Galina Rybina, Yuri Blokhin and Sergey Parondzhanov. Intelligent planning methods and features of their usage for development automation of dynamic integrated expert systems.
The problems of intellectualization in the development process of dynamic integrated expert systems basing on the the problem-oriented methodology and the AT-TECHNOLOGY workbench are considered. The experience from carrying out intellectual planning for the synthesis of architectural layouts of prototypes in integrated expert systems, the intelligent planner usage, reusable components, typical project procedures, and other components of the intellectual software environment in the AT-TECHNOLOGY complex is described.
Galina Rybina and Elena Sergienko. Ontological approach as a base of standard intelligent tutoring problems with use of tutoring integrated expert systems
The aim of this work is the analysis and synthesis of experience in the develop-ment and usage of tools for intellectual tutoring, functioning as part of AT-TECHNOLOGY workbench in the study process.
Soichiro Arai and Junichi Takeno. Discussion on explicit consciousness, sub-consciousness, and self-awareness in a conscious system.
What is “self-awareness”? How can explicit consciousness and sub-consciousness be mapped in relation to each other? How are they related to the self? How can these entities be represented in an artificial conscious system? These questions are the focus of this article. People are aware of only the behavior that they are focusing on; they cannot be directly aware of routine behavior such as walking and breathing. The latter is generally called unconscious behavior, and here we call it sub-conscious behavior. To understand self-awareness, therefore, firstly it is important to map explicit …
Naoya Arakawa. Simulating the Usage Acquisition of Two-Word Sentences with a First- or Second-Person Subject and Verb.
This article examines a minimalist mechanism in a simple language game to acquire the use of two-word sentences consisting of a first- or second-person pronoun as the subject and a verb as the predicate. In an experiment, a learner agent with minimalist architecture learned to select the subject and verb while interacting with a caretaker agent. The assumptions and implications of the experiment are discussed.
Kensuke Arai and Junichi Takeno. Discussion on the Rise of the Self in a Conscious System.
What is human self? Some argue that there is no such thing as self. However, the subjective feeling that “I am writing these words” makes it hard to deny the existence of the self. We assume that as long as there is the term “self,” there must be some collection of neural networks that represents the concept of the term. Although the whole picture is still a mystery, we have taken a step forward to unraveling the mystery by introducing the idea that “the emergence of a new behavior that prioritizes the body underlies the rise of the self.” When performing imitation behavior, a …
Daiki Matsumoto, Hanwen Xu and Junichi Takeno. Simulation of the Cognitive Process in Looking at Rubin’s Vase.
We have successfully simulated the cognitive process in looking at Rubin’s Vase. Rubin’s Vase is an ambiguous image developed by the Danish psychologist Edgar Rubin. The ambiguous image allows the viewer to interpret it in more than one way. The Rubin’s Vase image used in this study depicts a vase in the center in a way that its contour matches the human profile, allowing the viewer to interpret the image as either “a vase in the center” or “two faces looking at each other.” The program we have developed is designed to enable the internal representation systems to change their …
Tomoya Sumioka and Junichi Takeno. Discussion of Stalking Behavior Using a Conscious System.
Stalking behavior, characterized by specific and dreadful acts such as persistent following, repeated sending of unwanted gifts, lack of sympathy, and even willingness to kill the victim, has become a serious concern in modern society. However, since stalking behavior has something partly in common with any criminal behavior, further discussion of this topic is considered helpful in determining factors behind various criminal behavior. Thus, there is an urgent need to investigate how this mysterious and dangerous behavior arises. There are three main types of stalking behavior: …
Vladimir Redko and Zarema Sokhova. Model of Collective Behavior of Investors and Producers in the Decentralized Economic System.
The paper presents the interaction mechanism between investors and producers in a decentralized economic system. The main element of the interaction is the iterative process. In this process, each investor takes into account the contributions of other investors into producers. The model is investigated by means of the computer simulation, which demonstrates the effectiveness of the considered mechanism.
Yuichi Takayama and Junichi Takeno. A conscious robot that can venture into an unknown environment in search of pleasure.
A “conscious system that can venture into an unknown environment” has been proposed. This study models the process of consciousness of a person who is going into an unknown environment. First, we assumed that to go into an unknown environment, the person needs to be curious about that environment and assured of its safety. Curiosity is a tendency to become interested in unknown phenomena and draw information from them. We consider that to acquire the behavior of going into an unknown environment (curiosity behavior), firstly the person needs in some way to go through many experiences of …
Vladimir Red’Ko. Model of Interaction between Learning and Evolution.
The lecture characterizes the following main properties of interaction be-tween learning and evolution: 1) the mechanism of the genetic assimilation, 2) the hiding effect, 3) the role of the learning load at investigated processes of learning and evolution
Alexandr Petukhov. The theory of information images: basics of model.
This paper presents the basic principles of the Information Image Theory. Methods and approaches suggested in the current article allow us to compare different levels of the described processes depending on the chosen architecture of the model; they are also able to simulate the processes of distortion and generation information images during information and communication social interaction. Expansion and addition of information images theory in terms of information transmission among individuals enables us to speak about the space of individual information images. The existence of such …
Pavel Gusev and Georgii Borzunov. The analysis of modern methods for video authentication.
This report is dedicated to the review of existing methods for video authentication. The study includes analysis and classification of existing methods by using algorithms and by problems which are solved by video authentication. The report presents the definition of video authentication, the typical authentication scheme is described and known algorithms are classified. The existing methods are analyzed in which the most promising directions are revealed and recommendations for further evolution of this subject.
