Showing 47 of 47 papers
in Integrated Theory Of Computer Science
Hu Jianghao, Wang Feng
To address issues such as low registration efficiency and large errors in the registration of two partially overlapping point clouds, we propose a point cloud registration algorithm based on mixed features sampled from the overlapping region. First, we predict the overlap score for each point throug…
Zhang Xiayu, Chen Xiaoping
Employing reinforcement learning to address robot manipulation problems offers numerous advantages; however, traditional reinforcement learning algorithms encounter challenges associated with sparse rewards, and the policies obtained are difficult to directly deploy in real-world environments. To en…
Wang Fulin, Liao Xianxi, Feng Xiandong, Zhang Chengdong, Leng Xiyuan
To address the problems of ambiguous boundaries between high-value and low-value parts and unreasonable disassembly depth of waste products, a multi-objective disassembly scheme decision-making method for products considering functional degradation of parts is proposed. The influence of specific par…
Liu Mengqing, Wang Xueming
To resist quantum algorithm attacks and address the vulnerability where malicious signers exploit the complete anonymity of ring signature technology to output multiple signatures for double-spending attacks, while simultaneously solving the problem of unnecessary system overhead waste, a novel latt…
Zhang Yi, Wu Qi, Zhou Shuangshuang, Jia Mengchao
To address the issues of high latency in existing low-orbit satellite network authentication schemes that utilize centralized authentication methods and significant computational overhead arising from complex bilinear mappings, we introduce a certificateless authentication model and propose an effic…
Li Jian, robust
Traditional ciphertext retrieval schemes in cloud environments generate document vectors and query vectors based on statistical models, without considering the deep semantic information of documents and requests. This paper proposes a deep semantic ciphertext retrieval model based on a hybrid cloud …
He Zuowei, Tao Jiaqing, Leng Qiangkui, Zhai Junchang, Meng Xiangfu
Synthetic Minority Over-sampling Technique (SMOTE) is one of the effective methods for addressing class imbalance problems. However, SMOTE's linear interpolation mechanism restricts synthetic samples to the line connecting original samples, resulting in a lack of diversity in new samples, and this l…
Dong Hai, Lin Guodong
To address the fresh food closed-loop supply chain network design problem, a robust optimization model for fresh food closed-loop supply chain networks is established to resolve uncertainties in the supply chain network. First, for a fresh food supply chain network structure encompassing 5 nodes, a …
Shuzhi Li, Zou Yijie, Deng Xiaohong, Luo Zhiqiong, Liu Huiwen
To address the issues that the Raft algorithm cannot resist attacks from Byzantine nodes and that logs are susceptible to tampering and forgery, we design an RB-Raft (Resist Byzantine-Raft) algorithm that resists Byzantine nodes. First, we employ a hash chain approach to perform iterative hashing on…
Li Chao, Li Yufei, Huo Feizhou, Zhang Qinqin
To investigate the effects of hazard factors such as temperature, smoke, and CO concentration on evacuation in fire scenarios, a fire evacuation model based on dynamic coupling of FDS and cellular automata is established. The model establishes a one-to-one correspondence between FDS grids and cellul…
Qiu Tao, Xie Peiliang, Deng Guopeng, Xi Hongmei, <PARA id="1">Zheng Zhi</PARA>, Xia Xiufeng
Complex event processing is a technique for analyzing event streams in dynamic environments. Typically implemented based on finite state automata, complex event processing techniques generate a large number of overlapping partial matches on the event stream during the matching process, requiring the…
Xu Pengjin, Liang Chengji
A bi-level programming model is established to address the actual battery swapping characteristics of automated guided vehicles (AGVs) in automated container terminals, aiming to reduce the total task completion time and total battery swapping time of AGVs while rationally planning the number of bat…
Shi Meifeng, Xiao Shichuan, Feng Xin
To address the issues of slow convergence and susceptibility to local optima in existing ant colony optimization-based algorithms for solving distributed constraint optimization problems, this paper proposes a Random disturbance based multi-population ant colony algorithm to solve distributed constr…
Yuan Haobin, Zhao Tao, Zhong Yuzhong
To address the suboptimal segmentation performance of existing visible-infrared (RGB-T) image semantic segmentation models, this paper proposes a nested segmentation network based on deep difference feature complementary fusion. Specifically, the encoder and decoder components are interconnected via…
Zhang Yuting, Liu Yong
To address the deficiencies of the School-Based Optimization (SBO) algorithm, including poor search performance and susceptibility to local optima, this paper proposes an SBO algorithm integrated with educational psychology (SBO based on Educational Psychology, SBO-EP). During the teaching phase, th…
Liu Ji, Jia Fangdi
To improve the accuracy of overlapping community detection, we propose CLPANNI (Cycle Label Propagation Algorithm with Neighbor Node Influence), an optimized algorithm based on cycle structures derived from LPANNI. The algorithm extracts minimal cycle information of nodes, measures node importance u…
