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47th ICT and Electronics Convention, MIPRO 2024

作者： Kovačević, Željko Bubnic, Bostjan Kosar, Tomaž Zagreb University Of Applied Sciences Department Of Computer Science And Information Technology Zagreb Croatia University Of Maribor Faculty Of Electrical Engineering And Computer Science Maribor Slovenia

ISBN: (纸本)9798350382495

Technology is changing how students learn in the 21st century significantly. Integrating mobile devices in teaching, learning, and assessment processes has emerged as an important strategy for improving teaching methodologies and students' learning. However, adopting mobile devices presents several challenges, including understanding the students' performance, impact on time, and efficiency in the assessment process. This study explores this area with an empirical study of using mobile devices and compares the results to those using traditional desktop computers. In the educational environment, we investigated students' effective use while interacting with mobile and desktop versions of the Second Introductory programming summative assessment. Multinational/multi-institutional research involved a comparative analysis between two student groups undertaking identical tasks on mobile phones and desktop computers. Our results suggest that the students' results are not affected significantly by using the mobile version of the assessment application. These results highlight the usability of mobile devices as a flexible and effective tool for various educational applications, strengthening their role in the modern learning environment. © 2024 IEEE.

关键词： Object oriented programming

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Environmental Disinfection Based on Mobile Intelligent Networking Highly Efficient Ultraviolet Light Machines

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Aerosol and Air Quality Research 2024年第2期24卷 1-10页

作者： Chung, Chun-Yen Sung, Wen-Tsai Wang, Lin-Chi Siami, Lailatus Santos, John Paul Computer and Game Development Program Kun Shan University Tainan710303 Taiwan Department of Electrical Engineering National Chin-Yi University of Technology Taichung411030 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Environmental Engineering Chung Yuan Christian University Taoyuan32023 Taiwan Department of Civil Engineering Chung Yuan Christian University Taoyuan32023 Taiwan

Since 2019, the world has suffered from the outbreak of the "Coronavirus Disease (COVID)-19 pandemic. This study used the principle of Ultraviolet (UV)-C disinfection to produce a mobile high-power UV-C sterilizer. It focused on combining intelligent control systems, human sensors, and Internet of Things (IoT) systems to carry out disinfection tasks in unmanned indoor spaces. Because of its mobile nature, the sterilizer could be moved at any time in various learning, research, and activity rooms for disinfection. In addition to manually controlling the sterilizer, a Wi-Fi or Narrowband (NB)-IoT-enabled remote control was provided to start the disinfection process. In order to prevent ultraviolet light from harming the human body, sensors were employed self-acting to detect the presence of people and turn off the ultraviolet light when people were detected in the area. At the same time, a camera on the sterilizer would capture an image and notify the relevant personnel through a LINE notification, to prevent the human body from being exposed to ultraviolet light, causing harm to the teachers and students on campus. During operation, voice broadcast reminders and a status indicator could provide information about the operation status. After disinfection, users could view the disinfection process through a mobile device application or a webpage, which would automatically notify relevant personnel of the disinfection status through a LINE notification. In this way, the disinfection progress could be updated at anytime, anywhere and the current disinfection status in the classroom could be displayed in real-time, allowing teachers and students on campus to carry out teaching and learning in a safe and secure environment. © The Author(s).

关键词： Internet of things

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Bi_(2)O_(2)Se nanoplates for broadband photodetector and full-color imaging applications

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Nano Research 2023年第5期16卷 7638-7645页

作者： Han Wang Songqing Zhang Xingxuan Wu Huijia Luo Junliang Liu Zesheng Mu Ruirui Liu Guang Yuan Yujun Liang Jin Tan Yongling Ren Wen Lei Department of Electrical Electronic and Computer EngineeringThe University of Western AustraliaCrawley 6009Australia Department of Electronic Engineering School of IOT engineeringJiangnan UniversityWuxi 214122China College of Information Science and Engineering Ocean University of ChinaQingdao 266100China Faculty of Materials Science and Chemistry China University of GeosciencesWuhan 430074China

