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Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), International Conference o

作者： Hassaan Th. H. Thabet Aqeel A. Al-Hilali Haitham B. Qasim Thabit H. Thabit Firas M. Mahmood Dept. of Medical Instruments Techniques Engineering Al-Hadba University College Mosul Iraq Dept. of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Dept. of Computer Science Al-Esraa University College Baghdad Iraq Dept. of Computer Engineering and Information Ninevah University Mosul Iraq Dept. of Informatics and Software Engineering Cihan University-Erbil Iraq

The presence of water in human life is crucial, and God has blessed humans much with its availability. This paper tries to reduce the amount of water that people use for washing in all aspects of daily life and instead utilize it to irrigate gardens and maintain hygienic facilities. The importance of water as a fundamental ingredient and the range of social and age groups that regularly take advantage of the washing process made it an ideal location for water waste during the washing process. This is why the authors choose this region to conduct their research. The monitoring and management of water usage during the washing process are simulated using PLC techniques.

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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Robotics, engineering, science, and Technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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On the Feasibility of RIS-enabled Cooperative Driving

On the Feasibility of RIS-enabled Cooperative Driving

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IEEE Vehicular Networking Conference (VNC)

作者： Michele Segata Paolo Casari Marios Lestas Dimitrios Tyrovolas Taqwa Saeed George Karagiannidis Christos Liaskos Department of Information Engineering and Computer Science University of Trento Italy Dept. of Electrical Engineering Frederick University Cyprus Dept. of Electrical Engineering Aristotle University of Thessaloniki Greece School of Information Technology Halmstad University Sweden Cyber Security Systems and Applied AI Research Center Lebanese American University (LAU) Lebanon Dept. of Computer Science and Engineering University of Ioannina & FORTH Greece

Future cooperative autonomous vehicles will require high-performance communication means to support functions such as cooperative maneuvering and cooperative perception. The high-bandwidth requirements of these functions can be met through mmWave communications, whose utilization is often hindered by the harsh propagation conditions of typical vehicular environments. A solution to this problem is the use of reconfigurable intelligent surfaces (RISs), which enable the reflection of signals in a configurable direction, and have recently gained attention in the vehicular domain. In this paper, we provide an initial feasibility study, highlighting the challenges ahead and the performance RISs need to deliver in order to enable this type of communications. Specifically, we utilize CoopeRIS, a simulation framework for RISs integrated into the Plexe/Veins/SUMO ecosystem that we develop as further contribution and will release to the public.

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Intra-Datacenter Load Balancing in a Federated Cloud with Throttled Algorithm

Intra-Datacenter Load Balancing in a Federated Cloud with Th...

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2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Akinola, Damola Gideon Adetiba, Emmanuel Abayomi, Abdultaofeek Nnaji, Uche Thakur, Surendra Moyo, Sibusiso Covenant University Covenant Applied Informatics and Communications African Center of Excellence Department of Electrical and Information Engineering Ota Nigeria Durban University of Technology HRA Institute for Systems Science Durban South Africa Mangosuthu University of Technology Department of Information and Communication Technology Durban South Africa Covenant University Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Ota Nigeria Durban University of Technology KZN E-Skills CoLab Durban South Africa Stellenbosch University School for Data Science and Computational Thinking Department of Mathematical Sciences Stellenbosch7602 South Africa

ISBN: (纸本)9798350358155

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users' requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named;the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment. © 2024 IEEE.

