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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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Twitter Bot Detection with Multi-Head Attention and Supervised Contrastive Learning 21

Twitter Bot Detection with Multi-Head Attention and Supervis...

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21st International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2024

作者： Qiang, Liu Jiazhong, Lu Yuanyuan, Huang Weisha, Zhang Jun, Lv School of Cybersecurity Xin Gu Industrial College Chengdu University of Information Technology Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China SUGON Industrial Control and Security Center Chengdu610225 China School of Foreign Languages University of Electronic Science and Technology of China Chengdu611731 China Co. Ltd. China

ISBN: (纸本)9798331519254

The task of detecting bots on Twitter is an indispensable task for combating social network disinformation, curbing rumors, and managing online public opinion. However, today's social bots often disguise themselves by mimicking various aspects of real user characteristics to escape detection, which poses an unprecedented challenge to the existing Twitter bot detection task. To address this, an innovative detection method is presented in this study that improves the accuracy of Twitter bot detection by realizing the effective fusion of multi-dimensional features through the multi-head attention mechanism and applying it to a relational graph convolutional network. It also combines supervised contrastive learning to strengthen the differentiation ability of the high-latitude features. Experiments conducted on the publicly available dataset Twibot-20, compared to the baseline, the proposed method achieves approximately 1% better results in both Accuracy and the Matthews Correlation Coefficient, proving its effectiveness. © 2024 IEEE.

关键词： Contrastive Learning

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Helmet wearing detection based on YOLOv5 3

Helmet wearing detection based on YOLOv5

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3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Wu, Chao Wang, De-Yong Shi, Wen-Xi Fang, Jian Zhao, Xue-Yi Fu, Yan-Yun School of Information Science and Engineering Xinjiang University Urumqi830000 China XinJiang Lianhai INA-INT Information Technology Co. Ltd. Urumqi830000 China Key Laboratory of Big Data of Xinjiang Social Security Risk Prevention and Control Urumqi830000 China Beijing Academy of Science and Technology Beijing100035 China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

Complex environments, such as dense personnel and background interference, affect the detection accuracy of whether personnel wear helmets. To solve this problem, a new detection algorithm for helmets based on YOLOv5 is studied in this paper. Firstly, RepVGGblock is used to replace the common convolution in the network to effectively utilize the computing power of GPU. Secondly, the efficient channel attention mechanism is incorporated into the C3 module of the backbone network to enhance the feature identification ability of the backbone network for the hard hat. Then, the boundary box regression function is changed to SIoU to redefine the distance loss and improve the regression accuracy. Finally, the detection performance of multi-scale targets is improved by adding detection layers. The test results on the self-made safety helmet data set show that the average accuracy of the improved YOLOv5 model reaches 94.6%, which is 4.1% higher than that of the original model, and can meet the requirements of target detection. © 2023 SPIE.

关键词： Computing power

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Cooperative Local Path Planning for Multi-unmanned Vehicles Formation Using the Enhanced Artificial Potential Field 3rd

Cooperative Local Path Planning for Multi-unmanned Vehicles...

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Zhang, Xin Duan, Xuting Zhou, Jianshan Zhang, Long Opening Project of Key Laboratory of Operation Safety Technology on Transport Vehicles Ministry of Transport PRC Beijing China School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China Zhongguancun Laboratory Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

ISBN: (纸本)9789819711024

An enhanced approach utilizing APF(artificial potential field) method is introduced in this paper. By adopting this approach, the challenge of local minima that may occur when dealing with local path planning for unmanned vehicles is tackled. When the unmanned vehicle approaches an obstacle, a virtual attractive potential field is implemented, utilizing the deviation in the heading angle of the vehicle to control the steering angle. Consequently, the vehicle can avoid obstacles, resolving the issue of local minima and enabling its application in path planning for multi-unmanned vehicles. The ROS with Gazebo simulation platform is used to verify the enhanced algorithm’s effectiveness in multi-unmanned vehicle path planning in an unknown environment. © Beijing HIWING Scientific and Technological information Institute 2024.

关键词： Motion planning

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A robust TDOA based solution for source location using mixed Huber loss

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Journal of Systems Engineering and Electronics 2021年第6期32卷 1375-1380页

作者： YOU Mingyi LU Annan Science and Technology on Communication Information Security Control Laboratory No.36 Research Institute of China Elec-tronics Technology Group CorporationJiaxing 314033China No.36 Research Institute of China Electronics Technology Group Corporation Jiaxing 314033China

This paper proposes a source localization solution robust to measurement outliers in time differences of arrivals(TDOA)*** solution uses a piecewise loss function named as mixed Huber loss(MHL)proposed based on the classical Huber loss(HL)and its refined *** MHL is able to effectively mitigate the impact of all levels of measurement outliers by setting two triggering *** practice,appropriate triggering threshold values can be obtained through simulation given the level of measurement noise and a rough range of potential measurement outliers.A clustering based approach is proposed to further improve the robustness of localization solution against reference sensor related *** are included to examine the solution's performance and compare it with several *** proposed MHL based solution is shown to be superior to the classical solution and the *** solution is shown to be even robust to multiple measurement ***,the influence of range measurement outliers in the reference sensor can be effectively mitigated by the clustering based approach.

