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arXiv 2024年

作者： Elsayed, Nazik Osman, Yousuf Babiker M. Li, Cheng Zhang, Jiong Wang, Shanshan Pual C. Lauterbur Research Centre for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Peng Cheng Laboratory Shenzhen518055 China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangzhou510080 China Institute of Biomedical Engineering Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences China Faculty of Mathematical and Computer Sciences University of Gezira Sudan

Cardio-cerebrovascular diseases are the leading causes of mortality worldwide, whose accurate blood vessel segmentation is significant for both scientific research and clinical usage. However, segmenting cardio-cerebrovascular structures from medical images is very challenging due to the presence of thin or blurred vascular shapes, imbalanced distribution of vessel and non-vessel pixels, and interference from imaging artifacts. These difficulties make manual or semi-manual segmentation methods highly time-consuming, labor-intensive, and prone to errors with inter-observer variability, where different experts may produce different segmentations from a variety of modalities. Consequently, there is a growing interest in developing automated algorithms. This paper provides an up-to-date survey of deep learning techniques, for cardio-cerebrovascular segmentation. It analyzes the research landscape, surveys recent approaches, and discusses challenges such as the scarcity of accurately annotated data and variability. This paper also illustrates the urgent needs for developing multi-modality label-efficient deep learning techniques. To the best of our knowledge, this paper is the first comprehensive survey of deep learning approaches that effectively segment vessels in both the heart and brain. It aims to advance automated segmentation techniques for cardio-cerebrovascular diseases, benefiting researchers and healthcare professionals. Copyright © 2024, The Authors. All rights reserved.

关键词： Medical imaging

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Adjusted and Controllability Properties of Memristor Rucklidge System

Adjusted and Controllability Properties of Memristor Rucklid...

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Memristive Computing and applications (ICMCA), IEEE International Conference on

作者： Hongyan Zang Lili Huang Shourong Zhang Annie Anak Joseph Haiyan Fu Tengfei Lei Collaborative Innovation Center of Memristive Computing Application Qilu Institute of Technology Jinan P. R. China Faculty of Engineering Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia College of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan P. R. China Shandong Vanform High Energy Physics Technology Co. Ltd. Jinan P. R. China Department of Electrical and Electronics Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia College of Computer and Information Engineering Qilu Institute of Technology Jinan P. R. China Collaborative Innovation Center of Memristive Computing Application(CICMCA) Qilu Institute of Technology Jinan P. R. China

There are many models of memristors, but there are no reports on exponential memristors. In this paper, a three- dimension memristor Rucklidge system with exponential memristor is proposed by introducing exponential function and constructing exponential memristor. The dynamic behavior of the system is analyzed by means of Lyapunov exponent and bifurcation diagram. The complex attractor coexistence and amplitude modulation characteristics of the system are found. The internal variable of memristor is introduced into the second two-dimensional equation as a feedback term, and a conditional symmetric system is constructed for the three-dimensional memristor system, which can realize the polarity control of output signal. By discussing the dynamic characteristics of exponential memristor chaotic system and the control mechanism of amplitude modulation, bias and conditional symmetry, the complex dynamic characteristics of exponential function memristor are revealed, which lays a foundation for its application in the field of secure communication.

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Image cryptography algorithm based on a new composite chaotic system and Latin square collaborative mechanism

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Optics and Lasers in Engineering 2025年 193卷

作者： Tian, Anhong Yue, Zhongze Fu, Chengbiao Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Faculty of Land Resource Engineering Kunming University of Science and Technology Kunming650093 China Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and Technology Kunming650500 China

