Cybernetics and Physics最新文献_第5页

An inverse problem for matrix processing: an improved algorithm for restoring the distance matrix for DNA chains 矩阵处理的逆问题：一种改进的DNA链距离矩阵恢复算法

Cybernetics and Physics Pub Date : 2022-12-30 DOI: 10.35470/2226-4116-2022-11-4-217-226

B. Melnikov, Ye Zhang, D. Chaikovskii

{"title":"An inverse problem for matrix processing: an improved algorithm for restoring the distance matrix for DNA chains","authors":"B. Melnikov, Ye Zhang, D. Chaikovskii","doi":"10.35470/2226-4116-2022-11-4-217-226","DOIUrl":"https://doi.org/10.35470/2226-4116-2022-11-4-217-226","url":null,"abstract":"We consider one of the cybernetic methods in biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the distance matrix for DNA chains. Such a matrix is formed on the basis of any of the possible algorithms for determining the distances between DNA chains. The objects of research of these algorithms (for mammals), as a rule, are one of the following 3 variants: the main histocompatibility complex, the mitochondrial DNA, and “the tail” of the Y chromosome.\u0000In the paper we give an improved algorithm for restoring the distance matrix for DNA chains. Compared to our previous publications, the following changes have been made to the algorithm. We abandoned the use of the branches and bounds method, but at the same time significantly improved the greedy auxiliary algorithm used in it. In this paper, we apply only this greedy algorithm to the general solution of the distance matrix reconstruction problem. As a result of the conducted computational experiments carried out on one of the two considered criteria for the quality of the algorithms, significant improvements were obtained compared to the results given in our previous publications. At the same time, the total running time of the algorithm remained almost the same as in the previous version.","PeriodicalId":37674,"journal":{"name":"Cybernetics and Physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42720547","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

Vibration field control of a two-rotor vibratory unit in the double synchronization mode 双转子振动机组双同步振动场控制

Cybernetics and Physics Pub Date : 2022-12-30 DOI: 10.35470/2226-4116-2022-11-4-246-252

O. Tomchina

引用次数: 2

Strong convergence on a stochastic controlled Lotka-Volterra 3-species model with L´evy jumps 具有L´evy跳跃的随机控制Lotka-Volterra三种群模型的强收敛性

Cybernetics and Physics Pub Date : 2022-12-30 DOI: 10.35470/2226-4116-2022-11-4-227-233

C. Romero-Meléndez, D. Castillo-Fernández

引用次数: 1

The history of cybernetics and artificial intelligence: a view from Saint Petersburg 控制论和人工智能的历史:来自圣彼得堡的观点

Cybernetics and Physics Pub Date : 2022-12-30 DOI: 10.35470/2226-4116-2022-11-3-253-263

Alexander L. Fradkov, A. Shepeljavyi

引用次数: 3

Incremental deep learning training approach for lesion detection and classification in mammograms 增量深度学习训练方法用于乳腺钼靶病变检测和分类

Cybernetics and Physics Pub Date : 2022-12-30 DOI: 10.35470/2226-4116-2022-11-4-234-245

Siavash Salemi, Hamed Behzadi-Khormouji, H. Rostami, Ahmad Keshavarz, Yaser Keshavarz, Yahya Tabesh

