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Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms

IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1045-1063页

作者： Chaoyue Zu Chao Yang Jian Wang Wenbin Gao Dongpu Cao Fei-Yue Wang the College of Computer Science and Technology Jilin UniversityChangchun 130012China Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou 221004China the College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun 130012 Chongqing Xibu Automobile Proving Ground Management Co.Ltd. Chongqing 404100China the State Grid JIBEI Electric Power Company Limited Management Training Center China the Advanced Vehicle Engineering Center Cranfield UniversityCranfield MK430ALUK the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

A global planning algorithm for intelligent vehicles is designed based on the A* algorithm, which provides intelligent vehicles with a global path towards their destinations. A distributed real-time multiple vehicle collision avoidance(MVCA)algorithm is proposed by extending the reciprocal n-body collision avoidance method. MVCA enables the intelligent vehicles to choose their destinations and control inputs independently,without needing to negotiate with each other or with the coordinator. Compared to the centralized trajectory-planning algorithm, MVCA reduces computation costs and greatly improves the robustness of the system. Because the destination of each intelligent vehicle can be regarded as private, which can be protected by MVCA, at the same time MVCA can provide a real-time trajectory planning for intelligent vehicles. Therefore,MVCA can better improve the safety of intelligent vehicles. The simulation was conducted in MATLAB, including crossroads scene simulation and circular exchange position simulation. The results show that MVCA behaves safely and reliably. The effects of latency and packet loss on MVCA are also statistically investigated through theoretically formulating broadcasting process based on one-dimensional Markov chain. The results uncover that the tolerant delay should not exceed the half of deciding cycle of trajectory planning, and shortening the sending interval could alleviate the negative effects caused by the packet loss to an extent. The cases of short delay(< 100100 ms) and low packet loss(< 5%) can bring little influence to those trajectory planning algorithms that only depend on V2 V to sense the context, but the unpredictable collision may occur if the delay and packet loss are further worsened. The MVCA was also tested by a real intelligent vehicle, the test results prove the operability of MVCA.

关键词： Collision avoidance intelligent vehicles intervehicle communication simulation testing trajectory planning

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knowledge Compilation Methods Based on the Clausal Relevance and Extension Rule

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Chinese Journal of Electronics 2018年第5期27卷 1037-1042页

作者： NIU Dangdang LIU Lei LYU Shuai College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering (Jilin University) Ministry of Education

We introduce the concepts of Relevancematrix(RM) and Relevance-set(RS). And we construct the association between RM and the knowledge compilation(KC) methods based on Extension rule(ER). Based on the basic parameters of RS and the relationship between RM and the KC methods based on ER, we design two efficient heuristics, called M2S(maximum sum of elements in RS and sum of literals in RS) and MNE(minimum number of maximum terms not extended by RS). Both of above heuristics intend to find the minimum set of maximum terms which cannot be extended by RS. Furthermore,we apply M2S and MNE on KCER. M2S KCER(KCER with M2S) and MNE KCER(KCER with MNE) are designed and implemented based on M2S and MNE, respectively. Experimentally, for the SAT instances with random lengths of clauses, M2S KCER and MNE KCER can improve the efficiency and quality of KCER sharply, and they are two best KC algorithms of EPCCL(each pair contains complementary literal) theory in all KC algorithms based on KCER.

关键词： Extension rule knowledge compilation Clausal relevance Heuristic strategy

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CellMirror: Deciphering Cell Populations from Spatial Transcriptomics Data by Interpretable Contrastive Learning

CellMirror: Deciphering Cell Populations from Spatial Transc...

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Medical Artificial Intelligence (MedAI), IEEE International Conference on

作者： Junjie Xia Jiangnan Cui Zhenyu Huang Shuangquan Zhang Fang Yao Yijian Zhang Chunman Zuo Department of Applied Mathematics Institute of Artificial Intelligence Donghua University Shanghai China Institute of Artificial Institute Donghua University Shanghai China College of Computer Science and Technology Jilin University Changchun China School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China Affiliated Shenzhen Maternity and Child Healthcare Hospital Institute of Maternal and Child Medicine Southern Medical University Shenzhen China Department of General Surgery Xinhua Hospital Affiliated to Shanghai Jiao Tong University of Medicine Shanghai China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

Spatial transcriptomics (ST) has enabled us elucidating tumor microenvironments, however, the technological limitations without single-cell resolution severely hinder its application. Here, we propose CellMirror, an interpretable contrastive learning model to decipher heterogeneous cell populations in ST data by single-cell RNA-sequencing (scRNA-seq) data. Specifically, CellMirror learns the disentangled shared (representing biological variations in both data) and salient features (specific to ST data) by two contrastive variational encoders, while constructing the relations between genes and features by a shared linear decoder. In various cancer samples, CellMirror outperforms other tools in learning common features for label transfer, and interpretation of features. Particularly, in breast cancer studies, CellMirror detects finer domains in ST data missed by other methods, and is robust to dissect cell populations in ST data using independent scRNA-seq data. These results demonstrate applications of CellMirror in interpreting the complex tumor structure in ST data by integrating scRNA-seq data.

