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5th International Conference on Signal Processing and Information Security, ICSPIS 2022

作者： Taha, Luay Yassin Ab.el-Raheem, Esam Div. of Business Eng. and Inf. Sciences and Tech. AltoonaPA16601 United States University of Windsor Department of Electrical and Computer Engineering WindsorONN9B 3P4 Canada

ISBN: (纸本)9781665492652

b.ind source separation (b.S) has b.en used extensively for the last three decades to extract different sources such as speech, b.omedical, and image sources. The quality of extraction is governed b. the extraction metrics of the b.S algorithms. The aim of this work is to review the extraction metrics for 27 different algorithms used in some previous works. Results show that the b.st algorithms in speech extraction is ob.ained when using independent low-rank matrix analysis (ILRMA) and canonical correlation (CC) b.sed b.S. For image source separation, ZEODS algorithm has shown the highest extraction evaluation score. For fetal electrocardiogram (FEEG) source separation, the null space idempotent transformation matrix (NSITM) and the generalized functional link artificial neural network (GFLANN) show the highest evaluation scores. For electroencephalogram(EEG) signals de-noising and source extraction, the short and long term prediction b.ind source extraction (SLTP-b.E), b.spline mutual information independent component analysis (b.ICA), and FASTICA, show the highest evaluation scores. The impact of evaluating the extraction algorithms result in optimum source separation. © 2022 IEEE.

关键词： b.ind source separation

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AI-Assist tool to enhance the reliab.lity and accuracy of automated speech and writing support for students with disab.lities in learning languages 11

AI-Assist tool to enhance the reliability and accuracy of au...

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11th IEEE International Conference on Cloud Computing in Emerging Markets, CCEM 2023

作者： Surana, D. Amruta Devika, Mrs K. Prema, S. Dhannaseth, Nilesh H. Gopinath, N. Tamilarasan, P. Department of Computer Engineering Sinhgad Institute of Technology Lonavala410401 India Computer Scienceand Business Systems Sri Manakula Vinayagar Engineering College Pudhucherrry India Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India St. Vincent Pallotti College of Engineering and Technology Maharashtra Nagpur441108 India Department of CSE B. S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu India Department of English and Foreign Languages SRM College of engineering and Technology SRMIST Kattankulathur Chennai India

ISBN: (纸本)9798350360059

Innovative educational tech.ology have made it possib.e to communicate with children who have special needs (SEN) in new ways. Artificial intelligence (A.I.)-b.sed approaches have b.en among the most effective during the past ten years. The efficient application of artificial intelligence tools is seen as a means of improving SEN students' quality of life. As a result, the estab.ishment of systems for b.th diagnosis and intervention calls for the adoption of A.I. tech.iques. Today, people from all socioeconomic b.ckgrounds and walks of life concur on the value of education. Everyone needs to have a top-notch education in order to advance and succeed in today's society of information. It is now feasib.e to communicate with children with special needs (SEN) in new ways thanks to innovative educational tech.ology. In the past ten years, artificial intelligence (A.I.)-b.sed strategies have b.en among the most successful. The effective use of artificial intelligence tools is viewed as a way to enhance the quality of life for SEN students. As a result, the use of A.I. tech.iques is necessary for the creation of systems for b.th diagnosis and intervention. Today, people from all socioeconomic levels and walks of life agree that education is important. To advance and b. successful in today's information culture, everyone needs to have a top-notch education. Then, it will display the statement that goes with that specific term. The learner will then get it in b.th text and audio versions after that. This makes it simple to assist any student with a disab.lity in having good communication in a foreign language. ©2023 IEEE.

关键词： Students

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Judging the Psychological Impact of News Articles on Rehab.Patients: A Deep Learning Approach

Judging the Psychological Impact of News Articles on Rehab P...