Masahiro Miyata and Takashi Omori. Modeling emotion and inference as a value calculation system.
There were many modeling studies on the emotion. But most of them were phenomenological and don’t approach to the brain or cognitive mechanism. In this study, we discuss on a possibility of its computational modeling based on an idea that an emotion in a wider sense is a value calculation system for an action decision. First, we show a possible brain architecture that the emotion system has a tight interaction with the cortical intelligent system through an interaction between the brain information processing areas of neocortex and limbic system. Then, in this study, we focused on a …
Andrey Trukhachev and Natalia Ivanova. Extracting of High-level Structural Representation from VLSI Circuit Description Using Tangled Logic Structures.
This paper proposes a method of automatic VLSI circuit analysis. On the first step transistors are grouped by their structure. Groups with irregular structure are highly interconnected to each other. Detecting Tangled Logic Structures (TLS) with a GTL-depended linear ordering and genetic algorithm divides the circuit due to its functional structure and forms the gate-level VLSI circuit. High-level functional blocks in circuit description consist of gate-level cells groups, which are also highly interconnected. After TLS-blocks extracting, it is possible to describe their function. …
Anton Yakovenko and Galina Malykhina. Bio-inspired approach for automatic noise-robust voice recognition using auditory modeling and neural networks.
This paper presents a biologically inspired approach to the problem of the voice biometrics. Aim of this study is to examine capacity of the automatic system, based on a physiologically appropriate computational model of the auditory perception and neural networks, to recognize voices of different speakers through the analysis of the provided text-independent speech examples, as well as performance evaluation of the proposed approach compared to the conventional MFCC-based method. The idea stems from the human ability to successfully extract a various information from speech in the process …
Haruo Mizutani, Michihiko Ueno, Naoya Arakawa and Hiroshi Yamakawa. Whole brain connectomic architecture to develop general artificial intelligence.
Whole Brain Connectomic Architecture (WBCA) is defined as a software architecture of the artificial intelligence (AI) computing platform which consists of empirical neural circuit information in the entire brain. It is constructed with the aim of developing a general-purpose biologically plausible AI to exert brain-like multiple cognitive functions and behaviors in a computational system. We have developed and implemented several functional machine learning modules, based on open mouse connectomic information, which correspond to specific brain regions. WBCA can accelerate efficient …
Timofei Voznenko, Alexander Dyumin, Evgeniya Aksenova, Alexander Gridnev and Vladislav Delov. The Experimental Study of ‘Unwanted Music’ Noise Pollution Influence on Command Recognition by Brain-Computer Interface.
Nowadays, the alternative methods of human-computer interactions that can drastically improve usability of cyber-physical systems and devices, as mobile robots, especially for disabled persons are in development. These methods includes usage of brain-computer interfaces (BCI). Unfortunately, BCI’s aren’t reliable enough to handle critical devices outside lab environments, since the quality of command recognition can be influenced by external conditions, as noise pollution that can distract the user of BCI. In this paper, we are presenting the experimental study results of the influence of …
Alexander Gridnev, Timofei Voznenko and Eugene Chepin. The Decision-Making System for a Multi-Channel Robotic Device Control.
Nowadays, there is a trend of significant robotic devices functionality increase. Accordingly, the robotic devices can perform more operations and have more new ways to control them. Therefore, in some cases there is a situation when the robotic device receives control commands, i.e. instructions for performing different operations from different alternative control channels. It is a problem of a command selection for execution when different control channels have contradictory information. If there are multiple control channels, which have fundamentally different principle of operation, and …
Timofei Voznenko, Eugene Chepin and Gleb Urvanov. The Control System Based on Extended BCI for a Robotic Wheelchair.
In most cases, the movement of wheelchairs is controlled by disabled people using a joystick or by an accompanying person. Significantly disabled patients need alternative control methods without using the wheelchair joystick, because it is undesirable or impossible for these patients. In this article we present the implementation of a robotic wheelchair based on a powered wheelchair which is controlled not by the joystick but by the on-board computer that receives and processes data from the extended brain-computer interface (extended BCI). Under this term we understand the robotic complex …
Mikhail Kupriyashin and Georgii Borzunov. Algorithmic Foundation for Benchmarking of Computational Platforms Running Asymmetric Cryptosystems.
General purpose benchmarks do not yield accurate performance estimates for special tasks. In this paper we consider implementation of exact algorithms for the 0-1 Knapsack Problem in order to determine the performance of parallel computation platforms intended for running or performing analysis on asymmetric ciphersystems. We study some features of exact parallel algorithms for the Knapsack Problem, as well as load balancing techniques for them. We propose an algorithmic foundation for computational platform benchmarking aimed at getting accurate performance estimates for these platforms.
Vadim Shakhnov, Vadim Kazakov, Lyudmila Zinchenko and Vladimir Makarchuk. Cognitive Data Visualization of Chirality-Dependent Carbon Nanotubes Thermal and Electrical Properties.
The report examines different approaches to the presentation and preliminary processing of multidimensional data on the thermal conductivity of carbon nanotubes. The proposed approach can simplify the process of data analysis.
Alexander Dyumin. Application for help with reviewing as a Program Committee Member.
Data Science, Machine Learning, AI in Robotics, Networks, General Algorithms, NLP, Computer Architectures (Clouds, DC, etc).
