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Innovative Communication Solutions for Specially-Abled Individuals: A Machine Learning-Approach to EEG Interpretation

Innovative Communication Solutions for Specially-Abled Indiv...

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international conference on computer Applications In Electrical Engineering-Recent advances (CERA)

作者： Anikait thakur G J Girish Krithik K Vani K Kapilash Saumarghya Ray S Parthasarathy Department of Computer Science and Engineering PSG College of Technology Coimbatore Tamil Nadu India

In this study, the use of electroencephalography (EEG) as a brain-computer interface (BCI) for people with communication difficulties is being investigated. the study aims to decode EEG data into words, providing an alternative means of communication for patients with ailments like ALS, stroke, or any physical brain injuries. Raw data were preprocessed, and features were extracted using 24 signal features to convert continuous time-series data to discrete features for word classification. Out of the total features, feature selection was performed using two techniques: K -best features using ANOVA f-score and recursive feature elimination using an SVM kernel. then various machine learning and deep learning techniques were used to analyse the data to classify the intended communication activities from the EEG signals. the results concluded by providing the best interclass accuracy of 46.10% using a multi-layered perceptron model with selected 200 features using recursive feature elimination. the findings of this research will aid in creating more effective and convenient BCI systems that can enhance the quality of life for individuals with communication disabilities.

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SSNTech2@LT-EDI-RANLP-2023: Homophobia/Transphobia Detection in Social Media Comments Using Linear Classification Techniques 3

SSNTech2@LT-EDI-RANLP-2023: Homophobia/Transphobia Detection...

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3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

作者： Vaidhegi, D. Priya, M. Rajalakshmi, S. Angel Deborah, S. Mirnalinee, T.T. Department of Computer Science and Engineering Sri Sivasubramaniya Nadar College of Engineering Tamil Nadu Chennai603110 India

ISBN: (纸本)9789544520847

the abusive content on social media networks is causing destructive effects on the mental well-being of online users. Homophobia refers to the fear, negative attitudes and feeling towards homosexuality. Transphobia refers to negative attitudes, hatred and prejudice towards transsexual people. Even though, some parts of the society have started to accept homosexuality and transsexuality, there are still a large set of the population opposing it. Hate speech targeting LGBTQ+ individuals, known as homophobia/transphobia speech, has become a growing concern. this has led to a toxic and unwelcoming environment for LGBTQ+ people on online platforms. this poses a significant societal issue, hindering the progress of equality, diversity, and inclusion. the identification of homophobic and transphobic comments on social media platforms plays a crucial role in creating a safer environment for all social media users. In order to accomplish this, we built a ML model using SGD and SVM classifier. Our approach yielded promising results, with a weighted F1-score of 0.95 on the English dataset and we secured 4th rank in this task. © 2023 LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th international conference on Recent advances in Natural Language Processing, RANLP 2023 - Proceedings. All rights reserved.

关键词： Support vector machines

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Free-Hand-Sketched Logic Circuit Detection Using Vision Transformers

Free-Hand-Sketched Logic Circuit Detection Using Vision Tran...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Noha Aly EIMasry Mohamed Waleed Fakhr Fahima A. Maghraby Department of Computer Science Arab Academy for Science Technology and Maritime Transport Cairo Egypt Faculty of Computer Science Misr International University Cairo Egypt Department of Computer Engineering Arab Academy for Science Technology and Maritime Transport Cairo Egypt

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

this paper investigates the application of Vision Transformers (ViTs), specifically DETR (DEtection TRans-former), for the detection and classification of digital logic gates in hand-sketched digital logic circuits (DLC). A novel dataset of 295 hand-sketched DLC images was developed, capturing all seven fundamental gate types: AND, OR, NOT, NAND, NOR, XOR, and XNOR. the dataset introduces real-world complexities, such as variations in sketching styles, pen types, and paper textures, therefore addressing gaps in existing datasets. the performance of DETR is compared with the state-of-the-art YOLOv8 model under various preprocessing configurations, including grayscale conversion and image resizing. the results show that YOLO achieves higher overall detection accuracy, while DETR demon-strates strengths in capturing spatial relationships and complex patterns in abstract sketches. Additionally, the study analyses the effects of training duration and dataset structure on performance, highlighting the sensitivity of ViTs to preprocessing and spatial feature preservation. this work advances the understanding of transformer-based models for DLC recognition, advancing the way for more effective automated tools in engineering and education.

关键词： YOLO Training computer vision Power engineering Accuracy Sensitivity Logic circuits Logic gates Transformers Integrated circuit modeling

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An Empirical Analysis of Different Classifiers on COVID-19 Vaccination Data 7th

An Empirical Analysis of Different Classifiers on COVID-19 V...

