chennai India Assistant Professor Department of Computer Science and Engineering Sathyabama Insititute of Science and Technology Chennai India

In the world, about 21 percent of death occurs in the age group of 28-72 years because of a cardiac arrest. Many people among us lose their life because of heart-attack. After the occurrence of heart-attack only, the patient can be monitored. To help our society from heart-attack, I am developing a system that helps to decrease the death rate and early detection of a heart attack. Thus, this system is used to save the life of many people. We detect the prior occurrence of heart-attack of a patient using their monitored lungs datasets using image processing along with IoT.

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Smart Health Care Pathology

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Journal of Physics: Conference Series 2021年第1期1770卷

作者： Nama Saikumar N. T. V. Nitesh A. Viji Amutha Mary Mercy Paul Selvan UG Student Department of Computer Science and Engineering Sathyabama Insititute of Science and Technology Chennai India Associate Professor Department of Computer Science and Engineering Sathyabama Insititute of Science and Technology Chennai India Assistant Professor Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

Wireless sensor networks have wide use in different fields such as medical, military defense. This paper discusses the primary hidden protection framework for data privacy. The hidden key, remote node, and base station are used to connect and hack through secrets. We used fiber labeling technologies to secure data transmission Between the base station and the far node. We combined those techniques with Data slice, homomorphism, data privacy and data security defense encryption technology. The only way to obtain more than a sufficient number of different secrets That can decode data from base station to remote node. To order to protect data privacy, the homomorphism encryption technology Sets up a safe and powerful network of wireless sensors.

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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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An evaluation of deep learning approaches for detection of voice disorders.

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IOP Conference Series: Materials science and engineering 2021年第1期1085卷

作者： M S Chinchu B. Kirubagari Assistant Professor at SJCET Palai & Research Scholar Computer science and Engineering Department India AssociateProfessor& Research Guide Computer science and Engineering Department India.

The human voice manufacturing system is a complicated natural device capable of modulating pitch and loudness Human sound frequency particularly. The part in which the folded is the primary source underlying internal and/or external factors often destroys vocal folds justification. Some changes consequences are reflected in functioning emotional state soul. Therefore it essential to identify variations at an early stage gives the patient an endangerment overcome any impact modernize their quality of life will-less detection disorders using depth study methods plays an important role as has been proven to facilitate the process. Many researchers have explored technologies for streamlined that can help clinics diagnose noise paper we present the conducted research activities.

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Detection of Online Fake Reviews Based on Text Emotion

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

作者： S Kiruthika V Vishnu Priyan Assistant professor Department of Computer Science Engineering Sri Krishna College of Technology Coimbatore Student Department of Computer Science Engineering Sri Krishna College of Technology Coimbatore

online groups offer clients with ways to overpower a few data hurdles and limitations, like the challenge to get self-governing data about movies and for the co-occurrence of positive and negative reactions within reviews. False reviews will disturb such choices because of misleading data, causing commercial disadvantages for the customers. Recognition of false opinions has thus expected very large concentration now days. But, many websites have only concentrated on handling the problematical comments and reviews. Our work tends to categorize people opinions into groups of true orfalse polarization by employing text feature analysis. In our work, our team analyze people opinions by implementing Sentiment Analysis techniques to recognize false opinions. Sentiment Analysis and text feature categorization techniques were used to a database containing people opinions. Furthermore, the estimation reviews acquired from reviewers could be categorized into good or bad opinions, that could be utilized by a customer to choose a movie. Further the proposed technique will graph based on the classification of true and fake reviews as the analysis of good and bad reviews for a product (movie). It will help us to predict the ratio of fake reviews to true reviews easily. To estimate the accomplishment of SA technique, this work has employed accurateness, exactness, recollection and F-degree as a performance rate.

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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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