Gayar Salakhutdinov and Irina Grigoryeva. Impulse X-ray spectrometer based on the thermoluminescent detectors.
We have developed the compact spectrometer for hot plasma impulse X-ray diagnostics, based on the analysis of thermoluminescent detectors main characteristics. The main results of X-ray emission research on various plasma devices are represented.
Gayar Salakhutdinov. Sources of ion emission in micropinch discharge plasma.
A set of spectrometers for simultaneous research of spatial structure of x-ray and ion emission sources in high current discharge is described. Experimental results of micropinch plasma ion and x-ray emission sources and their origin are discussed. Spectral characteristics of ion emission from micropinch plasma discharge are discussed.
Dmitry Efanov and Pavel Roschin. The Port-in-Use Covert Channel Attack.
We propose a port-is-in-use attack, which is intended for leaking sensitive information in multilevel secure operating systems. Our approach is based on TCP socket mechanism widely used in Linux for interprocess communication. Despite the strong limitations inherent in operating systems with mandatory access control, sockets may not be restricted by the security policy, which makes it possible theoretically to transfer information from one process to another from a high security level to a low one. The proposed attack belongs to the operating system storage transition-based class attack. The …
Anna Epishkina and Sergey Zapechnikov. A technique of blockchain dispersal for efficient storage.
Blockchain has become a very popular technique of creating non-editable data registers. Over time, very significant amount of data accumulates in these registers. At the same time access to this data occurs relatively rarely, mainly in order to take reference or resolve conflicts. Traditional technology implies that each participant of peer-to-peer network stores a full copy of the blockchain. We propose to apply algorithms of information array dispersal and reconstruction to drastically reduce the amount of data stored by nodes of blockchain network. We provide evaluation of memory usage …
Anna Epishkina and Sergey Zapechnikov. Discovering and clustering hidden time patterns in blockchain ledger.
Currently, non-editable blockchain-based ledgers become important tools for cryptocurrency transactions, auditing, smart contracts, copyright registration and many other applications. In this regard, there is a need to analyze the typical, repetitive actions written to the ledger, for example, to identify suspicious cryptocurrency transactions, a chain of events that led to information security incident, or to predict recurrence of some situation in the future. We propose to use for these purposes the algorithms for T-patterns discovering and to cluster the identified behavioral patterns …
Anna Epishkina and Sergey Zapechnikov. On attribute-based encryption for access control to multidimensional data structures.
Multidimensional data structures are widely used in modern information technologies. We demonstrate that, in addition to well-known applications for OLAP, the blockchain ledgers can also be interpreted as multidimensional data structures. They sometimes contain private or other sensitive information. We argue that attribute-based encryption is a handy tool to control access to multidimensional data structures, discussing the advantages and disadvantages of ciphertext-policy and key-policy attribute-based encryption for this task. We propose a tentative scheme of key and attribute management …
Anastasia Beresneva and Anna Epishkina. Handwritten Signature Verification: the State of The Art.
Nowadays handwritten signature and its verification is utilized in a lot of applications including e-commerce. An analysis of verification algorithms and areas of their practical usage is provided. The focus of the investigation is on verification method based on neural network. This type of verification algorithm is realized as a mobile application and its main characteristics are obtained. The directions of further work are concluded including a modification of an algorithm and its realization in order to remove its disadvantages.
Dmitry Efanov and Pavel Roschin. The All-Pervasiveness of the Blockchain Technology.
The concept of the blockchain technology is a distributed database contains records of transactions that are shared among participating members by combining peer-to-peer technology with public-key cryptography. Each transaction is confirmed by the consensus of a majority of the members, making fraudulent transactions unable to pass collective confirmation. Once a record is created and accepted by the blockchain, it can never be altered. Nowadays the blockchain technology is considered as the most significant invention after the Internet. If the latter connects people to realize online …
Agnese Augello, Ignazio Infantino, Adriano Manfre’, Giovanni Pilato and Filippo Vella. Social signs and reaction processing in a cognitive architecture for an humanoid robot.
The capability of recognizing human social sign is a key feature for a social robot: it makes possible a full, natural and effective interaction between human beings and the robot. We present a robot whose behavior depends on a cognitive architecture that considers the sociality demand a fundamental aspect of the human-machine interaction. The proposed approach focuses the attention on few important social signs directly connected with the emotive reactions and emotions of an humanoid robot. Furthermore, the cognitive architecture considers the verbal interaction by natural language …
Ignazio Infantino, Adriano Manfre’ and Umberto Maniscalco. Robot navigation based on an artificial somatosensorial system.
An artificial somatosensorial system processes robot’s perceptions by mean of suitable soft sensors. The robot moves in a real and complex environment, and the physical sensing of it causes a positive or negative reaction. A global wellness function drives the robot’s movements and constitutes a basis to compute the motivation of a cognitive architecture. The paper presents extensive experimentations and explains the influence of the parameters on the robot behavior and personality.
Javier Gomez Santos, Carlos León, Susana Bautista and Alan Tapscott. Towards a Cognitive Model of Leisure.
Despite the relevant role that leisure plays in day to day activities, general cognitive systems tend not to include specific models of leisure. In this paper we propose a computational model of a subset of the cognitive aspects guiding the election of leisure activities. The model is grounded on psychological descriptions of agents according to five basic personality dimensions (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) and classification of leisure activities according to the interests they trigger. The computational model is tested against …
Alisa Volkert, Stefanie Mueller and Alexandra Kirsch. Human-like prototypes for psychologically inspired knowledge representation.
