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AMHF-TP:Multifunctional therapeutic peptides prediction based on multi-granularity hierarchical features

Quantitative Biology 2025年第1期13卷 127-141页

作者： Shouheng Tuo YanLing Zhu Jiangkun Lin Jiewei Jiang School of Computer Science and Technology Xi’an University of Posts and TelecommunicationsXi’anChina Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’anChina Xi’an Key Laboratory of Big Data and Intelligent Computing Xi’anChina School of Electronic Engineering Xi’an University of Posts and TelecommunicationsXi’anChina

Multifunctional therapeutic peptides(MFTP)hold immense potential in diverse therapeutic contexts,yet their prediction and identification remain challenging due to the limitations of traditional methodologies,such as extensive training durations,limited sample sizes,and inadequate generalization *** address these issues,we present AMHF-TP,an advanced method for MFTP recognition that utilizes attention mechanisms and multi-granularity hierarchical features to enhance *** AMHF-TP is composed of four key components:a migration learning module that leverages pretrained models to extract atomic compositional features of MFTP sequences;a convolutional neural network and selfattention module that refine feature extraction from amino acid sequences and their secondary structures;a hypergraph module that constructs a hypergraph for complex similarity representation between MFTP sequences;and a hierarchical feature extraction module that integrates multimodal peptide sequence *** with leading methods,the proposed AMHF-TP demonstrates superior precision,accuracy,and coverage,underscoring its effectiveness and robustness in MFTP *** comparative analysis of separate hierarchical models and the combined model,as well as with five contemporary models,reveals AMHFTP’s exceptional performance and stability in recognition tasks.

关键词： deep learning hypergraph multifunctional therapeutic peptides multi-granularity hierarchical features

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A Novel Four-State Switchable Dual-Band Bandpass Filter with High OFF-State Suppression Based on Multi-Mode Resonators

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Progress In Electromagnetics Research C 2024年 144卷 189-198页

作者： Yang, Bingjie Wang, Zhongbao Liu, Hongmei Gao, Mingming Fang, Shaojun School of Information Science and Technology Dalian Maritime University Liaoning Dalian116026 China Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications Liaoning Technical University Liaoning Huludao125105 China

A novel switchable dual-band bandpass filter (BPF) is proposed, where each passband can be independently controlled. The filter is composed of a tri-mode resonator, a dual-mode resonator, and feed lines coupling with the resonators. By controlling the PIN diodes loaded on the open end of the resonators, four operating states (i.e., dual bands, lower passband, upper passband, and all-stop band) are realized. A switchable dual-band BPF prototype is designed, fabricated, and measured with the center frequencies of 1.575 and 2.45 GHz having the bandwidths of 300 and 220 MHz, respectively. The prototype occupies an area of 0.128λ2g, where λg is the guided wavelength at the center frequency of the lower band (1.575 GHz). The measurement results indicate that the proposed switchable dual-band BPF has low insertion loss and high OFF-state suppression. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Bandpass filters

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Tracking Objects and Activities with Attention for Temporal Sentence Grounding 48

Tracking Objects and Activities with Attention for Temporal ...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Xiong, Zeyu Liu, Daizong Zhou, Pan Zhu, Jiahao Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Peking University Wangxuan Institute of Computer Technology China

ISBN: (纸本)9781728163277

Temporal sentence grounding (TSG) aims to localize the temporal segment which is semantically aligned with a natural language query in an untrimmed video. Most existing methods extract frame-grained features or object-grained features by 3D ConvNet or detection network under a conventional TSG framework, failing to capture the subtle differences between frames or to model the spatio-temporal behavior of core persons/objects. In this paper, we introduce a new perspective to address the TSG task by tracking pivotal objects and activities to learn more fine-grained spatio-temporal behaviors. Specifically, we propose a novel Temporal Sentence Tracking Network (TSTNet), which contains (A) a Cross-modal Targets Generator to generate multi-modal templates and search space, filtering objects and activities, and (B) a Temporal Sentence Tracker to track multi-modal targets for modeling the targets' behavior and to predict query-related segment. Extensive experiments and comparisons with state-of-the-arts are conducted on challenging benchmarks: Charades-STA and TACoS. And our TSTNet achieves the leading performance with a considerable real-time speed. © 2023 IEEE.

关键词： Computer vision

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Edge Computing Task Scheduling with Joint Blockchain and Task Caching in Industrial Internet

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Computers, Materials & Continua 2023年第4期75卷 2101-2117页

作者： Yanping Chen Xuyang Bai Xiaomin Jin Zhongmin Wang Fengwei Wang Li Ling School of Computer Science and Technology Xi’an University of Posts and TelecommunicationsXi’an710121China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an710121China Xi’an Key Laboratory of Big Data and Intelligent Computing Xi’anShaanxi710121China ZTE Corporation Shenzhen51805China

Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.