关键词： time differences of arrivals(TDOA) robust localization Huber loss(HL) outlier mitigation

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Thermal camera based on frequency upconversion and its noise-equivalent temperature difference characterization

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Advanced Photonics Nexus 2023年第4期2卷 44-49页

作者： Zheng Ge Zhi-Yuan Zhou Jing-Xin Cheng Li Chen Yin-Hai Li Yan Li Su-Jian Niu Bao-Sen Shi University of Science and Technology of China CAS Key Laboratory of Quantum InformationHefeiChina University of Science and Technology of China CAS Center for Excellence in Quantum Information and Quantum PhysicsHefeiChina Science and Technology on Electro-Optical Information Security Control Laboratory TianjinChina

We present a scheme for estimating the noise-equivalent temperature difference(NETD)of frequency upconversion detectors(UCDs)that detect mid-infrared(MIR)*** particular,we investigate the frequency upconversion of a periodically poled crystal based on lithium niobate,where an MIR conversion bandwidth of 220 nm can be achieved in a single-poled period by a special ***,for an MIR radiating target at a temperature of 95℃,the NETD of the device was estimated to be 56 mK with an exposure time of 1 ***,a direct measurement of the NETD was performed utilizing conventional methods,which resulted in 48 *** also compared the NETD of our UCD with commercially available direct MIR *** show that the limiting factor for further NETD reduction of our device is not primarily from the upconversion process and camera noise but from the limitations of the heat source and laser *** detectors have good temperature measurement performance and can be used for a variety of applications involving temperature object identification and material structure detection.

关键词： mid-infrared detection frequency upconversion noise equivalent temperature difference

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High Precision Translational Compensation for Ultrahigh Resolution ISAR 13

High Precision Translational Compensation for Ultrahigh Reso...

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13th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2021

作者： Yang, Lichao Science and Technology on Communication Information Security Control Laboratory No. 36 Research Institute of CETC China

ISBN: (纸本)9781665418126

In recent years, due to the emergence of ultrahigh resolution (UHR) radar systems, the bandwidth of radar has been increasing. However, conventional imaging algorithms have difficulties in the translational compensation of UHR inverse synthetic aperture radar (ISAR) data with high order range cell migration (RCM) and phase error. In this paper, a high-precision translational compensation method based on power flatness optimization (PFO) is proposed. The algorithm constructs the optimal criterion of power flatness and ensure the complete extraction of the prominent point energy. Then, the original data is compensated in the two-dimensional data domain through the prominent point phase inversion matrix. The results show that the proposed algorithm has significantly improved accuracy in the translational compensation of ultrahigh-resolution ISAR imaging compared with traditional algorithms. © 2021 IEEE.

关键词： Inverse synthetic aperture radar

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Timing and carrier synchronization algorithm of MQAM signal

Timing and carrier synchronization algorithm of MQAM signal

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2021 International Conference on Signal Image Processing and Communication, ICSIPC 2021

作者： Zhou, Huaji Yang, Lifeng Lei, Yingke Science and Technology on Communication Information Security Control Laboratory Jiaxing China National University of Defense Technology Hefei China

ISBN: (数字)9781510645417

ISBN: (纸本)9781510645400

This paper is focused on the synchronization algorithm of the blind demodulation in the case of unknown any prior information, which is aiming to meet the requirement of blind demodulation of MQAM signal when non-cooperative communication. After the signal passes through the Gaussian channel, in order to correct the time offset, the Gardner timing loop based on the FIR pre-filtering of self-noise reduction is studied and the carrier synchronization loop based on PD algorithm and DD algorithm switching principle is aiming to correct the phase offset. Through the simulation signal respectively on the timing and carrier loop simulation, the results show that the design Loop synchronization effect is good, in the project has a greater application value. © 2021 SPIE.

关键词： Demodulation

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Energy Minimization Oriented Resource Allocation for Relay Assisted NOMA-MEC Networks

Energy Minimization Oriented Resource Allocation for Relay A...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Qianru Wang Liping Qian Yuan Wu Xiaoniu Yang College of Information Engineering Zhejiang University of Technology Hangzhou China State Key Laboratory of Internet of Things for Smart City University of Macau China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

With the growing demand for image transmission, there is a need for solutions that offer low energy consumption and low latency. In this paper, we present a novel relay-assisted system based on non-orthogonal multiple access (NOMA) and mobile edge computing (MEC). Our proposed system compresses images at the device end, decompresses them at either a relay or a cloud server (CS). The primary objective is to minimize system energy consumption under given task delay constraints. Considering that this is a non-convex optimization problem, we solve it by decomposing it into a continuous subproblem and a discrete subproblem. To solve the continuous subproblem, we convexify it by introducing new parameters and change variables to get the optimal the computing power of devices, relay and CS, sampling rate of devices, transmission power of devices and relay. To solve the discrete subproblem, we propose a cross-entropy (CE) algorithm to obtain the optimal decompression decision and subcarrier allocation decision. Simulation results demonstrate the accuracy and effectiveness of our algorithm in optimizing total energy consumption compared to the Linear Interactive and General Optimizer (LINGO) and frequency division multiple access (FDMA) methods.

关键词： Performance evaluation NOMA Energy consumption Image coding Multi-access edge computing Simulation Optimization methods Resource management Servers Relays

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Size-Invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection 41

Size-Invariance Matters: Rethinking Metrics and Losses for I...

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41st International Conference on Machine Learning, ICML 2024

作者： Li, Feiran Xu, Qianqian Bao, Shilong Yang, Zhiyong Cong, Runmin Cao, Xiaochun Huang, Qingming Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Sun Yat-sen University Shenzhen Campus China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD. Copyright 2024 by the author(s)

关键词： Object detection

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