Encryption algorithms based on chaos theory have become a prominent research focus in the field of information security. However, existing chaotic systems exhibit several limitations, including discontinuous chaotic intervals, low complexity of chaotic signals, and insufficient robustness in their dynamical behavior. These deficiencies pose potential risks to the application of chaotic cryptography. To address these issues, this paper proposes a universal two-dimensional composite hyperchaotic system model (2D-CHS). Through rigorous theoretical analysis, it is demonstrated that the number of positive Lyapunov exponents (LEs) in 2D-CHS is always equal to its dimensionality, indicating the existence of infinitely many coexisting attractors and strong robustness against dynamical degradation. To validate the effectiveness of the proposed 2D-CHS, three one-dimensional chaotic maps are first employed as seed maps to construct three 2D chaotic mappings as representative examples. Evaluation and experimental results demonstrate that the newly generated chaotic maps exhibit broader and more continuous chaotic intervals than traditional chaotic maps, and they also outperform existing systems in terms of LEs, the 0–1 test, sample entropy (SE), permutation entropy (PE), and correlation dimension (CD). Furthermore, a digital circuit implementation scheme based on a microcontroller is designed to verify the practical feasibility and physical realizability of the proposed system. Finally, the novel 2D chaotic system is integrated with Latin square matrices to develop a high-efficiency image encryption algorithm. Experimental results confirm that the algorithm demonstrates excellent efficiency and security performance. © 2025

关键词： Lyapunov functions

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Recommender System for Telecom Packages Based on the Deep & Cross Network

Research Square

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Research Square 2021年

作者： Shi, Congming Wang, Wen Wei, Shoulin Lv, Feiya School of Software Engineering Anyang Normal University China Faculty of Information Engineering and Automation Kunming University of Science and Technology China Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology China

With the evolution of 5G technology, the telecom industry has influenced the livelihood of people and impacted the development of the national economy significantly. To increase revenue per customer and secure long-term contracts of users, telecommunications firms and enterprises have launched different types of telecom packages to satisfy the varying requirements of users. Although several recommender systems have been proposed in recent years for telecommunication package recommendation, extracting effective feature information from large and complex consumption data remains challenging. Considering the telecom package recommendation problems, traditional recommendation methods either use complex expert feature engineering or fail to perform end-to-end deep learning training. In this study, a recommender system based on deep & cross network (DCN), deep belief network (DBN), Embedding, and Word2Vec is proposed using the powerful learning abilities of deep learning. The proposed system fits the telecom package recommender system in terms of click-through rate prediction to provide a potential solution for the recommendation challenges faced by telecom enterprises. The proposed model can effectively capture the finite order interactional features and deep hidden features. Additionally, the text information in the data is completely used to further improve the recommendation ability of the model. Moreover, the proposed method does not require feature engineering. We conducted comprehensive experiments using real-world datasets, and the results verify that our method can generate improved recommendation accuracy in comparison with those observed in DBN, DCN, deep factorization machine, and deep neural network models individually. © 2021, CC BY.

关键词： Recommender systems

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Collaborative Learning Assessment via Information and Communication technology

Collaborative Learning Assessment via Information and Commun...

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IEEE International Conference on Research, Innovation and Vision for the Future

作者： Asif Khan Mohammad Kamrul Hasana Taher M. Ghazal Shayla Islam Haitham M. Alzoubi Umi Asma' Mokhtar Rizwan Alam Munir Ahmad Department of Computer Application Integral University Lucknow India Faculty of Information Science and Technology Center for Cyber Security Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia Skyline University Collage United Arab Emirates Institute of Computer Science and Digital Innovation UCSI University Malaysia CSSCIVE Bhopal India National Collage of Business Administration and Economics

ISBN: (纸本)9781665461672

In technological revolution, Information technology has changed the face on how Education is experienced and perceived. Learning is quickly becoming an imperative. ICT have great potential to spread learning however, the benefits of these technologies have to be made available during the daily learning hours of the students. This paper concentrates on specifying the potentials of using e-learning systems in teaching and learning and exploring how Machine Learning can be incorporated to analyses daily learning activities of students and specially content preparation and presentation tools application of e-Learning as a teaching aid for teachers. We also analyzed the e-learning facilities available in the present era that can be used by teachers to make a collaborative and participative environment of learning for the students. Results proved the productivity of the proposed model which comes from the choice of more fitting highlights chosen by the Learning algorithm. Furthermore, proposed system is used to accurately and effectively predict to evaluate collaborative learning of students performance in its early stage.

