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2024 International Conference on engineering and Computing, ICECT 2024

作者： Khan, Shaheryar Hassan Raheel, Aasim Majid, Muhammad Anwar, Syed Muhammad Arsalan, Aamir UET Department of Computer Engineering Taxila Pakistan UET Department of Software Engineering Taxila Pakistan FJWU Department of Software Engineering Rawalpindi Pakistan

ISBN: (纸本)9798350349719

The gaming industry, encompassing both console and mobile platforms, has experienced remarkable growth in recent years. Assessing emotional responses during gameplay presents a significant challenge. This study employs electroen-cephalography (EEG) signals to discern players' emotions while engaged in mobile gaming. Specifically, two popular mobile games, Temple Run and Subway Surfers, were chosen to represent diverse gaming environments. Each game underwent three separate trials, during which EEG data was collected using a commercially available 4-channel MUSE headband. Following each trial, players indicated their emotional state on a 9-point valence and arousal scale. Statistical analysis, including a t-Test, was conducted on the valence and arousal scores for both games, revealing a significant difference in emotional responses (p 0.05). Player data was labeled using the majority voting technique based on the three trials. Features were extracted from both the frequency domain and time domain which were used to classify valence and arousal into two classes using support vector machine (SVM) and k-nearest neighbor (KNN) classifiers. The KNN classifier achieved the highest accuracy rates, with 80.55. © 2024 IEEE.

关键词： Emotion Recognition

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MDEV Model:A Novel Ensemble-Based Transfer Learning Approach for Pneumonia Classification Using CXR Images

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computer Systems Science & engineering 2023年第7期46卷 287-302页

作者： Mehwish Shaikh Isma Farah Siddiqui Qasim Arain Jahwan Koo Mukhtiar Ali Unar Nawab Muhammad Faseeh Qureshi Department of Software Engineering Mehran University of Engineering and TechnologyJamshoroPakistan College of Software Sungkyunkwan UniversitySuwonKorea Department of Computer Systems Mehran University of Engineering and TechnologyJamshoroPakistan Department of Computer Education Sungkyunkwan UniversitySeoulKorea

Pneumonia is a dangerous respiratory disease due to which breathing becomes incredibly difficult and painful;thus,catching it early is *** physicians’time is limited in outdoor situations due to many patients;therefore,automated systems can be a *** input images from the X-ray equipment are also highly unpredictable due to variances in radiologists’***,radiologists require an automated system that can swiftly and accurately detect pneumonic lungs from chest *** medical classifications,deep convolution neural networks are commonly *** research aims to use deep pretrained transfer learning models to accurately categorize CXR images into binary classes,i.e.,Normal and *** MDEV is a proposed novel ensemble approach that concatenates four heterogeneous transfer learning models:Mobile-Net,DenseNet-201,EfficientNet-B0,and VGG-16,which have been finetuned and trained on 5,856 CXR *** evaluation matrices used in this research to contrast different deep transfer learning architectures include precision,accuracy,recall,AUC-roc,and *** model effectively decreases training loss while increasing *** findings conclude that the proposed MDEV model outperformed cutting-edge deep transfer learning models and obtains an overall precision of 92.26%,an accuracy of 92.15%,a recall of 90.90%,an auc-roc score of 90.9%,and f-score of 91.49%with minimal data pre-processing,data augmentation,finetuning and hyperparameter adjustment in classifying Normal and Pneumonia chests.

关键词： Deep transfer learning convolution neural network image processing computer vision ensemble learning pneumonia classification MDEV model

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Enhancing Arabic Cyberbullying Detection with End-to-End Transformer Model

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computer Modeling in engineering & Sciences 2024年第11期141卷 1651-1671页

作者： Mohamed A.Mahdi Suliman Mohamed Fati Mohamed A.G.Hazber Shahanawaj Ahamad Sawsan A.Saad Information and Computer Science Department College of Computer Science and EngineeringUniversity of Ha’ilHa’il55476Saudi Arabia Information Systems Department College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Software Engineering Department College of Computer Science and EngineeringUniversity of Ha’ilHa’il55476Saudi Arabia Computer Engineering Department College of Computer Science and EngineeringUniversity of Ha’ilHa’il55476Saudi Arabia

Cyberbullying,a critical concern for digital safety,necessitates effective linguistic analysis tools that can navigate the complexities of language use in online *** tackle this challenge,our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers(BERT)base model(cased),originally pretrained in *** model is uniquely adapted to recognize the intricate nuances of Arabic online communication,a key aspect often overlooked in conventional cyberbullying detection *** model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media(SM)tweets showing a notable increase in detection accuracy and sensitivity compared to existing *** results on a diverse Arabic dataset collected from the‘X platform’demonstrate a notable increase in detection accuracy and sensitivity compared to existing methods.E-BERT shows a substantial improvement in performance,evidenced by an accuracy of 98.45%,precision of 99.17%,recall of 99.10%,and an F1 score of 99.14%.The proposed E-BERT not only addresses a critical gap in cyberbullying detection in Arabic online forums but also sets a precedent for applying cross-lingual pretrained models in regional language applications,offering a scalable and effective framework for enhancing online safety across Arabic-speaking communities.