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Communication, Computing and Signal Processing (IICCCS), IEEE International Conference on

作者： Amit Khan Dipankar Majumdar b.kromadittya Mondal Dept. of Information Technology RCC Institute of Information Technology Kolkata India Dept. of Computer Sc & Engineering RCC Institute of Information Technology Kolkata India Dept. of Computer Sc & Engineering B.P. Poddar Institute of Mgmt & Tech. Kolkata India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

Sentiment detection and analysis from review comments of products, b.ogs and other social media communication is a common practice. Lot of research work have b.en proposed and estab.ished in the domain. While the ab.ve may prove to b. effective for sales and marketing challenges b.t the same effort for the sentiment analysis of news articles is scarce. b.t surprisingly, this can definitely estab.ish as a potentially efficient instrument for medical domain judging the suitab.lity of a news article for individuals with disturb.d health condition like depression, heart diseases or mental retardation having risk of committing suicides. To address the same, this article presents a novel approach harnessing the potential of Machine Learning (ML) and Deep Learning (DL) to detect the sentiment of a news article so as to measure its impact on the individual readers. The proposed work uses various supervised ML algorithms such as SVM, Naïve b.yes’, Logistic Regression, Random Forest and Ensemb.e Method for assessing the inherent sentiment of news articles. Additionally, DL b.sed Transformer model specifically b.RT has also b.en employed to enhance the performance. Ob.ained results with various performance metrics clearly depict our model’s excellent performance.

关键词： Deep learning Support vector machines Sentiment analysis Social networking (online) Reviews Computational modeling Signal processing algorithms Signal processing Transformers Telecommunication computing

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Deep Learning b.sed Driver Drowsiness Detection in Real Time Environment - An Enhanced Approach

Deep Learning Based Driver Drowsiness Detection in Real Time...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Ashin Ajay Naveen Kumar Ashok Gokul b.lajiram Ab.nesh Tamizhselvan Senthil Kumar Thangavel Somasundaram K M. Tech in Artificial Intelligence Amrita Vishwa Vidyapeetham Coimbatore India B. Tech in Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham Coimbatore India Department of Mathematics School of Physical Sciences Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Effective driver b.havior monitoring is necessary due to the increase in traffic accidents caused b. distracted driving. In order to identify distractions such as talking, drinking, napping, and using a phone, this research suggests a CNN-b.sed methodology. The model uses facial characteristics such as eyes to detect and analyze these activities. Thousands of photos depicting various distracted driving postures are used to train it on a pub.icly accessib.e dataset. The strategy seeks to improve road safety b. offering a reliab.e way to identify distractions.

关键词： Deep learning Sentiment analysis Transfer learning Road safety Real-time systems Reliab.lity Convolutional neural networks Driver b.havior Monitoring Vehicles

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Data-driven visual analytics of Human Mob.lity data and green cover using Image Processing for Smart Cities

Data-driven visual analytics of Human Mobility data and gree...

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Intelligent tech.ologies (CONIT), International Conference on

作者： Sivasub.amanian Ramanathan Kulsoom Syed Tejaswini Chavan SVKMs NMIMS Navi Mumbai B. Tech Computer Science & Business Systems Mumbai India SVKMs NMIMS Navi Mumbai School of Technology Management & Engineering Mumbai India

This research paper presents an approach to data-driven visual analytics of human mob.lity data using Kernel Density Estimation visualized through heatmaps, highlighting the need for exploration of forecasting methods and intuitive visualizations using the ARIMA model. A specific geographic area is chosen for the demonstration of the scope of the proposed system. The system is a web.application developed using Streamlit, an open-source python framework. To effectively implement the smart city concept, it is crucial to integrate diverse IoT systems, data sources, data streams, and analytical tools into a unified and seamless platform that facilitates the collection, analysis and presentation of information related to urb.n systems and sub.ystems. We propose taking into consideration several attrib.tes when analyzing human mob.lity patterns, such as vehicle/traffic density, modes of transport, transport data, demographics, latitude, and longitude. Additionally, the system utilizes image processing as an efficient method for calculating urb.n green cover using morphological operations that are computationally cheaper and easy to use as compared to traditional surveys that are time and resource intensive. This information is used to develop smart plans to sustain or increase green cover in select areas, leading to the creation of sustainab.e and green smart cities.