We evaluate human grouping of everyday objects for a psychologically inspired knowledge representation based on prototype theory. Our goal was to empirically identify items that form a group and the respective prototype. We conducted a study in which participants had to sort different kitchen objects into a digital kitchen. We chose a kitchen as a use case, since people have to tidy up dishes every day. Our overall aim is to develop a knowledge representation system that one day could be used by kitchen robots. We calculated an overall similarity matrix (OSM) and identified groups …
Anna Tikhomirova and Elena Matrosova. Algorithms for intelligent automated evaluation of relevance of search queries results.
This paper is devoted to the problem of automated evaluation of relevance of search queries results. High relevance of search algorithm output is the base of effective large quantities of data processing, which is worked at by users of modern informational systems. Automated and reliable estimate of relevance of search queries results will give the opportunity to lower time expenditures for the best algorithm choice. The usage of improved from this perspective algorithms will allow to raise effectiveness and user satisfaction when dealing with automatic search systems in any activities.
Nikita Ushakov and Vitaliy Ivanenko. Copyright protection of video content based on digital watermarks.
The paper proposes the method of digital watermark usage for video copyright protection, that may be a solution to the piracy of digital content. This paper studies different watermark embedding methods for videos. Modified DEW watermarking algorithm is proposed. This method stands out for its technique – the watermark is embedded exclusively by discarding certain high frequency coefficients. Different attacks on video container were studied. The watermark was exposed to most of the common attacks. Performance factors of this algorithm were calculated, they depend on three parameters: energy …
Dmitry Efanov and Vassili Leonov. Reverse Engineering of Altera FPGA Cyclone Family Bitstream by Differential Power Analysis.
The bitstream is used to describe the configuration data to be loaded into a complex programmable logic device (CPLD) or a field-programmable gate array (FPGA). Open source implementation of CPLD and FPGA compile, place and route and configuration bitstream assemble tools is hindered by the lack of documented open format. Differential power analysis is a form of power analysis which allows to factor the intermediate values within cryptographic or similar computations by statistically analyzing data collected from multiple operations. This paper presents a methodological approach to FPGA …
Christian Tsvetkov and Ivan Vankov. How do deep neural networks represent faces?
Deep learning models of vision have recently achieved human-level of performance in tasks such as object recognition and face identification. However, the extent to which these computational models resemble the way biological vision works remains unclear. We address this question by investigating how a deep learning model of face identification represents faces and by comparing the results to data from behavioural experiments. To this end, we use the Bubbles technique (Gosselin & Schyns, 2001) in order to find the critical regions within an image which are needed for correct face …
Antonio Luigi Perrone. A novel deep learning asymmetrical architecture for active learning applications in large data-sets annotations.
A novel deep learning asymmetrical architecture for active learning applications in large data-sets annotations
Boris Onykiy, Evgeniy Tretyakov, Larisa Pronicheva, Ilya Galin, Kristina Ionkina and Andrey Cherkasskiy. Methodology of learning curve analysis for development of incoming material clustering neural network.
This paper describes the methodology of learning curve analysis for development of incoming material clustering neural network. This methodology helps to understand deeply the learning curve adequate level and to bring learning curve structure to the relevant one of the thematic scope of incoming materials. The methodology is based on visual analysis and comprises the building of directed graphs in order to identify data templates. As the battlefield for material clustering the Nuclear Infrastructure Development Section (NIDS) of the International Atom Energy Agency (IAEA) is selected as the …
Max Talanov, Fail Gafarov, Jordi Vallverdú, Sergey Ostapenko, Marat Gazizov, Alexander Toschev, Alexey Leukhin and Salvatore Distefano. Simulation of serotonin mechanisms in NEUCOGAR cognitive architecture.
This work aims at demonstrating that the neuromodulatory mechanisms that control the emotional states of mammals (specifically rat’s brains) can be represented and re-implemented in a computational model processed by a machine. In particular we specifically focus on two neurotransmitters, sero- tonin and dopamine, starting from their fundamental role in basic cognitive processes. In our specific implementation, we represent the simulation of the ‘disgust-like’ state based on the three dimensional neuromodulatory model of affects or emotions, according to the ‘cube of …
Artem Chernyshov, Anita Balandina, Anastasiya Kostkina and Valentin Klimov. Intelligent search system for huge non-structured data storages with domain-based natural language interface.
Nowadays the number of huge companies and corporations has in their disposition various non-structured texts, documents and other data. The absence of clearly defined structure of the data makes the implementation of searching queries complicated and even impossible depending on the storage size. The other problem connected with staff, which may face the problem with misunderstanding of the special query languages, knowledge of which is necessary for the execution of searching queries. To solve these problems, we propose the semantic search system, the possibilities of which include the …
Vlada Kugurakova, Denis Ivanov and Alexander Pudov. The scheme for implementation of the hippocampus based on biologically realistic neuronal network.
In this letter, we described the necessary components of the scheme for implementation of a rat’s hippocampus in a computational system. This is an essential asset for the simulation of different conditions and prediction of the emotional states, as well as the ability of the brain to learn through the study of the flowing metabolic processes.
Natalia Miloslavskaya. Analysis of SIEM Systems and their Usage in Security Operations and Security Intelligence Centers.
The brief analysis of concept and evolution of Security Information and Event Management (SIEM) systems and their usage in Security Operations Centers (SOCs) and Security Intelligence Centers (SICs) for intranet’s information security management are presented.
