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Optimal Quad Channel Long Short-Term Memory Based Fake News Classification on English Corpus

Computer Systems Science & Engineering 2023年第9期46卷 3303-3319页

作者： Manar Ahmed Hamza Hala J.Alshahrani Khaled Tarmissi Ayman Yafoz Amal S.Mehanna Ishfaq Yaseen Amgad Atta Abdelmageed Mohamed I.Eldesouki Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The term‘corpus’refers to a huge volume of structured datasets containing machine-readable *** texts are generated in a natural communicative *** explosion of social media permitted individuals to spread data with minimal examination and filters *** to this,the old problem of fake news has *** has become an important concern due to its negative impact on the *** manage the spread of fake news,automatic recognition approaches have been investigated earlier using Artificial Intelligence(AI)and Machine Learning(ML)*** perform the medicinal text classification tasks,the ML approaches were applied,and they performed quite ***,a huge effort is required from the human side to generate the labelled training *** recent progress of the Deep Learning(DL)methods seems to be a promising solution to tackle difficult types of Natural Language Processing(NLP)tasks,especially fake news *** unlock social media data,an automatic text classifier is highly helpful in the domain of *** current research article focuses on the design of the Optimal Quad ChannelHybrid Long Short-Term Memory-based Fake News Classification(QCLSTM-FNC)*** presented QCLSTM-FNC approach aims to identify and differentiate fake news from actual *** attain this,the proposed QCLSTM-FNC approach follows two methods such as the pre-processing data method and the Glovebased word embedding ***,the QCLSTM model is utilized for *** boost the classification results of the QCLSTM model,a Quasi-Oppositional Sandpiper Optimization(QOSPO)algorithm is utilized to fine-tune the *** proposed QCLSTM-FNC approach was experimentally validated against a benchmark *** QCLSTMFNC approach successfully outperformed all other existing DL models under different measures.

关键词： English corpus fake news detection social media natural language processing artificial intelligence deep learning

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Effects of natural-based SiO2 nanocoolant on car radiator: Thermal profile

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Materials Today: Proceedings 2022年 66卷 2734-2737页

作者： Ruey Ong, Huei Mohd Eqhwan Iskandar, Wan Yapp Joo, Ming Rahman Khan, Md. Maksudur Khairul Anuar Mohamed, Muhammad Faculty of Engineering & Technology DRB-HICOM University of Automotive Malaysia Peramu Jaya Industrial Area Pekan Pahang 26607 Malaysia Department of Chemical Engineering College of Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Kuantan Pahang 26300 Malaysia Centre for Mathematical Sciences College of Computing & Applied Sciences Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang Pahang 26300 Malaysia

Nanofluid as a transport medium has a great deal of potential in heat transfer engineering applications. In this work, nanosilica was derived from natural sources, rice husk through incineration and chemical treatment process. Various SiO2 nanoparticle volume concentrations (0–1 vol%) were dispersed in EG/water binary mixture assisted by ultrasound technique to produce SiO2 nanocoolant. Scanning Electron Microscopy (SEM) was used to identify the surface morphology and size of the nanosilica. Furhermore, the study was further conducted in a car radiator to determine the thermal profile consists of the effect of nanoparticle concentration and the longevity testing of the nanocoolant. Findings show that nanosilica particles were in range of 15–25 nm with irregular shape. Moreover, the heat transfer performance was enhanced as the SiO2 concentration was increased. Apart from that, SiO2 1 vol% shows a great thermal behaviour as it takes a shorter time to achieve and maintain at optimal working temperature compared to other samples. Apart from that, it can be observed that SiO2 nanocoolant possesses slightly higher properties than the base fluid and conventional coolant. The results also revealed the average heat transfer coefficient is directly proportional to the volume concentration of nanofluids and the heat transfer performance of the radiator increased with the inclusion of nanoparticles to the base fluid. © 2022

关键词： Scanning electron microscopy

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GA-Net: Gated Attention Mechanism Based Global Refinement Network for Image Inpainting 29

GA-Net: Gated Attention Mechanism Based Global Refinement Ne...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Qiu, Ran Zhao, Shengrong Liang, Hu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350330717

Underwater images are often affected by problems such as light attenuation, color distortion, noise and scattering, resulting in image defects. A novel image inpainting method is proposed to intelligently predict and fill damaged areas for complete and continuous visualization of the image. First, in order to effectively solve the problem of color distortion caused by light refraction in underwater environments, the improved gated attention mechanism is used. This mechanism improves the local details by learning and weighting the important features of the image. Second, gated convolution automatically determines the degree of restoration for each pixel based on local features of the original image. It eliminates distractions such as low contrast and scattering, retaining more original detailed information. By doing so, image inpainting techniques improve the quality and visualization of underwater images. © 2023 IEEE.

关键词： Gated convolution Image inpainting Underwater images

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Software for the quantification of glistenings in intra-ocular lenses

Software for the quantification of glistenings in intra-ocul...

