Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika最新文献

On Using the Decision Trees to Identify the Local Extrema in Parallel Global Optimization Algorithm 用决策树识别并行全局优化算法中的局部极值

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-08-01 DOI: 10.14529/cmse230301

引用次数: 0

On a Hypothesis of the Theory of Formal Languages. Part I 形式语言理论的一个假设。第一部分

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-08-01 DOI: 10.14529/cmse230305

{"title":"On a Hypothesis of the Theory of Formal Languages. Part I","authors":"","doi":"10.14529/cmse230305","DOIUrl":"https://doi.org/10.14529/cmse230305","url":null,"abstract":"The main subject of the article is the consideration of problems arising in the study of the necessary conditions for the equality of infinite iterations of finite languages. In previous publications, the author considered examples of the application of a special binary equivalence relation corresponding to this equality in a set of finite languages, and considered both examples describing the necessary conditions for its implementation and examples of its use. Further reducing the problem under consideration is applied to one of such necessary conditions: to finite automata and to infinite iterative trees. In addition, the article presents several variants of the formulation of an important hypothesis on the set of finite languages, its study also provides other options for reducing the problem under consideration to special problems of studying nondeterministic finite automata. At the same time, if the formulated hypothesis is fulfilled, some of these problems are solved in polynomial time, and some are not; with the continuation of work on this topic, the last fact may make it possible to reformulate the problem P=NP in the form of a special problem of the theory of formal languages.","PeriodicalId":34704,"journal":{"name":"Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135052376","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

Computer-aided Design and Execution of Effective Programs for Numerical Algorithms 数值算法有效程序的计算机辅助设计与执行

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-08-01 DOI: 10.14529/cmse230303

{"title":"Computer-aided Design and Execution of Effective Programs for Numerical Algorithms","authors":"","doi":"10.14529/cmse230303","DOIUrl":"https://doi.org/10.14529/cmse230303","url":null,"abstract":"Designing effective parallel programs for multiprocessor architectures is difficult because there are no clear formal rules to follow. The concept of the Q-determinant can be applied to solve this problem when implementing numerical algorithms. This theory allows for automated analysis of the algorithm parallelism resource, automated comparison of the parallelism resources of algorithms solving the same algorithmic problem. In addition, it makes it possible to design effective programs for the implementation of numerical algorithms using a specially developed design method, improve the efficiency of the implementation of numerical methods and algorithmic problems. The results obtained on the basis of the Q-determinant concept are one of the options for solving the problem of effective implementation of numerical algorithms, methods and algorithmic problems on parallel computing systems. However, the fundamental problem of computer-aided design and execution for any numerical algorithm of a program that implements the algorithm effectively remains unresolved. The paper describes the development of a software system for designing and executing Q-effective programs that is unified for numerical algorithms. A Q-effective program is an effective program designed using the concept of a Q-determinant. The system is intended for use on parallel computing systems with shared memory. It consists of a compiler and a virtual machine. The compiler converts the representation of the algorithm in the form of a Q-determinant into an executable program that uses the algorithm’s parallelism resource completely. The virtual machine executes the program generated by the compiler. The paper also provides an experimental study of the created software system using the SUSU Tornado supercomputer.","PeriodicalId":34704,"journal":{"name":"Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135052030","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

Detection of Time Series Anomalies Based on Data Mining and Neural Network Technologies 基于数据挖掘和神经网络技术的时间序列异常检测

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-08-01 DOI: 10.14529/cmse230304

