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Dynamic Multi-scale Feature Integration Network for unsupervised MR-CT synthesis

Neural Networks 2025年 189卷 107584页

作者： Tang, Meng Jiang, Jiuming Zhang, Xue Zhou, Tao Zhang, Yizhe Qiu, Bin Zhang, Li School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Department of Diagnostic Radiology National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing100021 China Department of Thoracic Surgery National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing100021 China

Unsupervised MR-CT synthesis presents a significant opportunity to reduce radiation exposure from CT scans and lower costs by eliminating the need for both MR and CT imaging. However, many existing unsupervised methods face limitations in capturing different anatomical structures due to their inability to model features with large receptive fields, and the receptive fields of different structures can vary. To address this challenge, we propose a novel Dynamic Multi-scale Feature Integration Network (DMFI-Net) tailored for unsupervised MR-CT synthesis. Our DMFI-Net dynamically adjusts its receptive field to extract multi-scale receptive field features, effectively capturing intricate anatomical details to enhance the synthesis performance. Specifically, we present a Global Context-enhanced Kernel Selection (GCKS) module, which intelligently modulates the receptive fields of convolutions for capturing fine-grained details essential to image transformation. By incorporating global cues, the module enriches multi-scale receptive features with comprehensive semantic information, which is crucial for synthesizing globally distributed target regions or organs. Additionally, a Scale Enhancement Module (SEM) is proposed to integrate features extracted with different scales, preserving richer spatial information. Furthermore, we present a scale-aware reconstruction branch to bolster the encoder's feature extraction capability and improve model generalization. This branch is capable of reconstructing downsampled input images that have undergone random masking, underscoring the model's robust feature extraction ability. Extensive experimental results on one private and two public MR-CT datasets demonstrate that our model significantly outperforms state-of-the-art MR-CT synthesis methods in both qualitative and quantitative evaluations. The implementation code will be released upon acceptance of this manuscript at https://***/taozh2017/DMFINet. © 2025

关键词： Image coding

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UHF IoT Humidity and Temperature Sensor for Smart Agriculture Applications Powered from an Energy Harvesting System

UHF IoT Humidity and Temperature Sensor for Smart Agricultur...

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2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022

作者： Nadeem, Adnan Chatzichristodoulou, David Quddious, Abdul Shoaib, Nosherwan Vassiliou, Loukia Vryonides, Photos Nikolaou, Symeon Frederick Research Center Nicosia Cyprus School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan Rf and Microwave Solutions Ltd Cyprus Kios Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Agricultural Research Institute Nicosia Cyprus Electrical Engineering Department Frederick University Nicosia Cyprus

ISBN: (数字)9798350396454

ISBN: (纸本)9798350396454

This manuscript presents a novel UHF IoT humidity and temperature sensor module that is powered from an integrated energy harvesting (EH) system. The module is intended for smart agriculture applications. The sensing module is powered from the collected RF energy that is harvested by a meander monopole antenna operating at 915 MHz (US UHF band) and therefore the use of a battery is not required. The rectifying voltage doubler converts the received RF energy into DC while the Power Management Unit (PMU) boosts-up and stores the rectified voltage providing a regulated output voltage of 1.8V to the RFID tag IC (ROCKY100) and 3.3V to the microcontroller unit (MCU) and the humidity and temperature sensor IC. The communication RFID antenna uses the European UHF frequency band centered at 868 MHz. When the RFID tag IC is supplied with 1.8 V from the PMU it operates in semi-passive mode and it effectively increases its communication range. The ROCKY100 is EPC C1G2 compliant and is compatible with power harvesting modules and SPI communication to support external low-power sensors and actuators. In addition, a capacitive digital humidity and temperature sensor (HTS221) is used as the sensing module for soil measurements. The process of measuring the relative humidity and temperature of the soil is controlled with a Texas Instrument mixed signal microcontroller that possesses two SPI interfaces that allows it to communicate with the RFID IC and the sensor in parallel. Upon receiving a SPI directed read request from the RFID reader, the ROCKY100 SPI bridge requests the value of the last measurement from the microcontroller and the humidity and temperature measurements taken by the HTS221 IC are sent to the RFID reader. The use of harvested wireless energy as a power source makes the demonstrated module a potentially batteryless and thus a 'Green' sensor. © 2022 IEEE.

关键词： Radio frequency identification (RFID)

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A new model based on Dynamic Naive Bayes classifier for retweet behavior prediction

A new model based on Dynamic Naive Bayes classifier for retw...

