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2025 International Workshop on Advanced Imaging Technology, IWAIT 2025

作者： Jian, Muwei Zhong, Yanjie Lam, Kin-Man School of Computer Science and Technology Shandong University of Finance and Economics Jinan China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong

ISBN: (数字)9781510688131

ISBN: (纸本)9781510688124

Medical image segmentation is essential for accurately extracting tissue structures or pathological regions from medical ***, medical image segmentation methods are often influenced by factors such as image noise and irregular shapes, making precise segmentation *** tackle these challenges, this paper proposes a triple-branch medical image segmentation network (TB-Net) that incorporates implicit boundary *** boundary map, acquired through a boundary detection algorithm, is used to restrict the results of the boundary *** experiments indicate that TB-Net achieves state-of-the-art performance on publicly available polyp datasets. © 2024 SPIE.

关键词： Image segmentation

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Facial recognition system based on the Haar cascade classifier method 24

Facial recognition system based on the Haar cascade classifi...

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24th International Conference on Computational Problems of electrical engineering, CPEE 2023

作者： Karpiuk, Nazar Klym, Halyna Vasylchychyn, Ivanna Lviv Polytechnic National University Department of Specialized Computer Systems Lviv Ukraine Lviv Polytechnic National University Department of Theoretical and General Electrical Engineering Lviv Ukraine

ISBN: (纸本)9798350330342

This scientific research is devoted to the analysis and testing of the Haar cascade classifier method for face recognition. The paper also justifies the choice of algorithm and provides a description of the implementation of the system on which the analysis was conducted. During the research, the developed system was tested on a sample of facial photographs that included images at different distances from the camera, different lighting conditions, and with different facial positions in the camera's plane of view. An analysis of the test results was conducted, and conclusions were drawn regarding the factors that should be considered when designing and using a facial recognition system to achieve high accuracy. © 2023 IEEE.

关键词： Face recognition

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Enhancing Multimodal Rumor Detection with Statistical Image Features and Modal Alignment via Contrastive Learning 21st

Enhancing Multimodal Rumor Detection with Statistical Image...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Zhou, Chenyu Li, Xiuhong Li, Zhe Chen, Fan Sheng, Jiabao Chen, Bin Wang, Haoyu School of Computer Science and Technology Xinjiang University Xinjiang China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong Department of Electrical Engineering Stanford University CA United States Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9789819601219

The swift proliferation of multimodal rumors on social media, particularly those with manipulated images and complex intermodal interactions, significantly challenges current detection methods. In response, we utilize statistical image features, including mean and variance, to capture spatial attributes effectively and improve the detection of image-tampered tweets. To tackle complex intermodal correlations, we introduce a contrastive learning approach that aligns features across modalities efficiently. Additionally, we introduce a cross-attention fusion module (CAFM) that enhances the integration of image and text modalities, thereby improving multimodal rumor detection performance. In conclusion, we propose the cross-attention fusion network (ConCAFN), leveraging contrastive learning for robust multimodal rumor detection. Extensive experiments on two real-world datasets confirm the model’s enhanced capability to detect multimodal rumors accurately, demonstrating our methods’ effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Foundry Manufactured 6-bit Resolution, 150µm Long Slow-Light Electro-Optic Modulator for On-Chip Photonic Tensor Computing

Foundry Manufactured 6-bit Resolution, 150µm Long Slow-Ligh...

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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Zhang, Meng Begovic, Amir Yin, Dennis Gangi, Nicholas Gu, Jiaqi Huang, Rena Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering 110 8th Street TroyNY12180 United States Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85281 United States

We demonstrate 6-bit DAC resolution with an ultra-compact slow-light electro-optic modulator. The 10× modulation length reduction enables 31× compute density, 1.17× energy efficiency, and 36.1× energy efficiency per unit area for photonic tensor computing. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Light modulation

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TELEX: Two-Level Learned Index for Rich Queries on Enclave-based Blockchain Systems

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IEEE Transactions on Knowledge and Data engineering 2025年第7期37卷 4299-4313页

