Automatically translated preprints from the Chinese arXiv (ChinaXiv).
Showing 50 of 1495 papers
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 …
Bone age assessment is a commonly used method for detecting endocrine and growth abnormalities in children; however, low-quality hand X-ray images in deep learning methods reduce the final assessment accuracy. To address this issue, we propose an alignment network that increases the region of intere…
To enhance the solution efficiency for the Multi-Depot Vehicle Routing Problem (MDVRP), we propose an end-to-end deep reinforcement learning framework. First, MDVRP is formulated as a Markov Decision Process (MDP), encompassing definitions of state, action, and reward. Additionally, we propose an im…
Text representation needs to address the ambiguity of textual terms and accurately define their semantic features within specific contextual environments. To tackle the problems of word polysemy and contextual characteristics, we propose an SCDVAB model for text semantic disambiguation. The main inn…
This work aims to identify models capable of describing size effects on the modulus and hardness of polymers as measured by indentation testing. First, elastic size effects are described through a model developed by introducing an elastic unloading load model that incorporates couple-stress elastici…
High-quality research papers should exhibit several essential attributes regarding research topic selection, research process, and research outcomes, with topic selection being the foremost concern. An inability to select appropriate topics precludes meaningful research and, by extension, scholarly …
This paper is a biochemistry design experiment thesis from Harbin Institute of Technology (Weihai). The experiment employed the 2,6-dichloroindophenol method to determine the vitamin C content in vitamin beverages and effervescent tablets, discussed the feasibility of using pre-made vitamin beverage…
Let $Z_n$ be a supercritical branching process in an i.i.d. environment. In this paper, we obtain two non-uniform Berry-Esseen bounds for $Z_n$. This result extends the Berry-Esseen bound of Grama et al. [Stochastic,Process.,Appl.,127(4),1255-1281,2017] to the non-uniform case. Finally, we discuss a…
Currently, most research on CD-CAT has been conducted based on 0-1 scoring data, whereas in actual educational and psychological testing, there also exists a large amount of nominal response data. This study develops a CD-CAT suitable for nominal response data (hereinafter referred to as NCD-CAT) ba…
Typically, cognitive diagnosis necessitates diagnostic evaluation of examinees through cognitive diagnosis models. The validity of diagnostic results generated by cognitive diagnosis models depends on the congruence between examinees' response patterns and the selected model. Consequently, when eval…
In recent years, the field of social class psychology has exhibited a pronounced research orientation toward subjective social class, prominently manifested by an emphasis on the subjective class component within the concept of social class, with a tendency to focus on subjective class in theoretica…
The COVID-19 outbreak has caused tremendous damage to individuals' normal lives and societal development. Recently, with the emergence of novel coronavirus variants, people worldwide continue to face the threat of COVID-19. Vaccination is considered one of the most effective methods to combat this p…
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…
To address the issues of time-consuming training, large memory consumption, and difficulty in model updating associated with traditional offline hashing algorithms, as well as the phenomenon of substantial label loss in real-world image datasets, we propose an online hashing algorithm for balanced l…
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…
To achieve accurate classification of breast pathology WSI images, we propose a gated convolutional neural network classification method based on hybrid connections. A hybrid module incorporating local residual connections and global dense connections is constructed, with squeeze-and-excitation gate…
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…
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…
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…
During periods of social disasters such as pandemics, the number of trauma survivors increases dramatically; coupled with transportation disruptions, traditional psychological rescue efforts struggle to respond promptly to large-scale psychological crises among disaster victims. Expressive writing, …
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…
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…
Existing mobile crowdsensing task recommendation methods share common drawbacks: on one hand, they fail to fully consider the impact of spatio-temporal information on worker preferences, resulting in low recommendation accuracy; on the other hand, they ignore the influence of task popularity on reco…
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…
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…
Mobile crowdsensing data contains image and spatio-temporal contextual information that can be utilized for detecting changes in street view images; however, such data is typically low-quality and non-standard. To accurately detect changes in street scenes, this paper primarily addresses the data qu…
In deploying blockchain-based IoT applications, technical obstacles have emerged, including lack of fine-grained privacy protection, low transaction processing efficiency, high latency, and insufficient flexibility and dynamism. To further advance the popularization and practical deployment of block…
To further improve the accuracy and speed of optical flow matching in visual SLAM, this paper proposes an improved optical flow matching algorithm that integrates Inertial Measurement Unit (IMU) information to remove motion blur. The algorithm first employs a point spread function computed from IMU …
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…
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…
Named Data Networking (NDN), as a novel Internet architecture, aims to address the ever-increasing data traffic. Based on its consumer-driven content retrieval model, NDN naturally supports consumer mobility. However, producer mobility remains a challenging problem, requiring additional mechanisms t…
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…
In the IoT service discovery process, users typically express their requirements through their own intentions, whereas service descriptions constitute explanations of service functionalities; consequently, mismatches between these two elements impact the accuracy of service discovery. Simultaneously…
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…
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 …
Link prediction is an important problem in the field of data mining. Similarity methods based on random walks generally assume that the probability of a walking particle transferring to neighboring nodes is equal, ignoring the influence of node degree values on the transfer probability. To address t…
To reduce data storage requirements and transmission overhead in wireless Internet of Things (IoT), a local directed acyclic graph blockchain scheme (LDB) based on directed acyclic graph (DAG) is proposed. This scheme addresses node storage constraints and transmission overhead by enabling wireless …
To address the issues of the TextRank algorithm ignoring syntactic information and thematic information when extracting document keywords, we propose a document keyword extraction model based on syntactic analysis and thematic distribution. The model extracts document keywords through a two-stage pr…
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 …
Currently, research on the Stochastic Duration Distributed Resource-Constrained Multi-Project Scheduling Problem (SDRCMPSP) is scarce, with most studies focusing on static scheduling schemes that cannot adjust and optimize strategies in real-time in response to environmental changes or promptly addr…
In response to the current challenges of load uncertainty, renewable energy integration, and "dual carbon" objectives in power systems, this paper establishes a real-time pricing model that incorporates load uncertainty and carbon trading within the smart grid context, while fully considering the we…
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…
With the goal of enhancing the cognitive reasoning capability of recommendation algorithm models and overcoming the current limitation where traditional recommendation algorithms heavily rely on data quality, resulting in constrained performance, we propose an implicit deep collaborative recommendat…
SM9-IBS is an identity-based signature algorithm industry standard published by China in 2016. Although identity-based signature algorithms reduce the complexity of system management of user public keys, they suffer from the difficult problem of key revocation. Furthermore, the special structure of …
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…
We propose a multi-description coding image enhancement method based on joint side and central decoding feature learning, which simultaneously considers both side decoding image enhancement and central decoding image enhancement, thereby enabling better network training through joint optimization of…
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…
Aspect-level sentiment analysis aims to determine the sentiment polarity toward specific aspects in reviews; however, few studies have investigated the impact of complex sentences on sentiment classification. Based on this, we propose an aspect-level sentiment analysis model based on BERT and a self…
Based on comment data from Eastmoney.com's Shenzhen Component Index stock forum between January 1, 2018 and December 31, 2019, this study extracts investor sentiment embedded therein using a deep learning BERT model, and employs a TVP-VAR model to investigate the time-varying dynamic relationships a…
Abstract: Glaciers are known as natural ''solid reservoirs'', and they play a dual role between the composition of water resources and the river runoff regulation in arid and semi-arid areas of China. In this study, we used in situ observation data from Urumqi Glacier No. 1, Xinjiang Uygur Autonomou…
