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A Modified CycleGAN for Multi-Organ Ultrasound Image Enhancement via Unpaired Pre-Training

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Journal of Beijing institute of technology 2024年第3期33卷 194-203页

作者： Haonan Han Bingyu Yang Weihang Zhang Dongwei Li Huiqi Li School of information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Medical technology Beijing Institute of TechnologyBeijing 100081China

Handheld ultrasound devices are known for their portability and affordability,making them widely utilized in underdeveloped areas and community healthcare for rapid diagnosis and early ***,the image quality of handheld ultrasound devices is not always satisfactory due to the limited equipment size,which hinders accurate diagnoses by *** the same time,paired ultrasound images are difficult to obtain from the clinic because imaging process is ***,we propose a modified cycle generative adversarial network(cycleGAN) for ultrasound image enhancement from multiple organs via unpaired *** introduce an ultrasound image pre-training method that does not require paired images,alleviating the requirement for large-scale paired *** also propose an enhanced block with different structures in the pre-training and fine-tuning phases,which can help achieve the goals of different training *** improve the robustness of the model,we add Gaussian noise to the training images as data *** approach is effective in obtaining the best quantitative evaluation results using a small number of parameters and less training costs to improve the quality of handheld ultrasound devices.

关键词： ultrasound image enhancement handheld devices unpaired images pre-train and finetune cycleGAN

HetNets Under Decoupled Uplink and Downlink Access with UE Random Discontinuous Transmission: Local Delay and Energy Efficiency

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China Communications 2024年第3期21卷 205-216页

作者： Zhang Yue Zheng Fuchun Luo Jingjing School of Electronic and information Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China

Due to the limited uplink capability in heterogeneousnetworks (HetNets), the decoupled uplinkand downlink access (DUDA) mode has recently beenproposed to improve the uplink performance. In thispaper, the random discontinuous transmission (DTX)at user equipment (UE) is adopted to reduce the interferencecorrelation across different time slots. By utilizingstochastic geometry, we analytically derive themean local delay and energy efficiency (EE) of an uplinkHetNet with UE random DTX scheme under theDUDA mode. These expressions are further approximatedas closed forms under reasonable *** results reveal that under the DUDA mode, there isan optimal EE with respect to mute probability underthe finite local delay constraint. In addition, with thesame finite mean local delay as under the coupled uplinkand downlink access (CUDA) mode, the HetNetsunder the DUDA mode can achieve a higher EE witha lower mute probability.

关键词： decoupled uplink and downlink access(DUDA) heterogeneous networks(HetNets) random discontinuous transmission(DTX) stochastic geometry

A Method of Generating Semi-Experimental Biomedical Datasets

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Journal of Beijing institute of technology 2024年第3期33卷 219-226页

作者： Jing Wang Naike Du Zi He Xiuzhu Ye School of information and Electronics Beijing Institute of TechnologyBeijing 100081China

This paper proposed a method to generate semi-experimental biomedical datasets based on full-wave simulation *** system noise such as antenna port couplings is fully considered in the proposed datasets,which is more realistic than synthetical *** this paper,datasets containing different shapes are constructed based on the relative permittivities of human ***,a back-propagation scheme is used to obtain the rough reconstructions,which will be fed into a U-net convolutional neural network(CNN)to recover the high-resolution *** results show that the network trained on the datasets generated by the proposed method can obtain satisfying reconstruction results and is promising to be applied in real-time biomedical imaging.

关键词： electromagnetic imaging dataset biomedical imaging

A Deformable network with Attention Mechanism for Retinal Vessel Segmentation

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Journal of Beijing institute of technology 2024年第3期33卷 186-193页

作者： Xiaolong Zhu Wenjian Li Weihang Zhang Dongwei Li Huiqi Li School of information and Electronics Beijing Institute of TechnologyBeijing 100081China

The intensive application of deep learning in medical image processing has facilitated the advancement of automatic retinal vessel segmentation *** overcome the limitation that traditional U-shaped vessel segmentation networks fail to extract features in fundus image sufficiently,we propose a novel network(DSeU-net)based on deformable convolution and squeeze excitation residual *** deformable convolution is utilized to dynamically adjust the receptive field for the feature extraction of retinal *** the squeeze excitation residual module is used to scale the weights of the low-level features so that the network learns the complex relationships of the different feature layers *** validate the DSeU-net on three public retinal vessel segmentation datasets including DRIVE,CHASEDB1,and STARE,and the experimental results demonstrate the satisfactory segmentation performance of the network.

关键词： retinal vessel segmentation deformable convolution attention mechanism deep learning

A Deep Learning Method to Process Scattered Field Data in Biomedical Imaging System

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Journal of Beijing institute of technology 2024年第3期33卷 213-218页

作者： Jing Wang Naike Du Xiuzhu Ye School of information and Electronics Beijing Institute of TechnologyBeijing 100081China

This paper proposed a deep-learning-based method to process the scattered field data of transmitting antenna,which is unmeasurable in inverse scattering system because the transmitting and receiving antennas are multiplexed.A U-net convolutional neural network(CNN)is used to recover the scattered field data of each transmitting *** numerical results proved that the proposed method can complete the scattered field data at the transmitting antenna which is unable to measure in the actual experiment and can also eliminate the reconstructed error caused by the loss of scattered field data.

