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6th International Conference on Advancements in Computing, ICAC 2024

作者： Gunasekara, Tharindu Thihan, Disira Kodithuwakku, Sansika Dissanayake, Dinuka Fernando, Harinda Vidhanaarachchi, Samitha Sindhujan, Archchana Sri Lanka Institute of Information Technology Malabe Dept. of Software Engineering Sri Lanka Sri Lanka Institute of Information Technology Malabe Dept. of Computer Computer Systems Engineering Sri Lanka University of Surrey Dept. of Computer Science and Electronic Engineering United Kingdom

ISBN: (纸本)9798331517878

Fake news continues to proliferate, posing an increasing threat to public discourse. The paper proposes a framework of a Mixture of Experts, Sentiment Analysis, and Sarcasm Detection experts for improved fake news detection. This approach captures the emotional cues in the text through a Sentiment Analysis expert, which is based on bidirectional encoder representations from Transformers (BERT) models with sentiment vectors generated using SentiWordNet and Integrated Gradients. It combines a sarcasm detection expert based on BERT, recognizing sarcasm and its type to help classify fake news. By fusing these experts through a Mixture of Experts gateway, subtle linguistic cues often found in fake news are more effectively analyzed, leading to improved accuracy in detecting misinformation. Experimental results are presented as 96% for the Sarcasm expert with the BERT base model and 83% for the Sentiment Analysis expert with the distilled version of the BERT (DistilBERT) base model, proving the effectiveness of the proposed approach in beating traditional methods. © 2024 IEEE.

关键词： fake news detection gateway mixture of experts sarcasm detection sentiment analysis

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Synthesis of Agent-Based Decision-Making systems with Multiple Coalitions

Synthesis of Agent-Based Decision-Making Systems with Multip...

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2023 International Conference on Electromechanical and Energy systems, SIELMEN 2023

作者： Ababii, Victor Sudacevschi, Viorica Munteanu, Silvia Carbune, Viorel Melnic, Radu Lasco, Victor Technical University of Moldova Department of Computer Sciences and Systems Engineering Chisinau Moldova Technical University of Moldova Department of Software Engineering and Automatics Chisinau Moldova

ISBN: (纸本)9798350315240

This paper presents a synthesis method of decision-making systems based on Agents forming multiple coalitions. The condition for coalition formation is defined by a mathematical model that solves the problem of global optimization of the objective function. The problem of synthesizing the agent-based system was formulated, and the mathematical model for negotiating the coalition formation process was developed. The process of initiation, dialogue and coalition formation is presented based on the sequence diagram. For structural modeling, Membrane Computation (P-systems) models are used that highlight the parallelism and topology of the Multi-Agent system. The Agent structure is defined as a collection of knowledge (data and processing methods) and input/output ports. The functional validation of the Agent and the Multi-Agent system was performed based on the Timed Petri Nets. © 2023 IEEE.

关键词： Petri nets

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Multi-Objective Decision Making System Based on Spatial -Temporal Logics 24

Multi-Objective Decision Making System Based on Spatial -Tem...

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24th International Conference on Control systems and computer Science, CSCS 2023

作者： Ababii, Victor Sudacevschi, Viorica Turcan, Ana Melnic, Radu Carbune, Viorel Cojuhari, Irina Technical University of Moldova Department of Computer Sciences and Systems Engineering Chisinau Moldova Technical University of Moldova Department of Software Engineering and Automatics Chisinau Moldova

ISBN: (纸本)9798350313390

Multi-objective decision making systems based on Spatial-Temporal logics presents a class of computational systems based on Artificial Intelligence in which spatial location and time evolution of processes (events) are taken into account. Multi-objective decision making systems showcase a distributed computing architecture based on Agents (Computational Nodes) that form a network for data processing. The functionality of the decision making system is based on events that are spatially and temporally localized. The set of Agents, based on the events, calculates its influence coefficient on the decision taken by the Agent. An Agent can generate both decisions, which lead to personal qualitative evolution, and events that will be processed by other Agents. This work elaborates the following: the multi-objective decision system diagram, the communication model between Agents, the set of operators for spatial-temporal logic, and the model for optimal solution search in event space. © 2023 IEEE.