关键词： Cloud platforms

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Knowledge Distillation Based Defense for Audio Trigger Backdoor in Federated Learning

Knowledge Distillation Based Defense for Audio Trigger Backd...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yu-Wen Chen Bo-Hsu Ke Bo-Zhong Chen Si-Rong Chiu Chun-Wei Tu Jian-Jhih Kuo Computer Systems Technology New York City College of Technology Brooklyn New York USA Dept. of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

The applications of Automatic Speech Recognition (ASR) on Internet-of-Things (IoT) devices have increased significantly in recent years, and Federated Learning (FL) is often used to improve ASR performance since its decentralized training mechanism ensures users' data privacy. However, FL is vulnerable to various attacks. The most challenging one to detect and defend against is trigger backdoor attack. Adversaries inject the trigger into the training audio data and participate in the FL training, causing the converged global model to mispredict the poisoned data. Unlike previous defense methods filtering suspicious models during model aggregation, we propose the Knowledge Distillation Defense Framework (KDDF) to detect and remove features of the potential triggers during the inference. KDDF utilizes Knowledge Distillation (KD) to train a validation model on each IoT device, which is used to identify suspicious data. Then, KDDF would try to eliminate the injected trigger during the model inference if the data is suspicious. Experimental results show that KDDF can effectively distinguish between benign and suspicious data and recover the classification results of suspicious data.

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Successive Interference Cancellation Based Defense for Trigger Backdoor in Federated Learning

Successive Interference Cancellation Based Defense for Trigg...

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IEEE International Conference on Communications (ICC)

Federated Learning (FL) provides a decentralized training mechanism that ensures users' data privacy. However, FL is vulnerable to backdoor attacks, a type of data poisoning attack. The adversaries tampered with the local models by injecting a trigger into a subset of training data. After the aggregation process, the global model would be poisoned and mispredict the input images that injected a trigger designed by an adversary. Unlike the existing defense methods attempting to identify and remove the abnormal model updates on the aggregation step, this paper proposes a Successive Interference Cancellation-based Defense Framework (SICDF) to detect and eliminate the trigger during model inference. SICDF first employs Explainable AI to infer where the trigger is and then uses image processing skills to eliminate potential trigger effects. Experiment results show that SICDF can effectively recover the poisoned data while only slightly reducing the accuracy of the clean model and benign data.

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A Proposed Gamification Elements of Educational Games 6

A Proposed Gamification Elements of Educational Games

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6th International Conference on computer and information sciences, ICCOINS 2021

作者： Elaish, Monther M. Hussein, Mahmood H. Shuib, Liyana Wan Ahmad, Wan Fatimah Becker, Katrin University of Benghazi Dept. Computer Science Benghazi Libya University of Malaya Dept. Software Engineering Kuala Lumpur Malaysia Universiti Teknologi Petronas Dept. Computer and Information Sciecnes Perak Malaysia Mount Royal University Dept. Mathematics and Computing CalgaryAlberta Canada

ISBN: (纸本)9781728171517

Research interest in gamification is currently enjoying global attention. However, while game design is often the focus of these gamification systems, interface design is overlooked. This is due to the expectations of field stakeholders and experts who consider interface to be only a minor element of the gamification experience. The aim of this paper is to propose a classification method that categorizes the gamification element into tangible and intangible. This new classification would provide a clear perspective about the elements before the design and development of an educational game has even begun. The proposed new method of classification would save researcher's time and effort by assisting in the selection of the most appropriate gamification elements for the situation at hand. © 2021 IEEE.

关键词： Game design

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RadioModRec-l: A Large Scale Radio Frequency Dataset for Automatic Modulation Recognition Research

RadioModRec-l: A Large Scale Radio Frequency Dataset for Aut...

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Emmanuel Adetiba Jamiu R. Olasina Obiseye Obiyemi Dept. of Electrical and Information Engineering Covenant Applied Informatics and Communication Africa Center of Excellence Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Dept. of Computer Engineering Federal Polytechnic Ilaro Ilaro Nigeria Dept. of Electrical Power Engineering Space Science Centre Durban University of Technology Durban South Africa

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

Access to well-curated large datasets remains a significant bottleneck in AI-based research within wireless communication. Rapid advancements in neighbouring fields, such as computer vision and natural language processing, are largely due to the availability of extensive open-access datasets. However, similar progress has not been observed in wireless communication. To address this gap, we curated a comprehensive dataset for fifteen digital modulation schemes, including 4QAM, 16QAM, 64QAM, 256QAM, 8PSK, 16PSK, 32PSK, 64PSK, 128PSK, 256PSK, CPFSK, DBPSK, DQPSK, GFSK, and GMSK. Our dataset considers Rayleigh and Rician channel models under Additive White Gaussian Noise (A WGN) with SNRs ranging from -20dB to + 20dB in 5dB increments. The data samples were converted to constellation signal images and carefully pre-processed. Named RadioModRec, this dataset provides a valuable resource for researchers to train and evaluate AI models. It is freely accessible on Kaggle, promoting further innovation in the wireless communication domain.

