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Facial Image-Based Autism Detection:A Comparative Study of Deep Neural Network Classifiers

Computers, Materials & Continua 2024年第1期78卷 105-126页

作者： Tayyaba Farhat Sheeraz Akram Hatoon SAlSagri Zulfiqar Ali Awais Ahmad Arfan Jaffar Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Faculty of Computer Science and Information TechnologyThe Superior UniversityLahore54600Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive *** and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like *** study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local *** research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate *** addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the *** findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation ***,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test *** validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD *** research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.

关键词： Autism Autism Spectrum Disorder(ASD) disease segmentation features optimization deep learning models facial images classification

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Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

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Computer systems Science & Engineering 2023年第8期46卷 2429-2445页

作者： Tariq Ahamed Ahanger Fadl Dahan Usman Tariq Department of Management Information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Management Information Systems College of Business Administration-Hawtat Bani TamimPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Sciences Faculty of Computing and Information Technology Al-TurbahTaiz UniversityTaiz9674Yemen

In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these *** WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services(QoS)*** challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS *** this paper,we introduce an extension of our previous works on the Artificial Bee Colony(ABC)and Bat Algorithm(BA).A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global *** bat agent is used to improve the solution of exhausted bees after a threshold(limits),and also an Elitist Strategy(ES)is added to BA to increase the convergence *** performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria(average fitness values,best fitness values,and execution time)that were measured for 30 different *** datasets are created from real-world datasets and artificially to form different scale sizes of WSC *** results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to *** signed-rank significant test is usedwhere the proposed algorithm results significantly differ fromother algorithms on 100%of datasets.

关键词： Internet of things artificial bee colony bat algorithm elitist strategy web service composition

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Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center

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Journal of Computer Science & technology 2023年第4期38卷 773-792页

作者：田文洪徐敏贤周光耀吴逵须成忠 Rajkumar Buyya School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Computer Science University of VictoriaVictoriaBCV8W 3P6Canada State Key Laboratory of Internet of Things for Smart City University of MacaoMacao 999078China School of Computing and Information Systems University of MelbourneMelbourne 3010Australia

Load balancing is vital for the efficient and long-term operation of cloud data *** virtualization,post(reactive)migration of virtual machines(VMs)after allocation is the traditional way for load balancing and consoli***,it is not easy for reactive migration to obtain predefined load balance objectives and it may interrupt services and bring ***,we provide a new approach,called Prepartition,for load *** partitions a VM request into a few sub-requests sequentially with start time,end time and capacity demands,and treats each sub-request as a regular VM *** this way,it can proactively set a bound for each VM request on each physical machine and makes the scheduler get ready before VM migration to obtain the predefined load balancing goal,which supports the resource allocation in a fine-grained *** with real-world trace and synthetic data show that our proposed approach with offline version(PrepartitionOff)scheduling has 10%–20%better performance than the existing load balancing baselines under several metrics,including average utilization,imbalance degree,makespan and Capacity_*** also extend Prepartition to online load *** results show that our proposed approach also outperforms state-of-the-art online algorithms.

关键词： cloud computing physical machine(PM) virtual machine(VM) reservation load balancing Prepartition

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A Quantum Q-Learning Model for the Capacitated Vehicle Routing Problem 17

A Quantum Q-Learning Model for the Capacitated Vehicle Routi...

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17th IEEE International Symposium on Embedded Multicore/Many-core systems-on-Chip, MCSoC 2024

作者： Xu, Jiahua Xie, Ningyi Lee, Xinwei Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng University of Tsukuba Graduate School of Science and Technology Japan Singapore Management University School of Computing and Information Systems Singapore University of Aizu Graduate School of Computer Science and Engineering Japan University of Aizu School of Computer Science and Engineering Japan University of Tsukuba Faculty of Engineering Information and Systems Japan