作者： Wu, Haotian Tang, Yuzhe Shen, Zhaoyan Tao, Jun Lin, Chenhao Peng, Zhe The Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Syracuse University Department of Electrical Engineering and Computer Science United States Shandong University School of Computer Science and Technology China Southeast University School of Cyber Science and Engineering China Xi'an Jiaotong University Faculty of Electronic and Information Engineering China The Hong Kong Polytechnic University Shenzhen Research Institute Hong Kong

Blockchain has become a popular paradigm for secure and immutable data storage. Despite its numerous applications across various fields, concerns regarding the user privacy and result integrity during data queries persist. Additionally, the need for rich query functionalities to harness the full potential of blockchain data remains an area ripe for exploration. In order to address these challenges, our paper first utilizes a framework based on the Trusted Execution Environment (TEE) and oblivious RAM technique to achieve both privacy and data integrity. To enhance the query efficiency over the entire blockchain, we then devise a two-level learned indexing methodology named TELEX within the TEE for both integer and string keys. We also propose different query processing algorithms for versatile query types, including exact queries, aggregate queries, Boolean queries, and range queries. By implementing the prototype and conducting extensive evaluation, we demonstrate the feasibility and remarkable improvement in efficiency compared to existing solutions. © 1989-2012 IEEE.

关键词： Query languages

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Development of SC Polar Decoder Design Scenario for 5G/6G Telecommunications Applications 17

Development of SC Polar Decoder Design Scenario for 5G/6G Te...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Boiko, Juliy Pyatin, Ilya Eromenko, Oleksander Khmelnytskyi National University Media and Intelligent Technologies Department of Telecommunications Khmelnytskyi Ukraine Khmelnytskyi Polytechnic Professional College Lviv Polytechnic National University Department of Computer Engineering Khmelnytskyi Ukraine Khmelnytskyi National University Department of Physics and Electrical Engineering Khmelnytskyi Ukraine

ISBN: (纸本)9798331520564

The paper considers hardware concepts for implementing a polar decoder based on a Field-Programmable Gate Array (FPGA). The data flow diagram of the successive cancellation (SC) decoder and the scheduling of the partial sum (S) calculation sequence are analyzed. The advantages of the semi-parallel successive cancellation (SPSC) decoder are shown, the decoder delay is determined for different frame lengths. This is achieved by the given architecture of the SPSC decoder, as well as the described architecture of the block for calculating S. A study of a model of a telecommunication channel with polar coding (PC) for different code rates and different digital modulation multiplicities is carried out. The capabilities of the adaptive modulation format and PC for implementing the required channel bandwidth are investigated. It is expected that the results will be useful in developing PC decoders for 5G/6G systems. © 2024 IEEE.

关键词： 5G mobile communication systems

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Dynamic Day and Night Cycle Impact in a Serious VR Game 10

Dynamic Day and Night Cycle Impact in a Serious VR Game

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10th International Conference on Virtual Reality, ICVR 2024

作者： Damastuti, Fardani Annisa Firmansyah, Kenan Arif, Yunifa Miftachul Barakbah, Ali Ridho Hariadi, Mochamad Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia Electronic Engineering Polytechnic Institute of Surabaya Department of Creative Multimedia Technology Surabaya Indonesia Universitas Islam Negeri Maulana Malik Ibrahim Department of Informatics Engineering Malang Indonesia Electronic Engineering Polytechnic Institute of Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350364231

The immersive nature of virtual reality (VR) gaming is significantly improved by the implementation of dynamic environmental systems. This paper focuses on the development and impact of a dynamic day and night cycle in a serious VR game. This feature is intended to simulate a full 24-hour cycle within a 10-minute gameplay session, resulting in a seamless transition between different times of day that impacts both the visual aesthetics and gameplay mechanics. The day and night cycle introduces strategic depth by requiring players to adjust their management strategies according to the time of day, which affects resource availability, operational efficiency, and conditions. This system not only enhances visual fidelity but also directly impacts gameplay, necessitating that player modify their strategies in response to the changing environment. Visual aesthetics are expected to increase by 15%, strategic profundity will be improved by 20%, and player immersion will be enhanced by 25%, according to the research findings. This investigation underscores the importance of natural cycles in enhancing the strategic complexity, interactivity, and realism of virtual reality environments, thereby offering valuable insights for the creation of future virtual reality games. © 2024 IEEE.

