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共 19843 条记录，以下是371-380 订阅

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Design and Implementation of a Comprehensive Intelligent E-Learning Systems Integrated Web App Solution For Dyslexic Students

Design and Implementation of a Comprehensive Intelligent E-L...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Deepalakshmi, R. Shanthalakshmi Revathy, J. Revathy, S.P. Kousika, N. Dept of Computer Science Velammal College of Engineering and Technology Tamil Nadu India Dept of Information Technology Velammal Engineering College Tamil Nadu India Dept of Computer Science Sri Krishna College of Engineering and Technology Tamil Nadu India

ISBN: (纸本)9798350305708

The prevalent learning disorder, dyslexia impair a person's capacity for reading, writing, and spelling. But with the aid of successful interventions like multisensory techniques, phonics training, and assistive technology, persons with dyslexia can improve their reading and writing skills and excel in school and in daily life. This research paper "Dyslexi Duo" is a comprehensive solution for dyslexic students in all age group and includes 3 major sections. A Super Pad for the age group >18 to help them read digital documents like pdf with ease. An Interactive & Educational game -Hydra Hunt for the age group of 4-10 to learn formation of words with letters using both visual & auditory techniques. This game incorporates 4 key elements: storyline, clear goals, multiple levels, and points. An attached mobile application "Alpha360" for the age group of 3-8, which is an interactive multimedia learning app using 3d viewing, TextToSpeech, SpeechToText technology & a multisensory approach. This entire application was tested & evaluated with dyslexic students of the corresponding age group. Overall, our application can be a one stop solution to help dyslexic students overcome theirchallenges at an earlier age and achieve academic success. © 2023 IEEE.

关键词： 3d Viewing Dyslexia Interactive multimedia learning app Multisensory methods Text To Speech

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A Novel Dual Channel Isolated Current Source Gate Driver for Fast Switching MOSFETs 50

A Novel Dual Channel Isolated Current Source Gate Driver for...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Elahi, Asjad Youssef, Mohamed Dept. of Electrical Computer and Software Engineering University of Ontario Institute of Technology OshawaON Canada

ISBN: (纸本)9781665464543

A new dual-channel discontinuous mode isolated current source gate driver (ICSGD) is proposed in this paper. The proposed gate driver can provide two isolated gate drive signals for two power MOSFETs in circuits where these switches are in sync. The proposed gate driver can achieve very fast turn on and turn off transitions, due to its current mode nature. In addition, this technique can achieve partial gate energy recovery by recovering a fraction of the RMS (CV2) energy, which is typically dissipated over the gate drive resistors in voltage source gate drive (VSGD) techniques. Thus, provides better efficiency. The proposed circuit consists of six transistors and a small pulse transformer to allow swift operation over a wide range of duty cycles. Current through the transformer is discontinuous to avoid conduction losses due to circulating currents such as in some resonant gate drivers (RGD). Consequently, the proposed ICSGD provides superior performance over its VSGD counterparts, especially in high-frequency (HF) operation. The design is implemented in both PSIM and Typhoon HIL (hardware in the loop) platforms. The model is verified with a match of results from PSIM and Typhoon. The PSIM & HIL results show that the ICSGD achieves a minimum of 20% efficiency improvement. © 2024 IEEE.

关键词： High frequency transformers

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Evaluating the Performance of Machine Learning Models in Handwritten Signature Verification

Evaluating the Performance of Machine Learning Models in Han...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Akter, Tahmina Akter, Mst. Sharmin Mahmud, Tanjim Chakma, Rishita Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350361537

Handwritten signatures remain a widely used method for personal authentication in various official documents, including bank checks and legal papers. The verification process is often labor-intensive and time-consuming, necessitating the development of efficient methods. This study evaluates the performance of machine learning models in handwritten signature verification using the ICDAR 2011 Signature and CEDAR datasets. The investigation involves preprocessing, feature extraction using CNN architectures, and optimization techniques. The most effective models undergo a rigorous evaluation process, followed by classification using supervised ML algorithms, such as linear SVM, random forest, logistic regression, and polynomial SVM. The results indicate that the VGG16 architecture, optimized with the Adam optimizer, achieves the satisfactory performance metrics. This study demonstrates the potential of ML methodologies to enhance the efficiency and accuracy of signature verification, offering a robust solution for document authentication. © 2024 IEEE.

