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EngMedicine 2025年第2期2卷

作者： Zheyu Du Ling Yang Hongliang He Xiaofeng Wu Xiaolong Qi Yudong Zhang Imaging Science and Technology Laboratory School of Computer Science and Technology Southeast University Nanjing China Liver Disease Center of Integrated Traditional Chinese and Western Medicine Department of Radiology Zhongda Hospital Medical School Southeast University Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University) Nanjing China Basic Medicine Research and Innovation Center of Ministry of Education Zhongda Hospital Southeast University State Key Laboratory of Digital Medical Engineering Nanjing China State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory for Biomaterials and Devices School of Biological Sciences & Medical Engineering Southeast University Nanjing China State Key Laboratory of Digital Medical Engineering School of Biological Science and Medical Engineering Southeast University Nanjing China

Cirrhosis is frequently associated with portal hypertension (PH), which can result in severe complications, including varices, ascites, and hepatic encephalopathy. The gold standard for diagnosing PH is the hepatic venous pressure gradient; however, its invasive nature necessitates the exploration of noninvasive diagnostic alternatives. Imaging techniques such as ultrasound, computed tomography, and magnetic resonance imaging are frequently employed but encounter challenges in the early detection of clinically significant portal hypertension (CSPH). Recent advances in artificial intelligence (AI), particularly machine and deep learning, have provided promising solutions. AI can analyze complex medical images and enhance diagnostic accuracy by identifying early indicators of PH. Techniques such as radiomics and vascularomics have demonstrated high efficacy in predicting CSPH, thereby improving noninvasive assessment. AI integration with multimodal data may yield more comprehensive, precise, and noninvasive diagnostic tools, facilitating early detection and enhancing the treatment of cirrhosis-related complications.

关键词： Clinically significant portal hypertension Cirrhosis Artificial intelligence Machine learning Deep learning

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The Phenology and Water Level Time-Series Mangrove Index for Improved Mangrove Monitoring

SSRN

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SSRN 2024年

作者： Sun, Weiwei Huang, Ke Yang, Gang Fu, Bolin Chen, Chao Meng, Xiangchao Feng, Tian Ge, Yong Department of Geography and Spatial Information Techniques Ningbo University Ningbo315211 China Zhejiang Collaborative Innovation Center Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research Ningbo315211 China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences & Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Geomatics and Geoinformation Guilin University of Technology Guilin541006 China School of Geography Science and Geomatics Engineering Suzhou University of Science and Technology Suzhou215009 China

Mangroves are declining and degrading under the influence of human activities and natural factors, making their accurate mapping and dynamic monitoring essential. However, most of the existing mangrove indices based on the spectral characteristics of multispectral images have some limitations in recognition accuracy and universality. Therefore, this study aimed to develop a robust and efficient Phenology and Water level Time-series Mangrove Index (PWTMI) for mangrove monitoring. PWTMI is constructed by combining spectral and temporal characteristics from dense time-series multispectral data, wherein phenology and water level time-series characteristics are extracted from NDVI and MNDWI time series. The results show that PWTMI outperforms existing multispectral-based mangrove indices and has an accuracy similar to a hyperspectral-based mangrove index, with overall accuracy ranging from 91.49% to 98.83% and F1 score ranging from 0.91 to 0.98 in four typical areas in China, indicating great potential for long time-series and large-scale mangrove monitoring. © 2024, The Authors. All rights reserved.

关键词： Water levels

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Research on Detection Method of Interest Flooding Attack on Content Centric Network

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computers, Materials & Continua 2020年第8期64卷 1075-1089页

作者： Yabin Xu Ting Xu Xiaowei Xu Beijing Key Laboratory of Internet Culture and Digital Dissemination Research Beijing100101China Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Information Science and Technology UniversityBeijing100101China School of Computer Beijing Information Science&Technology UniversityBeijing100101China Department of Information Science University of Arkansas at Little RockLittle Rock72204USA

To improve the attack detection capability of content centric network(CCN),we propose a detection method of interest flooding attack(IFA)making use of the feature of self-similarity of traffic and the information entropy of content name of interest *** the one hand,taking advantage of the characteristics of self-similarity is very sensitive to traffic changes,calculating the Hurst index of the traffic,to identify initial IFA *** the other hand,according to the randomness of user requests,calculating the information entropy of content name of the interest packets,to detect the severity of the IFA attack,***,based on the above two aspects,we use the bilateral detection method based on non-parametric CUSUM algorithm to judge the possible attack behavior in *** experimental results show that flooding attack detection method proposed for CCN can not only detect the attack behavior at the early stage of attack in CCN,but also is more accurate and effective than other methods.

