Most papers are machine-translated to English; some are originally in English.
Showing 50 of 1733 papers
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…
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 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…
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…
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…
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, …
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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 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…
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 …
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 …
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…
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…
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…
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 …
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…
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…
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…
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 …
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…
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 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…
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…
Abstract: With realizing the importance of ecosystem services to society, the efforts to evaluate the ecosystem services have increased. As the largest tributary of the Yellow River, the Weihe River has been endowed with many ecological service functions. Among which, water yield can be a measure of…
Abstract: Aeolian sandy soil in mining areas is characterized by intense evaporation and poor water retention capacity. This study was designed to identify a suitable biochar application method to improve soil water infiltration and minimize soil water evaporation for aeolian sandy soil. Using an in…
Planting cover crop has been suggested as a way of increasing soil organic carbon in agricultural land. Ryegrass (Lolium multiflorum L.), as a cover crop, could improve soil fertility and lower soil CO2 emission. However, effects of soil water content and nitrogen on soil carbon mineralization after…
This study investigates the application technology of near-ultraviolet femtosecond laser pulse inscription inside polymethylpentene. We discovered that this thermoplastic material exhibits polarization-sensitive characteristics. First, inscription experiments employed a lens with a numerical apertur…
Abstract Based on the E-Z Reader model and the integrated model of Chinese reading, there is controversy over whether word segmentation and lexical identification constitute an interactive unified process. By manipulating reading direction to alter text familiarity, we investigated its role in word …
Organizations often face a "dilemma" in employee management and organizational innovation—finding it difficult to provide stable employment yet having to rely on employees to achieve organizational innovation, which makes research on the impact of employee job insecurity on innovative behavior cruci…
The debate over whether verb metaphor processing is entirely based on perceptual-motor simulation or also involves the participation of abstract semantic processing systems, and how the two interact, has remained a subject of debate. This study investigated the processing mechanisms and integration …
The visual search ability of organisms is of vital survival significance for adapting to complex external environments. Attentional templates can enhance relevant information and suppress irrelevant information during search tasks, thereby rapidly locating targets. A summary of recent research findi…
This paper presents a comprehensive survey of subword tokenization methods in neural network-based natural language processing. It first elaborates on the out-of-vocabulary (OOV) problem stemming from closed vocabulary limitations in such approaches, and introduces three prevalent methods for addres…
Generalizability Theory is widely applied in the field of psychological and educational measurement. How to achieve optimal reliability of measurement procedures under budget constraints is an important issue that researchers need to consider, and this problem can be transformed into one of optimal …
Strain engineering of 2D materials is capable of tuning the electrical and optical properties of the materials without introducing additional atoms. However, there are still great challenges in realizing straining of 2D materials with CMOS compatibility. Here, a method for large-scale ultrafast stra…
To investigate the molecular mechanism differences of the key enzyme gene PtCHI in isoflavonoid metabolism among Pueraria varieties, and to preliminarily elucidate the causes for inter-varietal differences in isoflavonoid content, this study employed wild Pueraria and the starch-rich Pueraria cultiv…