{"title":"Detection of Time Series Anomalies Based on Data Mining and Neural Network Technologies","authors":"","doi":"10.14529/cmse230304","DOIUrl":"https://doi.org/10.14529/cmse230304","url":null,"abstract":"The article touches upon the problem of discovering subsequence anomalies in time series, which is currently in demand in a wide range of subject domains. We propose a new semi-supervised method to detect subsequence anomalies in time series. The method is based on the concepts of discord and snippet, which formalize, respectively, the concepts of anomalous and typical time series subsequences. The proposed method includes a neural network model that calculates the anomaly score of the input subsequence and an algorithm to automatically construct the model’s training set. The model is implemented as a Siamese neural network, where we employ a modification of ResNet as a subnet. To train the model, we proposed a modified contrast loss function. The training set is formed as a representative fragment of the time series from which discords, low-fraction snippets with their nearest neighbors, and outliers within each snippet are removed since they are interpreted as abnormal, atypical activity of the subject, and noise, respectively. Computational experiments over time series from various subject domains showed that the proposed model, compared with analogues, has on average the highest accuracy of anomaly detection with respect to the standard VUS-PR metric. The downside of the high accuracy of the method is the longer time spent on model training and anomaly detection compared to analogues. Nevertheless, in applications of intelligent building heating control, the method provides a speed sufficient to detect subsequence anomalies in real time.","PeriodicalId":34704,"journal":{"name":"Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135052675","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

Fusion Approach for Pneumonia Classification on Imbalanced Multimodal Data 基于不平衡多模态数据的肺炎分类融合方法

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-08-01 DOI: 10.14529/cmse230302

{"title":"Fusion Approach for Pneumonia Classification on Imbalanced Multimodal Data","authors":"","doi":"10.14529/cmse230302","DOIUrl":"https://doi.org/10.14529/cmse230302","url":null,"abstract":"In medical practice, the primary diagnosis of diseases should be carried out quickly and, if possible, automatically. The processing of multimodal data in medicine has become a ubiquitous technique in the classification, prediction and detection of diseases. Pneumonia is one of the most common lung diseases. In our study, we used chest X-ray images as the first modality and the results of laboratory studies on a patient as the second modality to detect pneumonia. The architecture of the multimodal deep learning model was based on intermediate fusion. The model was trained on balanced and imbalanced data when the presence of pneumonia was determined in 50% and 9% of the total number of cases, respectively. For a more objective evaluation of the results, we compared our model performance with several other open-source models on our data. The experiments demonstrate the high performance of the proposed model for pneumonia detection based on two modalities even in cases of imbalanced classes (up to 96.6%) compared to single-modality models’ results (up to 93.5%). We made several integral estimates of the performance of the proposed model to cover and investigate all aspects of multimodal data and architecture features. There were accuracy, ROC AUC, PR AUC, F1 score, and the Matthews correlation coefficient metrics. Using various metrics, we proved the possibility and meaningfulness of the usage of the proposed model, aiming to properly classify the disease. Experiments showed that the performance of the model trained on imbalanced data was even slightly higher than other models considered.","PeriodicalId":34704,"journal":{"name":"Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135052031","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

Application of the Design Method for Q-effective Programs Implementing Dijkstra’s Algorithm 实现Dijkstra算法的q有效程序设计方法的应用

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-05-01 DOI: 10.14529/cmse230203

引用次数: 0

Anomaly Detection in Digital Industry Sensor Data Using Parallel Computing 基于并行计算的数字工业传感器数据异常检测

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-05-01 DOI: 10.14529/cmse230202

引用次数: 0

On New Version of the Apex Method for Solving Linear Programming Problems 求解线性规划问题顶点法的新版本

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-05-01 DOI: 10.14529/cmse230201

引用次数: 0

Working with Data in the SYNHRO Educational Programming Language 在SYNHRO教育编程语言中处理数据

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-05-01 DOI: 10.14529/cmse230205

引用次数: 0

Solving Grid Equations Using the Alternating-triangular Method on a Graphics Accelerator 在图形加速器上用交变三角法求解网格方程

Vestnik IuzhnoUral''skogo gosudarstvennogo universiteta Seriia Vychislitel''naia matematika i informatika Pub Date : 2023-05-01 DOI: 10.14529/cmse230204

A. Sukhinov, V. Litvinov, A. Chistyakov, A. Nikitina, N. Gracheva, N. Rudenko

引用次数: 0