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Diabeties Predection Using Biosensors

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

作者： N. Ravinder N. Rajesh V. Kantha Rao T. Praveen M. Sridhar Asst. Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Associate Professor Department of CSE Aurora's Science and Technological Institute Hyderabad

Biosensors are little investigative gadgets that join a component of natural acknowledgment and a physio-compound transducer to change an organic sign into an electrical perusing. Their specialized allure these days lies in their solid proficiency, high affectability, and consistent limit with regards to estimation. A biosensor embedded in contact central focuses to decide the degree of tear glucose and to hand-off the information to the patient's body siphon. The siphon can mix insulin, the missing hormone, the necessary degree. This machine evades the distinctive blood checks and implantations for interesting sorts of diabetes that are really basic consistently. Diabetes characteristics are calculated by the sensor and the algorithms of machine learning are used to obtain the solution. Glucose measurements in blood plasma are positive, suggesting that the sensor is designed to estimate physiological blood glucose levels with negligible atomic effects. We are aimed at contributing to the growing biotechnology sector, with a focus on Glucose-Oxidise Biosensor (GOB) modelling from a regression perspective through quantitative learning methods. Blood glucose monitoring was developed as an effective tool for diabetes administration. Since it is suggested to maintain typical levels of blood glucose, a progression of appropriate biosensors of glucose has been developed. The technology of glucose biosensors, including treatment tools, reliable glucose monitoring systems and non-invasive glucose detection frameworks, has been fully developed over the last 50 years. In any case, a few steps are still associated with the achievement of accurate and reliable measurement of glucose. Utilizing a few AI calculations to demonstrate the amperometric reaction of a GOB with subordinate factors under various conditions, for example, temperature, benzoquinone, pH and glucose levels. In particular, kernel-based regression techniques, such as support vector machines, are being used toda

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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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Innovative Task Scheduling Algorithm in Cloud Computing

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

作者： S. Magesh Kumar V. Auxilia Osvin Nancy A Balasundaram Seena Naik korra D Kothandaraman E Sudarshan Associate Professor Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Assistant professor Department of IT S. A. Engineering College Chennai Tamil Nadu India Assistant Professor Center for Cyber Physical Systems (CPS) School of Computer Science and Engineering Vellore Institute of Technology (VIT) Chennai Tamil Nadu India Associate Professor School of Computer Science and Artificial Intelligence S R University Warangal India Associate Professor Sumathi Reddy Institute of Technology for Women Warangal India

This work concentrates around the task scheduling depends on QoS and imperative of desire. Under nature of vibrant cloud computing, effectiveness improving of scheduling of task and load balancing are interminable issues. For clients, be that as it may, it's progressively imperative to meet their necessities of QoS. This paper identifies with an improvement decency intention depends on new Berger's model under the earth of vibrant cloud computing. As indicated by the distinctive kind of task scheduling, we portray the need of decency, proficiency and the Balance among advantage and reasonableness separately. We recompile the CloudSim and recreate the three undertaking task scheduling above based on expanded CloudSim individually. The exploratory outcomes show that this calculation portion not just meet the guideline of offering need to profit with because of thought to decency, yet additionally address clients' issues of orchestrated QoS.

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H-array system on picture languages with array rewriting rules

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AIP Conference Proceedings 2020年第1期2277卷

作者： D. K. Sheena Christy P. John Paul D. G. Thomas 1Assistant Professor Department Of Mathematics SRM Institute Of Science And Technology India 2Teaching Associate Department Of Computer Of Science And Engineering SRM Institute Of Science And Technology India 3Professor Department Of Science and Humanities Saveetha School Of Engineering SIMATS India

Splicing systems was first proposed by Head on organic considerations to demonstrate indubitable chimeric behavior of DNA particles and are of current intrigue and study. In this paper, we study some of the chomskian hierarchy of array grammars namely (Regular:Regular)array grammar,(Context Free:Regular)array grammar and (Regular:Context Free)array grammar using H-array system. The Array rewriting rules is limited to extent by the action of row and column splicing.

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Highly accurate HEp-2 Specimen Image Segmentation and Classification using LBP and HoG using CNN classifier

Highly accurate HEp-2 Specimen Image Segmentation and Classi...

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International Conference on Advanced computer Control, ICACC

作者： C C Manju M. Victor Jose Research Scholar Department of Computer Science and Engineering Noorul Islam Center for Higher Education Kumaracoil Tamilnadu – 629180 India Associate Professor Department of MCA Noorul Islam Center for Higher Education Kumaracoil Tamilnadu – 629180 India

ISBN: (纸本)9781728155241

Classification of Human Epithelial-2 (HEp-2) cell is noteworthy in the analysis of Autoimmune Diseases (AD). In this work, HEp-2 Specimen Image Segmentation and Classification utilizing deep convolution neural network (DCNN) with histogram of oriented gradients (HOG) and Local Binary Pattern (LBP) highlights (HEp2-SIC-DCNN). We proposed to order HEp-2 example pictures. HEp-2 cells are preprocessed to improve the classification exactness. Contrast limited adaptive histogram equalization technique (CLAHE) is used to improve the pixel quality. To extract features, HOG and LBP are considered in the pixel domain. The proposed method can classify different x classes such as homogeneous, speckled, nucleolar, centromere, nuclear membrane and Golgi. To enhance the training process data augmentation is used. Various sets of data are generated by rotating images in different angles to get more sample images. HEp2-SIC-CNN is tested with various images from ICPR 2014 database with various condition such as scale and rotation. Accuracy (MCA) of about 95.56%, which is every much higher compared to previous work related to available ICPR 2014 dataset.

