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International Conference on Communications, Information System and computer engineering (CISCE)

作者： Zhen Zhang Yaqi Gong Xiangguo Zhao Jun Chen Jianyu Ren Jintao Ouyang School of Electrical Engineering Yingkou Institute of Technology Yingkou China School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China School of Software Northeastern University Shenyang China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

To solve the problems of low efficiency of algorithm execution and not fully considering the POI needs of users in different time-periods in point-of-interest (POI) recommendation. In this paper, propose a Multiple time-periods POI recommendation model MP-DELM based on distributed extreme learning machine (DELM). According to the user's different periods and different types of POI access requirements, the data set was processed in different periods; extract POI preference features: distance preference feature, personalized preference feature, popularity preference feature, and friend preference feature, in which for the friend preference feature, social friend feature and the trajectory feature are integrated for the first time, and a new trajectory friend similarity calculation method is proposed; in order to improve the efficiency of POI recommendation, improve DELM classifier. And the online sequential extreme learning machine (OS-ELM) is used to update training data in real time. Finally, we prove that the MP-DELM recommendation model can effectively improve the accuracy and efficiency of POI recommendation in the real datasets.

关键词： Extreme learning machines Social networking (online) Computational modeling Training data Feature extraction Real-time systems Vectors

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Depth-Centric Dehazing and Depth-Estimation from Real-World Hazy Driving Video 39

Depth-Centric Dehazing and Depth-Estimation from Real-World ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Fan, Junkai Wang, Kun Yan, Zhiqiang Chen, Xiang Gao, Shangbing Li, Jun Yang, Jian PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology China Huaiyin Institute of Technology China

ISBN: (纸本)157735897X

In this paper, we study the challenging problem of simultaneously removing haze and estimating depth from real monocular hazy videos. These tasks are inherently complementary: enhanced depth estimation improves dehazing via the atmospheric scattering model (ASM), while superior dehazing contributes to more accurate depth estimation through the brightness consistency constraint (BCC). To tackle these intertwined tasks, we propose a novel depth-centric learning framework that integrates the ASM model with the BCC constraint. Our key idea is that both ASM and BCC rely on a shared depth estimation network. This network simultaneously exploits adjacent dehazed frames to enhance depth estimation via BCC and uses the refined depth cues to more effectively remove haze through ASM. Additionally, we leverage a non-aligned clear video and its estimated depth to independently regularize the dehazing and depth estimation networks. This is achieved by designing two discriminator networks: DMFIR enhances high-frequency details in dehazed videos, and DMDR reduces the occurrence of black holes in low-texture regions. Extensive experiments demonstrate the proposed method outperforms current state-of-the-art techniques in both video dehazing and depth estimation tasks, especially in real-world hazy scenes. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Discriminators

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An Output Feedback Game-Theoretic Approach for Defense Against Stealthy GNSS Spoofing Attacks

An Output Feedback Game-Theoretic Approach for Defense Again...

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American Control Conference (ACC)

作者： Surabhi Athalye Filippos Fotiadis Kyriakos G. Vamvoudakis Jérôme Hugues School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA Carnegie Mellon University/Software Engineering Institute Pittsburgh PA USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We employ a game-theoretic approach to mitigate stealthy spoofing attacks on an aerial cyber-physical system. The attacker's objective is to drive the vehicle away from its nominal trajectory while misleading the system operator of the adversarial deviation. We characterize this as a dual actuation-deception attack; the former involves corrupting the vehicle's actuating input, and the latter is done by spoofing the measurable output; that is, the acceleration effort and the Global Navigation Satellite System (GNSS) sensor reading, respectively. The attack is designed to be stealthy, implying that its effect on the system's trajectory is indiscernible from that of a naturally occurring disturbance. The defender aims to counter such an attack and steer the aerial vehicle back towards its nominal path. We couple receding horizon control and game-theoretic methods to derive optimal attack and defense policies.

关键词： Accelerometers Global navigation satellite system Cyber-physical systems Trajectory Output feedback

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Development of a Control System for a Lower Limb Exoskeleton Rehabilitation Robot for Stroke Patients with Standing Instability

Development of a Control System for a Lower Limb Exoskeleton...