关键词： Productivity Electronic learning Federated learning Computational modeling Education Fitting Collaboration

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DRL-Based Pricing-Driven for Task Offloading and Dynamic Resource in Vehicle Edge Computing

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IEEE Transactions on Mobile Computing 2025年

作者： Wu, Sijun Yang, Liang Li, Junjie Guo, Hongzhi Ahmad, Ishtiaq Da Costa, Daniel Benevides Jiang, Hongbo Niyato, Dusit Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Northwestern Polytechnical University Natl. Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Cybersecurity Shaanxi Xi'an710072 China Czech Technical University in Prague Department of Telecommunication Engineering Faculty of Electrical Engineering Prague166 27 Czech Republic Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia Nanyang Technological University School of Computer Science and Engineering Singapore639798 Singapore

Vehicle Edge Computing (VEC) assists vehicles in performing latency-sensitive tasks by deploying resources near the vehicle. Designing an incentive mechanism for vehicles and VEC is crucial for realizing an intelligent transmission system. Considering the rationality of resource allocation, we model the utility functions of the VEC and the vehicle, which are used as optimization objectives. Specifically, the VEC allocates resources through pricing to maximize revenue under resource-constrained conditions, and the vehicle weighs payments against energy consumption to determine offloading and resource allocation. Given the vehicle movement and the variable channel state, we use the Deep Reinforcement Learning (DRL) algorithm to solve these optimization problems. To reduce the learning difficulty of the DRL algorithm in complex VEC scenarios with multiple optimization variables, we propose a Pricing-Driven Resource Allocation (PDRA) algorithm that performs mobility-aware task offloading and calculates the optimal values of the optimization variables in the utility function of the vehicle to reduce the decision dimension. Furthermore, we also propose a DRL-based Pricing-Driven Dynamic Resource Allocation (DPDDRA) algorithm to achieve efficient resource allocation. Extensive experimental results show that the proposed algorithms can reduce the learning difficulty while maximizing VEC and vehicle revenue in complex VEC scenarios. © 2002-2012 IEEE.

关键词： Deep reinforcement learning

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Model Checking Quantum Continuous-Time Markov Chains 32

Model Checking Quantum Continuous-Time Markov Chains

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32nd International Conference on Concurrency Theory, CONCUR 2021

作者： Xu, Ming Mei, Jingyi Guan, Ji Yu, Nengkun MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Lab of Trustworthy Computing East China Normal University Shanghai China Shanghai Key Lab of Trustworthy Computing East China Normal University Shanghai China State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney Australia

ISBN: (纸本)9783959772037

Verifying quantum systems has attracted a lot of interests in the last decades. In this paper, we initialise the model checking of quantum continuous-time Markov chain (QCTMC). As a real-time system, we specify the temporal properties on QCTMC by signal temporal logic (STL). To effectively check the atomic propositions in STL, we develop a state-of-the-art real root isolation algorithm under Schanuel's conjecture;further, we check the general STL formula by interval operations with a bottom-up fashion, whose query complexity turns out to be linear in the size of the input formula by calling the real root isolation algorithm. A running example of an open quantum walk is provided to demonstrate our method. © Ming Xu, Jingyi Mei, Ji Guan, and Nengkun Yu;.

关键词： Model checking

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Heat Transfer Performance of Flat Micro-Heat Pipe with Sintered Multi-Size Copper Powder Wick

SSRN

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SSRN 2022年

作者： Zhao, Zhengang Peng, Guohong Zhang, Yanhui Zhang, Dacheng Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Green Energy Electric Power Measurement Digitalization Control and Protection Yunnan Kunming650500 China Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

