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2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022

作者： Zerrouki, Nabil Houacine, Amrane Harrou, Fouzi Bouarroudj, Riadh Cherifi, Mohammed Yazid Sun, Ying DI2M Laboratory Center for Development of Advanced Technology Algiers Algeria Lcpts Laboratory Algiers Algeria King Abdullah University of Science and Technology Cemse Division Thuwal Saudi Arabia Usthb Computer Science Department Algiers Algeria

ISBN: (数字)9781665451932

ISBN: (纸本)9781665451932

Hand gesture recognition (HGR) is one of the main axes of the Human-computer Interaction (HCI) research field. And computer vision is a very active dedicated research area. However, traditional vision-based methods, like using a fixed camera to record video sequences of sign language, have some serious drawbacks inherent to the fixed camera location, complex lighting conditions, and cluttered backgrounds. Motivated by these potential limitations, the present paper addresses the detection and classification of hand gestures based rather on wearable video monitoring data. A new feature extraction strategy based on five hand's partial occupancy areas in images is provided. And a deep learning formalism, using the Long Short-Term Memory (LSTM) algorithm, has been implemented to ensure an effectual separation between classes. To analyze the performances of the classification, available data have been used for experiments, and both virtual and real museum scenarios are considered. The obtained results demonstrated that the combined five area ratios and LSTM classification were not only able to recognize different hand gestures but it was also able to distinguish between actions with a high degree of similarity (like slide left and slide right classes). The use of deep learning-based LSTM algorithm in the classification phase helped in reducing significantly the number of misclassifications, and achieving an outstanding recognition performance when challenged with real-world data. © 2022 IEEE.

关键词： Feature extraction

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Low-code/No-code Development : A systematic literature review

Low-code/No-code Development : A systematic literature revie...

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

作者： Hind El Kamouchi Mohamed Kissi Omar El Beggar Department of Computer Science Faculty of Sciences and Techniques Laboratory LIM University Hassan II Casablanca Mohammedia Morocco

The emerging trend of Low-code/No-code development has garnered significant attention from both the business and academic communities. This article provides a systematic literature review that explores the different aspects of Low-code/No-code development. The review focuses on gathering state-of-the-art research, methodologies, and frameworks in this field. It also identifies key challenges and benefits associated with Low-code/No-code development. This review aims to provide a comprehensive understanding of the current trends and advancements in this kind of software engineering. This study could serve as a valuable resource for researchers, practitioners, and organizations looking to adopt Low-code/No-code approaches. Overall, this review contributes to the existing body of knowledge by providing insightful findings and suggestions for future research directions in the Low-code/No-code development realm.

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Optimal Link Configuration for Covert Heterogeneous Wireless Networks with Power Constraints

Optimal Link Configuration for Covert Heterogeneous Wireless...

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Annual Conference on Information sciences and Systems (CISS)

作者： Amna Gillani Beatriz Lorenzo Majid Ghaderi Fikadu Dagefu Dennis Goeckel Department of Electrical and Computer Engineering University of Massachusetts Amherst Amherst MA USA Department of Computer Science University of Calgary Calgary Canada U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory Adelphi MD USA

ISBN: (数字)9798331513269

ISBN: (纸本)9798331513276

Heterogeneous Networks (HetNets) leverage multiple communication interfaces (e.g., Wi-Fi, cellular, Bluetooth) seamlessly integrated to enhance connectivity and capacity across diverse environments. These capabilities can be advantageous for covert communication, where the objective is to ensure undetectable transmission in the presence of an adversary. This work investigates optimal power allocation strategies for covert communication within HetNets under maximum power constraints. We propose a polynomial-time (m 2 ) algorithm for optimal link configuration by allocating power across multiple modes. Next, we address network-level covertness by allocating the end-to-end covertness constraint across links in a two-hop system that maximizes throughput. Leveraging the link configuration approach, we derive the optimal power allocation for each mode and link, ensuring the overall transmission remains undetectable. Numerical results demonstrate that the proposed method outperforms existing single-link and two-hop approaches, achieving higher efficiency and security in covert communication across HetNets.

