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2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)最新文献

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The role of connections topology on synchronization in neural network 神经网络中连接拓扑对同步的作用
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923133
M. Mishchenko, Natalia S. Kovaleva, D. Bolshakov, V. Matrosov
{"title":"The role of connections topology on synchronization in neural network","authors":"M. Mishchenko, Natalia S. Kovaleva, D. Bolshakov, V. Matrosov","doi":"10.1109/DCNA56428.2022.9923133","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923133","url":null,"abstract":"Complex networks describe a wide range of systems in nature and society. Every complex network has certain topological features which strongly influence the dynamics. We studied the dynamics of a complex network of excitable elements with different coupling topologies. The role of network topology, noise level and coupling strength on the resulting dynamical modes has been observed. The effect of hub removal on network dynamics has been studied.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127837517","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
Self-organized criticality in a neural network with the small-world topology 具有小世界拓扑的神经网络的自组织临界性
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923224
Illarion Ushakov, M. Mishchenko, V. Matrosov
{"title":"Self-organized criticality in a neural network with the small-world topology","authors":"Illarion Ushakov, M. Mishchenko, V. Matrosov","doi":"10.1109/DCNA56428.2022.9923224","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923224","url":null,"abstract":"The phenomenon of self-organized criticality in a neural network with the “Small-world” topology has been studied. We studied the critical value of coupling strength as a function of the total number of connections in the network. The dependence of critical coupling strength on the number of connections obeys the power law.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127908763","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
Analysis of eye-tracking data during the Sternberg working memory task in subjects with asthenic syndrome 衰弱综合征受试者在Sternberg工作记忆任务中的眼动追踪数据分析
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923207
Oleg Piljugin, Artem Badarin, V. Antipov, V. Grubov, Belousova Yana, A. Tynterova, V. Rafalskiy, N. Shusharina, A. Hramov
{"title":"Analysis of eye-tracking data during the Sternberg working memory task in subjects with asthenic syndrome","authors":"Oleg Piljugin, Artem Badarin, V. Antipov, V. Grubov, Belousova Yana, A. Tynterova, V. Rafalskiy, N. Shusharina, A. Hramov","doi":"10.1109/DCNA56428.2022.9923207","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923207","url":null,"abstract":"In the current study, we analyzed eye-tracking data from subjects with asthenic syndrome during the performance of Sternberg Working Memory Task. To determine the severity of asthenia we used Multidimensional Fatigue Inventory. We showed that people with the asthenic syndrome are characterized by a rapid increase in subjective fatigue during the experiment. We confirmed the relationship between the subjective level of fatigue and pupil size. We believe that eye-tracking is a suitable method for objectively identifying mental fatigue during a cognitive task.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132404610","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
The simplest neuron models with bistability occurring as a result of accounting new ion channels 最简单的双稳定性神经元模型是由于计算新的离子通道而产生的
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923176
N. Stankevich, Elmira Bagautdinova
{"title":"The simplest neuron models with bistability occurring as a result of accounting new ion channels","authors":"N. Stankevich, Elmira Bagautdinova","doi":"10.1109/DCNA56428.2022.9923176","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923176","url":null,"abstract":"A family of Hodgkin-Huxley-type models demonstrating bistability between silent state and bursting oscillations is proposed. In models several ion channels were taking into account to achieve some specific types of bistability and behavior. We studied parameter space of our models with method of chart of dynamical regimes, areas of bistability were localized. Scenarios of bistability occurrence is described. Specific time series character for new ion channel are studied","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130671827","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
Development of "City of the Futureʺ Scene to Assess the User Experience in a Virtual Reality environment 开发“未来城市”场景，评估虚拟现实环境下的用户体验
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923144
A. Tychkov, N. Bofanova, A. Alimuradov, D. Chernyshov, Ilia S. Miltykh
{"title":"Development of \"City of the Futureʺ Scene to Assess the User Experience in a Virtual Reality environment","authors":"A. Tychkov, N. Bofanova, A. Alimuradov, D. Chernyshov, Ilia S. Miltykh","doi":"10.1109/DCNA56428.2022.9923144","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923144","url":null,"abstract":"Virtual reality is rapidly becoming a key method in digital medicine. It is a prospective area of research. The detailed examination of users and its impact on patients is required to introduce virtual reality in medicine. A detailed examination of virtual reality users, followed by an assessment of virtual reality effects, is required for wide adaptation of this technology. The virtual reality of 12 healthy subjects was examined. For this study, we used the custom-designed VR scene “City of the Future”. An HTC Vive Pro headset was used for VR immersion. A physical examination and neurological examination were performed using the State-Trait Anxiety Inventory, Visual analog scale, and Simulator Sickness Questionnaire. All subjects were divided into two groups based on the SSQ score. Group 1, with no or slight side effects, accounted for 58.3%. Group 2 included 41.7% participants with mild to moderate simulator disorder. The strain and trait anxiety level based on the State-Trait Anxiety Inventory in Group 2 with VR-related side effects was higher than in Group 1, which had no simulator sickness. We suppose that VR experience can have positive or negative user feedback or cause simulator sickness based on psychoemotional factors such as anxiety. Dynamic monitoring and the development of an adaptive system for users in the virtual reality environment, which will monitor the dynamic individual characteristics of the person, are needed. This will improve the adaptation mechanisms and lead to a positive virtual experience.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132016788","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
