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Chronic Wound Assessment with Semi-supervised Hierarchical CNNs

Chronic Wound Assessment with Semi-supervised Hierarchical ...

Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition, S+SSPR 2024

作者： Ghahremani, Shahram Department of Electrical Engineering and Computer Science York University TorontoONM3J 1P3 Canada

ISBN: (纸本)9783031805066

The assessment of chronic wound healing often depends on visual inspection, but subjective methods can introduce variability and hinder reliable predictions. Current computer-aided detection (CAD) tools encounter limitations in automated assessment, particularly in the fine-grained analysis of tissues with irregular textures. This paper introduces a new approach, a semi-supervised hierarchical convolutional neural network (SHCNN), for robust and efficient chronic wound assessment. SHCNN simultaneously handles two crucial tasks: accurate wound size measurement and fine-grained segmentation of seven tissue types. The model is initially trained using limited pixel-level annotations, and later relies on image-level labels, alleviating the need for scarce and arduously obtained pixel-level annotations. Evaluation on a dataset with 1200 image-level and 600 pixel-level annotations demonstrates the effectiveness of SHCNN. It achieves an average pixel-wise accuracy of 81% for tissue segmentation and measurement errors of 2% (small wounds) and 3% (large wounds). These findings suggest that SHCNN has the potential to replace manual assessment, providing a valuable tool for automated chronic wound management. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Channel-Feedback-Free Transmission for Downlink FD-RAN:A Radio Map Based Complex-Valued Precoding Network Approach

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China Communications 2024年第4期21卷 10-22页

作者： Zhao Jiwei Chen Jiacheng Sun Zeyu Shi Yuhang Zhou Haibo Xuemin(Sherman)Shen School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310058China Department of Mathematics and Theories Peng Cheng LaboratoryShenzhen 518000China Department of Electrical and Computer Engineering University of WaterlooWaterlooOntarioN2L 3G1Canada

As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network ***,with the decoupling of uplink base stations and downlink base stations in FDRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the *** paper proposes a novel transmission scheme without relying on physical layer channel ***,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user *** comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input ***,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified *** also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss *** evaluate the performance of the proposed scheme on the public DeepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.

关键词： beamforming complex neural networks deep learning FD-RAN

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OFFLINE-FIRST STRATEGIES - A NOVEL CONCEPT FOR THE MIGRATION OF WORKLOADS USING VIRTUAL MACHINES OMITING LIMITATIONS OF TRADITIONAL SERVICE DEPLOYMENT CONCEPTS 21

OFFLINE-FIRST STRATEGIES - A NOVEL CONCEPT FOR THE MIGRATION...

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21st International Conference on Applied Computing 2024, AC 2024 and 23rd International Conference on WWW/Internet 2024, ICWI 2024

作者： Cocos, Henry-Norbert Frankfurt University of Applied Sciences Department of Computer Science and Engineering Nibelungenplatz 1 Frankfurt am MainD-60318 Germany

ISBN: (纸本)9789898704627

The project aims to investigate the outsourcing of cloud services to clients by including heterogeneous, client-side resources and cooperation between cloud and client in the execution of services. For this purpose, an offline-first strategy shall be formulated, developed, and investigated to be used as a counterpart to the cloud-first strategy and enable the utilization of services without a permanent cloud connection. The scope of the offline-first strategy is to achieve autonomy for applications while cooperating with cloud services. To achieve the independence and simultaneous cooperation of applications in this context, methods of service migration are to be researched to enable the provision of services. In summary, this should increase resilience when using services, improve the stability of services along the cloud-to-edge supply, and allow transparent use for the end user. Furthermore, lab experiments were conducted to investigate the behavior of virtual machines during live migration in two setups, simulating a WAN link. The experiments show that migration over a WAN link takes five times longer for RAM-intensive tasks than in a LAN. This provides initial insights into selecting the technological basis for this project. © 2024 Proceedings of the International Conferences on Applied Computing and WWW/Internet 2024. All rights reserved.

关键词： Cloud platforms

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DESIGN AND IMPLEMENTATION OF A VIRTUAL LAB PLATFORM FOR ACADEMIC TEACHING: EXPERIENCE IN THE DEVELOPMENT AND USE OF A NEW PLATFORM FOR THE DIGITIZATION OF LABORATORIES FOR computer science CLASSES 21

DESIGN AND IMPLEMENTATION OF A VIRTUAL LAB PLATFORM FOR ACAD...