关键词： Wireless networks Heuristic algorithms Interference Throughput Robustness Heterogeneous networks Topology Resource management Security Wireless fidelity

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Snapshot boosting: a fast ensemble framework for deep neural networks

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science China(Information sciences) 2020年第1期63卷 77-88页

作者： Wentao ZHANG Jiawei JIANG Yingxia SHAO Bin CUI Center for Data Science Peking University National Engineering Laboratory for Big Data Analysis and Applications Department of Computer Science Beijing Key Lab of Intelligent Telecommunications Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications Key Lab of High Confidence Software Technologies Department of Computer SciencePeking University

Boosting has been proven to be effective in improving the generalization of machine learning models in many fields. It is capable of getting high-diversity base learners and getting an accurate ensemble model by combining a sufficient number of weak learners. However, it is rarely used in deep learning due to the high training budget of the neural network. Another method named snapshot ensemble can significantly reduce the training budget, but it is hard to balance the tradeoff between training costs and diversity. Inspired by the ideas of snapshot ensemble and boosting, we propose a method named snapshot boosting. A series of operations are performed to get many base models with high diversity and accuracy, such as the use of the validation set, the boosting-based training framework, and the effective ensemble strategy. Last, we evaluate our method on the computer vision(CV) and the natural language processing(NLP) tasks, and the results show that snapshot boosting can get a more balanced trade-off between training expenses and ensemble accuracy than other well-known ensemble methods.

关键词： ensemble learning deep learning boosting neural network snapshot ensemble

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Unified Diffusion-Based Rigid and Non-Rigid Editing with Text and Image Guidance

Unified Diffusion-Based Rigid and Non-Rigid Editing with Tex...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jiacheng Wang Ping Liu Wei Xu School of Electronic Information and Communications Huazhong University of Science and Technology Hubei Key Laboratory of Smart Internet Technology Department of Computer Science and Engineering University of Nevada Reno

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Existing text-to-image editing methods tend to excel either in rigid or non-rigid editing but encounter challenges when combining both, resulting in misaligned outputs with the provided text prompts. In addition, integrating reference images for control remains challenging. To address these issues, we present a versatile image editing framework capable of executing both rigid and non-rigid edits, guided by either textual prompts or reference images. We leverage a dual-path injection scheme to handle diverse editing scenarios and introduce an integrated self-attention mechanism for fusion of appearance and structural information. To mitigate potential visual artifacts, we further employ latent fusion techniques to adjust intermediate latents. Compared to previous work, our approach represents a significant advance in achieving precise and versatile image editing. Comprehensive experiments validate the efficacy of our method, showcasing competitive or superior results in text-based editing and appearance transfer tasks, encompassing both rigid and non-rigid settings.

关键词： Visualization Fuses Text to image

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Dual Mode pMUT for Structural Health Monitoring of Piping Systems in Advanced Reactors

Dual Mode pMUT for Structural Health Monitoring of Piping Sy...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Khan, Talha Masood Sabino, John Xu, Chenxi Obregon, Javier Adkins, Joshua Wilis Daly, Matthew Heifetz, Alexander Kultgen, Derek Wiliam Ozevin, Didem University of Illinois Chicago Department of Civil Materials and Environmental Engineering ChicagoIL United States University of Illinois Chicago Department of Electrical and Computer Engineering ChicagoIL United States Argonne National Laboratory Nuclear Science and Engineering Division LemontIL United States

ISBN: (纸本)9798350346459

The objective of this work is to develop a durable MEMS sensor for in situ monitoring of advanced reactor piping. Existing sensors for structural health monitoring (SHM) in nuclear reactor environments have limited temperature ranges and service lifetimes, owing to material constraints. Micromachined transducers using aluminum nitride (AlN) as a sensing element, and silicon carbide (SiC) as a substrate, have the potential to address this challenge. In this work, piezoelectric Micromachined Ultrasonic Transducers (pMUT) capable of delivering passive (acoustic emission) and active (guided wave) ultrasonic sensing for SHM in a high-temperature environment are studied. These sensors will be able to couple directly to the structures for real-time SHM of advanced reactor piping systems. A customized microfabrication process is used to produce dual-mode sensing operation at a small footprint of 5×5 mm2. This process involves sputtering a 1 μm thick AlN sandwiched between metal and handle layer. The frequency modes of the pMUT device are tuned to 140 kHz by varying the lateral dimensions of the sensor. Sensor locations on piping are determined by generating plane waves using finite element simulations and studying the wave dispersion. With higher sensitivity, our pMUT sensors are capable of detecting the smallest defect energy at high temperatures, while decreasing the number of sensors on piping. © 2023 IEEE.