ISBN: (纸本)9798331530471

The research on Variational Quantum Algorithms (VQAs) has gained significant momentum because of their promising practicality in the noisy intermediate-scale quantum (NISQ) era. Recent studies highlight the potential of VQAs in reinforcement learning (RL) by replacing classical components with parameterized quantum circuits (PQCs). Building on this, we propose a quantum Q-learning model for the Capacitated Vehicle Routing Problem (CVRP), combining a PQC with an RL training process. We present a PQC for embedding both static and dynamic states in RL environments. The proposed PQC approximates the Q-value function by using the expectation values of different observables. Experimental results demonstrate that the proposed PQC outperforms the existing PQC for the CVRP with fewer quantum resources. Furthermore, our method shows competitive performance compared to the classical counterpart. © 2024 IEEE.

关键词： Vehicle routing

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Quality Obstacles of Distance Learning: Experiences from Students of the University of Benghazi 3

Quality Obstacles of Distance Learning: Experiences from Stu...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2023

作者： Suweel, Osamah Sulayman Yahya Maatuk, Abdelsalam M. Abdalla, Mohamed A E Benghazi University Faculty of Information Technology Dept. of Information Systems Benghazi Libya Libyan International Medical University Faculty of Information Technology Benghazi Libya Benghazi University Faculty of Information Technology Dept. of Software Engineering Benghazi Libya

ISBN: (纸本)9798350319897

Adopting distance learning with a high level of quality in universities and educational institutions is a real challenge. Therefore, several studies and organizations have provided different standards to evaluate the quality of long-distance and to measure the obstacles. This study examines the quality obstacles of the long-distance learning techniques applied at the Faculty of information technology at the University of Benghazi, Libya. The British Quality Assurance Agency (BQAA) standards are utilized and presented as a questionnaire to the students at the faculty. The total participant number is 223 respondents. The study findings show that the students face severe challenges in all categories of the BQAA of technical, social, and organizational obstacles. The level of challenges is represented in the negativity of the response 69.1%, 60.1%, and 59.44% of the determined categories. © 2023 IEEE.

关键词： Quality assurance

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The Concept of Cognition as Categorization in the Development of New Metaheuristics and Algorithms Inspired by Nature 46

The Concept of Cognition as Categorization in the Developmen...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Tulicic, Domagoj Ivkovic, Nikola College for Information Technologies Department of Computer Systems and Networks Zagreb Croatia Faculty of Organization and Informatics Department of Computing and Technology Varaždin Croatia

ISBN: (纸本)9789532331042

The sensorimotor system is a crucial mechanism that enables organisms to categorize information in their environment, a skill necessary for survival. According to cognitive scientist Steven Harnad's 'To Cognize is to Categorize: Cognition is Categorization all living things are essentially sensorimotor systems. This approach is proposed to serve as a novel concept for the development of algorithms inspired by swarm intelligence. Many authors of such algorithms have drawn inspiration from animal species, attempting to emulate their abilities to interact with and navigate their environment. However, these abilities are essentially rooted in the organisms' categorization skills, which are a fundamental characteristic of all sensorimotor systems. Therefore, when designing new algorithms and metaheuristics, it is unnecessary to seek out new species with specific behaviors;instead, the entire sensorimotor system can be observed, and its sensor capabilities can be incorporated even if they do not exist in nature. In order to justify this, abstraction was used as a way to demonstrate the creation of concepts. The paper offers a new perspective on the development of swarm intelligence algorithms and promotes a holistic approach to algorithm design based on Steven Harnad's viewpoint of sensory motor systems. © 2023 MIPRO Croatian Society.