关键词： Virtual environments

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Foundry Manufactured 6-bit Resolution, 150μm Long Slow-Light Electro-Optic Modulator for On-Chip Photonic Tensor Computing

Foundry Manufactured 6-bit Resolution, 150μm Long Slow-Ligh...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Zhang, Meng Begović, Amir Yin, Dennis Gangi, Nicholas Gu, Jiaqi Huang, Rena Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering 110 8th Street TroyNY12180 United States Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85281 United States

ISBN: (纸本)9781957171395

关键词： Light modulation

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Enhancing Septic Shock Detection through Interpretable Machine Learning

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computer Modeling in engineering & Sciences 2024年第12期141卷 2501-2525页

作者： Md Mahfuzur Rahman Md Solaiman Chowdhury Mohammad Shorfuzzaman Lutful Karim Md Shafiullah Farag Azzedin Department of Information and Computer Science King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Department of Electrical and Computer Engineering North South UniversityDhaka1229Bangladesh Department of Computer Science Taif UniversityTaif21974Saudi Arabia College of Applied Arts and Technology Seneca PolytechnicTorontoM2J 2X5Canada Department of Control&Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

This article presents an innovative approach that leverages interpretable machine learning models and cloud computing to accelerate the detection of septic shock by analyzing electronic health *** traditional methods,which often lack transparency in decision-making,our approach focuses on early detection,offering a proactive strategy to mitigate the risks of *** integrating advanced machine learning algorithms with interpretability techniques,our method not only provides accurate predictions but also offers clear insights into the factors influencing the model’s ***,we introduce a preference-based matching algorithm to evaluate disease severity,enabling timely interventions guided by the analysis *** innovative integration significantly enhances the effectiveness of our *** leverage a clinical health dataset comprising 1,552,210 Electronic Health Records(EHR)to train our interpretable machine learning models within a cloud computing *** techniques like feature importance analysis and model-agnostic interpretability tools,we aim to clarify the crucial indicators contributing to septic shock *** transparency not only assists healthcare professionals in comprehending the model’s predictions but also facilitates the integration of our system into existing clinical *** validate the effectiveness of our interpretable models using the same dataset,achieving an impressive accuracy rate exceeding 98%through the application of oversampling *** findings of this study hold significant implications for the advancement of more effective and transparent diagnostic tools in the critical domain of sepsis management.

关键词： Sepsis prediction machine learning cloud computing

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A Power Electronic Converters-Inspired Approach for Modeling PWM Switched-Based Nonlinear Hydraulic Servo Actuators

A Power Electronic Converters-Inspired Approach for Modeling...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bozza, Augusto Cavone, Graziana Carli, Raffaele Dotoli, Mariagrazia The Department of Electrical and Information Engineering The Polytechnic of Bari Italy The Department of Civil Computer Science and Aeronautical Technologies Engineering The University Roma Tre Rome Italy

ISBN: (纸本)9798350337020

This paper investigates a novel approach for properly modeling Hydraulic Servo Actuators (HSAs) based on ON-OFF switching valves. HSAs represent very high efficiency and small size-to-power ratio hydraulic actuators. Their functioning is guaranteed by their control system that ensures the desired flow-rate, and consequently, the proper pressure, to be provided to the actuator's chambers. Nevertheless, achieving a good model of such HSAs for control purposes is non-trivial, due to their hybrid nature inherited from the switching between the different operating modes produced by valves. To overcome this limit, we propose an average equivalent discrete-time model of the chambers' pressure dynamics related to a single control input for the digital valves. The proposed model takes inspiration from the analogy existing between hydraulic systems and power electronic converters, and guarantees the same performance as the traditional model, with the advantage of greatly simplifying the control of the servo actuator. Finally, the consistency of the proposed model with respect to its nonlinear hybrid version is proved via numerical examples. © 2023 IEEE.

关键词： Electro-Hydraulic Analogy Hybrid Systems Hydraulic Servo Actuators Nonlinear Systems Pulse Width Modulation (PWM) Switching Systems

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