{"title":"Incremental deep learning training approach for lesion detection and classification in mammograms","authors":"Siavash Salemi, Hamed Behzadi-Khormouji, H. Rostami, Ahmad Keshavarz, Yaser Keshavarz, Yahya Tabesh","doi":"10.35470/2226-4116-2022-11-4-234-245","DOIUrl":"https://doi.org/10.35470/2226-4116-2022-11-4-234-245","url":null,"abstract":"Recently, Deep Convolutional Neural Networks (DCNNs) have opened their ways into various medical image processing practices such as Computer-Aided Diagnosis (CAD) systems. Despite significant developments in CAD systems based on deep models, designing an efficient model, as well as a training strategy to cope with the shortage of medical images have yet to be addressed. To address current challenges, this paper presents a model including a hybrid DCNN, which takes advantage of various feature maps of different deep models and an incremental training algorithm. Also, a weighting Test Time Augmentation strategy is presented. Besides, the proposed work develops the Mask-RCNN to not only detect mass and calcification in mammography images, but also to classify normal images. Moreover, this work aims to benefit from a radiology specialist to compare with the performance of the proposed method. Illustrating the region of interest to explain how the model makes decisions is the other aim of the study to cover existing challenges among the stateof-the-art research works. The wide range of conducted quantitative and qualitative experiments suggest that the proposed method can classify breast X-ray images of the INbreast dataset to normal, mass, and calcification.","PeriodicalId":37674,"journal":{"name":"Cybernetics and Physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45002511","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

Optimization approach to the velocity field determining problem 速度场确定问题的优化方法

Cybernetics and Physics Pub Date : 2022-11-17 DOI: 10.35470/2226-4116-2022-11-3-131-135

E. Kotina, D. Ovsyannikov, M. Elizarova

引用次数: 0

An approach for obtaining estimation of stability of large communication network taking into account its dependent paths 一种考虑依赖路径的大型通信网络稳定性估计方法

Cybernetics and Physics Pub Date : 2022-11-17 DOI: 10.35470/2226-4116-2022-11-3-145-150

B. Melnikov, Y. Terentyeva

{"title":"An approach for obtaining estimation of stability of large communication network taking into account its dependent paths","authors":"B. Melnikov, Y. Terentyeva","doi":"10.35470/2226-4116-2022-11-3-145-150","DOIUrl":"https://doi.org/10.35470/2226-4116-2022-11-3-145-150","url":null,"abstract":"The physical data layer transmits bits over physical communication channels, such as coaxial cable or twisted pair. That is, it is this level that directly transmits data. At this level, the characteristics of electrical signals that transmit discrete information are determined. After that it is necessary to consider the control of the communication network, its various algorithms. When designing a communication network, a prerequisite is to calculate its stability, and in the case of large scale communication networks, this is a big problem. The most common deterministic, as well as fairly fast approximate method, which is often implemented at the present time, is the method by which the stability of the communication direction which is estimated by analyzing independent paths only. The main disadvantage of this method is obtaining an understated estimate of stability due to unaccountable dependent routes of communication directions. And this leads to inefficient use of resources. Our proposed methodology allows to take into not only independent paths, but also dependent ones, which is the basis for obtaining a significantly more correct estimate. It is based on an algorithm for checking the presence of a certain path and, based on it, an algorithm for obtaining an exact assessment of stability. The paper also provides analytical and statistical analysis of the considered algorithms. In particular, a special parameter was introduced that characterizes the probability of a failure event of communication lines, in which the number of failed communication lines lies in a certain specified range; after which a study of the function describing this parameter was carried out.","PeriodicalId":37674,"journal":{"name":"Cybernetics and Physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49267014","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: 1

A cybernetic view on international stability under multiple sanctions and counter-sanctions 多重制裁与反制裁下国际稳定的控制论观点

Cybernetics and Physics Pub Date : 2022-11-17 DOI: 10.35470/2226-4116-2022-11-3-165-168

A. Fradkov

引用次数: 1

Synchronization Of Two-Rotor Vibration Units Using Neural Network-Based PID Controller 基于神经网络PID控制器的双转子振动单元同步

Cybernetics and Physics Pub Date : 2022-11-17 DOI: 10.35470/2226-4116-2022-11-3-136-144

Hoang Duc Long, N. Dudarenko

引用次数: 0

Physical hysteresis of the piezoelectric drive in precise image velocity stabilization system built into the Earth observing orbit telescope 地球观测轨道望远镜精密图像速度稳定系统中压电驱动的物理滞后

Cybernetics and Physics Pub Date : 2022-11-17 DOI: 10.35470/2226-4116-2022-11-3-157-164

Y. Somov, S. Butyrin, T. Somova

引用次数: 0