关键词： inverse problem scattered field deep learning

Grouping Decision Algorithm for Dynamic Terminals in Random Access networks

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Journal of Communications and information networks 2024年第2期9卷 176-183页

作者： Hongliang Sun Tongfei Chen Chuangye Zhao Mengxin Chen College of information and Control Engineering Jilin Institute of Chemical TechnologyJilin 132022China

This paper proposes a grouping decision algorithm for random access networks with the carrier sense multiple access (CSMA) mechanism, which can balance the traffic load and solve the hidden terminal issue. Considering the arrival characteristics of terminals and quality of service (QoS) requirements, the traffic load is evaluated based on the effective bandwidth theory. Additionally, a probability matrix of hidden terminals is constructed to take into account the dynamic nature of hidden terminal relations. In the grouping process, an income function is established with a view to the benefits of decreasing the probability of hidden terminal collisions and load balancing. Then, we introduce the grey wolf optimization (GWO) algorithm to implement the grouping decision. Simulation results demonstrate that the grouping algorithm can effectively alleviate the performance degradation and facilitate the management of network resources.

关键词： random access network hidden terminal collision probability effective bandwidth traffic load grey wolf optimization

Constructing the Impossible Differential of Type-II GFN with Boolean Function and Its Application to WARP

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Chinese Journal of Electronics 2024年第1期33卷 80-89页

作者： Jiali SHI Guoqiang LIU Chao LI College of Liberal Arts and Sciences National University of Defense Technology Hunan Engineering Research Center of Commercial Cryptography Theory and technology Innovation State Key Laboratory of information Security Institute of Information Engineering

Type-Ⅱ generalized Feist el network(GFN) has attracted a lot of attention for its simplicity and high *** differential attack is one of the powerful cryptanalytic approaches for word-oriented block ciphers such as Feistel-like *** deduce the impossible differential of Type-Ⅱ GFN by analyzing the Boolean function in the middle *** main idea is to investigate the expression with the variable representing the plaintext(ciphertext) difference words for the internal state *** adopting the miss-in-the-middle approach,we can construct the impossible differential of Type-Ⅱ *** an illustration,we apply this approach to WARP,a lightweight 128-bit block cipher with a 128-bit key which was presented by Banik et *** SAC *** structure of WARP is a 32-branch Type-Ⅱ ***,we find two 21-round truncated impossible differentials and implement a 32-round key recovery attack on *** the 32-round key recovery attack on WARP,some observations are used to mount an effective *** the advantage of the early abort technique,the data,time,and memory complexities are 2125.69chosen plaintexts,2126.6832-round encryptions,and 2100-bit,*** the best of our knowledge,this is the best attack on WARP in the single-key scenario.

关键词： Ciphers Boolean functions Parallel processing Complexity theory

Weighted sum power maximization for STAR-RIS-aided SWIPT systems with nonlinear energy harvesting

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Science China(information Sciences) 2024年第10期67卷 343-358页

作者： Weiping SHI Cunhua PAN Feng SHU Yongpeng WU Jiangzhou WANG Yongqiang BAO Jin TIAN School of network and Communication Nanjing Vocational College of Information Technology National Mobile Communications Research Laboratory Southeast University School of information and Communication Engineering Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent School of information and Communication Engineering Nanjing Institute of Technology Engineering School of networks and Telecommunications Jinling Institute of Technology

The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting(STAR)-RIS-aided simultaneous wireless information and power transfer(SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting(ES),time switching(TS), and mode switching(MS). The objective of this paper is to maximize the weighted sum power(WSP) of all energy harvesting receivers(EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station(BS)and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers(IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization(AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs *** findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided sy

关键词： STAR-RIS beamforming SWIPT alternating optimization nonlinear energy harvesting

A Layered Energy-Efficient Multi-Node Scheduling Mechanism for Large-Scale WSN

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Computers, Materials & Continua 2024年第4期79卷 1335-1351页

作者： Xue Zhao Shaojun Tao Hongying Tang Jiang Wang Baoqing Li Science and technology on Microsystem Laboratory Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai200050China

In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criticalobjectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. Theproposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH)election, pre-selection, and task set selectionmechanisms, where the latter two kinds of selections forma two-layerselection mechanism. The CH election innovatively introduces the movement trend of the target and establishesa scoring mechanism to determine the optimal CH, which can delay the CH rotation and thus reduce energyconsumption. The pre-selection mechanism adaptively filters out suitable nodes as the candidate task set to applyfor tracking tasks, which can reduce the application consumption and the overhead of the following task setselection. Finally, the task node selection is mathematically transformed into an optimization problem and thegenetic algorithm is adopted to form a final task set in the task set selection mechanism. Simulation results showthat HMNCS outperforms other compared mechanisms in the tracking accuracy and the network lifetime.

关键词： Node scheduling pre-selection target tracking WSN