Alisa Volkert, Stefanie Mueller and Alexandra Kirsch. Human-like Prototypes for Psychologically Inspired Knowledge Representation.
We evaluate human grouping of everyday objects for a psychologically inspired knowledge representation based on prototype theory. Our overall aim is to develop a knowledge representation system that one day could be used by kitchen robots. We conducted a study in which participants had to sort different kitchen objects into a digital kitchen. We chose a kitchen as a use case, since people have to tidy up dishes every day. We calculated an overall similarity matrix and identified object groups whenever at least half of the participants put two items on the same shelf. Out of these object …
Viacheslav E. Wolfengagen, Larisa Yu. Ismailova and Sergey V. Kosikov. Model of conversion of data objects for defining the object-relation mapping.
The paper considers the problem of building of the transformable object-relation mapping. It is shown that an essential part of the task is to get the conversion of data objects doing their representation adjusted for the corresponding data model. It is offered to receive the decision by a semantic method in case of which the formal models of object system and relational system are considered and their interpretations are set. The transformation mappings are considered as a kind of mappings saving interpretations of the given form. Creation of model of converting of data objects on the basis …
Sergey Yarushev and Alexey Averkin. Modular Neural Networks in Time Series Forecasting.
In this paper, modular neural networks, their key features and benets need to conventional neural networks monolithic architecture. Also in this paper we describe a number of neural networks, which are based on self-organizing Kohonen maps, and that can be successfully ap- plied to the identication of dynamic objects, and describes the new, developed and successfully applied to the identication of dynamic objects modular neural networks, their architecture, learning algorithms, and work, the article reviewed examples of modular neural networks, and conducted a comparative analysis with …
Ricardo Gudwin, André Luis Paraense, Suelen Mapa de Paula, Eduardo Fróes, Wandemberg Gibaut, Elisa Castro, Vera Figueiredo and Klaus Raizer. The Multipurpose Enhanced Cognitive Architecture (MECA).
In this paper, we present an overview of MECA, the Multipurpose Enhanced Cognitive Architecture, a cognitive architecture developed by our research group and implemented in the Java language. MECA was designed based on many ideas coming from Dual Process Theory, Dynamic Subsumption, Conceptual Spaces and Grounded Cognition, and constructed using CST, a toolkit for the construction of cognitive architectures in Java, also developed by our group. Basically MECA promotes an hybridism of SOAR, used to implement rule-based processing and space-state exploration in System 2 modules, with a Dynamic …
Vlada Kugurakova and Denis Ivanov. Robot Dream paradigm for Anthropomorphic Social Agent.
In this paper, we discuss the possibilities of integration of the Robot Dream paradigm with Anthropomorphic Social Agent (ASA). Anthropomorphic Social Agent is essentially a user interface specifically designed for simulating the realistic human-to-human interaction. The main idea behind the Robot Dream paradigm is to provide highly realistic social behavior when resources of the machine are limited by outsourcing resource-intensive computation to the cloud. We believe that these two concepts go together nicely.
Denis Kleyko and Evgeny Osipov. No two brains are alike: Cloning a hyperdimensional associative memory using cellular automata computations.
This paper looks beyond of the current focus of research on biologically inspired cognitive systems and considers the problem of replication of its learned functionality. The considered challenge is to replicate the learned knowledge such that uniqueness of the internal symbolic representations is guaranteed. This article takes a neurological argument \no two brains are alike” and suggests an architecture for mapping a content of the trained associative memory built using principles of hyperdimensional computing and Vector Symbolic Architectures into a new and orthogonal basis of …
Mikhail Ivanov and Andrey Starikovskiy. New Life of Old Standard: Transition from One-Dimensional Version to 3D.
The trend of recent years has been the advent of 2D and 3D cryptographic transformations. Stand-ards that have appeared in the 21st century, specify algorithms based on the use of 2D and 3D transformations (AES, Kuznechik, Keccak, Stribog). In the article a 3D version of cryptographic transformation specified by GOST 28147-89 is suggested. The 3D GOST algorithm is characterized by the high degree of parallelism at the level of elementary operations. Increasing bit depth of the processed data blocks from 64 to 512 bits al-lows 3D GOST to be used for the synthesis of hash algorithms. Algorithm …
Sergey Zhurin. Selection of rational set of Methods for Insider’s Identification.
A huge range of international regulatory documents state the importance of counteracting insiders. One of the most important aspects of the preventive measures against an insider is personnel checks using different techniques, including interviews, social network analysis, lie detector. Being limited in money, it is necessary to choose a technique check list rationally. Here is present the sequence for detection the rational set of methods in several cases related to personal check.
Jake Hecla, Timur Khabibullin and Anastasia Tolstaya. Gamma-Probe for Locating the Source of Ionizing Radiation.
The radionuclide diagnostics unit, described in the article, detects pathological changes of organs and systems of a person. The device is a portable detector of gamma rays that allows to diagnose superficial malignancies using radiopharmaceuticals injected into the body. The gamma probe uses crystal LaBr3:Ce as a scintillator and silicon photomultiplier SiPM as a photodetector. The focus of this paper is the improvement of the amplifier, which originally produced misshapen pulses unsuitable for energy discrimination. Using LTSPICE, a free circuit-modelling program, we performed extensive …
Mikhail Alyushin, Alexander Alyushin and Lyubov Kolobashkina. Laboratory Approbation of a New Approach for Contrast Enhancement of Human Face Thermal Image Based on Selective Multifunction Pixel Brightness Conversion Function.