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2-Thumbs Typing: A Novel Bimanual Text Entry Method in Virtual Reality Environments

2-Thumbs Typing: A Novel Bimanual Text Entry Method in Virtu...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Zigang Zhang Minghui Sun BoYu Gao Limin Wang College of Software Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China College of Information Science and Technology/Cyber Security Jinan University Guangzhou China

We propose a new technique named 2-Thumbs Typing (2TT) enabling text entry with a touchpad in HTC VIVE controller using two thumbs. 2TT method works similarly with bimanual handwriting input but using new designed uni-stroke gestures considering only strokes' direction. We first design a set of gestures and improve them to finish the final design by a preliminary study through memory, performance efficiency and ease of use. The initial results show that the 2TT technique is easy and comfortable to use, no additional equipment required and supporting eyes-free entry. 2TT can reach 8.5 words per minute with extensive training.

关键词： Training Three-dimensional displays Conferences Memory management Thumb Virtual reality User interfaces

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Discover the Binding Domain of Transmembrane Proteins Based on Structural Universality

Discover the Binding Domain of Transmembrane Proteins Based ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yihang Bao Fei He Weixi Wang Han Wang Minglong Dong School of Information Science and Technology Northeast Normal University Changchun China School of Information Science and Technology Northeast Normal University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China School of Biological Sciences Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781665429825

Transmembrane proteins (TMPs) serve as drug targets for more than half of the drugs currently available in the market. However, it had not been clearly explained how they realize their drug effects through multiple complex molecules bindings actions. Research into TMPs bindings and corresponding structural basis will provide key information for drug research and new drug development. In this study, we defined the binding domain of TMPs according to the binding region investigation of multiple conjugate types. A 3D deep learning model was architected to discover the structural universality inside those domains. The experimental results proved such binding domains existing on the surface of TMPs, and they are structural specific distinguishing to the surface regions without any binding activities. This work provides a new theoretical basis for TMPs binding research and can greatly boost the development of the drug industry.

关键词： Drugs Proteins Deep learning Industries Solid modeling Protein engineering Three-dimensional displays

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UAV Swarm-enabled Collaborative Secure Relay Communications with Time-domain Colluding Eavesdropper

arXiv

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arXiv 2023年

作者： Zhang, Chuang Sun, Geng Wu, Qingqing Li, Jiahui Liang, Shuang Niyato, Dusit Leung, Victor C.M. The College of Computer Science and Technology Jilin University Changchun130012 China The Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China Pillar of Engineering Systems and Design Singapore University of Technology and Design 487372 Singapore The School of Information Science and Technology Northeast Normal University Changchun130024 China The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China The Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Unmanned aerial vehicles (UAVs) as aerial relays are practically appealing for assisting Internet of Things (IoT) network. In this work, we aim to utilize the UAV swarm to assist the secure communication between the micro base station (MBS) equipped with the planar array antenna (PAA) and the IoT terminal devices by collaborative beamforming (CB), so as to counteract the effects of collusive eavesdropping attacks in time-domain. Specifically, we formulate a UAV swarm-enabled secure relay multi-objective optimization problem (US2RMOP) for simultaneously maximizing the achievable sum rate of associated IoT terminal devices, minimizing the achievable sum rate of the eavesdropper and minimizing the energy consumption of UAV swarm, by jointly optimizing the excitation current weights of both MBS and UAV swarm, the selection of the UAV receiver, the position of UAVs and user association order of IoT terminal devices. Furthermore, the formulated US2RMOP is proved to be a non-convex, NP-hard and large-scale optimization problem. Therefore, we propose an improved multi-objective grasshopper algorithm (IMOGOA) with some specific designs to address the problem. Simulation results exhibit the effectiveness of the proposed UAV swarm-enabled collaborative secure relay strategy and demonstrate the superiority of IMOGOA. Copyright © 2023, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Joint Task Offloading and Resource Allocation in Aerial-Terrestrial UAV Networks with Edge and Fog Computing for Post-Disaster Rescue

arXiv

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arXiv 2023年

作者： Sun, Geng He, Long Sun, Zemin Wu, Qingqing Liang, Shuang Li, Jiahui Niyato, Dusit Leung, Victor C.M. The College of Computer Science and Technology Jilin University Changchun130012 China The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China The School of Information Science and Technology Northeast Normal University Changchun130024 China Pillar of Engineering Systems and Design Singapore University of Technology and Design 487372 Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China The Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Unmanned aerial vehicles (UAVs) play an increasingly important role in assisting fast-response post-disaster rescue due to their fast deployment, flexible mobility, and low cost. However, UAVs face the challenges of limited battery capacity and computing resources, which could shorten the expected flight endurance of UAVs and increase the rescue response delay during performing mission-critical tasks. To address this challenge, we first present a three-layer post-disaster rescue computing architecture by leveraging the aerial-terrestrial edge capabilities of mobile edge computing (MEC) and vehicle fog computing (VFC), which consists of a vehicle fog layer, a UAV client layer, and a UAV edge layer. Moreover, we formulate a joint task offloading and resource allocation optimization problem (JTRAOP) with the aim of maximizing the time-average system utility. Since the formulated JTRAOP is proved to be NP-hard, we propose an MEC-VFC-aided task offloading and resource allocation (MVTORA) approach, which consists of a game theoretic algorithm for task offloading decision, a convex optimization-based algorithm for MEC resource allocation, and an evolutionary computation-based hybrid algorithm for VFC resource allocation. Simulation results validate that the proposed approach can achieve superior system performance compared to the other benchmark schemes, especially under heavy system workloads. Copyright © 2023, The Authors. All rights reserved.