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7th international conference on Information and Communication technology for Competitive Strategies, ICTCS 2022

作者： Ningombam, Sonithoi Roy, Arindam Debnath, Pradip Department of Computer Science Assam University Assam Silchar India Department of Applied Science and Humanities Assam University Assam Silchar India

ISBN: (纸本)9789811993039

During the COVID-19 pandemic, there are no other ways to communicate the whole world rather than connected through social media especially Twitter platform to share information. It is challenging to read through and comprehend everything that has been posted on Twitter about the COVID-19 vaccines. It is a fortunate that many advances such as machine learning (ML) methods and natural language processing (NLP) techniques are used to analyze the tweet, and we can observe the sentiments of the tweets that will reduce the human effort and could easily be classified tweets into their respective classes. In this study, we focus specifically on tweets about COVID-19 vaccination which have been gathered between March and April of 2022. We aim to explore the overall sentiments relative to COVID-19 vaccination, inclusive of how the sentiments are mainly concerns and evolved. To perform the empirical analysis, we use five machine learning classifiers, viz. decision tree, support vector machine (SVM), K-nearest neighbor (KNN), logistic regression, and Naïve Bayes classifiers and bidirectional encoder representations from transformers (BERT) model on the collected dataset. Among competent approaches, sentiment analysis based on the BERT model gives the highest accuracy. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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A Comparative Study of Brain Tumor Detection using Convolutional Neural Networks with MRI Images

A Comparative Study of Brain Tumor Detection using Convoluti...

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international conference on Information technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Jonayet Miah Md Maruf Hasan Ashiqul Haque Ahmed Eftekhar Hossain Ayon Duc M Ca Tahera Koli Department of Computer Science University Of South Dakota South Dakota USA Economics & Decision Science University of South Dakota South Dakota USA Department of Computer & Info Science Gannon University Erie Pennsylvania USA Department of Economics University of Tennessee Knoxville TN USA

this research emphasizes the global health challenge of brain tumors and emphasizes the importance of early detection using Convolutional Neural Networks (CNNs) on Magnetic Resonance Imaging (MRI). the dataset, including healthy and tumor MRI scans, underwent careful processing for CNN input. With a SoftMax Fully Connected layer, the CNN achieved 98% accuracy, outperforming Radial Basis Function (RBF) and Decision Tree (DT) classifiers. Feature extraction through clustering improved CNN accuracy, with the SoftMax classifier reaching 99.52% on test data. the study advances deep learning in medical image analysis, highlighting CNN-MRI synergy for precise brain tumor detection and potential advancements in early treatment and patient care.

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File Classification Containing Secret Key in Git Repository Using Character Level CNN and Shannon Entropy 4th

File Classification Containing Secret Key in Git Repository ...

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4th international conference on advances in Computational science and Engineering, ICACSE 2023

作者： Muhammad, Rafie Musdholifah, Aina Master Program in Computer Science FMIPA UGM Yogyakarta Indonesia Department of Computer Science and Electronics FMIPA UGM Yogyakarta Indonesia

ISBN: (纸本)9789819729760

Current technological developments are directly proportional to the number of information technology projects made. this project is usually in the form of a program formed from a code. To facilitate version control and contributions between developers, git tools are usually used which are placed on an online platform such as Github. If a repository on an online platform contains sensitive information such as secret key variables and the repository can be accessed by the public, then this can be used to harm the company or organization that owns the repository. Several ways have been done before to detect this secret key variable by using the regex method and using machine learning to minimize false positive results. In this research, we will try to build a text or file classification model that contains secret key variables using the character level CNN and Shannon entropy. the Shannon entropy algorithm is used during pre-processing to retrieve the group of words with the largest entropy value and the CNN character level will be used because it is considered suitable for this case since the value of the secret key is abstract and does not require a sequence context for the said secret key in a file. the results of this study were able to obtain an accuracy value of 96.1% for the accuracy value for the classification of files containing secret key. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Character level CNN Git repository Secret key Shannon entropy Text classification

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Design and Development of SEMS - An IoT-based Smart Environment Monitoring System

Design and Development of SEMS - An IoT-based Smart Environm...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Mohammed Fahim Hasan Sharif Md. Ataur Rahman Abbas Ali Khan Mohammad Monirul Islam Md. Tarek Habib Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh

the twenty-first century is known as the "Age of science and technology". By believing in the potential of technology to improve lives, people gain new experiences and come up with innovative innovations in response to how the global environment is changing as technology advances. With each passing day, the environment in our living space undergoes continuous changes. To address the crisis, a budget-friendly and beneficial environment monitoring system for the classroom was devised. this is an Internet of things (IoT)-based initiative. To create a classroom monitoring system dubbed "IoT-Based Smart Environment Monitoring System," where Multi-purpose sensors, NodeMCU, a display, an alarm, Firebase, and IoT technology were employed. An Android-based user interface was developed for monitoring real-time temperature, humidity, gas, smoke, and other parameters. thus, LPG gas, smoke, NH4, temperature, and humidity are detected and/or measured simultaneously with a user-friendly interface and a cheap cost.

