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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Wai, Khaing Hsu Funabiki, Nobuo Aung, Soe Thandar Lu, Xiqin Jing, Yanhui Sandi Kyaw, Htoo Htoo Kao, Wen-Chung Okayama University Department of Information and Communication Systems Okayama Japan Tokyo University of Agriculture and Technology Department of Computer and Information Science Tokyo Japan National Taiwan Normal University Department of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9798350340181

Nowadays, Java has been extensively used in industries as a reliable and portable object-oriented programming (OOP) language. To support novice students in learning Java programming, we have developed a web-based system called Java Programming Learning Assistant System (JPLAS). JPLAS offers the Code Writing Problem (CWP) among several types of exercise problems. A CWP instance requests a student to write a source code that will pass the provided test code in the assignment where the accuracy of the code is verified by running them on JUnit. In Java programming, every student should master basic OOP concepts, which can be challenging for novice students. This paper presents CWP instances for studying six basic OOP concepts including encapsulation, polymorphism, constructor, inheritance, abstract, and interface in JPLAS. Our preliminary evaluations of them confirm their validity. © 2023 IEEE.

关键词： Object oriented programming

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Development of U-Net Architecture for Audio Super Resolution 9

Development of U-Net Architecture for Audio Super Resolution

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9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Gunawan, Teddy Surya Sarif, Muhammad Rusdy Mohd Kartiwi, Mira Ahmad, Yasser Asrul International Islamic University Malaysia Electrical and Computer Engineering Department Kuala Lumpur53100 Malaysia International Islamic University Malaysia Information Systems Department Kuala Lumpur53100 Malaysia

ISBN: (纸本)9798350325218

Audio processing is used in a wide range of applications, including telecommunications and music streaming. Audio quality degradation during transmission and processing is a common issue in these fields, often caused by bandwidth constraints and the use of subpar equipment. This problem is exacerbated when the task requires converting low-quality audio input to high-resolution output, which is difficult for deep neural networks to do. To improve audio superresolution, this paper proposes a novel solution to this problem by embedding a U-Net-based architecture model within deep neural networks. Over 100 iterations, the U-Net architecture was trained, with loss values and Mean Squared Error (MSE) monitored at each epoch. A diverse dataset of audio signals with varying Signal-to-Noise Ratio (SNR) values ranging from 1 dB to 30 dB was used. The model's average SNR of 17.29 dB exceeds thresholds where listener detection of enhancements becomes difficult, demonstrating its ability to preserve subtle audio details. Furthermore, the Log-Spectral Distance (LSD) values revealed a mere 1.41 dB difference between the actual and reconstructed spectrograms, indicating that the model can recover lost information during upsampling. This research suggests a promising method for improving audio quality, particularly when bandwidth constraints or insufficient equipment prevent high-resolution audio transmission and processing. © 2023 IEEE.

关键词： Signal to noise ratio

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Q-Net: A Quantitative Susceptibility Mapping-Based Deep Neural Network for Differential Diagnosis of Brain Iron Deposition in Hemochromatosis 31

Q-Net: A Quantitative Susceptibility Mapping-Based Deep Neur...

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31st IEEE International Conference on Image Processing Challenges and Workshops, ICIPCW 2024

作者： Zabihi, Soheil Rahimian, Elahe Khademi, Sadaf Sharma, Soumya Sethi, Sean K. Gharabaghi, Sara Asif, Amir Haacke, E. Mark Jog, Mandar S. Mohammadi, Arash Concordia University Electrical and Computer Engineering Montreal Canada Concordia University Concordia Institute for Information Systems Engineering Montreal Canada Western University London Movement Disorders Centre London Health Sciences Centre London Canada Bingham Farms SpinTech MRI MI United States

