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Fast Hybrid Adaboost Binary Classifier For Brain Tumor Classification

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

作者： S. Jayaprada G. JayaLakshmi L. KanyaKumari Associate Professor Department of Computer Science & Engineering Gudlavalleru Engineering College Gudlavalleru Andhra Pradesh India Assistant Professor Department of Information Technology VR Siddhartha Engineering College Vijayawada Andhra Pradesh India Assistant Professor Department of Information Technology Andhra Loyola Institute of Engineering and Technology Vijayawada Andhra Pradesh India

The brain tumor is a dangerous disease and its characterization is a difficult undertaking for radiologists in light of the heterogeneous idea of the tumor cells. computer-Aided tasks and its implementation of the current models with their frameworks would suffice the design metrics to recognize and relate the different tumors including brain though the process with scanning of the brain would emphasize on MRI. The models with support vector machine-nearest neighbor, naïve bayes analysis are obtained aren't enough to produce the different scenario at each set of layers and its correlation values of the performance observed. We propose a design model with fast Adaboost binary classifier, ensemble approach with fast boosting algorithm with the pre-trained model's dataset to analyze the different problem which proposes a strategy for multiple application scenarios of feature extraction to provide a classification model for different tumors in the brain to improve different performance parametric values for each trained and test sets with the prediction algorithm with each design formulation.

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Secure IoT via Blockchain

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IOP Conference Series: Materials Science and engineering 2021年第1期1022卷

作者： Ruchi Garg Poonam Gupta Amandeep Kaur Assistant Professor Electronics and Communication Engineering Department M.M.(Deemed to be University) Mullana Ambala Haryana India Assistant Professor Computer Science and Engineering Department M.M.(Deemed to be University) Mullana Ambala Haryana India Associate Professor Computer Science and Engineering Department M.M. University Sadopur Ambala Haryana. India

Block chain technology had gained popularity because of its use in crypto-currencies like bitcoin. Today uses of blockchain are growing in number of areas like banking, industries, health centers and even security of IOT. Moreover, the use of IOT is growing exponentially every year with its aim in 5G technologies like e- health, smart homes, distributed intelligence etc. but it faces challenges in security and privacy. The privacy of a user data is at a risk because of its (i.e. IoT) centralized client-server model. This centralized approach of the server poses a serious vulnerability to the data security. This data at the server attracts the attackers to enter into the network and invade through the data and schedule attacks or inject a malware. It indicates that the central architecture of IoT possess a compromised confidentiality, integrity, and security of data which disrupts its use as the widespread adoption of this technology. Therefore, it is essential to evade the hostile centralized server architecture for IoT to enhance its security. It implies a need for decentralized architecture to maintain the data. The data can be kept at the different users without any central control with the help of blocks as suggested by Blockchain. This paper addresses the various security issues in IOT and how block chain helps in solving these issues.

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Development of peanut separator and thruster

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

作者： M Srinivasan S Nithya Sai Albert Alexander N Prabhakaran C Gokul G Visalaxi Assistant Professor Department of Electrical and Electronics Engineering Kongu Engineering College Erode district-638 060 Tamilnadu India Assistant Professor Department of Electronics and Communication Engineering Kathir College of Engineering Coimbatore district-641 062 Tamilnadu India Student Department of Electrical and Electronics Engineering Kongu Engineering College Erode district-638 060 Tamilnadu India Assistant Professor Department of Electrical and Electronics Engineering Velalar College of Engineering and Technology Erode-638012 India Assistant Professor Department of Computer Science and Engineering Bharath Institute of Higher Education and Research Chennai India

Peanuts have been in existence since the beginning of human life. It has a high carbon content and is rich in oil and protein. Peanut oil extraction is more common in most developing countries. Peanut is a commonly used, edible commodity, and oil is used as a cooking medium. Upon oil extraction, the by-product of the peanut cake often contains 43-65 per cent protein and 6-20 per cent fat, which is usually used as feed for cows and goats. There is currently a shortage of farm workers and an increase in harvesting costs. The factors mentioned above mean that farmers are not interested in growing peanuts. The removal of peanut shells is a time-consuming and costly operation. During harvesting, the temperature is very high, making it impossible for humans to work. Peanut thresher is used to solve these problems by removing peanuts that minimize time and expense. Our project focuses mainly on the design and development of a peanut cutting machine with a 0.5 hp motor. The workers removed the peanut capsules from the harvest at the beginning. The output of this method was very poor and did not meet consumer demand because it was a time-consuming operation. The main part of our project is a rotating drum with nails. They feed the peanuts to the rotating drum. Rotating drum tips isolate the pods from field harvest. There are large peanut harvesters on the market, but small farmers cannot afford these harvesters. Our machine is small, light and inexpensive. Farmers with a small farm may afford to use our machine.