关键词： Decision trees

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Strategies for Helping Anchor-Based Trackers Learn re-ID Features for Smart City Surveillance

Strategies for Helping Anchor-Based Trackers Learn re-ID Fea...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Chen, Xiu-Zhi Li, Mu-Chuan Chen, Yen-Lin National Taipei University of Technology Dept. of Computer Science & Information Engineering Taipei Taiwan

ISBN: (纸本)9798350324136

Re-identification has become a crucial issue in computer vision today as it allows for tracking objects in both continuous and discontinuous scenarios. Despite achieving perfect detection results, anchor-based trackers encountered difficulties in effectively learning re-identification features, due to various issues. This research proposes strategies aimed at improving the capability of anchor-based trackers to learn high-quality re-identification (re-ID) features. The model developed through our strategies can extract more distinct features and achieve almost 0.57 Multiple Object Tracking Accuracy (MOTA) on MOT20, even under a limited training dataset. This result indicates that our proposed strategies hold potential for improving the performance of anchor-based trackers. © 2024 IEEE.

关键词： Anchor-Based Tracker Re-Identification Smart City Surveillance

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An Effective Way to Detect Phishing Website Using Machine Learning 6

An Effective Way to Detect Phishing Website Using Machine Le...

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6th International Conference on Electrical engineering and Information and Communication technology, ICEEICT 2024

作者： Toyeer-E-Ferdoush Shorab, Mst. Sumaiya Ritu, Saima Akter International University of Business Agriculture and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350385779

In today's interconnected digital landscape, phishing represents a significant threat to both individuals and organizations. Phishers cleverly utilize deceptive techniques to extract sensitive information from unsuspecting users, posing a risk to critical account details. Despite various proposed methods to detect phishing websites, the adaptability of phishers continually challenges the efficacy of existing approaches. Recognizing the vital role of Machine Learning (ML) in combating these evolving threats, this research investigates the application of ML techniques. Common characteristics in phishing attacks can be identified through accurate ML analysis. This research employs a range of ML models and transformer models, including Catboost (Cat), XGBoost (XGB), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), TabNet, K-nearest neighbor (KNN), and Logistic Regression (LR) with grid-search. Among these models, the Catboost classifier achieved a remarkable accuracy of 97%. This study shows dedication to utilizing diverse methodologies to advance the field of phishing website detection. © 2024 IEEE.

关键词： Decision trees

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Twitter Scraping and Sentiment Analysis on Stock Price

Twitter Scraping and Sentiment Analysis on Stock Price

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Iniyan, S. Thangakumar, J. Rajendran, P. Selvi Hindustan Institute Of Science And Technology Dept. Of Computer Science And Engineering Chennai603103 India

ISBN: (纸本)9798350364828

social media is useful in the community for sharing and discussing various events with others. The study's main objective is to predict the sign of the stock by sentimental analysis regarding the Hindenburg report on Adani group stocks by obtaining tweets from Twitter. The study's findings will aid in understanding the effect of the Hindenburg report on the stocks of the Adani group. Excel files are downloaded from Twitter containing tweets from social media users. Tweets are cleaned up by eliminating noise data after extraction. Machine learning algorithms, such as Logistic Regression (LR), Linear support classification (SVC), Random Forest (RF), and voting, were used to classify the data into positive, Neutral, and negative groups. © 2024 IEEE.

关键词： Logistic regression

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Enhancing Decentralized Finance for Scalability, Interoperability, and User Experience 8

Enhancing Decentralized Finance for Scalability, Interoperab...

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8th IEEE International Conference on Computational System and Information technology for Sustainable Solutions, CSITSS 2024

作者： Nalini, N. Rao, Vishak Rao, Karthik Shobha, P. Nitte Meenakshi Institute of Technology Dept. of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798331505462

This research explores Decentralized Finance (DeFi) through the lens of enhanced applications, introducing the concept of Decentralized Finance Enhanced (DeFine). It examines the transformative potential of DeFi, analyzing its evolution and the innovative solutions driving its progress. The objective is to investigate how DeFine addresses scalability, interoperability, security, and user experience challenges in the DeFi ecosystem. Through case studies and analysis, this proposed work provides insights into the implications, opportunities, and risks associated with the adoption and maturation of DeFi enhancements. © 2024 IEEE.