关键词： Multi agent systems

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Challenge-Response Emotion Authentication Algorithm Using Modified Horizontal Deep Learning

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Intelligent Automation & Soft Computing 2023年第3期35卷 3659-3675页

作者： Mohamed Ezz Ayman Mohamed Mostafa Ayman Elshenawy College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia Systems and Computers Engineering DEPT Faculty of EngineeringAl-Azhar UniversityCairo11651Egypt Software Engineering&Information Technology Faculty of Engineering&TechnologyEgyptian Chinese UniversityEgypt

Face authentication is an important biometric authentication method commonly used in security *** is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social media to perform spooﬁng attacks and dynamic movements for penetrating secur-ity *** paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble *** proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a speciﬁc response for every authentication trial with a different sequence of *** proposed model is applied to the KDEF dataset using 10-fold *** improvements are made to the proposed ***,the VGG16 model is applied to the seven common ***,the system usability is enhanced by analyzing and selecting only the four common and easy-to-use ***,the horizontal ensemble technique is applied to enhance the emotion recognition accuracy and minimize the error during authen-tication ***,the Horizontal Ensemble Best N-Losses(HEBNL)is applied using challenge-response emotion to improve the authentication efﬁ-ciency and minimize the computational *** successive improvements implemented on the proposed model led to an improvement in the accuracy from 92.1%to 99.27%.

关键词： Face authentication challenge-response authentication transfer learning and horizontal ensemble technique

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Deep Learning with a Novel Concoction Loss Function for Identification of Ophthalmic Disease

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computers, Materials & Continua 2023年第9期76卷 3763-3781页

作者： Sayyid Kamran Hussain Ali Haider Khan Malek Alrashidi Sajid Iqbal Qazi Mudassar Ilyas Kamran Shah Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering Faculty of Computer ScienceLahore Garrison UniversityLahore54000Pakistan Department of Computer Science Applied CollegeUniversity of TabukTabukSaudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl Hofuf31982Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl HofufSaudi Arabia

As ocular computer-aided diagnostic(CAD)tools become more widely accessible,many researchers are developing deep learning(DL)methods to aid in ocular disease(OHD)*** eye diseases like cataracts(CATR),glaucoma(GLU),and age-related macular degeneration(AMD)are the focus of this study,which uses DL to examine their *** imbalance and outliers are widespread in fundus images,which can make it difficult to apply manyDL algorithms to accomplish this analytical *** creation of efficient and reliable DL algorithms is seen to be the key to further enhancing detection *** the analysis of images of the color of the retinal fundus,this study offers a DL model that is combined with a one-of-a-kind concoction loss function(CLF)for the automated identification of *** study presents a combination of focal loss(FL)and correntropy-induced loss functions(CILF)in the proposed DL model to improve the recognition performance of classifiers for biomedical *** is done because of the good generalization and robustness of these two types of losses in addressing complex datasets with class imbalance and *** classification performance of the DL model with our proposed loss function is compared to that of the baseline models using accuracy(ACU),recall(REC),specificity(SPF),Kappa,and area under the receiver operating characteristic curve(AUC)as the evaluation *** testing shows that the method is reliable and efficient.

关键词： Deep learning multi-classification focal loss CNN eye disease

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Deep Learning-Based Audio Splicing Forgery Detection Using PVTv2 Transformer

Deep Learning-Based Audio Splicing Forgery Detection Using P...

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2024 Innovations in Intelligent systems and Applications Conference, ASYU 2024

作者： Kanca, Elif Gulsoy, Tolgahan Ustubioglu, Arda Ustubioglu, Beste Ayas, Selen Baykal Kablan, Elif Ulutas, Guzin Department of Software Engineering Karadeniz Technical University Trabzon Turkey Department of Management Information Systems Trabzon University Trabzon Turkey Department of Computer Engineering Karadeniz Technical University Trabzon Turkey

ISBN: (纸本)9798350379433

Attacks on multimedia files by malicious users have become quite common, especially with the increase in the number of editing tools and their ease of use. Considering that such files can now be used both as evidence and for social visibility in all kinds of environments, it has become important to prove their authenticity. With the proposed method, the detection of merging forgeries in audio files has been carried out. For this purpose, the audio files received from the input are converted into cochleagram images. The PVTv2 based deep network architecture is trained with the generated cochleagram images. As a result of the training, the suspicious audio file given as input is labelled as original/fake. The proposed method gives 96.11% accuracy for 2s database, 94.63% accuracy for 3s database and 95.19% accuracy for 2s-3s database. © 2024 IEEE.

