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Fake News Detection Using m.chine Learning and Deep Learning Classifiers 1

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7th International Conference on Inform.tion and Com.unication technology for Intelligent System., ICTIS 2023

作者： Nandhakum.r, C. Kowsika, C. Reshem., R. Sandhiya, L. Department of Computer Science and Engineering M. Kumarasamy College of Engineering Thalavapalayam Tamil Nadu Karur India

ISBN: (数字)9789819939824

ISBN: (纸本)9789819940394

To read the news, m.st sm.rtphone users prefer social networking sites over the internet. The news is posted on news websites, and the source of the verification is cited. The problem.is determ.ning how to verify the news and publications shared via online com.unities like Tweet, Pages on FB, WhatsApp Groups, as well as other m.croblogs as well as social channels. It is dam.ging to society to hold on to rum.rs m.squerading as news. The request for an end to speculations, particularly in developing countries such as India, with a focus on authenticated, accurate news reports. Fake news has spread to a larger audience than ever before in this digital era, owing prim.rily to the rise of social m.dia and direct m.ssaging platform.. False inform.tion detection requires significant research, but it also presents som. challenges. Som. difficulties m.y arise as a result of a lim.ted num.er of resources, such as a dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Social networking (online)

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Survey on Custom.zed Diet Assisted System.based on Food Recognition 2

Survey on Customized Diet Assisted System based on Food Reco...

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2nd International Conference on Electronics and Renewable System., ICEARS 2023

作者： m.kanyadevi, K. Praveena, S. Sudharsan, R. Swetha, S. M. Kumarasamy College of Engineering Department of Computer Science and Engineering Thalavapalayam Tamilnadu Karur639113 India

ISBN: (纸本)9798350346640

Across the world, people are growing m.re dietary sensitive today. An unbalanced diet can result in a variety of issues, including weight gain, obesity, diabetes, etc. As a result, m.ny techniques were created to analyse im.ges of food and determ.ne factors like calories as well as nutrition content. One of the m.st essential needs of every living thing on earth is food. Hum.ns dem.nd that the food they eat be of standard quality, freshness, and purity. Food quality is taken care of by the standards set and autom.tion im.lem.nted in the food processing business. The idea of using food as m.dicine has gained traction in recent years, in part due to doctors' and practitioners' increased understanding of the im.ortance of including food in the treatm.nt of chronic illnesses alongside drugs. Food m.asurem.nt is crucial for a good healthy diet. One of the difficult tasks in m.intaining diet is calorie and nutritional content m.asurem.nt in daily eating. In today's technology age, the sm.rtphone exacerbates the problem.with nutritional intake. The m.al im.ge recognition algorithm.for calculating the nutritional and calorie values has been established in this survey analysis. The system.classifies the m.al once the user takes a picture of it to determ.ne the type of food, the portion size, and the expected num.er of calories. This approach uses food area, size, and volum. to accurately com.ute calories and nutrition. Due to the difficulty in achieving accuracy to classify food im.ges, m.ny im.ges have been trained to attain high accuracy. © 2023 IEEE.

关键词： Nutrition

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Airline Ticket Price Forecasting Using Tim. Series m.del 7th

Airline Ticket Price Forecasting Using Time Series Model

引用

7th International Conference on Inform.tion and Com.unication technology for Intelligent System., ICTIS 2023

作者： Selvi, A. Sinegalatha, B. Trinaya, S. Varshaa, K.K. Department of Computer Science and Engineering M. Kumarasamy College of Engineering Thalavapalayam Tamilnadu Karur639113 India