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Cognitive Computing and Complex Data (ICCD), International Conference on the

作者： Muxin Du Qingqing Wang Liucun Zhu Zhen Liu Lei Shi Yudong Fang Yinxi Gu School of Mechanical and Marine Engineering Beibu Gulf University Qinzhou China School of Electric and Information Engineering Beibu Gulf University Qinzhou China Sentinel Institute of Science and Technology Beibu Gulf University Qinzhou China School of Information Nagasaki Institute of Applied Science Nagasaki Japan Guangzhou Shiyuan Electronic Technology Company Limited Qinzhou China Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai'an China

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

Lower-limb exoskeleton robots can medically assist stroke patients in standing and walking, but there is little research on lower-limb exoskeleton robots that assist in standing balance. In this paper, we design the system of a lower limb exoskeleton rehabilitation robot that can assist in standing balance. We performed kinematic modeling with OpenSim and forward dynamics simulation with SCONE. Having identified the muscle groups and joints that affect standing balance more significantly. This paper focuses on the effects of the hip and iliopsoas muscles on standing balance. We have developed a control system for a lower-limb exoskeleton rehabilitation robot that realizes: when inputting a hip joint change angle signal, an opposite moment and angle are output to control the lower limb exoskeleton rehabilitation robot to assist the patient to achieve standing balance. The robotic system was simulated and analyzed using Matlab and the results showed the effectiveness of the system to keep the patient in standing balance.

关键词： Legged locomotion Limbs Exoskeletons Stroke (medical condition) Muscles Assistive robots Control systems MATLAB Robots Hip

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Research on Campus Physical Measurement System Based on CNN-LSTM

Research on Campus Physical Measurement System Based on CNN-...

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第二十届分布式计算及其应用国际学术研讨会

作者： Mengzhong Wei Yuting Fu Chao Li Yuanyuan Li Wanli Feng Quanyin Zhu Huaiyin Institute of Technology Computer & Software Engineering

In response to the 14 th Five-Year Plan and the2035 long-term goal outline,the goals of building smart communities and smart industries are clearly *** from the campus,there are many physical test projects in colleges and ***,so the campus physical test is transformable and *** article first proposes the idea of building a smart body measurement system;then,analyzes the CNN-LSTM(Convolutional Neural Network-Long short term memor)algorithm that is mainly used in the construction of the system;secondly,it analyzes the accuracy of the recognition of specific action processes and the debugging process of the actual *** out optimization and improvement;finally,make a report on the enforceability of the campus physical test system.

关键词： CNN-LSTM human pose estimation smart application Opencv

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KDTL: knowledge-distilled transfer learning framework for diagnosing mental disorders using EEG spectrograms

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Neural Computing and Applications 2024年第30期36卷 18919-18934页

作者： Singh, Shreyash Jadli, Harshit Padma Priya, R. Surya Prasath, V.B. Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore India Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Computer Science University of Cincinnati CincinnatiOH45221 United States

Electroencephalography (EEG) is a well-known modality in neuroscience and is widely used in identifying and classifying neurological disorders. This paper investigates how EEG data can be used along with knowledge distillation-based deep learning models to detect mental disorders like epilepsy and sleep disorders. The EEG signals are converted into time–frequency plots using short-time Fourier transforms. Further, we propose a novel methodology for using knowledge distillation-based transfer learning (KDTL). Knowledge distillation is becoming quite prevalent in the machine learning field and is associated with various applications in our work;we propose its use in the detection of mental disorders from EEG spectrograms. We convert the EEGs using short-term Fourier transform to obtain time–frequency representation and apply teacher-student by first training a large teacher model and use knowledge distillation to train a student model. In our experiments, we found that ConvNext teacher and MobileNet student combination obtained better results. Our proposed KDTL approach is tested on two datasets with multiple cases, namely the Bonn and ISRUC datasets and obtain 98% and 95% accuracies, respectively. Further experimental results show that the overall KDTL methodology can obtain high classification accuracy across both datasets in binary and multiclass classifications and proves to be better than multiple prior works. Further, our KDTL approach provides a way to train lightweight models which have a smaller number of trainable parameters and thereby constitute lower training time overall. Our proposed KDTL-based approach obtained accurate results in diagnosing mental disorders from EEG spectrograms. Compared to other related methods, KDTL outperformed across tasks with obtained good results in both binary and multiclass classifications. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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AI Integration in the IT Professional Workplace: A Scoping Review and Interview Study with Implications for Education and Professional Competencies 2024

AI Integration in the IT Professional Workplace: A Scoping R...