关键词： Fog computing

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Research on Opinion Spam Detection by Time Series Anomaly Detection 5th

Research on Opinion Spam Detection by Time Series Anomaly De...

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Wang, Ye Zuo, Wanli Wang, Ying College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9783030242732

With the continuous development of e-commerce, buying online product has become a more desirable shopping option for modern people, but the product reviews which people need to consult when they buy goods are easily become the root cause of misleading consumption. Black profit chains of online sales make a lot of spam opinion makers flood the network who guide consumer’s choice by writing deceptive and misleading spam opinions. In order to eliminate the impact of this black interest chain and safeguard the interests of the mass consumers, we propose a new model by using the time series anomaly detection, reducing the time complexity of spam opinion detection found by time series analysis, while improve the performance of spam detection. Based on time series anomaly detection, we analyze the content of reviews and the characteristics of reviewers and take experiments on real dataset that demonstrate advantages and effectiveness of the proposed approach. © 2019, Springer Nature Switzerland AG.

关键词： Anomaly detection

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A registration method for augmented reality system based on visual SLAM

A registration method for augmented reality system based on ...

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2019 International Conference on Electronic engineering and Informatics, EEI 2019

作者： Zhang, Zuoming Shu, Man Wang, Zixuan Wang, Hanwen Wang, Xin College of Software Engineering Jilin University Changchun China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Changchun China

ISBN: (纸本)9781728140766

In augmented reality, smart devices need to sense their own position in real physical space and complex scene structure to achieve good virtual reality interaction and three-dimensional registration. This paper proposes a technical framework of visual SLAM, which uses VO and BA methods based on feature points to obtain pose, and applies it to the augmented reality system to realize pose estimation, registration, tracking, collision and other effects of intelligent equipment independent of artificial or natural landmarks. © 2019 IEEE.

关键词： Augmented reality

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AMPCliff: Quantitative definition and benchmarking of activity cliffs in antimicrobial peptides

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Journal of Advanced Research 2025年

作者： Li, Kewei Wu, Yuqian Li, Yinheng Guo, Yutong Kong, Yanwen Wang, Yan Liang, Yiyang Fan, Yusi Huang, Lan Zhang, Ruochi Zhou, Fengfeng College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Jilin Changchun 130012 China School of Software Jilin University Jilin Changchun 130012 China School of Life Sciences Jilin University Jilin Changchun 130012 China Department of Computer Science Columbia University 116th and Broadway New York City 10027 NY United States School of Artificial Intelligence Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Jilin Changchun 130012 China School of Biology and Engineering Guizhou Medical University Guizhou Guiyang 550025 China School of Computer Engineering Changchun University of Engineering Jilin Changchun 130103 China Changchun Wenli High School Jilin Changchun 130062 China

Introduction: Activity cliff (AC) is a phenomenon that a pair of similar molecules differ by a small structural alternation but exhibit a large difference in their biochemical activities. This phenomenon affects various tasks ranging from virtual screening to lead optimization in drug development. The AC of small molecules has been extensively investigated but limited knowledge is accumulated about the AC phenomenon in pharmaceutical peptides with canonical amino acids. Objectives: This study introduces a quantitative definition and benchmarking framework AMPCliff for the AC phenomenon in antimicrobial peptides (AMPs) composed by canonical amino acids. Methods: This study establishes a benchmark dataset of paired AMPs in Staphylococcus aureus from the publicly available AMP dataset GRAMPA, and conducts a rigorous procedure to evaluate various AMP AC prediction models, including nine machine learning, four deep learning algorithms, four masked language models, and four generative language models. Results: A comprehensive analysis of the existing AMP dataset reveals a significant prevalence of AC within AMPs. AMPCliff quantifies the activities of AMPs by the metric minimum inhibitory concentration (MIC), and defines 0.9 as the minimum threshold for the normalized BLOSUM62 similarity score between a pair of aligned peptides with at least two-fold MIC changes. Our analysis reveals that these models are capable of detecting AMP AC events and the pre-trained protein language model ESM2 demonstrates superior performance across the evaluations. The predictive performance of AMP activity cliffs remains to be further improved, considering that ESM2 with 33 layers only achieves the Spearman correlation coefficient 0.4669 for the regression task of the −log(MIC) values on the benchmark dataset. Conclusion: Our findings highlight limitations in current deep learning-based representation models. To more accurately capture the properties of antimicrobial peptides (AMPs), it is ess

关键词： Activity cliff (AC) AMPCliff Antimicrobial peptide (AMP) Benchmark Minimum inhibitory concentration (MIC)

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