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Tunable Sparing of Disks in a Cloud Data Center

Tunable Sparing of Disks in a Cloud Data Center

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international conference on computer Applications In Electrical Engineering-Recent advances (CERA)

作者： Rohit Malawat Shrey Modi Rahul Vishwakarma Department of Material science and Metallurgy Indian Institute of Technology Roorkee Roorkee India Department of Computer Engineering & Computer Science California State University Long beach Long Beach USA Department of Computer Engineering & Computer Science California State Uni. Long Beach Long Beach CA USA

Disk Drive failure tolerance and optimum utilization of disks for storage are two of the most important challenges in the Cloud based data center. Addressing both these problems simultaneously can be tricky. To make the system failure tolerant, more storage needs to be added; this results in redundancy of storage. Providing a safety net for the disk is important to make sure that the disk can still operate. therefore, we propose a novel drive sparing mechanism which not only provides failure tolerance by maintaining the optimal number of spare drives in the storage system, but also deals with over-provisioned spare. the method first identifies the critical disks that may fail in the RAID group based on the Venn-ABERS framework which helps us to know about the conditional probability of the disk failure, and then implements a variable sparing mechanism where a few disks act as dual-purpose disks. We demonstrate variable sparing using two cases, first when minimum spare pool is sufficient, and second, when minimum spare pool is not sufficient for failure tolerance. By proactively addressing potential failure points, the drives are able to extend their lifespan and enhance reliability when the variable sparing is utilized. In this paper, we explain the mechanism of variable sparing of disks and share results of an evaluation experiment using an open-source dataset by utilizing our prototype system.

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Application Controlling Using Hand Gestures through Yolov5s 8th

Application Controlling Using Hand Gestures Through Yolov5s

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8th international conference on computers, Management and Mathematical sciences, ICCM 2022

作者： Rajendra Prasad, K. Tarun Naga Sai, Chadaram Bhaskar Ganesh, Guntuboina Rohini Raghavi, Baina Sri Saketh, Gunnam Computer Science Engineering Gitam School of Technology Gandhi Institute of Technology and Management Gitam Visakhapatnam India

ISBN: (纸本)9783031511660

With the aid of Python, OpenCV, Yolov5s, and PyAutoGui, we attempt to use hand gestures for controlling an application. the need for unfettered interaction has made it difficult for conventional input devices like the keyboard and mouse to be used. In linguistics, gestures with the hand are a crucial part of body language (Nagalapuram GD, Roopashree S, Varshashree D, Dheeraj D, Nazareth DJ, Controlling media player with hand gestures using convolutional neural network. In: 2021 IEEE Mysore sub section international conference (MysuruCon). 978-1-6654-3888-9/21/$31.00 ©2021 IEEE, https://***/10.1109/MYSURUCON52639.2021.9641567, 2021). Using the hand as a device makes it simple to interface with humans and computers. It would be intriguing to engage with machines using hand gestures (Li G, Li D, Yang A, Real-time hand gesture detection based on Yolov5s. In: Proceedings of the 41st Chinese control conference, July 25–27, Hefei, China, 2022). Different applications, Various software programs, including Media Player, PowerPoint, PDF viewers, and software that accepts keyboard and mouse input, are controlled by hand gestures. Interaction is simple, practical, and requires no tedious additional equipment when gestures are used (Paliwal M, Sharma G, Nath D, Rathore A, Mishra H, Mondal S, A dynamic hand gesture recognition system for controlling VLC media player. In: 2013 international conference on advances in technology and engineering (ICATE). IEEE, 2013). A camera-based hand detection system that employs a live webcam stream to identify the gesture once it has been observed. this system gives the user access to essential keyboard functions with the aid of the PyAutoGui package. With this technology, we can increase the usability of computers for people with mobility issues or who cannot have physical contact with peripherals. A deep learning algorithm called Yolov5s is used for object detection. the precision and recall are near to 1, the mAP (0.5) value for hand gest

关键词： Deep learning

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Integration of Blockchain and Fog Computing—A Review 5th

Integration of Blockchain and Fog Computing—A Review

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5th international conference on advances in Information Communication technology and Computing, AICTC 2024

作者： Kaur, Nirbeh Kumar, Shubham Kumar, Ritik Ranjana, Khushi Anand, Kumar Abhishek Gupta, Shailendra Kumar Department of Computer Science and Engineering Chandigarh University Punjab Mohali India Department of Electrical Engineering Chandigarh University Punjab Mohali India

ISBN: (纸本)9789819761050

"Integration of blockchain and fog computing" involves the two different concepts, i.e. blockchain technology and fog computing which has something in common—the decentralised system. the rapid advancement of technologies all over the world has put some threats to the data and information along with its development. the fog computing concept was put forward to enhance cloud computing applications in handling the IoT data. Fog computing, on the other hand, faces a number of difficulties, including storage, privacy, and security. Integration of blockchain with fog computing is the main approach which can help in overcoming these difficulties. Several researches are being done for integrating blockchain with fog computing in the field of health care, smart home, smart cities, IoT applications, drones network, mobile devices, transportation, financial, supply chain management, and many more. this research paper is a review study of relevant papers published on this topic already and gives an insight of the applications of integration of blockchain and fog computing. Our review paper has a systematic study of existing literature on this topic, and it provides an excellent overview of all the concepts that will play a crucial role for the researchers in their future studies. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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