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Conference on Artificial Intelligence and Robotics and Asia-Pacific International Symposium

作者： Rahebeh Mojtahedi Safari Amir Masoud Rahmani Sasan H. Alizaeh Department of Computer and Information Technology Engineering Qazvin Branch Islamic Azad University Qazvin Iran Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin Taiwan Faculty of Information Technology ICT Research Institute (Iran Telecommunication Research Center) Tehran Iran

At present, the prediction of user retweeting behavior plays a significant role in perceiving the underlying mechanism of information diffusion in the microblogging network. The problem of retweeting behavior prediction is usually considered as a classification task hence, the effort for the classification of the time-series data in the microblogging network has gained spacious attention. It is challenging to improve the classification accuracy of retweeting behavior prediction models, because the applied classifications still lack a tailored method. To address this, we present a retweeting behavior prediction model based on Dynamic Naïve Bayes classifier that is an appropriate classifier dealing with time-series data classification. In fact, we apply a time discretization approach and incorporate user individual, social and temporal features into our proposed prediction model to estimate accurately user retweeting behavior in the microblogging network over time. The real Twitter(X) microblogging dataset is used to evaluate the performance of the proposed model in the user retweeting prediction. The experimental results show that our proposed classifier due to its simple structure can avoid overfitting problem, and outperforms in compared to other baseline methods.

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Confidentially Computing DNA Matching Against Malicious Adversaries 1

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7th International Conference on Smart Computing and Communication, SmartCom 2022

作者： Tu, Xiaofen Liu, Xin Hu, Xiangyu Li, Baoshan Xiong, Neal N. School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou014010 China School of Computer Science Shanxi Normal University Xi’an710062 China National Engineering Research Center for E-Learning Central China Normal University Wuhan430079 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (数字)9783031281242

ISBN: (纸本)9783031281235

DNA is one of the most important information in every living thing. The DNA matching experiment is helpful for the study of paternity testing, species identification, gene mutation, suspect determination, and so on. How to study the DNA matching in the case of privacy protection has become the inevitable problems in the research of information security. The Hamming distance can reflect the similarity degree of two DNA sequences. The smaller the Hamming distance is, the more similar the two DNA sequences are. In this paper, the DNA sequence with l length is encoded with a 0–1 string with 3 l length, and the protocol of confidentially computing Hamming distance is designed, which calculated the matching degree of two DNA under the premise of protecting DNA privacy. In addition, in view of the criminal suspect DNA matching problem, we design a secure computation protocol against malicious adversaries using the zero-knowledge proof and the cut-choose method to prevent or find malicious behaviors, which can resist malicious attacks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： DNA

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Quantitative Applications of Weather Satellite Data for Nowcasting:Progress and Challenges

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Journal of Meteorological research 2024年第3期38卷 399-413页

作者： Jun LI Jing ZHENG Bo LI Min MIN Yanan LIU Chian-Yi LIU Zhenglong LI WPaul MENZEL Timothy J.SCHMIT John L.CINTINEO Scott LINDSTROM Scott BACHMEIER Yunheng XUE Yayu MA Di DI Han LIN Innovation Centre for Fengyun Meteorological Satellite(FYSIC) National Satellite Meteorological CentreChina Meteorological AdministrationBeijing100081China School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University and Southern Laboratory of Ocean Science and EngineeringZhuhai519082China Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai200241China Research Center for Environmental Changes Academia SinicaTaipei11529China Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-MadisonMadisonWI53706USA Sensors and Calibration Branch STAR/NESDISMadisonWI53706USA Wuxi University Wuxi214105China School of Computer Science Chengdu University of Information TechnologyChengdu610225China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing210044China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National and Local Joint Engineering Research Center of Satellite Geospatial Information TechnologyFuzhou UniversityFuzhou350108China

Monitoring and predicting highly localized weather events over a very short-term period,typically ranging from minutes to a few hours,are very important for decision makers and public *** these events usually relies on radar observations through monitoring and *** advanced high-resolution imaging and sounding observations from weather satellites,nowcasting can be enhanced by combining radar,satellite,and other data,while quantitative applications of those data for nowcasting are advanced through using machine learning *** applications include monitoring the location,impact area,intensity,water vapor,atmospheric instability,precipitation,physical properties,and optical properties of the severe storm at different stages(pre-convection,initiation,development,and decaying),identification of storm types(wind,snow,hail,etc.),and predicting the occurrence and evolution of the *** observations can provide information on the environmental characteristics in the preconvection stage and are very useful for situational awareness and storm *** paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges,and future perspectives are also addressed and discussed.