Broadband light detection and sensing are widely applied in modern *** a promising candidate for next-generation two-dimensional(2D)optoelectronic material,bismuth oxyselenide(Bi_(2)O_(2)Se)nanoplates exhibit many prospects in the application of visible light detection due to their peculiar *** this work,we report the photodetection performance of single-crystal 2D Bi_(2)O_(2)Se nanoplates grown on SiO_(2)based on a ternary-alloy growth model by utilizing chemical vapor deposition(CVD).The Bi_(2)O_(2)Se nanoplates were found to have an even and uniform square shape with side lengths up to 15μm and an approximate thickness of 15 nm.A visible-light photodetector was fabricated based on a CVD-grown Bi_(2)O_(2)Se nanoplate,and characterized by a set of illumination experiments using a 400 nm laser at temperatures ranging from 77 to 370 *** device exhibited superior performance at the temperature of 77 K,with a responsivity of 523 A/W,a specific detectivity of 1.37×10^(11)Jones,a response time of 0.2175 ms,an external quantum efficiency of 162,119.44%,resulting in high-quality and fullcolor imaging in the visible *** results indicate that the single-crystalline Bi_(2)O_(2)Se nanoplates have excellent potential in broadband photodetection and non-cryogenic imaging.

关键词： two-dimensional(2D)nanomaterial Bi_(2)O_(2)Se nanoplates chemical vapor deposition broadband light detection full-color imaging

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Solution to Coordination of Transmission and Distribution for Renewable Energy Integration into Power Grids:An Integrated Flexibility Market

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CSEE Journal of Power and Energy Systems 2023年第2期9卷 444-458页

作者： Tao Jiang Zhongwei Shen Xiaolong Jin Rufeng Zhang Alessandra Parisio Xue Li Xiao Kou Department of Electrical Engineering Northeast Electric Power UniversityJilin 132012China Key Laboratory of Smart Grid of Ministry of Education Key Laboratory of Smart Energy&Information Technology of Tianjin MunicipalityTianjin UniversityTianjin 300072China Department of Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN37996USA.

Nowadays,transmission system operators(TSOs)encounter the challenges of securely operating power grids with high penetration of *** this context,more flexibility is needed than ever to maintain system *** rapid development of coordinated transmission and distribution technology recently,active distribution networks(ADNs)which have abundant flexible resources,have the potential to provide flexibility to the ***,an integrated transmission-distribution flexibility market is proposed in this *** the proposed framework,the energy market is first cleared to obtain baseline generation *** the baseline generation schedules are treated as inputs to the flexibility ***,the integrated flexibility market is cleared to facilitate flexibility trading between transmission and distribution *** preserve the data privacy of different market participants,an alternating direction method of multipliers(ADMM)based method is utilized to clear the markets in a distributed *** the energy market and flexibility market-clearing model,transmission network market clearing models are linear programming(LP)models,and distribution network market clearing models are second order cone programming(SOCP)*** the proposed method,only limited information is exchanged between TSO and *** studies are conducted on a revised IEEE 30-bus transmission network with two 33-node *** results demonstrate the proposed flexibility market framework can enhance competitiveness of generation companies in the transmission network and distributed generators(DGs)in the ***,flexibility purchasing cost is reduced by 17.7%compared to traditional flexibility supplied by generators according to the case study results,and ADNs can gain additional flexibility profit by providing flexibility.

关键词： ADMM ADN energy market flexibility market TSO-DSO coordination

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A Deep Learning Approach for Detecting Diabetic Retinopathy

A Deep Learning Approach for Detecting Diabetic Retinopathy

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2024 International Conference on computer and Applications, ICCA 2024

作者： Nabil, Mohamed Hossam Hassan Hammam, Laila Bastawrous, Hany Ayad Ebrahim, Gamal A. The British University in Egypt Electrical Engineering Department Cairo Egypt Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Ain Shams University Faculty of Engineering Computer and Systems Engineerig Department Cairo Egypt

ISBN: (纸本)9798350367560

The World Health Organization (WHO) reports that diabetic retinopathy affects one-third of diabetics, regardless of their stage of the disease. Several research efforts are focused on its automated detection and diagnosis. Identifying diabetic retinopathy is crucial due to the damage that occurs to the blood vessels of the eye retina, leading to vision blur or even complete blindness. Thus, an annual checkup is needed for people with diabetes. Moreover, uncontrolled sugar levels for diabetes patients could worsen the current stage of diabetic retinopathy. Consequently, automated detection can greatly contribute to the treatment of disease. This can be carried out through several algorithms, including deep learning models and support vector machines, in addition to transfer learning. This contribution proposes a new approach for diabetic retinopathy automated detection based on convolutional neural network (CNN) models. The proposed model provides both binary and multi-class detection. Both scenarios have shown promising results, where the training accuracies of both the binary classification and the multi-class are 92% and 94%, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Responsible Music Genre Classification Using Interpretable Model-Agnostic Visual Explainers