关键词： Deep learning

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A survey for light field super-resolution

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High-Confidence Computing 2024年第1期4卷 118-129页

作者： Mingyuan Zhao Hao Sheng Da Yang Sizhe Wang Ruixuan Cong Zhenglong Cui Rongshan Chen Tun Wang Shuai Wang Yang Huang Jiahao Shen State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Data Science and Intelligent Computing International Innovation InstituteBeihang UniversityHangzhou 311115China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Compared to 2D imaging data,the 4D light field(LF)data retains richer scene’s structure information,which can significantly improve the computer’s perception capability,including depth estimation,semantic segmentation,and LF ***,there is a contradiction between spatial and angular resolution during the LF image acquisition *** overcome the above problem,researchers have gradually focused on the light field super-resolution(LFSR).In the traditional solutions,researchers achieved the LFSR based on various optimization frameworks,such as Bayesian and Gaussian *** learning-based methods are more popular than conventional methods because they have better performance and more robust generalization *** this paper,the present approach can mainly divided into conventional methods and deep learning-based *** discuss these two branches in light field spatial super-resolution(LFSSR),light field angular super-resolution(LFASR),and light field spatial and angular super-resolution(LFSASR),***,this paper also introduces the primary public datasets and analyzes the performance of the prevalent approaches on these ***,we discuss the potential innovations of the LFSR to propose the progress of our research field.

关键词： Light field super-resolution Convolutional neural network Transformer Sub-aperture image Epipolar-plane image

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A Spectral Mask - Based on Method for Applying into Generalized Sidelobe Canceller Beamformer 12th

A Spectral Mask - Based on Method for Applying into Gener...

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Proceedings of the12th International Conference on Information Technology and its Applications, CITA 2023

作者： Huy, Nguyen Ba Anh, Pham Tuan The, Quan Trong Faculty of Control Systems and Robotics University ITMO St.Petersburg Russia Faculty of Software Engineering and Computer Systems University ITMO St.Petersburg Russia

ISBN: (纸本)9783031368851

The problem of signal processing is extracting the desired target speaker while suppressing the annoying background noise in complex recording situation, where exists third-party talker, transport vehicle or interference, noise. Speech quality or speech intelligibility are the major characteristics, which confirm the effectiveness of processed method. In speech applications, such as hearing-aids, hands-free telephony, teleconferencing, acoustic instruments, microphone array (MA) is applied for increasing the speech quality. MA uses the spatial response, the priori information about direction - of - arrival (DOA) of interest signal, the properties of recording environment to obtain speech components and remove noise. Generalized Sidelobe Canceller (GSC) is one of the most widely exploited in microphone array beamforming, due to its convenience and effective noise reduction. However, in several situations, the performance of GSC beamformer is often degraded, because of the imprecise DOA. In this paper, the authors suggested an additive spectral mask for improving the evaluation of GSC beamformer. The resulting experiment proves the received advantage of the author’s proposed algorithm to increase in the term of the signal-to-noise ratio (SNR). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Signal to noise ratio

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Baby Bump: A Monitoring System for Pregnant Mothers and Babies 9

Baby Bump: A Monitoring System for Pregnant Mothers and Babi...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Balasooriya, Dhanuka Perera, Sasini Wijendra, Dinuka R. Rathnayaka, Sahani Kishan, Rajendra Rajendran, Karthiga Thirukumar, Markandu Sri Lankan Institute of Information Technology Department of Computer Systems And Software Engineering Malabe Sri Lanka Teaching Hospital Department of Obstetrics & Gynaecology Batticaloa Sri Lanka

ISBN: (纸本)9798350394474

In contemporary times, nations like Sri Lanka are actively enhancing their efforts to improve the life expectancy of their citizens, with a strong focus on public health. The relationship between health and life expectancy is pivotal. Poor health conditions tend to diminish life expectancy, while robust health measures tend to extend it. Within the context of health, birth and death events are of paramount importance. Birth represents the genesis of life, enabling individuals to contribute to future generations and the overall population's expansion. It's the cornerstone of life on our planet. However, modern times have witnessed challenges in pregnancy and childbirth, with some infants not surviving the prenatal period or being born with health complications. Consequently, there is a pressing need to present a solution that can contribute to the betterment of maternal and infant health, ultimately augmenting Sri Lanka's life expectancy. The proposed solution is the development of a mobile application, encompassing features such as a Nutrition Predictor, Medicine Effect Predictor, AI chatbot, and Baby Status Predictor. This innovative application aims to address the complex issues surrounding pregnancy and childbirth, with the overarching goal of improving the nation's life expectancy. © 2024 IEEE.

关键词： Nutrition

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Offshore software Maintenance Outsourcing Process Model Validation:A Case Study Approach

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computers, Materials & Continua 2023年第3期74卷 5035-5048页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Adel Sulaiman Muhammad Akram Ahmad Salman Khan Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan

The successful execution and management of Offshore software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

关键词： Offshore outsourcing process model model validation vendor challenges case study

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