关键词： convolutional neural nets diseases feature extraction image classification image segmentation medical image processing image segmentation Medical image processing LBP gene LBP Image classification Taxonomy Feature extraction maladjustment Dataset images

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Discover the Adaption of Big Data Study in EHR Information

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

作者： R A V Krishna Rao Shaik Razia D. Harita Research Scholar Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Associate Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Profesor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

An adoption of digital health documents has recently developed in fantastic realm. A little vigor our bodies stockpile, cope and route their statistics in force. However, the subsistence of such tremendous and scrupulous unit poses new confront and problems for health professionals. In verity, even though the most essential intention of electronic fitness documentation is to achieve great tribal information from health flow of work data for very general practitioner make the most significant analytical tackle. This is due to more than one building and steps, which definitely discourages them from wanting more and more. We eliminate and accurately discover the appropriate adaptation of analytical tools to electronic records on physical condition to improve their use through the capacity of health professionals. A case study is presented on the discharge approach of EHR based on open fully electronic fitness documentation and appears in the adoption of health analysis.

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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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Coordinate Access System for Live Video Acquisition

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

作者： B. Annapurna T Rama Reddy Ch. V. Raghavendran Raushan Kumar Singh Vedurai Veera Prasad Associate Professor Department of Computer Science and Engineering Aditya College of Engineering Surampalem East Godavari Dt. AP India. Professor Department of Computer Science and Engineering Aditya Engineering College (A) Surampalem East Godavari Dt. AP India Professor Department of Information Technology Aditya College of Engineering and Technology Surampalem East Godavari Dt. AP India Technical Director Spectrum Solutions Pondicherry India Assistant Professor Department of Computer Science and Engineering Aditya College of Engineering Surampalem East Godavari Dt. AP India.

Biometric systems are the most advanced access technology developed so far in the 21st century. It does not even require to carry key cards or passwords in mind. Today most of the commercial and private entries are protected by biometric recognition systems like fingerprint scans facial recognition, retina scans, voice matching, etc. Even our phones, laptops, and daily access devices are equipped with biometric systems. In banks, the PCs are secured by the combination of passwords and fingerprint scans. Biometric scans are considered the most secure access technology so far. Our paper is to examine whether they are secure? Should we rely on them with our hard-earned money and social identity? Is there any way we can use these services without actually compromising our data and security? Our observation is on our digital identity. Promoting digitization in every department brings our topic in the picture. All our information is saved in our phones, our daily routine, whom we talk, what we purchase, whom we chat, where we travel, etc. Almost every smartphone has biometric fingerprint locks which means our phones have our fingerprint scans in database and with internet blend it's tethered worldwide. Our fingerprints are connected to our bank accounts, PAN Cards, Passport, and SIM Cards using Aadhar Cards. If someone has our fingerprint they can easily reach our Aadhar Card and through that to all our personal information. Most of the phone companies are Chinese, Korean, German, and American. As per their country policies, they must share their data with the governing authorities. We aim to create a security system without actually using the biometric scans. The system is an advancement of the biometric system but with better accuracy and intelligence. We interface image acquisition tools to live track the red color things. The web camera or inbuilt system lens can be used as the acquisition system. When the red color object is moved in front of the lens it shows the co

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Novel approach to enhance network security using key performance indicator in business analytics

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IOP Conference Series: Materials science and engineering 2020年第1期992卷

作者： M. Saranya T. P. Anithaashri Assistant Professor Department of Innovative Informatics Institute of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Chennai Tamilnadu India-602105 Associate Professor Department of Innovative Informatics Institute of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Chennai Tamilnadu India-602105

In Recent days, the challenges in Business applications are more in analyzing the complexities of day to day activities. Key execution pointer (KPIs) are business estimations used by corporate bosses and various directors to follow and examine factors thought about noteworthy to the achievement of a Business. Reasonable KPIs base on the business cycles and limits that senior organization sees as commonly huge for assessing progress toward meeting imperative destinations and execution targets. KPIs differ from relationship to affiliation subject to business needs. One of the key display pointers for an open association will likely be its stock expense, while a KPI for a covertly held startup may be the amount of new customers incorporated each quarter. Surely, even direct adversaries in an industry are likely going to screen different plans of KPIs specially designed to their individual business procedures and the leader's strategies for thinking.

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Design of an Infological Model for Prediction of Problems during Drilling Using Machine Learning and Systems Analysis

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IOP Conference Series: Earth and Environmental science 2022年第4期988卷

作者： A L Zolkin V D Munister R V Faizullin N N Smoktal Ph.D. in Engineering Science Senior Lecturer of Computer and Information Sciences Department of the Povolzhskiy State University of Telecommunications and Informatics Department of Mathematical Methods and Computer-Aided Design Private educational institution 'Donetsk Academy of Transport' Department of Enterprise Economics State educational institution of higher professional education 'Donetsk National Technical University' Associate Professor of the Department of Information Technologies in Public Administration Institute of Management Technologies MIREA — Russian technological university Teacher at the Department of 'Renewable Energy Sources and Electrical Systems and Networks' Sevastopol State University

The article deals with the actual problem of identification of probabilistic processes as a result of the operation of drilling rigs in the oil industry. The world experience of finding ways to solve optimal forecasting tools using machine learning is summarized. Mnemonic rule for the implementation of classification and ranking systems in the detection of feedbacks as probable indicators of complications of ongoing technological processes is implemented through the description of the formal model of the drilling process in form of a hidden Markov model. The results of evaluation of the developed mathematical apparatus in the form of predictive analytics and a cut of basic complications in the drilling process are presented. An infological diagram of the developed architectural solution of the analysis project is proposed. The results of the control algorithms formalization are given in conclusion. These results allow to ensure the effective procees modes of equipment operation and make it possible to save electricity and water.

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