Reinforcement learning in a spiking neural network with memristive plasticity 具有记忆可塑性的尖峰神经网络的强化学习
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923314
D. Vlasov, R. Rybka, A. Sboev, A. Serenko, A. Minnekhanov, V. A. Demin
{"title":"Reinforcement learning in a spiking neural network with memristive plasticity","authors":"D. Vlasov, R. Rybka, A. Sboev, A. Serenko, A. Minnekhanov, V. A. Demin","doi":"10.1109/DCNA56428.2022.9923314","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923314","url":null,"abstract":"The reinforcement learning paradigm is for the first time presented for spiking neural network architecture with memristor-based local dynamic plasticity. The models of two kinds of such plasticity are used in the simulation study of the Cartpole task. Applying the Gaussian receptive field time-encoding scheme and simple reinforcing current pulses determined by the sign of reward change, the successful learning is demonstrated for both types of memristive plasticity.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128931357","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
Development of methods and algorithms of technical vision for detecting the defect longitudinal crack on sheet metal 金属薄板缺陷纵向裂纹技术视觉检测方法与算法的发展
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923180
Mortin Konstantin, Shamshin Maksim
{"title":"Development of methods and algorithms of technical vision for detecting the defect longitudinal crack on sheet metal","authors":"Mortin Konstantin, Shamshin Maksim","doi":"10.1109/DCNA56428.2022.9923180","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923180","url":null,"abstract":"The paper presents a mathematical model of a fuzzy subset of a defect in a digital image and is described as a piecewise constant function. The analysis of the filtering of the flaw detection image is given to ensure the implementation of the quantization algorithm of detection with subsequent adaptive binarization of the obtained result. The developed method makes it possible to detect a sheet metal defect of the longitudinal crack type and calculate various geometric parameters of this defect. This approach allows not only to see the detection of a longitudinal crack, but also to minimize the errors of the second level of false positives on flaw detection images. The above result is compared with the annotation of the flaw detector and with the YOLOv3 neural network.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129062693","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
Measuring Cognitive Potential in People while Performing Tasks with Varying Complexity 测量人们在执行不同复杂任务时的认知潜能
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923082
A. Petukhov, A. Polevaia, S. Polevaya
{"title":"Measuring Cognitive Potential in People while Performing Tasks with Varying Complexity","authors":"A. Petukhov, A. Polevaia, S. Polevaya","doi":"10.1109/DCNA56428.2022.9923082","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923082","url":null,"abstract":"The purpose of the presented study is to assess the cognitive potential of a person based on the experimental data obtained in order to identify the cognitive capabilities of a person and its dynamics, e.g., to monitor recovery after a disease. To assess cognitive potential, two algorithms have been developed, one for assessing the level of cognitive complexity of a task, and the other for assessing the level of cognitive potential in a person. A complex of experimental methods has been applied using specially developed authorial methods; to assess the cognitive potential in an individual, mathematical methods for data processing and calculation of the introduced specific parameters were used. Specific methods are proposed using author's mathematical formulas for assessing the cognitive potential of a person based on experimental data and tasks of varying cognitive complexity as stimuli. Within the framework of this study, the methodology for assessing the value of cognitive potential in people based on the information representations (images) theory was created. To assess cognitive skills, including the so-called soft skills, a special online solution with the set of tools has been developed. The obtained parameters allow us to study the effect of social, genetic, and pathogenetic factors on cognitive potential. A theoretical approach and a technological platform for digital mapping of cognitive potential are proposed.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115865483","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
Epileptic EEG marking with machine learning approach 机器学习方法的癫痫脑电图标记
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923177
Vadim Grubov, Sergey Afinogenov, V. Maximenko, N. Utyashev
{"title":"Epileptic EEG marking with machine learning approach","authors":"Vadim Grubov, Sergey Afinogenov, V. Maximenko, N. Utyashev","doi":"10.1109/DCNA56428.2022.9923177","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923177","url":null,"abstract":"In the present study we implemented machine learning approach to detect seizures on epileptic EEG data. We aimed to propose a method for preliminary EEG marking, that can possibly find application in clinical decision support system.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117003144","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
Data classification using interferential neural network model 基于干扰神经网络模型的数据分类
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI: 10.1109/DCNA56428.2022.9923199
N. Babbysh
{"title":"Data classification using interferential neural network model","authors":"N. Babbysh","doi":"10.1109/DCNA56428.2022.9923199","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923199","url":null,"abstract":"Classical models of artificial neural networks have several disadvantages. To eliminate these shortcomings, a fundamentally new model of an artificial neural network, called the interferential model, is proposed. This model is based on the structure of biological neurons of the human brain. This work describes principles of work of interferential model. The results of the work show that the interferential model does not contain the disadvantages of classical neural networks. It is well suited for running classification task, as well as for pattern recognition.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125240057","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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