关键词： CCN interest flooding attack self-similar feature information entropy bilateral detection method

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5G车联网下工业园区的多层协同框架技术研究

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engineering 2021年第6期7卷 251-281页

作者：史彦军韩俏梅沈卫明王现斌 Department of Mechanical Engineering Dalian University of Technology Department of Electrical and Computer Engineering Western University State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology

第五代(5G)无线通信网络有望在垂直产业转型中发挥重要的作用。在众多日益发展的5G应用中,通过车用无线通信技术(V2X)通信可更高效地执行工业园区内的物流任务。本文提出了一种基于V2X的工业园区物流管控多层协同框架。该框架包括三层:... 详细信息

第五代(5G)无线通信网络有望在垂直产业转型中发挥重要的作用。在众多日益发展的5G应用中,通过车用无线通信技术(V2X)通信可更高效地执行工业园区内的物流任务。本文提出了一种基于V2X的工业园区物流管控多层协同框架。该框架包括三层:感知与执行层、物流层以及配置层。除以上三层之间的协同外,本研究还涉及了设备(端)、边缘服务器以及云服务器之间的协同技术。工业园区内的高效物流可通过四项功能来实现任务协同,这四项功能分别是:环境感知与地图构建、任务分配、路径规划,以及车辆运输。为了动态协调这些功能,本文将采用5G切片和V2X通信技术支持的端-边-云协同技术。然后,利用目标级联分析法对工业园区协同方案进行配置和评估。最后,通过一个工业园区物流分析案例,展示了所提出的协同框架的可行性。

关键词： 5G 车用无线通信技术工业园区物流端-边-云协同目标级联分析

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Functional neural network for decision processing, a racing network of programmable neurons with fuzzy logic where the target operating model relies on the network itself

arXiv

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arXiv 2021年

作者： Jumelle, Frederic So, Kelvin Deng, Didan Bright Nation Limited Smart-Space 3F Cyberport Hong Kong Neuromorphic Interactive System Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

In this paper, we are introducing a novel model of artificial intelligence, the functional neural network for modeling of human decision-making processes. This neural network is composed of multiple artificial neurons racing in the network. Each of these neurons has a similar structure programmed independently by the users and composed of an intention wheel, a motor core and a sensory core representing the user itself and racing at a specific velocity. The mathematics of the neuron’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education and medicine including the opportunity to design an intelligent learning agent with application in business operations supervision. We believe that this functional neural network has a promising potential to transform the way we can compute decision-making and lead to a new generation of neuromorphic chips for seamless human-machine interactions. © 2021, CC BY-NC-SA.

关键词： Neurons

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Individual risk profiling for portable devices using a neural network to process the cognitive reactions and the emotional responses to a multivariate situational risk assessment

arXiv

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arXiv 2021年

In this paper, we are presenting a novel method and system for neuropsychological performance testing that can establish a link between cognition and emotion. It comprises a portable device used to interact with a cloud service which stores user information under username and is logged into by the user through the portable device;the user information is directly captured through the device and is processed by artificial neural network;and this tridimensional information comprises user cognitive reactions, user emotional responses and user chronometrics. The multivariate situational risk assessment is used to evaluate the performance of the subject by capturing the 3 dimensions of each reaction to a series of 30 dichotomous questions describing various situations of daily life and challenging the user's knowledge, values, ethics, and principles. In industrial application, the timing of this assessment will depend on the user's need to obtain a service from a provider such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work or securing online payments. © 2021, CC BY-NC-SA.

关键词： Risk assessment

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Hierarchical bucket tree: An efficient account structure for blockchain-based system

Hierarchical bucket tree: An efficient account structure for...