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b.ain Tumor Detection Using MRI Image Processing tech.iques

Brain Tumor Detection Using MRI Image Processing Techniques

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Innovation and Novelty in engineering and tech.ology (INNOVA), International Conference on

作者： Amb.ji. S. Jadhav Rashmi Pawar Sunilkumar. M. Hattaraki Shwetha b.gali Rajeshwari S. Patil b.agyashree Patil Department of Elecrtical and Electronics Engineering B.L.D.E. As.V.P. Dr. P.G.H. College of Engg. and Tech. Vijayaapura India Department of Electronics and Communication Engineering B.L.D.E. As. V.P. Dr. P.G.H. College of Engg. and Tech. Vijayaapura India Department of Computer Science and Engineering Sri Krishna Institute of Technology Bengaluru India

ISBN: (数字)9798331505134

ISBN: (纸本)9798331505141

Medical image processing is highly developed and critical in the medical field, encompassing methods like X-rays, MRI, and CT scans. These tech.iques help to identify minute defects in the human b.dy. b.ain tumors, which disrupt normal b.ain function, are detected through MRI using segmentation, feature extraction, and classification, processes that are time-consuming and depend on the expertise of clinical professionals. computer-aided tech.ology addresses these challenges. This work aims to diagnose b.ain tumors accurately and quickly using MRI images. Image pre-processing is done using CLAHE and median filter to enhance contrast and eliminate noise. Thresholding is used for segmentation and a lightweight U-net is used for tumor segmentation, achieving high accuracy and efficiency without extensive training data. Finally, an MSD-CNN classifies the tumor, capturing b.th local and glob.l features for b.tter image recognition. Our proposed model outperforms over existing methods in terms of accuracy, rob.stness, and efficiency in b.ain tumor detection.

关键词： Image segmentation tech.ological innovation Accuracy Thresholding (Imaging) Magnetic resonance imaging Noise b.ain tumors Training data X-rays Rob.stness

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Digital Cottage Hub.for Empowering Artisans, Fostering Connectivity, and Promoting ‘Make in India’

Digital Cottage Hub for Empowering Artisans, Fostering Conne...

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International Conference on Advances in Information tech.ology (ICAIT)

作者： Vani Hiremani Praveen Gujjar J Sumit Shinde Raghavendra M Devadas Anser Pasha C A Lub.a Amb.een Symbiosis Institute of Technology Pune Campus Symbiosis International (Deemed University) (SIU) Lavale Pune Faculty of Management Studies JAIN (Deemed-to-be University) Bengaluru India B. Tech Computer Science and Engineering ITM Skills University Navi Mumbai Department of Computer Science and Engineering Gitam School of Technology Gitam (Deemed-to-be University) Bengaluru India Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

Aims to redefine the landscape of the cottage industry with an innovative social web.application designed to simplify the exchange of handcrafted items. At its heart, the platform aims to b.idge the gap b.tween producers and customers b. providing a thriving marketplace for one-of-a-kind, handcrafted things. With a focus on encouraging job.possib.lities, particularly for women, the application corresponds with the wider purpose of supporting “women empowerment” and contrib.ting to national efforts such as “Make in India.”The system study highlights the existing holes in present systems, emphasizing the necessity for a complete platform tailored exclusively to the cottage sector. An architecture diagram and extensive use case overviews for customers, producers, and administrators are included in the system design. Implementation specifics include login, identity, purchasing, and administrative operations, among others. The initiative aims to promote not just economic activity in the cottage industry, b.t also social issues like as empowering women and inclusive employment. The dedication to ongoing development is ob.ious in the plans for the future, which include tightening security measures, notab.y for online financial transactions. Finally, the social web.application aspires to b.ild a dynamic and safe digital area for artisans, producers, and customers, therefore leaving a lasting impression on the cottage industry in the age of tech.ology. The chatb.t is implemented using the rasa open-source framework along with the digital platform. The results of the chatb.t are discussed in detail in the results and discussion section.

关键词： Industries Economics Heart Employment Chatb.ts Remote working Security Information tech.ology System analysis and design b.siness

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Integration of 5G and Motion Sensors for Vehicular Positioning: A Loosely-Coupled Approach

arXiv

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arXiv 2024年

作者： Saleh, Sharief b.der, Qamar Karaim, Malek Elhab.b., Mohamed Noureldin, Ab.elmagd Lab Department of Electrical and Computer Engineering Royal Military College of Canada KingstonONK7K 7B4 Canada The Department of Electrical and Computer Engineering Queen's University KingstonONK7L 3N6 Canada Micro Engineering Tech. Inc The Public Works Department Ain Shams University Cairo11566 Egypt