Flat Micro-Heat Pipe (FMHP) with sintered copper powder wick is a popular device for heat flux management of highly integrated electronic circuits. To this end, a Sintered Multi-size copper powder wick (SMW) is prepared, basing a Sintered Single-size copper powder wick (SSW). The evaporator and condenser section of the SMW is a doublelayer structure with two copper powder diameters to increase the evaporation and condensation rates inside the FMHP. The adiabatic section is a single-layer structure with single powder diameter to add a capillary gradient force in the liquid channel. Six SSWs with different copper powder diameters are prepared and tested to compare with SMW. The methanol pumping experiment is carried out to evaluate the capillary pressure of different wicks, and the surface temperature experiment is carried out to evaluate the thermal transfer performance of the FMHP with different wicks, respectively. The experimental results show that the liquid transfer time of the SMW is shortened 16.59% compared to the SSW. The dynamic response time constant of the SMW FMHP is decreased by 0.9 s , and the overall thermal resistance is reduced by 14.22%. The SMW can enhance the heat transfer performance of the FMHP. © 2022, The Authors. All rights reserved.

关键词： Heat pipes

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PoW-Based Sybil Attack Resistant Model for P2P Reputation Systems 2nd

PoW-Based Sybil Attack Resistant Model for P2P Reputation Sy...

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2nd International Conference on Blockchain and Trustworthy Systems, Blocksys 2020

作者： Li, Biaoqi Fu, Xiaodong Yue, Kun Liu, Li Liu, Lijun Feng, Yong Yunnan Provincial Key Laboratory of Computer Technology Application Kunming650500 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China School of Information Science and Engineering Yunnan University Kunming650091 China

ISBN: (纸本)9789811592126

Peer-to-peer and other distributed systems are known particularly vulnerable to Sybil attack, so is P2P reputation systems. Reputation helps users to make better decisions in P2P systems, but Sybil attacker can obtain multiple identities and pretends to be multiple. It can control more than "one vote" to let others’ reputation change just as the attacker wants. This paper presents a Sybil attacker resistant model for P2P reputation systems by introducing multiple rounds of PoW (Proof-of-Work) verification and dynamic difficulty adjustment. A savvy attacker usually doesn’t carry out attacks without positive returns, so we minimize the expected profit of attackers through the using of puzzles. The costs and benefits are quantified as effectiveness in our model. We explore the effectiveness in two types of comparison, one is in dynamic or static difficulty adjustment, the other is executing once or multiple rounds of verification, and show the effectiveness of our model both analytically and experimentally. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Peer to peer networks

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Security and Privacy in Internet of Things (IoT) Environments

Security and Privacy in Internet of Things (IoT) Environment...

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International Conference on Science technology Engineering and Management (ICONSTEM)

作者： A. Bhoomadevi Prem latha Soundarraj Vishnu Gupta Sathish Kumar Kumaravel Sudhakar Deivasigamani Ankit Kumar Amity Institute of Public Health & Hospital AdministrationAmity University Noida School of Business and Management Christ University Pune Lavasa Maharashtra Department of Commerce Mahatma Gandhi Kashi vidyapith Varanasi Mathematics Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Chennai TamilNadu Digipulse Technologies Inc Suite 169 NJ USA Department of Computer Application Faculty of Science Swami Vivekanand Subharti University Meerut

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

Although the proliferation of IoT devices has led to unparalleled ease of use and accessibility, it has also raised serious privacy and safety issues. Using a systematic approach that incorporates security and privacy modelling, data analysis, and empirical trials, this study provides a deep dive into the topic of IoT security and privacy. Our results show how crucial it is to take precautions against “Information Disclosure” by using strong encryption and authorization protocols. The need to protect against “Unencrypted Data” vulnerabilities is further emphasized by vulnerability analysis. Encryption (AES-256) and other access control rules fare very well in the assessment of security systems. Furthermore, “Homomorphic Encryption” is identified as a potential strategy to protecting user privacy while retaining data usefulness based on our review of privacy preservation strategies. A more secure and privacyaware IoT environment may be fostered thanks to the findings of this study, which have ramifications for the industry, government, consumers, and academics. Addressing the ever-evolving security and privacy issues in the IoT will need a future focus on cutting-edge security mechanisms, privacy-preserving technology, regulatory compliance, user-centric design, multidisciplinary cooperation, and threat intelligence sharing.

关键词： Data privacy Privacy Analytical models Systematics Protocols Reviews Safety

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