ISBN: (纸本)9798331515942

Brain iron deposition, in particular deep gray matter nuclei, increases with advancing age. Hereditary Hemochromatosis (HH) is the most common inherited disorder of systemic iron excess in Europeans and recent studies claimed high brain iron accumulation in patient with Hemochromatosis. In this study, we focus on Artificial Intelligence (AI)-based differential diagnosis of brain iron deposition in HH via Quantitative Susceptibility Mapping (QSM), which is an established Magnetic Resonance Imaging (MRI) technique to study the distribution of iron in the brain. Our main objective is investigating potentials of AI-driven frameworks to accurately and efficiently differentiate individuals with Hemochromatosis from those of the Healthy Control (HC) group. More specifically, we developed the Q-Net framework, which is a data-driven model that processes information on iron deposition in the brain obtained from multi-echo gradient echo imaging data and anatomical information on T1-Weighted images of the brain. We illustrate that the Q-Net framework can assist in differentiating between someone with HH and HC of the same age, something that is not possible by just visualizing images. The study is performed based on a unique dataset that was collected from 52 subjects with HH and 47 HC. The Q-Net provides a differential diagnosis accuracy of 83.16% and 80.37% in the scan-level and image-level classification, respectively. © 2024 IEEE.

关键词： Brain mapping

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Adversarial Attacks in Problem Space for VBA Code Samples 1st

Adversarial Attacks in Problem Space for VBA Code Samples

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1st International Symposium on Intelligent Computing and Networking, ISICN 2024

作者： Fehrman, Brian Akowuah, Francis Xu, Shengjie Department of Electrical Engineering and Computer Science South Dakota Mines Rapid CitySD57701 United States Department of Management Information Systems San Diego State University San DiegoCA92182 United States

ISBN: (纸本)9783031674464

Machine learning is being used more frequently in cyber security. One area is in antivirus software. Learning-based antivirus software is not perfect, since threat actors can use adversarial data to craft attacks against these learning-based security products. This paper focuses on using machine learning to craft attacks against Microsoft (MS) Windows Defender. The goal of this work is to provide tooling and knowledge for: security vendors to tighten the security of their products, security professionals to aid in showcasing risks to customers, and law enforcement to help discover the locations and identities of cyber criminals. The attacks focus on modifying Visual Basic for Applications (VBA) code samples to flip Defender’s classification of those files. The modifications are done to the code itself (i.e., problem space) rather than just in feature space. The project attempts to extract information from MS Windows Defender to help craft the attacks. Preliminary results showed that the classification of some of the files was changed after targeted modification and that the attacks were feasible. Additional work will be conducted to further increase the reliability of the attacks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Invertibility of Discrete-Time Linear systems with Sparse Inputs

Invertibility of Discrete-Time Linear Systems with Sparse In...

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IEEE Conference on Decision and Control

作者： Kyle Poe Enrique Mallada René Vidal Applied Mathematics and Computational Science Group University of Pennsylvania PA Mallada is with the Department of Electrical and Computer Engineering Johns Hopkins University MD Departments of Electrical and Systems Engineering Radiology Computer and Information Science Statistics and Data Science University of Pennsylvania PA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

One of the fundamental problems of interest for discrete-time linear systems is whether its input sequence may be recovered given its output sequence, a.k.a. the left inversion problem. Many conditions on the state space geometry, dynamics, and spectral structure of a system have been used to characterize the well-posedness of this problem, without assumptions on the inputs. However, certain structural assumptions, such as input sparsity, have been shown to translate to practical gains in the performance of inversion algorithms, surpassing classical guarantees. Establishing necessary and sufficient conditions for left invertibility of systems with sparse inputs is therefore a crucial step toward understanding the performance limits of system inversion under structured input assumptions. In this work, we provide the first necessary and sufficient characterizations of left invertibility for linear systems with sparse inputs, echoing classic characterizations for standard linear systems. The key insight in deriving these results is in establishing the existence of two novel geometric invariants unique to the sparseinput setting, the weakly unobservable and strongly reachable subspace arrangements. By means of a concrete example, we demonstrate the utility of these characterizations. We conclude by discussing extensions and applications of this framework to several related problems in sparse control.

关键词： Linear systems Geometry Sufficient conditions Systematics Heuristic algorithms Standards

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Dispersion compensating fiber with Brillouin fiber laser generation

Dispersion compensating fiber with Brillouin fiber laser gen...