关键词： Real time systems

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Optimizing Forest Fire Prevention: Intelligent Scheduling Algorithms for Drone-Based Surveillance System 27

Optimizing Forest Fire Prevention: Intelligent Scheduling Al...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Jemmali, Mahdi Melhim, Loai Kayed B. Boulila, Wadii Amdouni, Hajer Alharbi, Mafawez T. College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates MARS Laboratory University of Sousse Sousse Tunisia Department of Computer Science Higher Institute of Computer Science and Mathematics Monastir University Monastir5000 Tunisia Department of Health Information Management and Technology College of Applied Medical Sciences University of Hafr Al Batin Hafr Al Batin39524 Saudi Arabia Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh12435 Saudi Arabia RIADI Laboratory National School of Computer Sciences University of Manouba Manouba Tunisia Ecole Supérieure des Sciences Economiques et Commerciales de Tunis Université de Tunis Tunisia Unit of Scientific Research Applied College Qassim University Buraydah51452 Saudi Arabia

Given the importance of forests and their role in maintaining the ecological balance, which directly affects the planet, the climate, and the life on this planet, this research presents the problem of forest fire monitoring using drones. The forest monitoring process is performed continuously to track any changes in the monitored region within the forest. During fires, drones' capture data is used to increase the follow-up speed and enhance the control process of these fires to prevent their spread. The time factor in such problems determines the success rate of the fire extinguishing process, as appropriate data at the right time may be the decisive factor in controlling fires, preventing their spread, extinguishing them, and limiting their losses. Therefore, this research presented the problem of monitoring task scheduling for drones in the forest monitoring system. This problem is solved by developing several algorithms with the aim of minimizing the total completion time required to carry out all the drones' assigned tasks. System performance is measured by using 990 instances of three different classes. The performed experimental results indicated the effectiveness of the proposed algorithms and their ability to act efficiently to achieve the desired goal. The algorithm RID achieved the best performance with a percentage rate of up to 90.3% with a time of 0.088 seconds. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： algorithms drone fire Forest monitoring

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Study of Ultra-Thin Cadmium Telluride Solar Cells

Study of Ultra-Thin Cadmium Telluride Solar Cells

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IEEE Conference Photovoltaic Specialists (PVSC)

作者： Mariyam Mukhtar Elisa Artegiani Narges Torabi Ikram Anefnaf Jessica Jazmine Nicole Barrantes Matteo Meneghini Alessandro Romeo Department of Computer Science LAPS-Laboratory of Photovoltaic and Solid-State Physics University of Verona Verona Italy Department of Information Engineering University of Padova Padova Italy

ISBN: (数字)9781665464260

ISBN: (纸本)9781665475822

The absorber material CdSeTe/CdTe has a high absorption coefficient of 10 4 cm 1 , allowing for extremely thin absorbers, with a graded bandgap from 1.40 to 1.50 eV, which is very close to the optimum for single junction solar cells. In this work, we have fabricated different absorber thicknesses ranging from 0.5 m to 0.8 m to study ultra-thin absorbers for CdSeTe/CdTe solar cells. Decreasing the absorber thickness, the costs and the environmental consumption are strongly reduced. In this paper, we analyze the impact of the thickness reduction on the electrical parameters of the devices containing Se. Currently, our best-performing ultra-thin CdSeTe/CdTe solar cell has an efficiency of 11 %.

关键词： Photovoltaic systems Costs Spontaneous emission Photonic band gap Photovoltaic cells Wavelength measurement Doping Junctions Tellurium Electrons

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Comparative Study between Global and Local Explainable Models

Comparative Study between Global and Local Explainable Model...

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

作者： Sidi Mohamed Dafali Mohamed Kissi Omar El Beggar Laboratory LIM Department of Computer Science Faculty of Sciences and Techniques University Hassan II Casablanca Mohammedia Morocco

Despite opaque machine learning models outperform transparent models, users are still unable to comprehend and trust their ***, Explainable Artificial Intelligence (XAI) becomes a prominent research area. The main objective of this discipline is providing new techniques, tools and models that explain how opaque machine learning models operate to give predictions or simply offer some information about system *** this article, we present an experimental evaluation of explainable models used in XAI, namely: LIME, SHAP, ANCHOR and EBM. Those models are applied on the results of two opaque machine learning models: Random Forest and XGBoost. Our experimental evaluation covers various aspects for comparison including:•Examining the explainability coverage of methods.•Comparing explanations provided by each method.

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Improving Chinese Spelling Correction by Ranking

Improving Chinese Spelling Correction by Ranking

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International Joint Conference on Neural Networks (IJCNN)

作者： Junjia Feng Shuai Wang Wenbiao Yin Lin Shang Department of Computer Science and Technology State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Chinese Spelling Check (CSC) aims to detect and correct Chinese spelling errors. Most Chinese spelling errors are the misuse of semantically, phonetically or graphically similar characters. Previous state-of-the-art works on the CSC task pursue transitions from misspelled sentences to correct sentences directly. However, it is difficult to force the current CSC methods to find the correct answer at one run. Thus, we propose a simple and effective method for CSC task by making fully use of the trained model to generate multiple candidate sentences and simply ranking to select the best, in which no additional training and parameters are required. The experimental results show that our approach outperforms previous methods and achieves the state-of-the-art performances.

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