关键词： Wireless communication Technological innovation Transfer learning Stochastic processes Rician channels Market research Natural language processing Optimization Residual neural networks Radio spectrum management

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Deep Ear Biometrics for Gender Classification

arXiv

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arXiv 2023年

作者： Singh, Ritwiz Kashyap, Keshav Mukherjee, Rajesh Bera, Asish Chakraborty, Mamata Dalui Department of Computer Science and Engineering Haldia Institute of Technology WB India Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Pilani Campus Rajasthan333 031 India Dept. of Computer Science and Engineering National Institute of Technology West Bengal Durgapur India

Human gender classification based on biometric features is a major concern for computer vision due to its vast variety of applications. The human ear is popular among researchers as a soft biometric trait, because it is less affected by age or changing circumstances, and is non-intrusive. In this study, we have developed a deep convolutional neural network (CNN) model for automatic gender classification using the samples of ear images. The performance is evaluated using four cutting-edge pre-trained CNN models. In terms of trainable parameters, the proposed technique requires significantly less computational complexity. The proposed model has achieved 93% accuracy on the EarVN1.0 ear dataset. © 2023, CC BY.

关键词： Biometrics

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Mental Health Professionals' Insights on Digital Health Solutions for Anxiety in the UAE

Mental Health Professionals' Insights on Digital Health Solu...

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IEEE International Requirements engineering Conference Workshops (REW)

作者： Mariam Al Meqbaali Sofia Ouhbi Reem K Jan Leena Amiri Fadwa Al Mugaddam Mohamed Adel Serhani Nazar Zaki Dept. Computer Science & Software Engineering CIT UAEU Al Ain UAE Dept. Information Technology Uppsala University Uppsala Sweden Mohammed Bin Rashid University of Medicine and Health Sciences Dubai UAE Dept. Psychiatry and Behavioral Science CMHS UAEU Al Ain UAE College of Computing and Informatics University of Sharjah Sharjah UAE

ISBN: (数字)9798350395518

ISBN: (纸本)9798350395525

In recent years, anxiety disorders have become more prevalent worldwide, leading to an increased demand for mental healthcare services. Barriers such as stigma and cost, limit access to these services, prompting the exploration of alternative solutions. Digital technology shows significant promise in improving access to mental healthcare services. This study aims to explore the preferences, and concerns of Mental Health Professionals (MHPs) regarding digital health solutions for self-management of anxiety disorders in the UAE via an online survey. Participation was voluntary and anonymous, with 18 MHPs taking part. The survey included 12 questions covering demographics and key design elements. Most respondents displayed positive attitudes toward integrating digital anxiety solutions in the UAE, providing feedback and highlighting considerations. 61% endorsed the use of digital technology in anxiety disorder treatment, while 94% favored mindfulness exercises for anxiety management. 72% expressed interest in utilizing technology for therapy. Notable concerns raised included privacy and dependency. Guided by MHPs insights, we propose a conceptual framework for the design of digital anxiety solutions in the UAE. This framework prioritizes cultural appropriateness and language accessibility, offering solutions in Arabic and English. It encompasses diverse features, including a blended approach, treatment approaches, and relaxation techniques, to address anxiety disorders and ensures user safety through risk assessment and management. This framework can assist developers of digital anxiety solutions by highlighting the features and elements that MHPs deem most important.

关键词： Surveys Privacy Anxiety disorders Medical treatment Mental health Safety Electronic healthcare

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