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作者： Chen, Weili Zheng, Zibin Ma, Mingjie He, Pinjia Zhou, Yuren Bian, Jing School of Data and Computer Science National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou510006 China Department of Computer Science ETH Zurich Switzerland School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Province Key Laboratory of Computational Science Guangzhou China

systems built on top of blockchain are often inefficient. One reason for the inefficiency is that these systems include too many hash operations. To address this problem, we conduct an empirical study on the transaction history of a real-world blockchain-based system (i.e., Ethereum), which contains 300,821 accounts and 14,240,095 transactions. We found that the account usage frequency is highly heterogeneous. Based on this finding, this paper presents hierarchy bucket tree (HBT), an efficient account structure with user transaction behaviour information embedded, to reduce the number of hash operations and thus enhance the efficiency of blockchain-based systems. Extensive experiments have been conducted and the experimental results show that HBT reduces hash operations by nearly 80% compared with the existing account structure. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Blockchain

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Bridging microcombs and silicon photonic engines for optoelectronics systems

arXiv

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arXiv 2021年

作者： Shu, Haowen Chang, Lin Tao, Yuansheng Shen, Bitao Xie, Weiqiang Jin, Ming Netherton, Andrew Tao, Zihan Zhang, Xuguang Chen, Ruixuan Bai, Bowen Qin, Jun Yu, Shaohua Wang, Xingjun Bowers, John E. State Key Laboratory of Advanced Optical Communications System and Networks Department of Electronics School of Electronics Engineering and Computer Science Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Peng Cheng Laboratory Shenzhen518055 China Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China

Microcombs have sparked a surge of applications over the last decade, ranging from optical communications to metrology. Despite their diverse deployment, most microcomb-based systems rely on a tremendous amount of bulk equipment to fulfill their desired functions, which is rather complicated, expensive and power-consuming. On the other hand, foundry-based silicon photonics (SiPh) has had remarkable success in providing versatile functionality in a scalable and low-cost manner, but its available chip-based light sources lack the capacity for parallelization, which limits the scope of SiPh applications. Here, we bridge these two technologies by using a power-efficient and operationally-simple AlGaAs on insulator microcomb source to drive CMOS SiPh engines. We present two important chip-scale photonic systems for optical data transmissions and microwave photonics respectively: The first microcomb-based integrated photonic data link is demonstrated, based on a pulse-amplitude 4-level modulation scheme with 2 Tbps aggregate rate, and a highly reconfigurable microwave photonic filter with unprecedented integration level is constructed, using a time stretch scheme. Such synergy of microcomb and SiPh integrated components is an essential step towards the next generation of fully integrated photonic systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Light transmission

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Cuckoo-based malware dynamic analysis

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International Journal of Performability engineering 2019年第3期15卷 772-781页

作者： Wang, Lele Wang, Binqiang Liu, Jiangang Miao, Qiguang Zhang, Jianhui National Digital Switching System Engineering and Technological Research Center Zhengzhou450002 China Nanjing Information Technology Institute Nanjing210000 China Department of Computer Science Xidian University Xi'an710071 China

Aiming at the problems of the huge number of malware currently in the big data environment, the insufficient ability of automatic malware analysis available, and the inefficiency of the classification of malicious attributes, in this paper, we propose a Cuckoo-based malware dynamic analysis system that can be extended, analyzed quickly, and has application value. The system proposes a semantic feature model based on deep learning, uses a deep recursive neural network model to describe the multi-layered aggregation relationship of program semantics, and builds a malware semantic aggregation model. The model can automatically complete the acquisition and analysis of behavioural features of unknown program samples and perform attribute discrimination on unknown program samples efficiently and accurately. © 2019 Totem Publisher, Inc.

关键词： Semantics

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Three-Dimensional Imaging by Interferenceless Optical Scanning Holography

SSRN

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SSRN 2022年

作者： Liu, Jung-Ping Tsai, Chen-Ming Poon, Ting-Chung Tsang, P.W.M. Zhang, Yaping Department of Photonics Feng Chia University 100 Wenhwa Rd. Seatwen Taichung40724 Taiwan Digital Optics Center Feng Chia University 100 Wenhwa Rd. Seatwen Taichung40724 Taiwan Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States Department of Electrical Engineering City University of Hong Kong Hong Kong Yunnan Provincial Key Laboratory of Modern Information Optics Kunming University of Science and Technology Yunnan Kunming650500 China

Optical scanning holography (OSH) can perform high quality, speckle-free three-dimensional (3D) holographic imaging. However, conventional OSH system contains an interferometer, which is sensitive to environmental disturbances. Here, we developed an interferenceless OSH (IOSH) system to overcome this issue. In IOSH, the interferometer is replaced by a digital micro device (DMD) together with a projection module. The Fresnel zone plates are directly displayed on the DMD and projected to the object target. The high frame-rate DMD can serve as both the display device and the scanning device, and thus the system is compact, robust, and low cost. We have studied the system performance by analyzing the 3D complex point spread function. The ability of 3D imaging by IOSH has also been demonstrated experimentally. © 2022, The Authors. All rights reserved.

关键词： Imaging systems

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