Wu Fei, Wang Wei
Social media account credibility assessment is an important component in ensuring the healthy development of online social ecosystems. To address issues such as multi-dimensional credibility assessment indicators for social media accounts and diverse data information uncertainties, a credibility ass…
Ma Yinghong, Jiang Lingyun
In fifth-generation mobile communications, network slicing is employed to provide an optimal network for diverse services. In the context of RAN slicing scenarios across multiple base stations, conventional resource allocation methods fail to meet slice requirements when the number of slices varies …
Zhao Xingbo, Li Mengdong, Wang Ying, Zhu Yilin
Bullens et al. left an open problem in CSI-Fish, namely designing an identification protocol that allows the system challenge space to be #1;, rather than a small set #1;. This paper proposes a zero-knowledge proof scheme based on supersingular isogenies. The scheme treats the challenge C as an isog…
Wang Jin, Zhang Xinyou
Due to their limited battery life and computing power, autonomous vehicles struggle to meet the processing demands of latency-sensitive or compute-intensive tasks while ensuring driving range. To address this issue, this paper proposes an autonomous vehicle task offloading strategy based on deep Q-n…
Huang Hao, Yan Qian, Gan Ting, Shijun Li
Analyzing student evaluation data for teachers in teaching evaluation systems enables teachers to comprehend students' authentic attitudes toward instructors, summarize teaching experience, improve subsequent teaching methods, and enhance teaching quality. However, during teaching evaluations, issue…
Li Chen, He Ming, Wang Yong, Luo Ling, Han Wei
Action Recognition (AR) represents a research hotspot in the field of computer vision, with extensive application prospects in security surveillance, autonomous driving, production safety, and other domains. First, the connotation and extension of action recognition are analyzed, and the technical c…
Xing Zhiwei, Zhang Qianqian, Luo Qian, Chen Zhaoxin
To address the issue that gate reallocation algorithm results struggle to satisfy the operating habits of different operators, a gate reallocation recommendation algorithm that aligns with the operational habits of actual operational staff is proposed. First, a decision environment space model is co…
Zhang Bo, Zhao Peng, Zhang Jinjin, Zeng Zhaoju, Xiao Xuhao
Integrating knowledge graphs into recommendation systems can leverage the semantic relationships between entities in knowledge graphs to learn user and item representations. Embedding propagation-based methods utilize the graph structure of knowledge graphs to learn relevant features, but as the pro…
Zhou Xuanlang, Qiu Weigen, Zhang Lichen
To improve text classification accuracy and address the issue of insufficient utilization of node features in text graph convolutional neural networks, a novel text classification model is proposed that intrinsically integrates the advantages of text graph convolution and Stacking ensemble learning …
Han Zonghuan, Liu Mingguo, Li Shen, Chen Lijia, Tian Min, Lan Tianxiang, Liang Qian
In industrial applications, fully supervised semantic segmentation for surface imprinted character images incurs high dataset annotation costs for enterprises. To address this issue, we propose a dual-branch feature fusion domain adaptation segmentation method (Dual-branch Feature Fusion Domain Adap…
Gao Xiaotian, Zhang Qian, Lü Fan, Hu Fuyuan, Hu Fuyuan
The novel view synthesis task refers to generating novel-view images of a scene from multiple reference images. However, in multi-object scenes, inter-object occlusion leads to incomplete acquisition of object information, resulting in artifacts and misalignment issues in the generated novel-view sc…
Wang Jianxin, Shi Yingjie, Liu Hao, Huang Haiqiao, Du Fang
Hand-drawn sketch image translation is a challenging research topic in computer vision, with significant application value in artistic design and e-commerce. Currently, GAN-based hand-drawn sketch image translation remains in its infancy. This article analyzes the challenging issues confronting sket…
Zhao Chun, Dong Xiaoming, Ren Yiying
Emerging intelligent transportation systems hold significant promise for improving traffic flow, optimizing fuel efficiency, reducing delays, and enhancing overall driving experience. Currently, traffic congestion constitutes an extremely serious challenge for humanity, particularly severe at urban …
Luo Haojia, Pan Dazhi
For the Dual-Resource Constrained Flexible Job Shop Scheduling Problem (DRCFJSP), a Cuckoo Algorithm with an improved decoding scheme is proposed to optimize the makespan. Since DRCFJSP requires consideration of both machine allocation and worker processing status, the traditional decoding method is…
Zhao Haiyan, Xia Wenzhong, Cao Jian, Chen Qingkui
In open source communities, the promptness and quality of responses to developers' issues critically determine community vitality. Therefore, identifying and recommending appropriate problem solvers for newly submitted issues facilitates community development. This paper proposes a problem solver re…
Qiao Jian, Chen Shaobo, He Mengying