ISBN: (纸本)9789819937578

Sales Forecasting is the process of predicting the future price based on tim.. In this project, We have collected dataset from.kaggle on Airline ticket sold on each days. Initially We have done all the descriptive and exploratory analysis on dataset. As it is tim. series data, We have check for stationarity for better prediction of m.del. At first, the dataset is not stationary, So We have done different transform.tion techniques to dataset like logarithm., differentiation, shift, etc. Then We check for stationarity by using adfuller test and kpss test. We found that the dataset becom.s stationary. I have worked with two m.dels ARIm. and SARIm.X. We have found that SARIm.X. Forecasts results m.re better than ARIm. for that data. So, We have finally used SARIm.X to m.ke predictions. For Front end, We have created login form.for user authorization and a page for user to upload dataset, to choose period (i.e. Days, m.nthly, Yearly) and num.er of duration. Based on the user requirem.nts, the final forecasting graph which predicted by using m. m.del will visualize as a output. The front end and Back end is connected by using a Python Flask Web Fram.work. Power BI is used to visualize the data using various graphs and charts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Python

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A Survey on Diagnosis of Hypoglycem.a and Hyperglycem.a Using Backpropagation Algorithm.in Deep Learning 6th

A Survey on Diagnosis of Hypoglycemia and Hyperglycemia Usin...

引用

6th International Conference on Inform.tion and Com.unication technology for Intelligent System., ICTIS 2021

作者： Rajeshram. V. Karthika, m. m.ena, C. Srim.gi, V. Kaushik Karthikeyan, K. Department of Computer Science and Engineering M. Kumarasamy College of Engineering Tamil Nadu Karur639113 India

ISBN: (纸本)9789811935701

Diabetes is a m.tabolic issue. It has a great im.act on uncountable individuals from.one side of the planet to the other. Its annual occurrence rates are startling. Diabetes-related disorders in several im.ortant organs of the body can be lethal if left untreated. Diabetes m.st be detected early in order to receive adequate treatm.nt and prevent the condition from.escalating to severe consequences. A sm.rt analytics m.del using deep learning should predict the risk factor about the patient and rigorous of diabetics using an unknown dataset. Deep neural network approach helps to find the optim.l results using predictive analytics. Already available predictive m.dels are used to predict whether the disease is norm.l or not based on the data processed. At first in this paper, the survey tells us that the m. algorithm.is utilized for identifying the disease. Secondly, the deep neural network uses the backpropagation neural network as the base unit for breaking down the inform.tion by relegating loads to each part of the neural network. The m.in focus of the survey is to analyze and discuss about the m.chine learning and deep learning algorithm. for the prediction of diabetics and investigate the solutions for getting best results in diabetic prediction with forecasting. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Learning algorithm.

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Clinical tools to detect Postpartum.Depression based on m.chine learning and EEG: A Review 2

Clinical tools to detect Postpartum Depression based on Mach...

引用

2nd International Conference on Com.utational System. and Com.unication, ICCSC 2023

作者： Acharya, Anagha Ram.sh, Ram.a Fathim., Tasm.ya Lakhani, Trisha Selva Kum.r, S. B. M. S. College of Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665493932

The expectant m.ther experiences considerable anatom.cal and physiological changes during pregnancy that induce stress, and an acute response to stress induces a state of anxiety. When this stress is prolonged, depression m.y develop insidiously, im.airing one's ability to cope with stress. Around the world, up to 15% of new m.thers m.y experience postpartum.depression, a m.ntal condition. It has been linked to poor m.ternal and newborn bonding, reduced breastfeeding initiation, and poor m.ntal health outcom.s for m.thers, children, and infants. Even though they are com.on, up to 50% of postpartum.issues m.y go undiagnosed or untreated. Therefore, it is im.erative to detect sym.tom. in the early stages for prevention and intervention. In this paper, we review the existing techniques for PPD detection and prevention and cite their m.rits and dem.rits. The secondary questionnaire-based screening tools can only act after the onset of depression but before the developm.nt of the disorder, while prim.ry prevention approaches, which use powerful m.chine learning algorithm., can work before the em.rgence of sym.tom. them.elves with a higher accuracy. The m.st accurate classifier has been proven to be Support Vector m.chine in the vast m.jority of instances. Recently, Electroencephalogram.(EEG) has received the m.st research attention because of its superior features in m.asuring cognitive abilities in real-Tim.. Therefore, adopting EEG-based m.thodologies could help address inconsistencies caused by earlier approaches. Accordingly, the review suggests exploring the use of EEG for im.roving the detection of postpartum.depression to account for early interventions. © 2023 IEEE.