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World Congress on Engineering, WCE 2014

作者： Japunya, Teeranoot Jitpakdee, Parisut Uyyanonvara, Bunyarit Aimmanee, Pakinee Philippaki, Eva Hull, Chris Barman, Sarah Sirindhom International Institute of Technology Thammasat University Thailand Sirindhom International Institute of Technology Thammasat University Thailand Applied Vision Research Centre School of Health Sciences City University London Northampton Square United Kingdom Digital Imaging Research Centre Faculty of Science Engineering and Computing Kingston University Penrhyn Road United Kingdom

ISBN: (纸本)9789881925275

An intraocular lens (IOL) is implanted in the eye after a cataract surgery. When an IOL is in an aqueous environment, glistenings that are fluid-filled microvacuoles are often observed. Previously, studies of glistenings involved tedious work of manual glistenings labeling and rough estimation of glistening distribution. This paper proposes a software that can be used for automatic glistenings detection. The software evaluates glistenings appearance in a lens, separating the IOL lens into 3 zones and accurately computingthe average area, density and distribution to assist the user. The results are compared with clinicians hand-drawn ground truth for validation. The proposed GUI front-end is easy to use and very suitable for users who want accurate and quick glistenings detection. Numerical results can be achieved without manual drawing and rough estimation.

关键词： Intraocular lenses

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Legacy Moderization: A Cloud Migration Strategy With Serverless Microservice Architecture

Legacy Moderization: A Cloud Migration Strategy With Serverl...

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Intelligent computing and Control (IC&C), International Conference on

作者： Qi Zhi Ang Peter ChunYu Yau Chin Sean Sum Qi Cao Dennis Wong School of Computing Science University of Glasgow United Kingdom Singapore Institute of Technology Singapore Faculty of Applied Sciences Macao Polytechnic University China

This paper provides an overview, presents the work-in-progress study of how software architecture can be modernized using the latest technologies. We will discuss the reasons why software modernization is required, how to choose an optimal solution from the architecture perspective, related migration strategy and the related points to note. The paper will also discuss some of the common issues faced while reviewing the architecture. These issues would provide some insights to some frequently faced problems in development and deployment. Finally, a discussion on how containerization technology and load balancer could help in resolving some of the common issues faced. In this paper, we have evaluated our proposed approach in a realistic case study involving an actual organization, which was anonymized for identity protection A certain organization would be used to provide the corresponding review mentioned.

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A Netnographic-Based Semantic Analysis of Tweet Contents for Stress Management

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Computers, Materials & Continua 2022年第1期70卷 1845-1856页

作者： Jari Jussila Eman Alkhammash Norah Saleh Alghamdi Prashanth Madhala Mohammad Ayoub Khan HAMK Smart Research Unit Häme University of Applied SciencesHämeenlinna13100Finland Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Computer and Information Sciences Princess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Faculty of Management and Business Tampere UniversityTampere33720Finland College of Computing and Information Technologies University of BishaBisha67714Saudi Arabia

Social media platforms provide new value for markets and research *** article explores the use of social media data to enhance customer value *** case study involves a company that develops wearable Internet of Things(IoT)devices and services for stress *** and semantic annotation for recognizing and categorizing the context of tweets are conducted to gain a better understanding of users’stress management *** aim is to analyze the tweets about stress management practices and to identify the context from the ***,we map the tweets on pleasure and arousal to elicit customer *** analyzed a case study of a marketing strategy on the Twitter *** in the marketing campaign shared photos and texts about their stress management *** learning techniques were used to evaluate and estimate the emotions and contexts of the tweets posted by the campaign *** computational semantic analysis of the tweets was compared to the text analysis of the *** content analysis of only tweet images resulted in 96%accuracy in detecting tweet context,while that of the textual content of tweets yielded an accuracy of 91%.Semantic tagging by Ontotext was able to detect correct tweet context with an accuracy of 50%.

关键词： Social media stress semantic analysis Twitter context recognition

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Two dynamical models for male infertility and their stability and sensitivity analysis

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Scientific Reports 2025年第1期15卷 1-23页

作者： Somaye Ghiasi Hafezi Mahdi Ranjbar Sohrab Effati Atena Ghasemabadi Alvand Naserghandi Farzad Allameh Kosar Namakin Biostatistics School of Health Mashhad University of Medical Sciences Mashhad Iran Department of Applied Mathematics Faculty of Mathematical Science Ferdowsi University of Mashhad Mashhad Iran Center of Excellence of Soft Computing and Intelligent Information Processing (SCIIP) Ferdowsi University of Mashhad Mashhad Iran Esfarayen University of Technology Esfarayen North Khorasan Iran Men’s Health & Reproductive Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Student Research Committee Shahid Beheshti University of Medical Sciences Tehran Iran

Mathematical models can estimate the success rate of assisted reproductive technology (ART) and determine which treatment suits the best. In this study, the authors introduce two new dynamic models that can predict the success rate of ART models for each individual based on the etiology of their infertility, clinical findings, and lab tests. The study shows that the equilibrium point free of disease is asymptotically stable and forward bifurcation occurs. Our dynamical models evaluate ART success rates in our subgroups considering couples under Intrauterine insemination (IUI), In Vitro Fertilization–Embryo Transfer (IVF), Intra–Cytoplasmic Sperm Injection (ICSI) treatment methods. Sensitivity analysis of parameters suggests that an increase in infertile couples who use IUI and ICSI treatment methods can result in better disease control and a more favorable outcome. It should be noted that the proposed models provide a systematic framework for simulating the dynamics of infertility and assessing the effectiveness of various ART. From a clinical perspective, these models have the potential to enhance decision-making by predicting the probability of ART success under diverse treatment scenarios. Such predictions may facilitate the personalization of treatment strategies based on individual patient profiles and contribute to more efficient resource allocation and planning within fertility centers.

