作者:
Chen, KeHan, XiaosongLi, XiaoranLiang, YanchunXu, DongGuan, RenchuJilin University
Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Software Changchun China Jilin University
Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Changchun China Zhuhai College of Science and Technology
Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education School of Computer Science Zhuhai China University of Missouri
Christopher S. Bond Life Sciences Center Department of Electrical Engineering and Computer Science Columbia United States
Drug-Drug Interaction (DDI) task plays a crucial role in clinical treatment and drug development. Recently, deep learning methods have been successfully applied for DDI prediction. However, training deep learning mode...
详细信息
In modern air traffic management, generating synthetic flight trajectories has emerged as a promising solution for addressing data scarcity, protecting sensitive information, and supporting large-scale analyses. In th...
详细信息
Accurate microseismic source localization is crucial for detecting potential geological hazards during mining operations, ensuring the safe and efficient progress of excavation activities. The accuracy and reliability...
详细信息
ISBN:
(数字)9798331531225
ISBN:
(纸本)9798331531232
Accurate microseismic source localization is crucial for detecting potential geological hazards during mining operations, ensuring the safe and efficient progress of excavation activities. The accuracy and reliability of source localization are closely linked to the selection of appropriate algorithms. While the Particle Swarm Optimization (PSO) algorithm offers the advantage of fast convergence, it is prone to premature convergence and low localization accuracy when directly applied to source localization. To address these issues, this study employs chaotic mapping to replace traditional methods for initializing the particle population, enhancing population diversity. The proposed method is validated through engineering case studies. The results demonstrate that, compared to the traditional PSO algorithm, the chaotic mapping-based improved PSO algorithm achieves faster convergence and superior optimization capabilities, making it suitable for solving practical engineering problems.
Currently, there are numerous thorny issues in structured data and semi-structured full-text search scheme with large-scale text nature, like long data synchronization delay, inconvenient personalized business process...
详细信息
Julia is an emerging programming language designed for high-performance and parallel computing. However, its simple-designed foreign function interface, ccall, lacks necessary security checks, making multilingual Juli...
Julia is an emerging programming language designed for high-performance and parallel computing. However, its simple-designed foreign function interface, ccall, lacks necessary security checks, making multilingual Julia applications vulnerable to exploitation. This paper introduces SAFEJ, an infrastructure developed to enhance Julia FFI security. SAFEJ includes two key components: 1) privilege separation to protect Julia by isolating the memory of Julia and native code and 2) pointer sanitization to filter and check memory accesses from unsafe native code to provide more flexible protection. We conducted extensive experiments to evaluate the effectiveness and performance of SAFEJ. The results demonstrate that SAFEJ effectively protects Julia from common memory attacks, and its efficiency tests indicate that pointer sanitization is on par with prior studies, while privilege separation achieves a maximum reduction of 85% in runtime performance overhead.
Person re-identification(ReID)aims to recognize the same person in multiple images from different camera *** person ReID models are time-consuming and resource-intensive;thus,cloud computing is an appropriate model tr...
详细信息
Person re-identification(ReID)aims to recognize the same person in multiple images from different camera *** person ReID models are time-consuming and resource-intensive;thus,cloud computing is an appropriate model training ***,the required massive personal data for training contain private information with a significant risk of data leakage in cloud environments,leading to significant communication *** paper proposes a federated person ReID method with model-contrastive learning(MOON)in an edge-cloud environment,named ***,based on federated partial averaging,MOON warmup is added to correct the local training of individual edge servers and improve the model’s effectiveness by calculating and back-propagating a model-contrastive loss,which represents the similarity between local and global *** addition,we propose a lightweight person ReID network,named multi-branch combined depth space network(MB-CDNet),to reduce the computing resource usage of the edge device when training and testing the person ReID ***-CDNet is a multi-branch version of combined depth space network(CDNet).We add a part branch and a global branch on the basis of CDNet and introduce an attention pyramid to improve the performance of the *** experimental results on open-access person ReID datasets demonstrate that FRM achieves better performance than existing baseline.
Multimodal contrastive learning aims to train a general-purpose feature extractor, such as CLIP, on vast amounts of raw, unlabeled paired image-text data. This can greatly benefit various complex downstream tasks, inc...
详细信息
Crowdsourcing Web Application has not been utilized effectively for hazard identification. This paper presents the development of a Web-based crowdsourcing platform for hazard identification. Hence, a Web Application ...
Crowdsourcing Web Application has not been utilized effectively for hazard identification. This paper presents the development of a Web-based crowdsourcing platform for hazard identification. Hence, a Web Application based on the Model- View-Controller framework is presented in this paper. The Web Application provides a platform through which data from IoT devices monitoring the environment for hazardous air pollutants can be visualized. Also, human users are enabled to report other forms of hazard around them through the crowdsourcing capability of the Web Application. The Laravel PHP framework is employed for the backend part of the Application while a combination of HyperText Markup Language, Tailwind Cascading Style Sheets and J avaScript were employed in the frontend part. JavaScript Object Notation is used as the data exchange format between the Internet of Things devices, cloud database and Web Application. Upon testing, the Application was confirmed to be working in line with the requirements gathered at the beginning of the development process. Notably, the IoT sensor data was visualizable through the Web Application in a user-friendly manner and users were able to communicate hazardous incidents using the App. Thus, the Web Application facilitates the hazard identification task, thereby improving the risk management processes.
Identification of contraband items from highly oc-cluded baggage of air travelers is a challenging task even for human experts with very high experience. Many researchers have been working rigorously to develop comput...
详细信息
Scrum is an incremental, interactive agile framework widely used to develop practical problems; the Scrum team focuses on achieving a common goal each cycle, "Sprint Goal" instead of the traditional sequenti...
Scrum is an incremental, interactive agile framework widely used to develop practical problems; the Scrum team focuses on achieving a common goal each cycle, "Sprint Goal" instead of the traditional sequential technique for delivering products. Although many organizations are adopting Scrum, it is still following the traditional manual approaches. Even though many tools are available in the market to facilitate project management and Scrum master tasks, the support is still limited and lacks the utilization of Artificial Intelligence science. This study focuses on integrating the Scrum framework with Artificial Intelligence to build a predicting model that can assist project management "in particular the Scrum master" to predict the achievement of the Scrum Team per Sprint using Story Points; this prediction is built based on several factors that can affect the burndown charts per Sprint.
暂无评论