Programming and Computer Software最新文献_第9页

Soft and Hard Skills Gained by Students through Real Projects Developed at a University Software Company 学生通过大学软件公司开发的真实项目获得的软技能和硬技能

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823080029

引用次数: 0

Artificial Intelligence (AI) Solution for Plasma Cells Detection 检测血浆细胞的人工智能 (AI) 解决方案

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823080121

{"title":"Artificial Intelligence (AI) Solution for Plasma Cells Detection","authors":"","doi":"10.1134/s0361768823080121","DOIUrl":"https://doi.org/10.1134/s0361768823080121","url":null,"abstract":"<span> <h3>Abstract</h3> <p>The article investigates the application of a neural network diagnosis model to histological images in order to detect plasma cells for chronic endometritis detection. A two-stage algorithm was developed for plasma cell detection. At the first stage, a CenterNet model was used to detect stromal and epithelial cells. The neural network was trained on an open dataset with histological images and further fine-tuned using an additional labeled dataset. A labeling protocol was used, and the coefficient of agreement between two experts was calculated, which turned out to be 0.81. At the second stage, using the developed algorithm based on computer vision methods, plasma cells were identified and their HSV color boundaries were calculated. For the two-stage algorithm the following quality metrics were obtained: precision = 0.70, recall = 0.43, f1-score = 0.53. The model then was modified to detect only plasma cells and trained on a dataset with histological images containing labeled plasma cells. The quality metrics of the modified detection model were obtained: precision = 0.73, recall = 0.89, f1-score = 0.8. As a result of the comparison, the modified detection model approach showed the best quality metrics. Automating the work of counting plasma cells will allow doctors to spend less time on routine activities.</p> </span>","PeriodicalId":54555,"journal":{"name":"Programming and Computer Software","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Runtime Verification of Operating Systems Based on Abstract Models 基于抽象模型的操作系统运行时验证

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823070034

D. V. Efremov, V. V. Kopach, E. V. Kornykhin, V. V. Kuliamin, A. K. Petrenko, A. V. Khoroshilov, I. V. Shchepetkov

引用次数: 0

Decentralized Conditional Gradient Method on Time-Varying Graphs 时变图的分散条件梯度方法

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823060075

R. A. Vedernikov, A. V. Rogozin, A. V. Gasnikov

引用次数: 0

Gradient-Free Algorithms for Solving Stochastic Saddle Optimization Problems with the Polyak–Łojasiewicz Condition 求解Polyak -Łojasiewicz条件下随机鞍型优化问题的无梯度算法

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823060063

S. I. Sadykov, A. V. Lobanov, A. M. Raigorodskii

引用次数: 0

Bots in Software Development: A Systematic Literature Review and Thematic Analysis 软件开发中的机器人：系统文献综述与主题分析

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823080145

{"title":"Bots in Software Development: A Systematic Literature Review and Thematic Analysis","authors":"","doi":"10.1134/s0361768823080145","DOIUrl":"https://doi.org/10.1134/s0361768823080145","url":null,"abstract":"<span> <h3>Abstract</h3> <p>Modern Software Engineering thrives with innovative tools that aid developers in creating better software grounded on quality standards. Software bots are an emerging and exciting trend in this regard, supporting numerous software development activities. As an emerging trend, few studies describe and analyze different bots in software development. This research presents a systematic literature review covering the state of the art of applied and proposed bots for software development. Our study spans literature from 2003 to 2022, with 82 different bots applied in software development activities, covering 83 primary studies. We found four bot archetypes: chatbots which focus on direct communication with developers to aid them, analysis bots that display helpful information in different tasks, repair bots for resolving software defects, and development bots that combine aspects of other bot technologies to provide a service to the developer. The primary benefits of using bots are increasing software quality, providing useful information to developers, and saving time through the partial or total automation of development activities. However, drawbacks are reported, including limited effectiveness in task completion, high coupling to third-party technologies, and some prejudice from developers toward bots and their contributions. We discovered that including Bots in software development is a promising field of research in software engineering that has yet to be fully explored.</p> </span>","PeriodicalId":54555,"journal":{"name":"Programming and Computer Software","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Variant of the Frank–Wolfe Algorithm for Convex Optimization Problems 求解凸优化问题的Frank-Wolfe算法的自适应变体

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823060038

G. V. Aivazian, F. S. Stonyakin, D. A. Pasechnyk, M. S. Alkousa, A. M. Raigorodsky, I. V. Baran

{"title":"Adaptive Variant of the Frank–Wolfe Algorithm for Convex Optimization Problems","authors":"G. V. Aivazian, F. S. Stonyakin, D. A. Pasechnyk, M. S. Alkousa, A. M. Raigorodsky, I. V. Baran","doi":"10.1134/s0361768823060038","DOIUrl":"https://doi.org/10.1134/s0361768823060038","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In this paper, we investigate a variant of the Frank–Wolfe method for convex optimization problems with the adaptive selection of the step parameter corresponding to information about the smoothness of the objective function (the Lipschitz constant of the gradient). Theoretical estimates of the quality of the approximate solution provided by the method using adaptively selected parameters <i>L</i><sub><i>k</i></sub> are presented. For a class of problems on a convex feasible set with a convex objective function, the guaranteed convergence rate of the proposed method is sublinear. A special subclass of these problems (an objective function with the gradient dominance condition) is considered and the convergence rate of the method using adaptively selected parameters <i>L</i><sub><i>k</i></sub> is estimated. An important feature of the result obtained is the elaboration of the case where it is possible to guarantee, after the completion of the iteration, at least double reduction in the residual of the function. At the same time, the use of adaptively selected parameters in theoretical estimates makes the method applicable to both smooth and non-smooth problems, provided that the iteration termination criterion is met. For smooth problems, it can be proved that the theoretical estimates of the method are reliably optimal up to multiplication by a constant factor. Computational experiments are carried out and a comparison with two other algorithms is made to demonstrate the efficiency of the algorithm on a number of both smooth and non-smooth problems.</p>","PeriodicalId":54555,"journal":{"name":"Programming and Computer Software","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138523804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On Accelerated Coordinate Descent Methods for Searching Equilibria in Two-Stage Transportation Equilibrium Traffic Flow Distribution Model 两阶段交通均衡交通流分配模型中寻找平衡点的加速坐标下降法

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s036176882306004x

N. A. Il’tyakov, M. A. Obozov, I. M. Dyshlevski, D. V. Yarmoshik, M. B. Kubentaeva, A. V. Gasnikov, E. V. Gasnikova

引用次数: 0

Robust Algebraic Connectivity 鲁棒代数连通性

IF 0.7 4区计算机科学

Programming and Computer Software Pub Date : 2023-12-01 DOI: 10.1134/s0361768823060051

I. A. Kuruzov, A. V. Rogozin, S. A. Chezhegov, A. B. Kupavskii

引用次数: 0

Twenty Similarity Functions for Two Finite Sequences 两个有限序列的20个相似函数

4区计算机科学

Programming and Computer Software Pub Date : 2023-10-01 DOI: 10.1134/s0361768823050031

I. Burdonov, A. Maksimov

引用次数: 0