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29th Working Group Reports on Innovation and technology in computer Science Education, ITiCSE WGR 2024

作者： Clear, Tony Cajander, Åsa Clear, Alison Mcdermott, Roger Daniels, Mats Divitini, Monica Forshaw, Matthew Humble, Niklas Kasinidou, Maria Kleanthous, Styliani Kultur, Can Parvini, Ghazaleh Polash, Mohammad Zhu, Tingting Department of Computer Science and Software Engineering Auckland University of Technology Auckland New Zealand Department of Information Technology Uppsala University Uppsala Sweden School of Business Eastern Institute of Technology Auckland New Zealand School of Computing Robert Gordon University Aberdeen United Kingdom Dpt. of Computer Science Norwegian University of Science and Technology Trondheim Norway The Alan Turing Institute Newcastle Upon Tyne United Kingdom Open University of Cyprus Nicosia Cyprus The Open University of Cyprus Nicosia Cyprus School of Computer Science Carnegie Mellon University PittsburghPA United States Manning College of Information and Computer Sciences University of Massachusetts Amherst Amherst United States School of Computer Science University of Sydney Sydney Australia Department of Geography Geomatics and Environment University of Toronto Mississauga Toronto Canada School of Computer Science Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400712081

As Artificial Intelligence (AI) continues transforming workplaces globally, particularly within the Information technology (IT) industry, understanding its impact on IT professionals and computing curricula is crucial. This research builds on joint work from two countries, addressing concerns about AI's increasing influence in IT sector workplaces and its implications for tertiary education. The study focuses on AI technologies such as generative AI (GenAI) and large language models (LLMs). It examines how they are perceived and adopted and their effects on workplace dynamics, task allocation, and human-system interaction. IT professionals, noted as early adopters of AI, offer valuable insights into the interplay between AI and work engagement, highlighting the significant competencies required for digital workplaces. This study employs a dual-method approach, combining a systematic and multi-vocal literature review and qualitative research methods. These included a thematic analysis of a set of 47 interviews conducted between March and May of 2024 with IT professionals in two countries (New Zealand and Sweden). The research aimed to understand the implications for computing students, education curricula, and the assessment of emerging professional competencies. The literature review found insufficient evidence addressing comprehensive AI practice methodologies, highlighting the need to both develop and regulate professional competencies for effective AI integration. Key interview findings revealed diverse levels of GenAI adoption, ranging from individual experimentation to institutional integration. Participants generally expressed positive attitudes toward the technology and were actively pursuing self-learning despite some concerns. The themes emerging from the interviews included AI's role in augmenting human tasks, privacy and security concerns, productivity enhancements, legal and ethical challenges, and the evolving need for new competencies in the workplace.

关键词： artificial intelligence

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Data Poisoning Attack to X-armed Bandits 21

Data Poisoning Attack to X-armed Bandits

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21st IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2022

作者： Luo, Zhi Li, Youqi Chen, Lixing Xu, Zichuan Zhou, Pan Huazhong University of Science and Technology School of Cyber Science and Engineering China Beijing Institute of Technology School of Cyberspace Science and Technology School of Computer Science China Shanghai Jiao Tong University Institute of Cyber Science and Technology China Dalian University of Technology School of Software China Huazhong University of Science and Technology Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China

ISBN: (纸本)9781665494250

X-armed bandits have achieved the state-of-the-art performance in optimizing unknown stochastic continuous functions, which can model many machine learning tasks, specially in big data-driven personalized recommendation. However, bandit algorithms are vulnerable to adversarial attacks. Existing works mainly focus on attacking multi-armed bandits in discrete setting;nevertheless, the attacks against X-armed bandits in continuous setting have not been well explored. In this paper, we aim to bridge this gap and investigate the robustness problem for the X-armed bandits. Specifically, we consider data poisoning attack and propose an attack algorithm named Confidence Poisoning Attack algorithm, which could hijack the clean tree-based X-armed bandits algorithm, i.e., high confidence tree (HCT) and make it choose the nodes including the arm targeted by the attacker very frequently with a sub-linear attack cost, i.e., O(Tα)(0 © 2022 IEEE.