The paper suggests a new approach to improving the contrast of the thermal image of a person’s face in the deep infrared region. The approach involves the analysis and modification of the histogram of the image and is based on the use of a selective multivalued function for encoding the brightness of image pixels. The approach is focused on processing first of all thermal images of the person, containing areas with various informativeness. The implementation of the approach in practice makes it possible to improve the contrast of the face image with preservation of all informative features …
Victor Morozov and Natalia Miloslavskaya. DLP Systems as a Modern Information Security Control.
The importance of using modern protection tools against internal information security (IS) threats is proved. The advantages of DLP systems over alternative solutions are disclosed. The principles and technologies underlying the operation of DLP systems are discussed. The architecture, application features and analytical capabilities of the SearchInform Information Security Perimeter (SearchInform) DLP system are described in detail.
Mikhail Alyushin, Lyubov Kolobashkina and Alexander Alyushin. Laboratory Approbation of the Algorithm for Isolating People’s Faces on a Thermal Infrared Image in the Case of their Quasi-Stationary Arrangement in a Room.
Increasing the effectiveness of training and training sessions is possible through the implementation of so-called biological feedback. Such feedback allows the teacher, or the instructor, to continuously monitor the current psycho-emotional and functional state of the students. As a result, it becomes possible to adapt the style, pace, training mode and the volume of the material outlined, depending on the current receptivity and fatigue level of the listeners. The main element of systems that implement biological feedback in practice are remote non-contact technologies. Such technologies …
Cynthia Avila-Contreras. A bioinspired model of early visual processing with feature and space based saliency for a cognitive architecture.
We present a computational model that describes the early stages of visual processing and the within selective attention mechanisms to generate feature-based activations of salient localizations, which may help to orient gaze or just maintain attention to it, as well as to construct more abstract representations in further processing. The model identifies related brain areas, the feasible computations of each one, and proposes the type of data generated and shared among the components. This work is part of the Selective aspect of an Attention System designed for a broader cognitive …
Masahiko Osawa and Michita Imai. The Functional Plausibility of Topologically Extended Models of RBMs as Hippocampal Models.
The hippocampus has distinctive functional and structural properties. In this research, we utilize Restricted Boltzmann Machines (RBMs) based models inspired by distinctive structures found in hippocampus; neurogenesis in the dentate gyrus (DG) and recurrent connections in CA3. We review two types of topologically extended models of RBMs inspired by hippocampus. In one type of models, units are dynamically added during the training phase, and in the other type, connections are partly recursive. We analyzed these models both as separate models and combined model. The two types of the proposed …
Margarita Zaeva and Andrew Evstifeev. Criteria for assessing the results of production activities of automobile gas filling compressor stations.
Within the framework of this paper, the performance indicators of the automotive gas filling compressor stations for 2014 – 2016 are considered. As a result of the analysis of the indicators of more than two hundred stations owned by PJSC Gazprom and transmitting information in the form of corporate statistical reporting forms criteria of estimation of efficiency of results of industrial activity of stations have been generated. The application of these performance evaluation criteria will allow to provide information to decision-makers about problematic entities of the organization in an …
Natalia Miloslavskaya and Svetlana Tolstaya. Organization’s Business Continuity in Cyberspace.
A reliable and efficient infrastructure of any organization plays an important role and at the same time concentrates various risks, including cybersecurity violation risks. To conduct business in cyberspace, it is extremely important to develop solutions that eliminate a contradiction between the inability to avoid modern cyberattacks and strong requirement to quickly restore organization’s business processes. The brief analysis of business continuity concept in application to cyberspace is given.
Aleksandr I. Panov, Konstantin S. Yakovlev and Roman Suvorov. Grid Path Planning with Deep Reinforcement Learning: Preliminary Results.
Single-shot grid-based path finding is an important problem with the applications in robotics, video games etc. Typically in AI community heuristic search methods (based on A* and its variations) are used to solve it. In this work we present the results of preliminary studies on how neural networks can be utilized to path planning on square grids, e.g. how well they can cope with path finding tasks by themselves as well as how they can be put into service to the conventional heuristic search algorithms, e.g. A*. Conducted experiments show that the agent robustly learns to achieve the goal …
Zulfiqar Ali and Muhammad Imran. A Zero-Watermarking Algorithm for Privacy Protection in a Voice Disorder Detection System.
Unauthorized access to the health information of an individual may create adverse circumstances in their personal life and/or professional career. Various smart healthcare systems have been suggested for use in smart homes and cities, which receive data through the Internet of Things and transmit over a network. One of the major concerns surrounding such healthcare systems is the privacy of individuals. To avoid such predicaments, a privacy protected healthcare system is developed in this study that protects the identity of an individual as well as detects vocal fold disorders. The privacy …
Lubov Podladchikova, Anatoly Samarin, Dmitry Shaposhnikov and Mikhail Petrushan. Modern views on visual attention mechanisms.
Modern views on visual attention mechanisms, some results of our last psychophysical experiments with eye movements recording and future steps of studying have been considered. Several groups of finding have been determined, namely: (i) unresolved objectives; (ii) problems for which contradictory data are known; (iii) finding which propose revision of some classic views; (iv) views consistent with data obtained in different research centers. The results of psychophysical tests directed on receiving of quantitative parameters of eye movements at performance of different visual tasks to …
Margarita Zaeva, Alexander Akhremenkov and Anatoly Tsirlin. Probabilistic assessment of the organization of tournaments and examinations using paired comparisons.