关键词： weather satellite quantitative applications nowcasting pre-convection

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A Lightweight and Robust Access Control Protocol for IoT-based e-Healthcare Network

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IEEE Transactions on Mobile Computing 2025年

作者： Ghaffar, Zahid Kuo, Wen-Chung Mahmood, Khalid Tariq, Tayyaba Shamshad, Salman Das, Ashok Kumar Alenazi, Mohammed J.F. National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University Department of Computer Science and Engineering College of Informatics 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh Saudi Arabia

Internet of Things (IoT) devices are crucial components in e-healthcare networks. It enables remote patient health monitoring and facilitates seamless communication among medical sensors, wearable devices, and healthcare providers through public communication channels. Despite these advantages, the use of public communication among medical sensors in e-healthcare networks introduces critical challenges, such as vulnerability to impersonation, physical capture, and ephemeral secret leakage, particularly in resource-constrained environments. In recent years, various access control protocols have been developed to mitigate these risks. However, these protocols often fail to ensure robust security while incurring significant communication and computation overhead. To overcome these limitations, we propose a lightweight and robust access control protocol for IoT-based e-healthcare networks using chaotic maps. We propose a novel protocol that integrates a PUF-based mechanism to mitigate the challenges of physical tampering and cloning attacks in e-healthcare networks. It leverages the inherent uniqueness of PUF and enhances security through the high-entropy properties of chaotic maps. We analyze the proposed protocol informally, which confirms that it significantly bolsters efficiency and security. We also validate the security using the Random or Real (RoR) model. Moreover, we verify the security of the proposed protocol using Scyther. These analyses highlight that the proposed protocol offers robust resistance to numerous attacks, such as impersonation, physical capture, and ephemeral secret leakage. Moreover, we also compare it with existing and relevant protocols. The comparative analysis showcases its superior performance. Notably, the proposed authentication protocol significantly reduces 46.84% computational overhead and decreases 31.30% communication overhead, underscoring its enhanced performance and resource efficiency. © 2002-2012 IEEE.

关键词： Authentication

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无人飞行器在不确定扰动下的动态目标跟踪

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engineering 2024年第4期35卷 74-85页

作者： Yanjie Chen Yangning Wu Limin Lan Hang Zhong Zhiqiang Miao Hui Zhang Yaonan Wang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Department of Computer Science Aberystwyth UniversityAberystwyth SY233DBUK School of Robotics Hunan UniversityChangsha 410082China College of Electrical and Information Engineering Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

关键词： Unmanned aerial vehicle Visual servoing Velocity observer Target tracking

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Design of Smart Farm Service Architecture Based-On Microservice

Design of Smart Farm Service Architecture Based-On Microserv...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Hye-Been Nam Sunghyun Yoon Juyoung Park Dong Sig Shin Sang-Hwan Lee Seok-Joo Koh Computer Science and Engineering Kyungpook National University Daegu Republic of Korea Protocol Engineering Center Electronics & Telecommunications Research Institute Daejeon Republic of Korea Convergence Technology Research Center Korea Institute of Machinery & Materials Daegu Republic of Korea Artificial Intelligence Data Research Team Korea Institute of Science and Technology Information Daejeon Republic of Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

With the rapid advancements in IoT, big data, and AI technologies, smart farm and agriculture have emerged as a key solution for improving productivity and maintaining optimal crop growth environments, leading to various ongoing studies. As part of this research, this paper proposes a microservice-based smart agriculture framework that integrates cloud and edge computing. The framework consists of cloud, edge, controller, and device entities, each playing a crucial role in ensuring efficient environmental control and real-time decision-making for crop growth. By incorporating edge computing, the proposed service architecture mitigates issues related to network latency and failures, thereby enhancing system stability and responsiveness. Moreover, the service management module, present in both cloud and edge entities, enables flexible service scalability and version control while ensuring seamless operation even during network outages. Through the implementation of a testbed, we validated the system's operational procedures and demonstrated that the edge-enabled architecture reduces response times by approximately 40% in high-latency network conditions. This study highlights the potential of edge computing in smart agriculture and lays the groundwork for future research focusing on comprehensive performance evaluations and high-availability service monitoring in various environments.