Existing short-term demand forecasting models for public bicycles have neglected the nature differences in how various environmental factors influence user demand, as well as the temporal dependencies of variable environmental factors. This paper distinguishes environmental factors into invariant fa…
Wu Zhuang, Tang Lun, Pu Hao, Wang Zhiping, Chen Qianbin
To address issues such as base station coverage holes and local traffic overload in urban vehicular networks, this paper proposes a dynamic pre-deployment scheme based on vehicle trajectory prediction information. First, to train a unified Seq2Seq-GRU trajectory prediction model, multiple UAVs equip…
Chen Wan, Cai Yanping, Li Aihua, Myrica rubra branch, Jiang Ke
To improve the real-time estimation accuracy of human vigilance, a real-time vigilance estimation method based on differential entropy (DE), improved moving average, and bidirectional two-dimensional principal component analysis (TD-2DPCA) is proposed. First, the total frequency band is decomposed i…
Xiaoming Zhang, Dou Quansheng, Chen Shuzhen, Huanling Tang
Few-shot relation extraction is a prominent research problem in natural language processing, which aims to train relation extraction models with low-cost annotated data. The currently widely-used prototype networks suffer from issues of inaccurate and incomplete class prototype representation. To ad…
Wang Yang, Zheng Jin, Ying Liu, Li Ping
Traffic flow prediction constitutes a crucial component of intelligent transportation systems. Due to the complexity of traffic data, long-term and accurate traffic flow prediction has consistently remained one of the most challenging tasks in time series forecasting. In recent years, researchers ha…
Liu Jin, Luo Xiaoshu, Xu Zhaoxing
To address the issues of insufficient feature extraction for facial expressions and inadequate generalization capability of lightweight networks in complex environments, as well as ambiguous expressions caused by single-label datasets' inability to effectively describe complex emotional tendencies, …
Li Yaqian, Zhang Xuyao, Li Qilong
To address the issue that inpainting networks in generative adversarial networks fail to simultaneously preserve global and local consistency of images while incurring substantial computational load, we incorporate the concept of progressive inpainting into an asymmetric U-Net architecture. First, w…
Bian Huajun, Wang Huajun, Zhao Hewei
A novel network framework (SR-Net) for RGB-D salient object detection is proposed. To effectively integrate the complementarity of multimodal features, depth feature extraction is employed as an independent branch, the Convolutional Block Attention Module (CBAM) is adopted for depth feature enhancem…
Tan Fuxiang, Qian Yurong, Kong Yuting, Zhang Hao, Zhou Daxin, Fan Yingying, Chen Long
Rain streaks severely degrade the quality of captured images, affecting subsequent computer vision tasks. To improve the quality of rainy images, we propose a Transformer-based single image deraining algorithm. First, the algorithm obtains a large receptive field through a transformer with a windowi…
Xia Jiqiang, Cui Pengshuai, Li Ziyong, Lan Julong
To address the problem of inconsistency between control-plane and data-plane flow rules caused by hardware/software failures and misconfigurations in the SDN data plane, we propose a P4-based consistency verification mechanism for SDN control-data plane flow rules (P4CV, P4-based Consistency Verific…
Meng Hui, Ren Lina, Li Ying
To address issues such as key abuse and digital certificate management in existing lattice-based proxy re-encryption schemes, we introduce an accountability mechanism and propose a novel identity-based accountable proxy re-encryption scheme. This scheme employs user identity ID to compute and genera…
Yao Yukun, Chen Xinyao, Yang Jie
To satisfy the personalized requirements of end users and reduce the transmission delay in D2D networks, a cooperative retransmission scheme based on instantly decodable network coding (IDNC) with terminal differentiation is proposed. First, this scheme introduces a novel IDNC algorithmic framework …
Meng Lei, Tang Xin, Xu Yanyan
To address the issue that existing vertical handover algorithms in heterogeneous wireless network environments struggle to achieve seamless handover for mobile users accessing networks and fail to provide stable communication services, a vertical handover algorithm based on mobile user location pred…
Dong Yongji, Wang Yu, Yuan Zheng
To address the inability of traditional software-based protocol stacks to meet the demands of high-speed data transmission and processing, a hardware-accelerated UDP protocol stack design scheme is proposed. Based on the highly efficient parallel characteristics of hardware, this scheme implements a…
Li Jian, Li Zhuo, Ma Tianxiang, Liang Jifeng
To address the limitation that existing clothing compatibility models predominantly focus on exploring compatibility between paired items, we propose a clothing compatibility prediction model based on hypergraph representation. The model first constructs a clothing hypergraph based on the different …
Fanjun Su, Ma Mingxu, Tong Guoxiang
Most existing algorithms utilizing Graph Neural Networks for text classification have overlooked the over-smoothing problem inherent in GNNs and the discrepancies arising from text graph topological differences, leading to suboptimal performance in text classification. To address this issue, we prop…