关键词： Cyberbullying offensive detection Bidirectional Encoder Representations from the Transformers(BERT) continuous bag of words Social Media natural language processing

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CLIP-Flow:Decoding images encoded in CLIP space

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Computational Visual Media 2024年第6期10卷 1157-1168页

作者： Hao Ma Ming Li Jingyuan Yang Or Patashnik Dani Lischinski Daniel Cohen-Or Hui Huang Visual Computing Research Center College of Computer Science and Software EngineeringShenzhen UniversityShenzhen 518060China Department of Computer Science Tel Aviv UniversityTel Aviv 6997801Israel School of Computer Science and Engineering the Hebrew University of JerusalemJerusalem 91904Israel

This study introduces CLIP-Flow,a novel network for generating images from a given image or *** effectively utilize the rich semantics contained in both modalities,we designed a semantics-guided methodology for image-and text-to-image *** particular,we adopted Contrastive Language-Image Pretraining(CLIP)as an encoder to extract semantics and StyleGAN as a decoder to generate images from such ***,to bridge the embedding space of CLIP and latent space of StyleGAN,real NVP is employed and modified with activation normalization and invertible *** the images and text in CLIP share the same representation space,text prompts can be fed directly into CLIP-Flow to achieve text-to-image *** conducted extensive experiments on several datasets to validate the effectiveness of the proposed image-to-image synthesis *** addition,we tested on the public dataset Multi-Modal CelebA-HQ,for text-to-image *** validated that our approach can generate high-quality text-matching images,and is comparable with state-of-the-art methods,both qualitatively and quantitatively.

关键词： image-to-image text-to-image contrastive language-image pretraining(CLIP) flow StyleGAN

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An infrastructure software perspective toward computation offloading between executable specifications and foundation models

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Science China(Information Sciences) 2025年第4期68卷 380-382页

作者： Dezhi RAN Mengzhou WU Yuan CAO Assaf MARRON David HAREL Tao XIE Key Laboratory of High Confidence Software Technologies (PKU) Ministry of Education School of Computer SciencePeking University School of Electronics Engineering and Computer Science Peking University Department of Computer Science and Applied Mathematics Weizmann Institute of Science

Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theories and methodologies [2]. Instead of replacing existing software modules implemented by symbolic logic, incorporating FMs' capabilities to build software systems requires entirely new modules that leverage the unique capabilities of ***, while FMs excel at handling uncertainty, recognizing patterns, and processing unstructured data, we need new engineering theories that support the paradigm shift from explicitly programming and maintaining user-defined symbolic logic to creating rich, expressive requirements that FMs can accurately perceive and implement.

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A Common Declarative Language for UML State Machine Representation, Model Transformation, and Interoperability of Visualization Tools 1st

A Common Declarative Language for UML State Machine Represe...

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1st International Symposium on software Fault Prevention, Verification, and Validation, SFPVV 2024

作者： Jannatpour, Ali Constantinides, Constantinos Department of Computer Science and Software Engineering Concordia University Montreal Canada

ISBN: (纸本)9789819616206

Originally presented in previous work to capture the set of fundamental elements of the UML state machine specification, Common Declarative Language (CDL) provides a model that can aid in the validation and verification of requirements. In this paper we target two objectives: First, we extend CDL by addressing one of the advanced concepts of the UML state machine specification, namely the notion of orthogonality which allows complex machine behavior through parallel state configurations. Second, we complement previous work by focusing on how CDL can serve as a platform for the representation of a state machine, how the language can be deployed for a model transformation where the initial machine (containing composite and/or orthogonal states) can be flattened into a model whose formal definition we provide, and finally how the CDL can be deployed to support interoperability among text-to-UML drawing tools [11]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Specification languages

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Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

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computers, Materials & Continua 2024年第7期80卷 61-103页

作者： Ahmed Khalid Rana Asif Rehman Byung-Seo Kim Department of Computer Science FAST School of ComputingNational University of Computer and Emerging SciencesLahore54000Pakistan Department of Software and Communications Engineering Hongik UniversitySejong City30016Republic of Korea

Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

关键词： Content centric network Internet of Things mobile ad hoc network named data network vehicular ad hoc network

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Effects of Fast Charging of EV Batteries at Low Temperatures Based on Temporary Lithium Plating and Temperature Gradients

Effects of Fast Charging of EV Batteries at Low Temperatures...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Chetri, Chandan Williamson, Sheldon Group Department of Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798350376067

The study investigates battery degradation under high C-rates and subzero temperatures, analyzing temperature gradients (ΔT/Δt) and differential temperature rises (ΔT) on 21700 lithium nickel cobalt aluminum oxide (NCA) battery. The research findings identifies maximum ΔT at charging rates of 2.5C and 3C, reaching 24.6°C and 29.96°C, respectively, at an ambient temperature of -10°C. At -15°C, charging rate of 2C resulted in ΔT of 20.9°C. Moreover, the voltage dip during fast charging at subzero temperatures increases with lower ambient temperatures and higher C-rates. Comparative analysis underscores anode as the most heated part, exhibiting steeper ΔT/Δt curves. Although the battery management system (BMS) may regulate the total temperature rise within safe operating limits, however, often ΔT/Δt may cause accelerated battery degradation and thermal runaway condition, especially during dynamic charging/discharging conditions. Therefore, it is imperative to monitor battery ΔT/Δt, rather than only ΔT to ensure reduced accelerated degradation and thermal safety. © 2024 IEEE.

关键词： State of charge

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On learning the right attention point for feature enhancement

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Science China(Information Sciences) 2023年第1期66卷 131-143页

作者： Liqiang LIN Pengdi HUANG Chi-Wing FU Kai XU Hao ZHANG Hui HUANG College of Computer Science and Software Engineering Shenzhen University Department of Computer Science and Engineering The Chinese University of Hong Kong School of Computer Science National University of Defense Technology School of Computing Science Simon Fraser University

We present a novel attention-based mechanism to learn enhanced point features for point cloud processing tasks, e.g., classification and segmentation. Unlike prior studies, which were trained to optimize the weights of a pre-selected set of attention points, our approach learns to locate the best attention points to maximize the performance of a specific task, e.g., point cloud classification. Importantly, we advocate the use of single attention point to facilitate semantic understanding in point feature learning. Specifically,we formulate a new and simple convolution, which combines convolutional features from an input point and its corresponding learned attention point(LAP). Our attention mechanism can be easily incorporated into state-of-the-art point cloud classification and segmentation networks. Extensive experiments on common benchmarks, such as Model Net40, Shape Net Part, and S3DIS, all demonstrate that our LAP-enabled networks consistently outperform the respective original networks, as well as other competitive alternatives, which employ multiple attention points, either pre-selected or learned under our LAP framework.

关键词： point convolution feature enhancement attention point deep neural network

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Identifying patients in need of psychological treatment with language representation models

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Multimedia Tools and Applications 2025年第1期84卷 397-418页

作者： Aygün, İrfan Kaya, Buket Kaya, Mehmet Department of Software Engineering Celal Bayar University Manisa Turkey Department of Electronics and Automation Fırat University Elazig Turkey Department of Computer Engineering Fırat University Elazig Turkey

Early diagnosis of psychological disorders is very important for patients to regain their health. Research shows that many patients do not realize that they have a psychological disorder or apply to different departments for treatment. The detection of hidden psychological disorders in patients will both increase the quality of life of patients and reduce the traffic of patients who apply to the wrong department. This study aimed to determine whether patients who consult a physician for any reason need psychological treatment. For this purpose, the relationships, and similarities between the sentences of previous psychiatric patients and the sentences of newly arrived patients were analyzed. Domain-based trained ELECTRA language model was used to detect sentence similarities semantically. In the study, the dialogues of patients with physicians in 92 different specialties were analyzed using the MedDialog dataset, which consists of online physician applications, and the DAIC-WOZ dataset. As a result of the experiments, 90.49% success was achieved for the MedDialog dataset and 89.36% for the DAIC-WOZ dataset. With the proposed model, patients in need of psychological treatment were identified and the medical departments where psychological problems were revealed the most were determined. These divisions are Neurology, Sexology, Cardiology, and Plastic Surgery, respectively. With the findings obtained, complications caused by psychological problems and types of diseases that are precursors to psychological disorders were determined. To the best of our knowledge, this article is the first study that aims to analyze all psychological illness instead of focusing on any of the psychological problems (depression, OCD, schizophrenia, etc.) and validated by electronic health records. © The Author(s) 2024.

关键词： Diseases

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