关键词： Swarm intelligence

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An Optimization Approach for Convolutional Neural Network Using Non-Dominated Sorted Genetic Algorithm-Ⅱ

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Computers, Materials & Continua 2023年第3期74卷 5641-5661页

作者： Afia Zafar Muhammad Aamir Nazri Mohd Nawi Ali Arshad Saman Riaz Abdulrahman Alruban Ashit Kumar Dutta Badr Almutairi Sultan Almotairi Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaMalaysia School of Electronics Computing and MathematicsUniversity of DerbyUK Department of Computer Science National University of TechnologyIslamabadPakistan Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia Department of Information Systems Faculty of Computer and Information SciencesIslamic University of MadinahMadinah42351Saudi Arabia

In computer vision,convolutional neural networks have a wide range of *** representmost of today’s data,so it’s important to know how to handle these large amounts of data *** neural networks have been shown to solve image processing problems ***,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher *** technique is time consuming and requires a lot of work and domain *** a convolutional neural network architecture is a classic NP-hard optimization *** the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and *** approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random *** address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized *** study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN *** addition,different types and parameter ranges of existing genetic algorithms are *** study was conducted with various state-of-the-art methodologies and *** have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature.

关键词： Non-dominated sorted genetic algorithm convolutional neural network hyper-parameter optimization

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AI LipReader-Transcribing Speech from Lip Movements 6

AI LipReader-Transcribing Speech from Lip Movements

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6th IEEE International Conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Ajitha, D. Dutta, Disha Saha, Falguni Giri, Parus Kant, Rohan School of Computer Science and Engineering Vellore Institute of Technology Vellore Department of Software Systems Vellore India School of Computer Science and Engineering Vellore Institute of Technology Department of Database Systems Vellore India School of Computer Science and Engineering Vellore Institute of Technology Vellore Department of Information Security Vellore India

ISBN: (纸本)9798350306613

Lip Reading AI is a discipline that is rapidly changing and has numerous applications in security, accessibility and human-computer interaction. This paper proposes a model which combines Convolutional Neural Networks (CNNs) to capture spatial capabilities, Long Short-Term Memory (LSTM) networks to examine temporal dependencies, and an adaptive interest mechanism. Meticulous preprocessing of the MIRACL VC-l dataset addressing challenges including one of a kind lip moves and occlusions accompanied with the aid of transitioning this study effortlessly to LRS2 dataset to complement lexemic versatility is one of its key function. The effects verify its robustness throughout unique datasets with superior overall performance towards cutting-edge techniques. Ablation checks suggest the crucial significance of every element in phrases of improving lip analyzing accuracy. Our proposed model version additionally suggests flexibility in restricted and naturalistic language situations. © 2024 IEEE.

关键词： Attention Mechanism Convolutional Neural Networks (CNNs) Deep Learning Lip Reading Long Short-Term Memory (LSTM) LRS2 Dataset MIRACLVC-J Dataset

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Smart Advertising Based on Customer Preferences and Manage the Supermarket 4

Smart Advertising Based on Customer Preferences and Manage t...

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4th International Conference on Advancements in computing, ICAC 2022

作者： Eishan Dinuka, W.H.A. Wickramasinghe, A.Y.S.W. Weerasinghe, W.S.H. Karunaratne, K.P.G. Liyanapathirana, Chethana Rupasinghe, Lakmal Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

As a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users' feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users' preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly. © 2022 IEEE.

关键词： Sales

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Attribute-Based Keyword Search over the Encrypted Blockchain

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Computer Modeling in Engineering & Sciences 2021年第7期128卷 269-282页

作者： Zhen Yang Hongao Zhang Haiyang Yu Zheng Li Bocheng Zhu Richard O.Sinnott Faculty of Information Technology Beijing University of TechnologyBeijing100124China School of Computing and Information Systems The University of MelbourneVictoria3010Australia

To address privacy concerns, data in the blockchain should be encrypted in advance to avoid data access fromall users in the blockchain. However, encrypted data cannot be directly retrieved, which hinders data sharing inthe blockchain. Several works have been proposed to deal with this problem. However, the data retrieval in theseschemes requires the participation of data owners and lacks finer-grained access control. In this paper, we proposean attribute-based keyword search scheme over the encrypted blockchain, which allows users to search encryptedfiles over the blockchain based on their attributes. In addition, we build a file chain structure to improve theefficiency of searching files with the same keyword. Security analysis proves the security of the proposed *** analysis and experimental results in performance evaluation show that our scheme is feasible andefficient.

关键词： Blockchain searchable encryption attribute-based encryption smart contract

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