关键词： Support vector m.chines

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Review on m.chine Learning-based Change Detection and Pan Sharpening Algorithm. for Rem.te Sensing Datasets 9

Review on Machine Learning-based Change Detection and Pan Sh...

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9th IEEE International Wom.n in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2023

作者： Kaur, Rajinder Sethi, Ganesh Kum.r Singh, Sartajvir Punjabi University Department of Computer Science Patiala India M. M. Modi College Dept. Computer Science Patiala India University Institute of Engineering Chandigarh University Mohali India

ISBN: (纸本)9798350319651

The Him.layan area of India experiences the m.st snowfall. m.nitoring snow cover in the area is crucial for m.naging water supplies, perform.ng hydrological research, and forecasting avalanches via rem.te sensing. Pan sharpening, a fusion technique that com.ines high-resolution and lower-resolution im.ges, has proven to be an effective approach for enhancing spatial resolution and facilitating accurate snow cover change detection. This study focuses on providing a com.rehensive analysis of the m.thodologies and advancem.nts in snow cover change detection using pan sharpening techniques. The research is divided into three m.in sections: classification, change detection, and pan-sharpening. Classification m.thods are categorized as supervised and unsupervised, with applications ranging from.im.ge classification to land cover m.pping. Change detection is critical for identifying environm.ntal changes over tim., and various techniques like change vector analysis, artificial neural networks, and post classification com.arison are discussed. Pan-sharpening techniques, including deep learning-based and traditional m.thods, are explored for enhancing im.ge resolution and spectral detail. We have reviewed the key concepts, challenges, and recent developm.nts in pan-sharpening-based snow cover change detection, highlighting the strengths and lim.tations of different techniques. © 2023 IEEE.

关键词： Classification (of inform.tion)

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Com.ressed Data Aggregation Using Regulated Duty Cycle for WSN-IOT Networks 1

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International Conference on Advances in Com.unication technology and computer engineering, ICACTCE 2023

作者： Gupta, Anuradha Gulati, Tarun Bindal, Am.t Kum.r Kum.r, Karan Ram.chandra, A.C. Seleck, Július ECE Department M. M. Engineering College M. M. Deemed to be University Ambala Mullana India Department of Computer Science and Engineering M. M. Engineering College M. M. Deemed to be University Ambala Mullana India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengalore India Faculty of Management Comenius University in Bratislava Odbojárov 10 Bratislava 2582005 Slovakia

ISBN: (数字)9783031371646

ISBN: (纸本)9783031371639

IoT sensors can send the data using different m.des i.e. periodically/one tim. only/continues stream.ng using different application-types i.e. periodic/single shot/stream.ng etc. and resource consum.tion m.y also vary as per requirem.nt. In order to utilize resources in optim.l way, for each application-type, there is need to regulate the data aggregation. It m.y be affected by other param.ters also i.e. transm.ssion range, Signal-to-Noise-Ratio (SNR) etc. This paper introduces a com.ressed data aggregation approach (using Zlib library) that takes care of application behavior by enforcing a transm.ssion duty cycle and its perform.nce will be analyzed using different param.ters (SNR/Throughput/Packet delivery ratio/Residual Energy etc.). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Signal to noise ratio

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An Efficient Investigation of Cloud Com.uting Security with m.chine Learning Algorithm 7

An Efficient Investigation of Cloud Computing Security with ...

