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Serdica Journal of Computing最新文献

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Integer Linear Programming Models and Greedy Heuristic for the Minimum Weighted Independent Dominating Set Problem 最小加权独立支配集问题的整数线性规划模型和贪婪启发式
Serdica Journal of Computing Pub Date : 2024-04-15 DOI: 10.55630/sjc.2023.17.117-136
Stefan Kapunac
{"title":"Integer Linear Programming Models and Greedy Heuristic for the Minimum Weighted Independent Dominating Set Problem","authors":"Stefan Kapunac","doi":"10.55630/sjc.2023.17.117-136","DOIUrl":"https://doi.org/10.55630/sjc.2023.17.117-136","url":null,"abstract":"This paper explores the Minimum Weighted Independent Dominating Set Problem and proposes novel approaches to tackle it. Namely, two integer linear programming formulations and a fast greedy heuristic as an alternative approach are proposed. Extensive computational experiments are conducted to evaluate the performance of these approaches on the established set of benchmark instances for the problem. The obtained results demonstrate that the introduced integer linear programming models are able to achieve optimal solutions on all instances with 100 nodes and significantly outperform existing exact methods on numerous other instances. Additionally, the greedy heuristic exhibits superior performance compared to competing greedy heuristics, particularly on random graphs. These findings suggest promising directions for future research, including the integration of these methods into hybrid algorithms or metaheuristic frameworks.","PeriodicalId":498747,"journal":{"name":"Serdica Journal of Computing","volume":"5 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140700161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Recognition of Handwritten Mathematical Expressions Using Systems of Convolutional Neural Networks 利用卷积神经网络系统识别手写数学表达式
Serdica Journal of Computing Pub Date : 2024-02-21 DOI: 10.55630/sjc.2023.17.107-116
Tate Rowney, Alexander I. Iliev
{"title":"Recognition of Handwritten Mathematical Expressions Using Systems of Convolutional Neural Networks","authors":"Tate Rowney, Alexander I. Iliev","doi":"10.55630/sjc.2023.17.107-116","DOIUrl":"https://doi.org/10.55630/sjc.2023.17.107-116","url":null,"abstract":"Accurate recognition of handwritten mathematical expressions has proven difficult due to their two-dimensional structure. Various machine-learning techniques have previously been employed to transcribe handwritten math, including approaches based on convolutional neural networks (CNNs) and larger encoder/decoder-based models. In this work, we explore a CNN-based method for transcribing handwritten math expressions into the typesetting language known as LaTeX. This approach utilizes machine learning not only for classifying individual characters but also for extracting individual characters from handwritten inputs and determining what forms of two-dimensionality exist within the expression. This approach achieves significant reliability when recognizing common mathematical expressions.","PeriodicalId":498747,"journal":{"name":"Serdica Journal of Computing","volume":"90 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140444155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
CWE Ontology CWE 本体论
Serdica Journal of Computing Pub Date : 2023-02-28 DOI: 10.55630/sjc.2022.16.39-56
Vladimir Dimitrov
{"title":"CWE Ontology","authors":"Vladimir Dimitrov","doi":"10.55630/sjc.2022.16.39-56","DOIUrl":"https://doi.org/10.55630/sjc.2022.16.39-56","url":null,"abstract":"CWE is a community-supported database of known weaknesses. It is under permanent update and development. MITRE Corporation hosts this database. It consists of several viewpoints structured at several abstract levels.
 CWE database is the base of CWE ontology. It redefines weaknesses in terms of the Semantic Web. This ontology is a part of ontology ecosystem developed to capture cybersecurity knowledge on known vulnerabilities, weaknesses, and attacks patterns.
 CWE ontology classifies CVE/NVD vulnerabilities. It is useful for research and investigation on new vulnerabilities and weaknesses using reasoners. In addition, CWE is useful for cybersecurity incident forensic investigations, software acquisition and development.","PeriodicalId":498747,"journal":{"name":"Serdica Journal of Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135733266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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