In this paper a criteria of comparison different tournament organization systems in sporting contests is offered, the criteria uses a probability of winning the fairly strongest player. Two probabilistic models have been analyzed. Calculating formulas for estimating of that probability and probability density of score points by one or another player were obtained. Gotten results also provide an order of objects presenting to experts in organization of examination by paired comparison. An analytical estimation of probability of tournament results (or pared comparison) was obtained, it allows …
Jonathan Rosales, Myrna S. Zamarripa, Felix Ramos and Marco-Antonio Ramos. Automatic reward system for virtual creatures, emergent processes of emotions and physiological motivation.
Emotional and motivational evaluations are part of the development of rewards within living beings. Particularly, during the perception of stimuli in the environment, these evaluations collaborate with one another to generate reward values automatically, without the need to involve rational processes. In this paper we propose a conceptual model of automatic reward for virtual creatures inspired by neuroscientific evidence, contemplating the processes of emotions and motivations, as well as the generation and recovery of automatic reward values. According to the evidence, the reward process ….
Larisa Ismailova, Sergey Kosikov and Viacheslav Wolfengagen. Basic constructions of the computational model of support for access operations to the semantic network in the field of implementation of the best available technologies.
The paper considers the approach to solving the task of storing data in the Web environment using semantic networks (SN). The control over the access to SN is identified as a critical task. An approach to the solution based on the use of the controlling SN is proposed. The rationale for the approach involves developing a computational model for supporting the access operations. The construction of a model based on intensional logic is proposed. The basic logical constructions, necessary for building a model, are considered. The testing of the model’s constructions was performed when building ….
Mikhail Egorchev and Yury Tiumentsev. Semi-empirical Neural Network Based Approach to Modelling and Simulation of Controlled Dynamical Systems.
A modelling and simulation approach is discussed for nonlinear controlled dynamical systems under multiple and diverse uncertainties. The main goal is to demonstrate capabilities for semi-empirical neural network based models combining theoretical domain-specific knowledge with training tools of artificial neural network field. Training of the dynamical neural network model for multi-step ahead prediction is performed in a sequential fashion. Computational experiments are carried out to confirm efficiency of the proposed approach..
Dmitry Kozlov and Yury Tiumentsev. Neural network based semi-empirical models for dynamical systems represented by differential-algebraic equations of index 2.
A simulation problem is discussed for nonlinear controlled dynamical systems represented by differential-algebraic equations of index 2.The problem is proposed to be solved in the framework of the semi-empirical approach combining theoretical knowledge for the plant with training tools of artificial neural network field. Special form network based semi-empirical models implementing implicit Runge-Kutta method of numerical integration are proposed to use. The training of the semi-empirical model allows to elaborate the models of aerodynamic coefficient implemented as a part it. The results of ….
Vishwanathan Mohan and Ajaz Ahmad Bhat. Joint Goal Human Robot collaboration-From Remembering to Inferring.
The ability to infer goals, consequences of one’s own and others’ actions is a critical desirable feature for robots to truly become our companions-thereby opening up applications in several domains. This article proposes the viewpoint that the ability to remember our own past experiences based on present context enables us to infer future consequences of both our actions/goals and observed actions/goals of the other (by analogy). In this context, a biomimetic episodic memory architecture to encode diverse learning experiences of iCub humanoid is presented. The critical feature is that ….
Emanuel Diamant. Rethinking BICA’s R&D challenges: Grief revelations of an upset revisionist.
Biologically Inspired Cognitive Architectures (BICA) is a subfield of Artificial Intelligence aimed at creating machines that emulate human cognitive abilities. What distinguish BICA from other AI approaches is that it based on principles drawn from biology and neuroscience. There is a widespread conviction that nature has a solution for almost all problems we are faced with today. We have only to pick up the solution and replicate it in our design. However, Nature does not easily give up her secrets. Especially, when it is about human brain deciphering. For that reason, large Brain Research ….
Mikhail Turov, Alexey Fomin, Elena Matrosova and Anna Tikhomirova. Medical knowledge-based decision support system.
This paper is devoted to the problem of automated supporting of decision-taking process in healthcare. The theranostic process is typified as an especial case of administrative process. Correct solutions of problems in medicine is based on metering big data. These data is represented by facts from real-life experience and numerous guidance of evidence-based healthcare. Taking into account of enormous aggregation of data for special isolated case is possible on application of automated decision support system based on technology of artificial neural network or genetic algorithm..
Norifumi Watanabe and Fumihiko Mori. Sensory Integration Model of Pedestrian by Vection and Somatosensory Stimulation.
In this study, we clarify the integration mechanism of sensory information of vision and somatosensory sensation in walking. In this experiment, we evaluated the possibility of affecting walking by attenuating a somatosensory sensation by giving vibration stimulation to the feet, and by presenting optic flow to the peripheral visual field to generate a self – motion sensation of vision superiority. Experimental results confirmed that walking in the direction opposite to the self – motion sensation is presented by presenting the optic flow and vibration stimulation. Based on the results of ….
Liudmila Zhilyakova. Model of heterogeneous interactions among complex agents. From a neural to a social network.
We describe a heterogeneous neural network where neurons interact by means various neurotransmitters. This feature enables exerting selective influence on neurons. We use this formalism as a basis for modeling interactions between agents in a social network in which two types of opposite activity are spreading. The main properties of agents and principles of activity spreading are defined. The classification of agents according to their parameters is represented..