关键词： Stochastic systems

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Through the Sci-Fi Lens: Exploring Social Media's Influence on Body Image and Bullying Among Adolescents in Boarding schools 21

Through the Sci-Fi Lens: Exploring Social Media's Influence ...

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21st International Learning and technology Conference, L and T 2024

作者： Mustapha, Jawahir Che Ghazali, Muhammad Azmin Mohamed Abdullah, Munaisyah Sulaiman, Nor Intan Saniah Rahman, Hezlin Aryani Abd Universiti Kuala Lumpur Malaysian Institute of Information Technology Informatics & Analytics Section Kuala Lumpur Malaysia Universiti Kuala Lumpur Malaysian Institute of Information Technology Computer Engineering Tech. Section Kuala Lumpur Malaysia Universiti Kuala Lumpur Malaysian Institute of Information Technology Software Engineering Section Kuala Lumpur Malaysia Universiti Utara Malaysia College of Arts and Science School of Quantitative Sciences Kedah Malaysia Universiti Teknologi Mara Centre of Statistical and Decision Science Studies Faculty of Computer and Mathematical Sciences Selangor Malaysia

ISBN: (纸本)9798350393569

This research investigates the complex relationships between social media, body image, and bullying among adolescent boarding school students, with an emphasis on the Malaysian context. Utilizing science fiction as a conceptual lens, the study presents hypothetical future scenarios to investigate how technological advancements could impact these interconnected issues. The paper seeks to provide nuanced insights into the ethical and policy implications of social media use in boarding schools by drawing on key theories such as Social Comparison Theory, Social-Ecological Model and Uses and Gratifications Theory. Through comparative analysis of hypothetical scenarios, this study aims to provide educators, policymakers, and technologists with a comprehensive understanding of the challenges and opportunities at this intersection. The ultimate objective is to contribute to the ongoing discourse concerning adolescent mental health and to propose actionable strategies for mitigating negative outcomes in the unique context of Malaysian boarding schools. © 2024 IEEE.

关键词： Social networking (online)

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Question-Answer Cross Language Image Matching for Weakly Supervised Semantic Segmentation

arXiv

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arXiv 2024年

作者： Deng, Songhe Zhuo, Wei Xie, Jinheng Shen, Linlin Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China

Class Activation Map (CAM) has emerged as a popular tool for weakly supervised semantic segmentation (WSSS), allowing the localization of object regions in an image using only image-level labels. However, existing CAM methods suffer from under-activation of target object regions and false-activation of background regions due to the fact that a lack of detailed supervision can hinder the model’s ability to understand the image as a whole. In this paper, we propose a novel Question-Answer Cross-Language-Image Matching framework for WSSS (QA-CLIMS), leveraging the vision-language foundation model to maximize the text-based understanding of images and guide the generation of activation maps. First, a series of carefully designed questions are posed to the VQA (Visual Question Answering) model with Question-Answer Prompt engineering (QAPE) to generate a corpus of both foreground target objects and backgrounds that are adaptive to query images. We then employ contrastive learning in a Region Image Text Contrastive (RITC) network to compare the obtained foreground and background regions with the generated corpus. Our approach exploits the rich textual information from the open vocabulary as additional supervision, enabling the model to generate high-quality CAMs with a more complete object region and reduce false-activation of background regions. We conduct extensive analysis to validate the proposed method and show that our approach performs state-of-the-art on both PASCAL VOC 2012 and MS COCO datasets. Code is available at: https://***/CVI-SZU/QA-CLIMS Copyright © 2024, The Authors. All rights reserved.

关键词： Chemical activation

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