关键词： Smart agriculture Performance evaluation Cloud computing Scalability Microservice architectures Crops computer architecture Real-time systems Time factors Edge computing

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DAS benchmarking methodology based on FWZIC II and FDOSM II to support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12747-12774页

作者： Mahmoud, U.S. Albahri, A.S. AlSattar, H.A. Zaidan, A.A. Talal, M. Mohammed, R.T. Albahri, O.S. Zaidan, B.B. Alamoodi, A.H. Qahtan, Sarah Baghdad Iraq Baghdad Iraq Baghdad Iraq Department of Computing FSKIK Universiti Pendidikan Sultan Idris Tanjung Malim35900 Malaysia Faculty of Engineering and IT British University in Dubia Dubai United Arab Emirates Parit Raja Johor Batu Pahat86400 Malaysia Department of Computer Science Faculty of Science Komar University of Science and Technology Sulaymaniyah Iraq Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan College of Health and Medical Technology Middle Technical University Baghdad Iraq Department of Business Administration College of Administrative Science The University of Mashreq Baghdad Iraq

This study proposed a novel methodology of data acquisition systems (DASs) benchmarking based on fuzzy-weighted zero-inconsistency (FWZIC II) and fuzzy decision by opinion score method (FDOSM II), which are applied in an intuitionistic fuzzy set (IFS) context and account for hesitation when benchmarking DASs, to support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles. The proposed methodology comprises two consecutive phases. The first phase involves constructing a decision matrix based on the intersection of the DAS alternatives and criteria. The second phase (development phase) proposes the formulation of a novel FWZIC II to weight the criteria and the formulation of a novel FDOSM II to benchmark DASs. Fourteen DASs were benchmarked based on the 15 DAS criteria, which included seven sub-criteria for ‘comprehensive complexity assessment’ and eight sub-criteria for ‘design and implementation’, which had a significant effect on the DAS design when implemented by industrial communities. A systematic ranking and sensitivity analysis were conducted to demonstrate that the benchmarking results were subject to systematic ranking, as indicated by the high correlations across all described scenarios of changing criteria weight values. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Benchmarking

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DRCTL: A Disorder-Resistant Computation Translation Layer Enhancing the Lifetime and Performance of Memristive CIM Architecture

DRCTL: A Disorder-Resistant Computation Translation Layer En...

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IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Heng Zhou Bing Wu Huan Cheng Jinpeng Liu Taoming Lei Dan Feng Wei Tong Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology School of Computer Science and Technology Huazhong University of Science and Technology Ministry of Education of China

ISBN: (数字)9798350350579

ISBN: (纸本)9798350350586

The memristive Computing-in-Memory (CIM) sys-tem can efficiently accelerate matrix-vector multiplication (MVM) operations through in-situ computing. The data layout has a significant impact on the communication performance of CIM systems. Existing software-level communication opti-mizations aim to reduce communication distance by carefully designing static data layouts, while wear-leveling (WL) and error mitigation methods use dynamic scheduling to enhance system reliability, resulting in randomized data layouts and increased communication overhead. Besides, existing CIM compilers di-rectly map data to physical crossbars and generate instructions, which causes inconvenience for dynamic scheduling. To address these challenges of balancing communication performance and reliability while coordinating existing CIM compilers and dy-namic scheduling, we propose a disorder-resistant computation translation layer (DRCTL), which improves system lifetime and communication performance through co-optimization of data layout and dynamic scheduling. It consists of three parts: (1) We propose an address conversion method for dynamic scheduling, which updates the addresses in the instruction stream after dynamic scheduling, thereby avoiding recompilation. (2) Dynamic scheduling strategy for reliability improvement. We propose a hierarchical wear-leveling (HWL) strategy, which reduces communication by increasing scheduling granularity. (3) Communication optimization for dynamic scheduling. We propose data layout-aware selective remapping (LASR), which helps dynamic scheduling methods improve communication lo-cality and reduce latency by exploiting data dependencies. The experiments demonstrate that HWL extends lifetime by 100.3-205.9 x compared to not using WL. Even with a slight lifetime decrease compared to the state-of-the-art WL (TIWL), it still supports continuous neural network training for 7 years. After applying LASR to HWL, the number of execution cycles, energy consumption

关键词： Training Energy consumption Processor scheduling Layout Dynamic scheduling In-memory computing Common Information Model (computing) System-on-chip Reliability Optimization

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