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SN computer science 2025年第1期6卷 1-26页

作者： Murindanyi, Sudi Hamza, Kyamanywa Kagumire, Sulaiman Marvin, Ggaliwango Department of Computer Science Makerere University Kampala Uganda Department of Electrical Engineering Korea University 145 Anam-ro Seongbuk-gu Seoul South Korea

The responsible artificial intelligence (AI) paradigm requires machine learning (ML) and AI engineers to ensure transparent and interpretable intelligent models across domains. This requirement becomes even more complex and crucial when dealing with feature learning using sound data, as deriving model explainers in this context is a more detailed and sophisticated process. In this work, we demonstrate a responsible approach to AI modeling and leverage three explainable artificial intelligence (XAI) tools to derive and establish explainers for the music genre classification model-agonistically. Explain like am 5 (ELi5), Shapley Additive exPlanations (SHAP), and Local Interpretable Model-agnostic Explanations (LIME) were particularly used to interpret and simplify the model’s decision-making processes regardless of their discrete mathematical foundations. This transparency provides a deeper understanding of sound feature patterns and characteristics that inform genre classes for the models through graphical and qualitative feature contributions to explain the model’s justification. We developed convolutions neural networks (CNNs) with and without cross-validation and a vision transformer (ViT) approach utilizing MobileNets. Ultimately, the CNN with cross-validation demonstrated superior performance, achieving 80% accuracy on the test set and 84% accuracy on the validation set. This work advances the border of music intelligence research and promotes the broader cause of responsible AI to ensure that complex models remain comprehensible and accountable. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning Model interpretability Music genre Responsible AI

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Optimizing QoE in IoT-Based Video Streaming through Deep Learning Algorithms 6

Optimizing QoE in IoT-Based Video Streaming through Deep Lea...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Darwich, Mahmoud Khalil, Kasem Bayoumi, Magdy University of Mount Union Department of Mathematics and Computer Science AllianceOH44601 United States University of Mississippi Department of Electrical and Computer Engineering MS38677 United States University of Louisiana Department of Electrical and Computer Engineering LafayetteLA70504 United States

ISBN: (纸本)9798350344349

The demand for video streaming services over Internet of Things (IoT) networks has surged, yet maintaining a high Quality of Experience (QoE) remains challenging due to network heterogeneity and resource constraints. This paper presents an innovative deep learning-based approach to optimize QoE in IoT-based video streaming. Leveraging convolutional neural networks (CNN) and long short-Term memory (LSTM) networks, the proposed framework dynamically adapts video streaming parameters in real-Time, such as bit rate, frame rate, and resolution, based on the existing network conditions and device capabilities. Through extensive simulations and real-world deployments, our approach exhibited a 24.5% reduction in re-buffering ratio, a 12.5% increase in average bitrate, and a 15% improvement in video quality measured by SSIM, compared to conventional methods. Furthermore, it reduced network bandwidth consumption by up to 150% without compromising on video quality. These results underscore the effectiveness of applying deep learning algorithms to optimize video streaming in complex IoT environments. © 2024 IEEE.

关键词： Video streaming

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Enhancing Healthcare Monitoring Systems: A Case Analysis in Optimization 18

Enhancing Healthcare Monitoring Systems: A Case Analysis in ...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Lalit, Mohit Bathla, Gaurav Singh, Surender Chandigarh University Computer Science and Engineering Department Mohali India Career Program Code Quotient Mohali India