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21st International Conference on Applied Computing 2024, AC 2024 and 23rd International Conference on WWW/Internet 2024, ICWI 2024

作者： Baun, Christian Kappes, Martin Cocos, Henry-Norbert Koch, Malte Martin Petrozziello, Maurizio Frankfurt University of Applied Sciences Department of Computer Science and Engineering Nibelungenplatz 1 Frankfurt am MainD-60318 Germany

ISBN: (纸本)9789898704627

This paper presents a virtual platform for university teaching that simplifies the creation and use of complex IT setups, even for students with little to no experience. Setting up infrastructures for courses like computer networks or IT security has traditionally been challenging. However, the platform presented in this paper simplifies the setup by using virtualization techniques for compute, network, and storage resources, reducing the efforts in preparation for lecturers, researchers, and students. The platform gives access to complex IT setups utilizing free software components. The project employs Proxmox Virtual Environment and CEPH for virtualization and distributed storage, respectively, providing a flexible and practical solution. On top of that, a novel graphical web interface for the easy access and use of the virtual infrastructures is implemented using ReactFlow. © 2024 Proceedings of the International Conferences on Applied Computing and WWW/Internet 2024. All rights reserved.

关键词： Students

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Investigation of Formation and Ultrasonic Disassembling of Red Blood Cell Aggregation Aimed for Maintenance of Blood Channel

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2022年第6期142卷 629-636页

作者： Hatakeyama, Mayu Akamatsu, Yuichiro Sato, Takayuki Department of Electrical Engineering and Computer Science Tokyo Metropolitan University 1-1 Minamiosawa Hachioji Tokyo192-0397 Japan

Establishment of real-time monitoring technique for blood viscosity during extracorporeal circulation treatment is needed. We have demonstrated that red blood cell (RBC, hereafter) aggregation degree, which highly correlates with the blood viscosity, can be estimated by the ultrasound spectroscopic observation of the RBC and the defining of the peak frequency by the Fast Fourier Transform process. In this study, the peak frequency was measured to investigate the aggregation degree of RBC flowing in a simple heart-lung machine. In addition, to disassemble the RBC aggregations that might cause the clogging of the circuit, a disassemble technique of the RBC aggregations using a focused 5 MHz ultrasonic transducer was also proposed. As the first step of this study, the disassembling of the RBC aggregations was carried out under the still condition and its effect was confirmed by the peak frequency method. © 2022 The Institute of Electrical Engineers of Japan.

关键词： Ultrasonic transducers

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Guest Editorial: Special Issue on Human-Machine Fusion Decision-Making for Emergency Handling

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IEEE Transactions on Automation science and engineering 2025年 22卷 4427-4433页

作者： Wu, Edmond Q. Li, Jianqiang Chen, Guimin Yuce, Mehmet R. Islam, Shafiqul Ser, Javier Del Yu, Hui Liu, Peter Xiaoping Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China College of Computer and Software Engineering Shenzhen University Shenzhen518060 China State Key Laboratory for Manufacturing Xi'an Jiaotong University Xi'an710049 China Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC3800 Australia Xavier University of Louisiana New OrleansLA70125 United States Tecnalia Institute Bizkaia48160 Spain School of Creative Technologies University of Portsmouth PortsmouthPO1 2UP United Kingdom Department of Systems and Computer Engineering Carleton University OttawaONKIS 5B6 Canada

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Accelerating Mobile Edge Generation (MEG) by Constrained Learning

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IEEE Transactions on Cognitive Communications and Networking 2025年第3期11卷 1854-1869页

作者： Xu, Xiaoxia Liu, Yuanwei Mu, Xidong Xing, Hong Nallanathan, Arumugam Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong School of Electronics Electrical Engineering and Computer Science BelfastBT3 9DT United Kingdom The Hong Kong University of Science and Technology IoT Thrust Guangzhou Guangzhou511453 China Hong Kong University of Science and Technology Department of ECE Hong Kong Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of

A novel mobile edge generation (MEG) framework is proposed for low-latency image generation on mobile devices. Exploiting a latent diffusion model (LDM) distributed across the edge server (ES) and the user equipment (UE), only low-dimension features need to be transmitted for creating artificial intelligence generative content (AIGC). Two novel modules, namely dynamic diffusion and feature merging, are conceived to compress the diffusion model and transmitted features, respectively. By jointly optimizing compression rates of denoising steps and feature merging, the image quality maximization problem is formulated subject to latency and energy consumption constraints. To address this problem in dynamic channel conditions, a low-complexity compression protocol is developed. First, a backbone LDM architecture is learned by offline distillation to support various compression options. Then, compression rates are predicted in online environment specific to channel and task features. To solve the resultant constrained Markov Decision Process (MDP), a constrained variational policy optimization (CVPO) based MEG algorithm, MEG-CVPO, is further developed to learn constraint-guaranteed optimization. Numerical results demonstrate that: 1) The proposed framework improves image distortions while reducing over 40% latency compared to conventional generation schemes. 2) MEG-CVPO stringently guarantee constraints and realizes a flexible trade-off between generation qualities and overheads. © 2015 IEEE.