关键词： Edge computing task scheduling blockchain task caching industrial security

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An X-Band Frequency Beam-Scanning Circularly-Polarized Leaky-Wave Antenna with Low Axial Ratio in All Half-Power Beamwidth Ranges

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Progress In Electromagnetics Research C 2024年 139卷 129-137页

作者： Zhang, Dezhuang Wang, Zhongbao Xu, Zhixia Liu, Hongmei Gao, Mingming Fang, Shaojun School of Information Science and Technology Dalian Maritime University Liaoning Dalian116026 China Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications Liaoning Technical University Huludao Liaoning 125105 China

A novel frequency beam-scanning circularly-polarized leaky-wave antenna with the axial ratio (AR) of less than 3 dB in all the half-power beamwidth ranges based on an H-shaped slow-wave transmission line is proposed for X-band applications. The proposed circularly-polarized leaky-wave antenna is composed of a novel slow-wave transmission line and two rows of elliptical patch structures, leading to wide AR bandwidth, backward-to-forward beam scanning, and stable gain. To verify the proposed antenna, one prototype with a center frequency of 10 GHz is designed and fabricated. Measured results indicate that the main beam scans from −25◦ to +28◦ within the operating frequency variation from 8.7 to 11.5 GHz. The 3-dB AR bandwidth and maximum gain are 27.7% and 10.28 dBic, respectively. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Slot antennas

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A Novel Bandpass-to-All-Stop Switchable Absorptive Filter with Ultra-Wideband Reflectionless Range

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Progress In Electromagnetics Research C 2024年 147卷 99-107页

作者： Yang, Bingjie Wang, Zhongbao Zhao, Shipeng Liu, Hongmei Gao, Mingming Fang, Shaojun School of Information Science and Technology Dalian Maritime University Liaoning Dalian116026 China Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications Liaoning Technical University Liaoning Huludao125105 China

A novel bandpass-to-all-stop switchable absorptive filter with an ultra-wideband reflectionless range is proposed in this paper. The bandpass section of the filter consists of a dual-mode resonator and two L-shaped feeding lines. The dual-port reflectionless characteristic is achieved by loading absorption networks at the end of the open stubs of the feeding lines, which are composed of two parallel coupled lines and absorption resistors. The switching of the reflectionless bandpass filter (RBPF) to the all-stop filter (ASF) is realized by controlling the on/off behavior of the PIN diode through the bias voltage. Measurements show that the filter prototype at the center frequency of 2.43 GHz with the 3-dB fractional bandwidth (FBW) is 8.23%. For the RBPF state, the filter has an ultra-wideband reflectionless FBW of 214% and upper stopband rejection better than 33 dB up to 6 GHz. Besides, the rejection is better than 30 dB from 0 to 5.32 GHz in the ASF state. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Ultra-wideband (UWB)

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A Write-Optimized PM-oriented B+-tree with Aligned Flush and Selective Migration 21

A Write-Optimized PM-oriented B+-tree with Aligned Flush and...

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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International Conference on big data and Cloud Computing, 16th IEEE International Conference on Social Computing and Networking and 13th International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： He, Xianyu Zhang, Runyu Tian, Pengpeng Zhou, Lening Lian, Min Yang, Chaoshu Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang China

ISBN: (纸本)9798350329223

Emerging Persistent Memories (PMs) usually have the severe drawback of expensive writes. Therefore, existing PM-oriented B+-trees mainly concentrate on alleviating the write overhead (i.e., reducing the writes to PM and the flush instructions). Unfortunately, these schemes still employ improper data organization in leaf nodes, which can lead to massive data migration during insertions or node splits. This paper proposes a write-optimized PM-oriented B+ -tree (WPB+ -tree) to solve the above problems. WPB+ -tree first adopts a buffer-assisted mechanism that temporarily stores the newly inserted data to reduce the overhead of data migration and flush. Second, WPB+ tree employs a selective migration of node entries to achieve less data migration when splitting a node. We implement the proposed WPB+ -tree with actual persistent memory. Compared with state-of-the-art solutions (i.e., FAST&FAIR and SSB-Tree), WPB+ -tree achieves up to 17%, 40%, and 20% higher throughput in the insert, search, and scan operations, respectively. © 2023 IEEE.

关键词： Cost reduction

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The Double Contrast for Unsupervised Person Re-Identification 24

The Double Contrast for Unsupervised Person Re-Identificatio...