关键词： Asymptotically stable Dynamical models Forward bifurcation Male infertility

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A spatial indexing structure based on object partition_ br-tree

A spatial indexing structure based on object partition_ br-t...

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Run-Tao Liu Zhong-Xiao Hao Institute of Information and Scientific Computing Technology College of Applied Science Harbin University of Science and Technology Harbin China Faculty of Computer Science Harbin University of Science and Technology Harbin China

In this paper, an index structure - BR-tree for spatial data , is proposed by combining the division for spatial data objects with bi-tree. In the structure, the topological relations between spatial data objects are recorded and the overlap between brother nodes is as small as possible. And the algorithm for constructing the BR-tree is presented and its time complexity is given. Finally, the algorithms for node insertion and range query are obtained.

关键词： Indexing Spatial databases Database systems Shape Wavelet analysis Pattern analysis Pattern recognition Environmental management Information analysis

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Neural network apply to predict aircraft trajectory for conflict resolution

Neural network apply to predict aircraft trajectory for conf...

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International Conference on Intelligent Systems: Theories and Applications (SITA)

作者： R. Kaidi M. Lazaar M. Ettaouil Faculty of Science and Technology Modeling and Scientific Computing Laboratory Fez MOROCCO National School of Applied Sciences Abdelmalek Essaadi University Tetouan MOROCCO

Today, Air Traffic keep increasing, for this raison, many research programs focus on collision avoidance technique. Aircraft trajectory prediction is a critical issue for Air Traffic Management (ATM). A safe and efficient prediction is a prerequisite for the implementation of automated tools that detect and solve conflicts between trajectories. Moreover, regarding the safety constraints, it could be more reasonable to predict intervals rather than precise aircraft positions. This paper a twofold objective; the first one, we develop an approach based on Artificial Neural Networks (ANNs), called Optimization of Multilayer Perceptron Architecture (OMPA), the second one, we use this approach to forecast trajectory in vertical plane to solve conflicts between two aircrafts in airspace.

关键词： Atmospheric modeling Nonhomogeneous media Neurons Aircraft Multilayer perceptrons Trajectory

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Fabrication and characterization of biological biosensors in sports injury treatment: High sensitivity of silver oxide using artificial neural network modeling

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Engineering Applications of Artificial Intelligence 2025年 156卷

作者： Wu, Youliang Moghadas, B. Kamyab Gu, Dongqiang Salahshour, S. Hashemi, M. Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China Hefei Normal University Hefei230601 China Department of Chemical Engineering Shiraz Branch Islamic Azad University Shiraz Iran Department of Applied Researches Chemical Petroleum & Polymer Engineering Research Center Shiraz Branch Islamic Azad University Shiraz Iran Department of Sports Medicine Senior Department of Orthopedics The Fourth Medical Center of PLA General Hospital Beijing100048 China Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Research Center of Applied Mathematics Khazar University Baku Azerbaijan Fast Computing Center Shabihsazan Ati Pars Tehran Iran

This study focuses on the potential of biosensor technology to revolutionize sports injury management. Conventional methods for sports injury management, such as physical examinations and imaging techniques, often lack the sensitivity and real-time monitoring capabilities required to track the healing process effectively. These methods are also invasive, relying on blood sampling, which can be uncomfortable for athletes. In contrast, the proposed wearable biosensor offers a non-invasive, painless alternative by measuring biomarkers like myoglobin and creatine kinase in sweat. This study introduces a novel graphene field-effect transistor biosensor integrated into a wristband, combined with an artificial neural network (ANN) model to predict material properties and optimize biomarker detection. The results show the potential of this technology to revolutionize sports injury management by providing real-time, accurate, and non-invasive monitoring of injury progression and recovery. The results indicate that changes in compressive strength and porosity have an impact on dissolution rate, pore size growth, and chemical stability. Lower compressive strength leads to an increase in dissolution rate, while higher compressive strength promotes pore size growth and chemical stability. The accuracy of the ANN model's predictions was evaluated using linear regression and demonstrated acceptable error levels compared to experimental testing. Among the nanocomposite hydrogel scaffolds containing silver oxide nanoparticles, a specific sample showed noteworthy characteristics, including a compressive strength of 2.4 Mega Pascal, 55 % porosity, 22 % dissolution rate, 27 % pore size growth, and 65 % chemical stability. © 2025 Elsevier Ltd

关键词： Enzyme sensors

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