关键词： Decentralized finance

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HAR-CLET: A Novel Conv-LSTM with Extra Tree Classifier for Human Activity Recognition

HAR-CLET: A Novel Conv-LSTM with Extra Tree Classifier for H...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Choudhury, Nurul Amin Soni, Badal National Institute of Technology Silchar Dept. of Computer Science and Engineering Assam Silchar India

ISBN: (纸本)9798350350821

In this paper, we propose a novel ensemble of Convolutional Neural Network-Long Short-Term Memory with an Extra Tree Classifier for automatic feature engineering in the spatiotemporal domain and classification of different human activities collected using inbuilt smartphone sensors. Prominent sensor-based HAR systems are trained and validated in extracted features of datasets collected in a controlled and simulated environment, which can adversely impact the reliability in real-world scenarios. Our approach utilizes unsimulated data from diverse users collected using inbuilt smartphone sensors in real world environment. Also, the proposed model was effectively trained and tested with multiple standard public datasets for validation and benchmarking with diverse evaluation metrics. With effective parameter tuning and lightweight feature extraction architecture, the proposed model achieved an average performance accuracy of 99 % with their own generated dataset, mHealth and MotionSense dataset, in comparatively optimized computational time compared to the benchmark models. © 2024 IEEE.

关键词： Convolutional neural networks

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LSTM Based Approach to Detect Fake News 2

LSTM Based Approach to Detect Fake News

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Khare, Sakhi Singh, Pushpa Kumar, Pankaj Gl Bajaj Institute of Technology Dept. of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350371055

In the age of technology, every day, we ingest a variety of news data, either willingly or accidentally. People will always use various social media apps and keep looking for information. The information passed through these social media apps is only sometimes valid. Many organizations or individuals spread the news to influence the mass public. This type of information is called fake news. Fake news is a common problem that naturally comes with social media. Detection of counterfeit news with ubiquitous data from social media is almost impossible. Fake news kills real journalism and spreads false information in society. Researchers are still looking for better solutions. In this paper, we find a better solution with Natural Language Processing (NLP). We used fake news challenge datasets for training and testing purposes. We aim to classify the news item into four stance labels: agree, disagree, discuss, and unrelated. We developed a Long Short-Term Memory (LSTM) based solution to organize the news article in the given stance label. We find that our approach classifies data effectively with 99% of accuracy © 2024 IEEE.

关键词： Fake News LSTM NLP Word Embedding

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Project Management and Evaluation system Using Node JS 3

Project Management and Evaluation system Using Node JS

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Kumar, Sanjay Umrao, Sandhya Gupta, Harsha Saxena, Kumud Greater Noida Institute of Technology Dept. of Computer Science Engineering Greater Noida India Noida Institute of Engineering and Technology Dept. of Computer Science Engineering Greater Noida India Noida Institute of Engineering and Technology Dept. of Information Technology Greater Noida India

ISBN: (纸本)9798350399264

Project Management is a social hub for students to interact and showcase their projects in a dynamic environment where other students and faculty can also put their thoughts. Major Project is the essential part of student's graduation, where they need to apply all the learning and build something innovative and inspiring. Students don't understand that what other students are developing because of no interaction. Thus with the help of this application, it is tried to solve this problem. An application is proposed to address about how student can go through an application to identify their capabilities and get an idea to develop a project accordingly. Students will be able to address a problem and find a solution to it, although through its inception organizing major projects can be a hassle therefore It is aptly called "Project Management"as students can join in a league with like-minded students for their major projects. Depending on factors like area of interest, the number of milestones covered and the grade received, the live popularity project tracking system provides a highly-standardized, automated technique for ranking. Top 10 projects are displayed on the homepage based on these *** are two key features in PMi)User Interactionii)Project Progress Tracking. © 2023 IEEE.

关键词： Students

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