ISBN: (纸本)9789380544519

In the past few years, fog computing (FC) has emerged as a promising complement to cloud computing. It offers reduced latency, minimal bandwidth consumption, and real-time data transfer. In healthcare, particularly in IoT-enabled systems, FC integration has become pivotal for real-time monitoring and immediate data transfer to health experts. The researchers all around the world proposed and developed various communication frameworks and come up with certain outputs in terms of quality-of-service parameters (QoS). However, these QoS parameters are not always appropriate for effective execution of the application. Following that, this study explores the integration of FC with multi-objective Optimization Algorithms (such as FFLY and GWO) to optimize crucial quality of service (QoS) metrics using a proposed linear function to optimize multi objectives, essential for sustained communication. The research focuses on optimizing multi objectives in healthcare monitoring systems. Experimental results reveal the superiority of the Grey Wolf Optimizer (GWO) over the Firefly Algorithm (FFLY). This study emphasizes the crucial significance of multi-objective optimisation algorithms in optimizing critical parameters for successful healthcare communication frameworks, which can lead to improvements in healthcare monitoring efficiency. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Fog Computing Healthcare 4.0 Industry 4.0 IoT Optimization

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Quantum Computing Circuit Design: A Tutorial 15

Quantum Computing Circuit Design: A Tutorial

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15th International Conference on Advanced Scientific Computing, ICASC 2024

作者： Abdul Wahid, Seham Al Asad, Arghavan Kaur, Rupinder Mohammadi, Farah Toronto Metropolitan University Electrical and Computer Engineering Department Toronto Canada School of Computer Science and Technology Algoma University Brampton Canada

ISBN: (纸本)9798350356526

Recent advancements in computing speed and capacity of Artificial Intelligence (AI) algorithms have reached a saturation level in performance due to the continuous application of Moore's law which resulted in the memory wall phenomenon. Quantum computing (QC), based on the principles of quantum mechanics which include superposition and entanglement, has the potential to contribute to the advancements of AI by providing exponential speedup. Quantum computers use quantum bits, also known as qubits, as the metric to demonstrate the power of quantum technology. Qubits, the fundamental unit of quantum information can exist in two states, 0 and 1, simultaneously, leveraging the principle of superposition. Quantum gates are the building blocks of quantum circuits, operating on qubits to transform one quantum state into another, and are comparative to classical logic gates. Designing and simulating quantum circuits can be completed using the Qiskit library design by IBM. Qiskit is a cloud-based, open access platform to real quantum computers with 5 to 16 qubits. This paper offers a straightforward tutorial on implementing one, two and three-qubit quantum gates, as well as designing quantum circuits using the Qiskit library, illustrated with an example of a quantum half adder implementation. © 2024 IEEE.

关键词： Qubits

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An experimental and numerical approach for optimization of internal and external corrugations with various geometries in cylindrical thin-walled concertina energy absorbers under quasi-static axial load

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Mechanics of Advanced Materials and Structures 2024年第25期31卷 6628-6642页

作者： Rahpeima, Reza Nateghi Boroujeni, Iman Nia, Ali Alavi Graduate institute of biomedical electronics and bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan Department of Mechanical Engineering Tarbiat Modares University Tehran Iran Department of Mechanical Engineering Bu-Ali Sina University Hamedan Iran

Thin-walled tubes have been extensively used as energy absorbers in many engineering structures that are under dynamic or quasi-static loads. In this article, the effect of corrugation and its geometry on the collapse characteristics of aluminum concertina tubes under quasi-static axial load is investigated both experimentally and numerically. The numerical simulations were performed with the use of LS-Dyna commercial software. Then, several chosen samples were tested experimentally to verify the results of the simulation. Forty different samples with four different corrugation geometries including singly isosceles triangular corrugation, continual isosceles triangular corrugation, continual scalene triangular corrugation, and continual semi-circular corrugation, and each with 10 different size dimensions were simulated. Among all of these simulations, six of them, each with two replicates were subjected to experimental tests. Experimental examples are aluminum cylindrical thin-walled tubes with the same thickness, height, and diameter that corrugations with different geometries are applied to them by the use of the cold rolling method. Finally, to describe the findings in more theoretical terms, a comparison between our obtained results and earlier theoretical investigations is made. The results show a significant influence of corrugations application on the improvement of the collapse characteristics of the cylindrical tubes so that the collapse style of intact tubes can be controlled by applying corrugations. The results show that by increasing the amplitude and number of corrugations, the absorbed energy, and the initial maximum force decrease. It is also found that among the different corrugation geometries, the corrugations with singly isosceles triangular geometry have the highest energy absorption as well as the lowest initial maximum force. © 2023 Taylor & Francis Group, LLC.

关键词： Geometry

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