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429 results on '"Wang, Weicheng"'

2. Towards an Understanding of Large Language Models in Software Engineering Tasks

Author

Zheng, Zibin, Ning, Kaiwen, Chen, Jiachi, Wang, Yanlin, Chen, Wenqing, Guo, Lianghong, and Wang, Weicheng

Subjects
Computer Science - Software Engineering
Abstract

Large Language Models (LLMs) have drawn widespread attention and research due to their astounding performance in tasks such as text generation and reasoning. Derivative products, like ChatGPT, have been extensively deployed and highly sought after. Meanwhile, the evaluation and optimization of LLMs in software engineering tasks, such as code generation, have become a research focus. However, there is still a lack of systematic research on the application and evaluation of LLMs in the field of software engineering. Therefore, this paper is the first to comprehensively investigate and collate the research and products combining LLMs with software engineering, aiming to answer two questions: (1) What are the current integrations of LLMs with software engineering? (2) Can LLMs effectively handle software engineering tasks? To find the answers, we have collected related literature as extensively as possible from seven mainstream databases, and selected 123 papers for analysis. We have categorized these papers in detail and reviewed the current research status of LLMs from the perspective of seven major software engineering tasks, hoping this will help researchers better grasp the research trends and address the issues when applying LLMs. Meanwhile, we have also organized and presented papers with evaluation content to reveal the performance and effectiveness of LLMs in various software engineering tasks, providing guidance for researchers and developers to optimize.

Published
2023

3. Towards Efficient Privacy-Preserving Deep Packet Inspection

Author

Wang, Weicheng, Lee, Hyunwoo, Huang, Yan, Bertino, Elisa, Li, Ninghui, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tsudik, Gene, editor, Conti, Mauro, editor, Liang, Kaitai, editor, and Smaragdakis, Georgios, editor

Published
2024
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5. Rhizocarpon sichuanense, a new species from Southwest China

Author

ZHANG Yanmeng, WANG Weicheng, WANG Yuhua, ZHONG Chunjiao, and HU Ling

Subjects
barbatic acid, rhizocarpaceae, lichenized ascomycetes, lichenized fungi, taxonomy, Botany, QK1-989
Abstract

In this paper, we study in Rhizocarpon Ramond ex DC. species by the method of combining phenotypic characteristics (morphology, anatomy and chemistry) with genotypic characteristics (ITS sequence). The aims of this present paper are to clarify the status of some species and explore the relationship between phenotype and genotype in Rhizocarpon. During the study on Rhizocarpon species from southwest China, R. sichuanense Y. M. Zhang, L. Hu & W. C. Wang sp. nov. is described as a new species in this genus. The new species is morphologically similar to R. cinereonigrum Vain and R. sinense Zahlbr., which also produces brown thallus, medulla I-, 8-spored ascus and brown ascospores with 1-septa. But it can be distinguished by the scattered, areolate to subsquamulose thallus, a distinct black prothallus, large ascospores are［(27-)32-42.5］μm ×［12.5-17.5(-20)］μm and the presence of barbatic acid is in the thallus. In phylogenetic trees, it is also similar to R. badioatrum (Flörke ex Spreng.) Th. Fr. which can be distinguished by the more continuous thallus with diffractaic acid or without secondary products, and the smaller spores［(23-36) μm × (13-16) μm］than this new species. The phylogenic results are as follows: (1) The new species R. sichuanense belongs to badioatrum group which belongs to Rhizocarpon subg. Phaeothallus; (2) It is unsuitable to classify some groups only based on anatomical characteristics (spore size and separation type) in Rhizocarpon, the chemical characteristics should also be considered. In this paper, the achievement of ITS sequences provide the basic data for an establishment of a more reasonable and natural classification system. In addition, we provide high resolution pictures of morphological, anatomical and chemical characteristics as well as detailed descriptions of the new species. The key to the species of Rhizocarpon subg. Phaeothallus with 1-septa brown spore (Badioatrum group) in the world is also provided, which will provide basic data for the further studies in this group.

Published
2024
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10. Identification method of canned food for production line sorting robot based on improved PSO-SVM

Author

GAO Haiyan, GAO Jinyang, and WANG Weicheng

Subjects
food production line, sorting robot, target recognition, particle swarm optimization algorithm, support vector machine, Food processing and manufacture, TP368-456
Abstract

Objective: To solve the problems of poor accuracy and low efficiency in target recognition methods for existing sorting robots in food production lines. Methods: On the basis of the analysis of the binocular vision food sorting system, a combination of improved particle swarm optimization algorithm and support vector machine was proposed for target recognition of food sorting robots. By improving the particle swarm optimization algorithm to optimize support vector machine parameters, an optimized support vector machine classification model was obtained. The classifier was trained for both global and local features, and feature weight coefficients were dynamically assigned to obtain the best recognition rate. Analyzed the performance of the proposed method through experiments, and verified its feasibility. Results: Compared with conventional methods, the proposed method had high recognition accuracy and efficiency in target recognition of food sorting robots, with an accuracy rate of 99.50% and an average recognition time of 0.048 s, which meet the needs of robot sorting. Conclusion: The proposed method can effectively identify canning, improved sorting accuracy and efficiency of sorting robots.

Published
2023
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20. PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols

Author

Cicala, Fabrizio, Wang, Weicheng, Wang, Tianhao, Li, Ninghui, Bertino, Elisa, Liang, Faming, and Yang, Yang

Subjects
Computer Science - Computers and Society, C.3, H.4, J.3, J.7, K.4, K.6.5
Abstract

Many proximity-based tracing (PCT) protocols have been proposed and deployed to combat the spreading of COVID-19. In this paper, we take a systematic approach to analyze PCT protocols. We identify a list of desired properties of a contact tracing design from the four aspects of Privacy, Utility, Resiliency, and Efficiency (PURE). We also identify two main design choices for PCT protocols: what information patients report to the server, and which party performs the matching. These two choices determine most of the PURE properties and enable us to conduct a comprehensive analysis and comparison of the existing protocols., Comment: 35 pages, 10 figures, 7 tables

Published
2020

49. Intelligent Condition Monitoring of Multiple Thermal Degradation of IGBT Modules Based on Case Temperature Matrix

Author

Zhan, Cao, Tang, Yizheng, Zhu, Lingyu, Wang, Weicheng, Gou, Yating, Ji, Shengchang, and Iannuzzo, Francesco

Abstract

This article presents an intelligent approach for monitoring various thermal degradations in insulated gate bipolar transistor (IGBT) modules. Thermal degradation at the baseplate solder and thermal interface material (TIM) both induce changes in the case temperature distribution, offering insights into the corresponding degradation type and level. To capture this information, a strategically placed thermocouple array forms a temperature matrix on the case surface. The normalization of the case temperature matrix effectively mitigates the influence of working conditions, such as load current or heatsink temperature. Furthermore, a model augmented with a convolutional neural network is utilized to classify the degradation type and level based on temperature matrixes. To generate datasets under diverse operational conditions, a finite-element model of a conventional IGBT module is developed. The model includes various degradation locations (baseplate solder fatigue, TIM degradation, baseplate solder, and TIM degradation) and levels (health, early degradation, severe degradation, failure). Gaussian noise is introduced to the simulation data to enhance both training and prediction accuracy. Additionally, experimental data from a two-level inverter is incorporated into the training dataset to further refine accuracy. The results affirm that this approach excels in accurately distinguishing the degradation type and evaluating the degradation level.

Published
2024
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