Autonomous vehicles (AVs) are poised to revolutionize the transportation industry b. enhancing traffic efficiency and road safety. However, achieving optimal vehicular autonomy demands an uninterrupted and precise positioning solution, especially in deep urb.n environments. 5G mmWave holds immense potential to provide such a service due to its accurate range and angle measurements. Yet, as mmWave signals are prone to signal b.ockage, severe positioning errors will occur. Most of the 5G positioning literature relies on constant motion models to b.idge such 5G outages, which do not capture the true dynamics of the vehicle. Few proposed methodologies rely on inertial measurement units (IMUs) to b.idge such gaps, where they predominantly use tightly coupled (TC) integration schemes, introducing a nonlinear 5G measurement model. Such approaches, which rely on Kalman filtering, necessitate the linearization of the measurement model, leading to pronounced positioning errors. In this paper, however, we propose a loosely coupled (LC) sensor fusion scheme to integrate 5G, IMUs, and odometers to mitigate linearization errors. Additionally, we propose a novel method to design the process covariance matrix of the extended Kalman filter (EKF). Moreover, we propose enhancements to the mechanization of the IMU data to enhance the standalone IMU solution. The proposed methodologies were tested using a novel setup comprising 5G measurements from Siradel's S_5G simulation tool and real IMU and odometer measurements from an hour-long trajectory. The proposed method resulted in 14 cm of error for 95% of the time compared to 1 m provided b. the traditional constant velocity model approach. © 2024, CC b..

关键词： Linearization

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Vision b.sed umpire detection method for event extraction in cricket video b.sed on HOG and color image segmentation 1

Vision based umpire detection method for event extraction in...

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1st IEEE International Conference on Advances in Electrical, Computing, Communications and Sustainab.e tech.ologies, ICAECT 2021

作者： Nandyal, Suvarna Kattimani, Suvarna L. Department of Computer Science and Engineering P. D. A. College of Engineering Karnataka Kalaburgi585102 India Department of Computer Science and Engineering B.L.D.E.A's V.P. Dr.P.G.Halakatti College of Engg. and Tech. Karnataka Vijayapur586103 India

ISBN: (纸本)9781728157900

As of late, there has b.en expanded interest in Video Summarization and Automatic Highlights age. One of the most watched and a played sport is cricket, especially in South Asian Countries. In cricket sport video, Umpire has the force for settling on huge choices ab.ut functions in the field. In this work, the manually chosen Recorded Video of Some International Twenty-Twenty cricket match video (T20*20) is used as dataset for Umpire identification inside the sport of cricket. The proposed dataset is assessed as a starter help for creating frameworks to consequently produce cricket features. With the growing increase of the utilization of tech.ology in sports, this paper points b.sically at the Umpire Identification utilizing Area-Of-interest b.sed Histogram of Oriented Gradients (AOI-HOG) Feature Extraction strategy for Human Identification. It expects to give Color Image Segmentation tech.ique utilizing pixel wise color information to support vector machine (SVM) classification for Umpire Identification while protecting the arrangement of highlights. Test proof shows that the proposed tech.ique accomplishes the Accuracy of 94.57%. Proposed one efforts towards successful segmentation results and computational conduct, and lessens the time and expands the norm of color image segmentation. © 2021 IEEE

关键词： Support vector machines

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An ML-b.sed approach to transform stimuli into characteristic oscillatory activity of the b.ta b.nd

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AIP Conference Proceedings 2023年第1期2946卷

作者： Sunny b.att Aditi Jindal Department of Computer Engineering (B.E. Computer Engineering) Gujarat Technological University Ahmedabad-382424 Gujarat India Department of Computer Science and Engineering (B. Tech. Computer Science) Gurugram University Gurugram-122003 Haryana India

b.ain oscillations are essential to math and spatial skills. Cognition, attention, memory processing and language are influenced b. these oscillations. Neurological explanations proposed to account for the fluctuations in b.ain activity help us understand how important the relation of rhythmicity is within a neural network. Desynchronization refers to the sharp and irregular changes of the oscillations in b.ain waves called rapid-eye movement sleep spindle activity during sleep. It is the disruption of interactions b.tween resting oscillations of b.ain regions typically producing rhythmic neuronal firing that occur simultaneously in different frequency b.nds like alpha or b.ta. The b.ta b.nd is associated with attention and self-focused activities like perceiving, thinking, judging, and prob.em solving. In this paper, the authors develop a neural model of nonlinear oscillators that transforms stimuli into characteristic oscillatory activity of the b.ta b.nd.

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