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2024 International Conference on Computer Vision and Deep Learning, CVDL 2024

作者： Liu, Daocheng Fu, Yanyun Shi, Wenxi Zhu, Zhansheng Wang, Deyong School of Computer Science and Technology Urumqi China Beijing Academy of Science and Technology Beijing China Key Laboratory of Big Data of Xinjiang Social Security Risk Urumqi China

ISBN: (纸本)9798400718199

At present, the most popular unsupervised person re-identification(Re-ID) research mainly uses some clustering methods to gather samples with similar features and generate a pseudo-label for each cluster, and uses the parameterless contrast loss to feedback correlation information between *** previous methods used the memory dictionary to store all instance-dependent features, but This approach does not take into account the different number of positive samples in each cluster, and the progress of each cluster update of the memory dictionary is not the *** order to improve the consistency of the update progress, a method is implemented to store the central feature vector in each cluster, but using a hard-sample feature vector in the cluster to update it, so that a single instance feature cannot represent the central feature well. In this article, we study out a method to combine hard instance contrast and cluster contrast, that is, the central feature vector in each cluster is stored in the memory dictionary, and the hard instance feature vector in each cluster is also stored *** addition, in terms of momentum update, the central feature vector and hard instance feature vector of each cluster in mini-batch are used for *** not only solves the problem of inconsistent update progress, but also better learns the similarity and difference of instances in the same cluster, and better aggregates instances within cluster and instances between clusters. Through three dataset experiments, it is concluded that this method has a good improvement. © 2024 ACM.

关键词： Vectors

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Segmenting vegetation from UAV images via spectral reconstruction in complex field environments

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植物表型组学（英文） 2025年第1期7卷 212-224页

作者： Zhixun Pei Xingcai Wu Xue Wu Yuanyuan Xiao Peijia Yu Zhenran Gao Qi Wang Wei Guo State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China State Key Laboratory of Green Pesticide Guizhou UniversityGuiyang 550025China New Rural Development Research Institute Guizhou UniversityGuiyang550025China Graduate School of Agricultural and Life Sciences The University of TokyoTokyo188-0002Japan

Segmentation of vegetation remote sensing images can minimize the interference of background,thus achieving efficient monitoring and analysis for vegetation *** segmentation of vegetation poses a significant challenge due to the inherently complex environmental ***,there is a growing trend of using spectral sensing combined with deep learning for field vegetation segmentation to cope with complex ***,two major constraints remain:the high cost of equipment required for field spectral data collection;the availability of field datasets is limited and data annotation is time-consuming and *** address these challenges,we propose a weakly supervised approach for field vegetation segmentation by using spectral reconstruction(SR)techniques as the foundation and drawing on the theory of vegetation index(Ⅵ).Specifically,to reduce the cost of data acquisition,we propose SRCNet and SRANet based on convolution and attention structure to reconstruct multispectral images of fields,***,borrowing from the Ⅵprinciple,we aggregate the reconstructed data to establish the connection of spectral bands,obtaining more salient vegetation ***,we employ the adaptation strategy to segment the fused feature map using a weakly supervised method,which does not require manual labeling to obtain a field vegetation segmentation *** segmentation method can achieve a Mean Intersection over Union(MIoU)of 0.853 on real field datasets,which outperforms the existing *** addition,we have open-sourced a dataset of unmanned aerial vehicle(UAV)RGB-multispectral images,comprising 2358 pairs of samples,to improve the richness of remote sensing agricultural *** code and data are available at egment_SR,and .

关键词： Segmentation Spectral reconstruction UAV field images

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Joint Double Auction-Based Channel Selection in Wireless Monitoring Networks

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2412-2426页

作者： Xia, Na Chen, Lei Li, Meng Yin, Yutao Zhang, Ke Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data China State Grid Electric Power Research Institute Co. Ltd Hefei230088 China

In wireless networks, utilizing sniffers for fault analysis, traffic traceback, and resource optimization is a crucial task. However, existing centralized algorithms cannot be applied to high-density wireless networks. Therefore, distributed optimization of channel selection to maximize the monitoring rate of sensors in Wireless Monitoring Networks (WMNs) is a challenge. This paper proposes a joint double auction-based distributed channel selection algorithm (J2A-CS) to maximize overall quality of monitoring (QoM). First, sniffers are redundantly deployed in WMNs, and an initial channel allocation strategy is formulated. Subsequently, sniffers collectively act as buyers and sellers at different stages. Finally, buyers bid asynchronously, and sellers settle synchronously to maximize the seller's marginal revenue and update the channel selection scheme. As a distributed channel selection algorithm, J2A-CS addresses the highest overall QoM issue in WMNs, demonstrating high scalability and fault tolerance. Simulation results show that J2A-CS significantly improves QoM compared to existing distributed algorithms and outperforms centralized algorithms in high-density scenarios. © 2004-2012 IEEE.

关键词： Sales

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