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Soft Computing Techniques for Clustering in WSN

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IOP Conference Series: Materials Science and engineering 2021年第1期1022卷

作者： Amandeep Kaur Poonam Gupta Ruchi Garg Associate Professor Computer Science and Engineering Department M.M. University Sadopur Ambala Haryana India Assistant Professor Computer Science and Engineering Department M.M. (Deemed to be) University Mullana Ambala Haryana India Assistant Professor Electronics and Communication Engineering Department M.M. (Deemed to be) University Mullana Ambala Haryana India

The large Wireless Senor Networks (WSNs) comprises Sensor Nodes (SN) in some hundreds with sensing and communication capabilities. Major limitation of WSN is limited energy source of SN. Clustering is one of energy efficient method for energy conservation in WSNs. Clustering is the process to distribute SN in various logical groups known as cluster. Each cluster bears a Cluster Head (CH), who is responsible for transmitting aggregated data of its cluster to Base Station (BS). The literature is enriched by various clustering protocols proposed with the assistance of soft computing. This paper, presents the survey of soft computing paradigm-based clustering protocols.

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Detection and Classification of Breast Cancer Using improved Grey Wolf Algorithm

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

作者： T Senthil J Deepika R. Nithya Assistant Professor Deparment of Electronics and Communication Engineering EngineeringBannari Amman institute of TechnologySathyamangalam ErodeTamilnadu India Assistant professor.Department of Information Technology Engineering Bannari Amman institute of TechnologySathyamangalam ErodeTamilnadu India Assistant professor.Department of Computer Science Engineering Engineering Bannari Amman institute of TechnologySathyamangala ErodeTamilnadu India

Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in significantly less number, there's motivation to expand a mechanized forecast machine for early expectation and visualization of malignancy. The sort of considerate and threatening tumor are accomplished the use of type methodologies of device becoming acquainted with wherein the device is found from the past records and predicts the sorts of late sources of info. This paper is an overall report on the execution of models utilizing Logistic Regression, Support Vector Machine (SVM) and Gray wolf algorithm(GWO). The outcomes are assessed with the exactness, accuracy, affectability, explicitness and False Positive Rate boundaries for every calculation and are thought about. These procedures are coded in Java and executed in MATLAB, the Image handling Environment. Our investigations have demonstrated that Gray wolf is the best for prescient examination with an exactness of 92.7%.We surmise from our test results that SVM is the appropriate calculation for expectation and in general Gray wolf has performed well close to SVM.

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Brain tumor detection from MRI images using deep learning techniques

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

作者： P Gokila Brindha M Kavinraj P Manivasakam P Prasanth Assistant Professor Department of Computer Technology - UG Kongu Engineering College Perundurai - 638 060 Student Department of Computer Technology - UG Kongu Engineering College Perundurai - 638 060

Brain tumor is the growth of abnormal cells in brain some of which may leads to cancer. The usual method to detect brain tumor is Magnetic Resonance Imaging(MRI) scans. From the MRI images information about the abnormal tissue growth in the brain is identified. In various research papers, the detection of brain tumor is done by applying Machine Learning and Deep Learning algorithms. When these algorithms are applied on the MRI images the prediction of brain tumor is done very fast and a higher accuracy helps in providing the treatment to the patients. These prediction also helps the radiologist in making quick decisions. In the proposed work, a self defined Artificial Neural Network (ANN) and Convolution Neural Network (CNN) is applied in detecting the presence of brain tumor and their performance is analyzed.

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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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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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Security Concerns during Photo Sharing in Social Network Platforms

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

作者： T Maragatham P Yuvarani J Sowndarya Shree Assistant Professor Department of Computer Technologu- PG Kongu Engineering College Perundurai Erode PG Scholar Kongu Engineering College Perundurai Erode

The posting of pictures in online social media could be a common way of keeping buyers socially connected with others within the development of social media advances. The wealthy point of interest within the picture hence rearranges the suspicion of delicate information around individuals' interior the photo by a malevolent client. In later a long time there has been a part of consideration to the way in which the security revelation of photographs was subsumed. When a client posts a photo, the picture must take into consideration the protection of all connected clients. This framework is anticipated to share such co-possessed pix. In addition to that, this approach proposes an eager way for the creator to track the edge, since of an equalization of privateers held with an anonymization and also with information traded with others. The anonymizing impacts of a picture are represented by an edge that's characterized by the distributer. Simulation results uncover that the trust-based photograph sharing component is helpful to scale back the security misfortune, and furthermore the extended edge normalization strategy would pay a sensible taken a toll to the consumer.

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