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2023 Al-Sadiq International Conference on Communication and information Technology, AICCIT 2023

作者： Ali, Hasanain Naser Abd Harun, Sulaiman Wadi Arsad, Norhana Abdali, Taj-Aldeen Naser Al-Khaleefa, Ahmed Salih Hassan, Mustafa H Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and Systems Engineering Bangi Malaysia Faculty of Engineering University of Malaya Photonics Engineering Laboratory Department of Electrical Engineering Kuala Lumpur Malaysia University of Misan Department of Electronic Computer Center Misan Iraq University of Misan Faculty of Education Department of Physics Misan Iraq Imam Ja'afar Al-Sadiq University College of Information Technology Department of Computer Technical Engineering Al-Muthanna Iraq

ISBN: (纸本)9798350341881

Short linewidth light lasers are essential for a wide range of applications, including quantum computing, spectroscopy, and sensing. Stimulated Brillouin scattering is an intriguing method for achieving extremely coherent light laser output. The demonstration of an unstable pulsed Brillouin erbium fiber laser (BFL) operating at kHz is shown here. The BFL works at 1550.1 nm, which is 0.09 nm higher than the Brillouin pump wavelength since the dispersion compensating fiber was pumped over the 24.77 mW threshold. It has an extreme power of 0.7 dBm, a side-mode suppression ratio of 29 dB, and a pump power of 59.12 mW at 980 nm. Due to the intrinsic instability in relaxation oscillation, which generates the nonlinear self-pulsing mechanism in the BEFL cavity, the BEFL produced a pulse train running at 200.9 kHz with a 24.77 mW pump. The pulse frequency was raised to 3.02 MHz. The pump power has been increased to 59.12 mW. Yet, as the pump power was raised further, more than one pulse was produced. This is the first example of generating kHz pulses in a BFL cavity. The laser system is straightforward, small, and all-fiber. These are the attempts of experimental work to realize the BFL with Q-switched multi-wavelength output using a specific length of DCF to generate the pulses. © 2023 IEEE.

关键词： Fiber lasers

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Enhanced Grid-Forming Inverter Control Through Integral Sliding Mode Control in a Cascaded Framework 4

Enhanced Grid-Forming Inverter Control Through Integral Slid...

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4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Rayane, Khaled Rabhi, Abdelhamid Oubbati, Brahim Khalil Benzoubir, Mohammed University of Laghouat LACoSERE Lab Laghouat Algeria Texas A and M University at Qatar Qatar Foundation Department of Electrical and Computer Engineering Doha Qatar University of Picardie Jules Verne Laboratory of Modelisation Information and Systems-MIS France

ISBN: (纸本)9798350306262

The microgrid (MG) relies heavily on the grid-forming inverter (GFI), making it a crucial component. Therefore, precise and adaptable control of the GFI is essential for microgrid operations due to its pivotal role in shaping voltage and regulating frequency. In this context, this paper introduces a Integral Sliding Mode Control (ISMC) based cascaded approach for controlling the GFI system. The primary goal of this control strategy is to produce a three-phase sinusoidal voltage with a specified amplitude while minimizing harmonic distortion in the output voltage under varying load conditions. The key advantage of the proposed GFI controller lies in its ability to deliver superior performance, characterized by low Total Harmonic Distortion (THD), rapid dynamic tracking capabilities, and robustness in the face of load fluctuations. A comparative assessment is conducted between the conventional repetitive controller and the newly proposed method, considering linear and nonlinear load scenarios. The simulation results provide strong validation for the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Sliding mode control

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Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting

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computers, Materials & Continua 2024年第9期80卷 4997-5027页

作者： Milos Dobrojevic Luka Jovanovic Lepa Babic Miroslav Cajic Tamara Zivkovic Miodrag Zivkovic Suresh Muthusamy Milos Antonijevic Nebojsa Bacanin Technical Faculty Singidunum UniversityBelgrade11000Serbia Informatics and Computing Singidunum UniversityBelgrade11000Serbia Business Economics Singidunum UniversityBelgrade11000Serbia Computing and Informatics Sinergija UniversityBijeljina76300Bosnia and Herzegovina Department for Information Systems and Technologies University“Union Nikola Tesla”Cara DusanaBelgrade11080Serbia Department for Computer Science and Informatics School of Electrical EngineeringUniversity of BelgradeBelgrade11000Serbia Department of Electrical and Electronics Engineering Kongu Engineering College(Autonomous)PerunduraiErode638060India Department of Mathematics Saveetha School of Engineering(Deemed to be University)SIMATS ThandalamChennai602105India MEU Research Unit Middle East UniversityAmman11831Jordan

Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones,computers,or *** can occur through various channels,such as social media,text messages,online forums,or gaming *** involves using technology to intentionally harm,harass,or intimidate others and may take different forms,including exclusion,doxing,impersonation,harassment,and ***,due to the rapid growth of malicious internet users,this social phenomenon is becoming more frequent,and there is a huge need to address this ***,the main goal of the research proposed in this manuscript is to tackle this emerging challenge.A dataset of sexist harassment on Twitter,containing tweets about the harassment of people on a sexual basis,for natural language processing(NLP),is used for this *** algorithms are used to transform the text into a meaningful representation of numbers for machine learning(ML)input:Term frequency inverse document frequency(TF-IDF)and Bidirectional encoder representations from transformers(BERT).The well-known eXtreme gradient boosting(XGBoost)ML model is employed to classify whether certain tweets fall into the category of sexual-based harassment or ***,with the goal of reaching better performance,several XGBoost models were devised conducting hyperparameter tuning by *** this purpose,the recently emerging Coyote optimization algorithm(COA)was modified and adjusted to optimize the XGBoost ***,other cutting-edge metaheuristics approach for this challenge were also implemented,and rigid comparative analysis of the captured classification metrics(accuracy,Cohen kappa score,precision,recall,and F1-score)was ***,the best-generated model was interpreted by Shapley additive explanations(SHAP),and useful insights were gained about the behavioral patterns of people who perform social harassment.

关键词： Coyote optimization algorithm NLP TF-IDF BERT XGBoost online harassment and cyberbullying metaheuristics

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Contrast enhancement of optical videoscope images

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Iran Journal of computer Science 2023年第3期6卷 261-275页

作者： Ammar, Reda Aboshosha, Sahar El-Hag, Noha A. Saifeldeen, Reda El-Shafai, Walid El-Banby, Ghada M. Ashiba, Huda I. Khalaf, Ashraf A. M. Elazm, Atef Abou El-Rabaie, El-Sayed M. Abd El-Samie, Fathi E. El-Safrawey, Amir Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Comm. Faculty of Engineering Minia University Minya Egypt Department of Management of Information Systems Higher Institute of Commercial Science El-Mahala El-Kobra Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Communications Engineering Bilbis Higher Institute of Engineering Sharqia Bilbis Egypt Security Engineering Laboratory Computer Science Department Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia

The videoscope (VS) images have poor quality and low contrast. Hence, in this paper, three proposed frameworks to improve the quality of VS images are presented. The first framework depends on contrast-limited adaptive histogram equalization (CLAHE) with adaptive gamma correction. The second framework depends on homomorphic processing. The third framework is based on the homomorphic enhancement with histogram equalization. The first one is superior from the entropy perspective, while the third one is superior from the contrast perspective. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Fuzzy enhancement Histogram equalization Homomorphic enhancement Spectral entropy

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Evolutionary-based Coordination of Multi-Robot systems with Dynamic Constraints

Evolutionary-based Coordination of Multi-Robot Systems with ...

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IEEE Symposium on systems and information engineering Design, SIEDS

作者： Vihar Shah Matthew Heeter Jose Vallarino Patrick Sherman Lauren Bramblett Nicola Bezzo Department of Systems & Information Engineering University of Virginia Charlottesville Virginia Department of Electrical & Computer Engineering University of Virginia Charlottesville Virginia

ISBN: (数字)9798350385144

ISBN: (纸本)9798350385151

Large-scale manufacturing facilities and power plants comprise numerous subsystems that require consistent monitoring and inspection to ensure reliable and secure operations. The use of multiple robotic systems is an expanding, robust, and cost-effective solution for such operations. To enable automated infrastructure monitoring, there are many challenges, such as path planning and task allocation for multiple robots and dynamic constraints. We formulate such challenges as a multiple Traveling Salesman Problem (mTSP) and propose an efficient task assignment solution that uses an evolutionary algorithm considering priority, energy, and time constraints. Our solution incorporates: a digital twin of a monitored environment, A* and artificial potential field methods for path planning and navigation, and human-in-the- loop prioritization. We validate the proposed method with state- of-the-art simulations in Gazebo/ROS for unmanned ground vehicles (UGVs) in cluttered environments.

关键词： Robot kinematics Traveling salesman problems Path planning Production facilities Time factors Resource management Reliability

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