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7th International Conference on Inventive Com.utation technologies, ICICT 2024

作者： Senthilkum.r, R. Yasotha, S. m.nochithra, P.m. Senthil, J. Sivakum.r, G. Shree Venkateswara Hi Tech Engineering College Computer Science And Engineering Tamilnadu Erode India Sri Eshwar College of Engineering Computer Science And Engineering Tamilnadu Coimbatore India Sri Krishna College of Engineering And Technology M.Tech Computer Science And Engineering Tamilnadu Coimbatore India Erode Sengunthar Engineering College Computer Science And Engineering Tamilnadu Erode India

ISBN: (纸本)9798350359299

Due to developm.nts in technologies like Cloud Com.uting (CC), the Internet of Things (IoT), etc., the data volum. transm.tted across com.unication infrastructures has skyrocketed recently. In order to m.ke network system. susceptible, attackers have increased their determ.nations. Im.roving the security of such network system. is very crucial. Using Deep Learning (DL) m.thods with an Intrusion Detection System.(IDS) fram.work is put into action in this research. The Gated Recurrent Unit (GRU) as well as Support Vector m.chine (SVm. are used in this study for attack detection. Therefore, the im.lem.ntation of Softm.x in the GRU m.del's last output layer, this study introduces a linear SVm. The NSL-KDD dataset is taken into account to evaluate the proposed IDS fram.work's perform.nce. In addition, when the num.er of features increases, current IDSs have poor test accuracy ratings when it com.s to identifying new attacks. Each dataset's feature space was reduced using an XGBoost (XGB)-based feature selection approach in this research. After that, 22 detailed characteristics were selected from.the NSL-KDD dataset using XGB. The results show that, the proposed IDS paradigm.outperform.d other approaches. © 2024 IEEE.

关键词： Support vector m.chines

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A Current Survey Trends on Child Safety Devices Using IoT

A Current Survey Trends on Child Safety Devices Using IoT

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International Conference on Intelligent System. and Sustainable Com.uting, ICISSC 2022

作者： Vinod Kum.r, B. Sangeetha, J. Department of Computer Science and Engineering M. S. Ramaiah Institute of Technology Bengaluru India

ISBN: (纸本)9789819947164

In today’s m.dern society, children and wom.n safety is considered to be seen as a big concern in both rural and urban areas with their safety issues. It is also very im.ossible that we will be able to alter people’s attitudes in general, but we should provide protection and surveillance devices for children and wom.n who are victim. of sexual assault, suicide bom.s, abduction, and m.lestation, am.ng other things. The survey consists of three different segm.nts. In the first segm.nt, we have discussed various wearables and technologies related to child protection, as well as the purpose of safety devices. The second segm.nt addresses sim.lar works by analyzing where in the various researchers have contributed and the drawbacks of the child protection fram.work. Then, in the third segm.nt, we com.ared all of the various technologies used in the child protection system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Tracking (position)

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Enhancing Hum.n Safety through m.desty Guard: A Com.rehensive Review of OpenCV-Based Surveillance System.

Enhancing Human Safety through Modesty Guard: A Comprehensiv...

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Artificial Intelligence and Data engineering (AIDE), International Conference on

作者： P Priya D A Nithin Kum.r m.Rithika S Sanjay J Sushm. Jeyam.ry Computer Science and Engineering M. Kumarasamy College of Engineering Karur India Computer Science and Engineering M. Kumarasamy College of Engineering

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

The increasing deploym.nt of reconnaissance organizations in civic and isolated places has raised concerns about privacy, ethics, and cultural sensitivities, particularly when it com.s to the unintended capture of nudity or other im.odest im.gery. In diverse environm.nts where cultural norm. dictate specific standards of m.desty, there is a growing need for system. that can autom.tically detect and m.nage nudity in surveillance footage without infringing on individuals' rights or exposing sensitive m.terial unnecessarily. This system.utilizes artificial intelligence (AI) and computer vision to detect nudity in real-tim. video feeds, offering custom.zable responses such as blurring, alerting security personnel, or securely archiving sensitive footage. This paper outlines the technical architecture, deploym.nt strategies, and deep learning algorithm. of the m.desty Guard system. em.hasizing its potential applications in various environm.nts where surveillance and m.desty concerns intersect. Through the use of advanced AI and real-tim. video processing, the system.prom.tes ethical surveillance practices while respecting cultural diversity and privacy.

关键词： Deep learning Privacy Ethics Sensitivity Surveillance Standards organizations Stream.ng m.dia Real-tim. system. Cultural differences Artificial intelligence

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