关键词： Markov processes

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Unveiling vulnerable smart contracts:Toward profiling vulnerable smart contracts using genetic algorithm and generating benchmark dataset

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Blockchain(Research and Applications) 2024年第1期5卷 58-84页

作者： Sepideh HajiHosseinKhani Arash Habibi Lashkari Ali Mizani Oskui Computer Science Department of Computer Science and EngineeringYork UniversityTorontoOntario M3J1P3Canada Behavior-Centric Cybersecurity Center(BCCC) School of Information TechnologyYork UniversityTorontoOntario M3J1P3Canada Financial and Crypto Advisory of Switzerland(FiCAS AG) ZugSwitzerland

Smart contracts(SCs)are crucial in maintaining trust within blockchain ***,existing methods for analyzing SC vulnerabilities often lack accuracy and effectiveness,while approaches based on Deep Neural Networks(DNNs)struggle with detecting complex vulnerabilities due to limited data *** paper proposes a novel approach for analyzing SC *** method leverages an advanced form of the Genetic Algorithm(GA)and includes the development of a comprehensive benchmark dataset consisting of 36,670 Solidity source code *** primary objective of our study is to profile vulnerable SCs *** achieve this goal,we have devised an analyzer called SCsVulLyzer based on GAs,designed explicitly for profiling ***,we have carefully curated a new dataset encompassing a wide range of examples,ensuring the practical validation of our ***,we have established three distinct taxonomies that cover SCs,profiling techniques,and feature *** taxonomies provide a systematic classification and analysis of information,improving the efficiency of our *** methodology underwent rigorous testing through experimentation,and the results demonstrated the superior capabilities of our model in detecting *** to traditional and DNN-based approaches,our approach achieved higher precision,recall,and F1-score,which are widely used metrics for evaluating model *** all these metrics,our model showed exceptional *** customization and adaptations we implemented within the GA significantly enhanced its *** approach detects SC vulnerabilities more efficiently and facilitates robust *** promising results highlight the potential of GA-based profiling to improve the detection of SC vulnerabilities,contributing to enhanced security in blockchain networks.

关键词： Smart contracts(SCs) Vulnerability Vulnerable smart contracts Vulnerability profiling Genetic algorithm

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Beamforming Optimization for Continuous Aperture Array (CAPA)-based Communications

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IEEE Transactions on Wireless Communications 2025年第6期24卷 5099-5113页

作者： Wang, Zhaolin Ouyang, Chongjun Liu, Yuanwei Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering China Kyung Hee University Department of Electronic Engineering Yongin-si17104 Korea Republic of

The beamforming optimization in continuous aperture array (CAPA)-based multi-user communications is studied. In contrast to conventional spatially discrete antenna arrays, CAPAs can exploit the full spatial degrees of freedom (DoFs) by emitting information-bearing electromagnetic (EM) waves through continuous source current distributed across the aperture. Nevertheless, such an operation renders the beamforming optimization problem as a non-convex integral-based functional programming problem, which is challenging for conventional discrete optimization methods. A couple of low-complexity approaches are proposed to solve the functional programming problem. 1) Calculus of variations (CoV)-based approach: Closed-form structure of the optimal continuous source patterns are derived based on CoV, inspiring a low-complexity integral-free iterative algorithm for solving the functional programming problem. 2) Correlation-based zero-forcing (Corr-ZF) approach: Closed-form ZF source current patterns that completely eliminate the inter-user interference are derived based on the channel correlations. By using these patterns, the original functional programming problem is transformed to a simple power allocation problem, which can be solved using the classical water-filling approach with reduced complexity. Our numerical results validate the effectiveness of the proposed designs and reveal that: i) compared to the state-of-the-art Fourier-based discretization approach, the proposed CoV-based approach not only improves communication performance but also reduces computational complexity by up to hundreds of times for large CAPA apertures and high frequencies, and ii) the proposed Corr-ZF approach achieves asymptotically optimal performance compared to the CoV-based approach. © 2025 IEEE. All rights reserved.

关键词： Iterative methods

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TOWARD DATA-DRIVEN FILTERS IN PARAVIEW

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Journal of Flow Visualization and Image Processing 2022年第3期29卷 55-72页

作者： Maharjan, Drishti Zaspel, Peter Department of Computer Science & Electrical Engineering Jacobs University Bremen Campus Ring 1 Bremen28759 Germany

Scientific visualization is a crucial part of many computational workflows in science and engineering. A given visualization is obtained by applying a series of filters or transformations to input data and finally mapping the filtered data to a graphical representation. So far, such filters mostly use deterministic algorithms to process the data. In this work, we aim at extending this methodology toward data-driven filters, filters that expose the abilities of pretrained machine learning models to the visualization system. The use of such data-driven filters can be of particular interest in fields like segmentation, classification, and surrogate models, where machine learning models often out-perform existing algorithmic approaches. The objective of this work is to give a starting point for developments toward data-driven filters in multipurpose visualization tools. To this end, we propose, develop, and provide a first software prototype that combines the standard visualization tool ParaView with the state-of-the-art deep learning framework PyTorch in order to expose machine learning models as data-driven filters. Several simple use cases for segmentation and classification filters are presented, showing the technical applicability of our approach. The resulting prototype is provided as open source to facilitate the future development of data-driven filters. © 2022 by Begell House, Inc. All rights reserved.

关键词： Data visualization

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