Zahra Gharaee, Peter Gärdenfors and Magnus Johnsson. Online Recognition of Actions Involving Objects.
We present a system for on-line action recognition that merges the information analyses of two parallel subsystems running in parallel. The first subsystem recognizes what action is performed by using a hierarchical self-organizing map system that analyses the spatial trajectories of the agent’s movements. The second subsystem determines which object the agent acts on by applying a proximity measure. The system has been tested on actions that involve objects and it shows excellent performance..
Valentin Nepomnyashchikh. Strategies of animals in an unfamiliar environment.
Animals employ a set of behavioral strategies when face an unfamiliar environment. A strategy is defined as an movement sequence which repeats itself until replaced by some other behavior. Some strategies are common for very different organisms – from Invertebrates to humans. Another behavioral property of different animals is that they alternate among several strategies instead of employing only one particular strategy. The alternation is spontaneous: it is observed even in the absence of any changes of external stimuli. A simplest example of the alternation is a series of leftward turns ….
Evgenii Vityaev and Alexander Demin. Cognitive architecture based on the functional systems theory.
In this paper the cognitive architecture based on the Functional Systems Theory (TFS) by P.K.Anokhin is presented. This architecture based on the main notions of this theory: goal, result, anticipation of the result. This theory is described on physiological and informational level. The logical structure of this theory was analyzed and used for the control system of the purposeful behavior development. This control system contains the hierarchy of functional systems that organize the purposeful behavior. The control system was used for the agents modeling that are solving the foraging task. ….
Piotr Boltuc. Strong Semantic Computing — a BICA framework.
Standard computing will be characterized as a functional extension of syntax. This is based, partly, on Searle’s Chinese Room argument. Using BICA philosophy, in particular the claim of continuity between human-animal-robot cognitive architectures, we will define strong semantics as the ability of a cognitive architectures to consult cognitive maps, in particular phenomenal content map. The goal of strong semantic computing in autonomous robotics should be to ‘know what is going on’ before engaging in detailed logical analysis (it can be called Gestalt computing). Such computing is ….
Evgenii Vityaev and Alexander Demin. Adaptive control of modular robots.
This paper proposes a learning control system of modular systems with a large number of degrees of freedom based on joint learning of modules, starting with finding the common control rules for all modules and finishing with their subsequent specification in accordance with the ideas of the semantic probabilistic inference. With an interactive 3D simulator, a number of successful experiments were carried out to train three robot models: snake-like robot, multiped robot and trunk-like robot. Pilot studies have shown that the approach proposed is quite effective and can be used to control the ….
Sei Ueno, Masahiko Osawa, Michita Imai, Tsuneo Kato and Hiroshi Yamakawa. Reinforcement Learning Framework for Robots in the Real World that Extends Cognitive Architecture: Prototype Simulation Environment “Re:ROS”.
Reinforcement learning, which is a field of machine learning, is effective for behavior acquisition in robots. The extension of cognitive architecture with synchronous distributed systems is also effective for behavior acquisition. However, early work on the reinforcement learning software framework does not solve the difference between asynchrony and synchrony, and it cannot apply cognitive architecture with asynchronous distributed systems. Therefore, we applied asynchronous distributed systems to reinforcement learning modules to adapt to asynchrony and to extend cognitive architecture ….
Edward Ayunts and Aleksandr I. Panov. Task Planning in “Block World” with Deep Reinforcement Learning.
At the moment reinforcement learning have advanced significantly with discovering new techniques and instruments for training. This paper is devoted to the application convolutional and recurrent neural networks in the task of planning with reinforcement learning problem. The aim of the work is to check whether the neural networks are fit for this problem. During the experiments in a block environment the task was to move blocks to obtain the final arrangement which was the target. Significant part of the problem is connected with the determining on the reward function and how the results ….
Frank Krueger. The neurobiological architecture of trust.
Trust pervades nearly every social aspect of our daily lives; it penetrates all human interactions from personal relationships to organizational interactions. A plethora of studies have started to gain a deeper understanding of the inherent nature of trust by combining behavioral paradigms with functional neuroimaging, electroencephalographic, lesion, endocrinological, and genetic methods in both healthy and psychopathological populations. However, an overarching framework that integrates those separate findings from different levels into a conceptual framework characterizing trust behavior ….
Maksim Sharaev, Vyacheslav Orlov and Vadim Ushakov. Information transfer between rich-club structures in the human brain.
The performance of the human brain depends on how effectively its distinct regions communicate, especially the regions which are more strongly connected to each other than to other regions, or so called “rich-clubs”. The aim of the current work is to find a connectivity pattern between the three brain rich-club regions without any a priori assumptions on the underlying network architecture. Rich-clubs for the analysis were previously identified with structural MRI. Functional magnetic resonance imaging (fMRI) data from 25 healthy subjects (1000 time points from each one) was acquired and ….
Elizaveta Stepanova and Vladimir Pavlovski. Realization of the gesture interface by multifingered robot hand.
The paper considers theoretical mechanical model of a multifingered arm with 21 degrees of freedom. The main objective of the work – is the synthesis of finger control schemes in the tasks of collaborative robotics, as well as gesture recognition task with the help of neural network training. As the demonstration we propose to observe the results of three gestures recognition with the help of constructed convolutional network. For three lables (classes) 201 images at different distance and at different angles were created. As a result of neural network training the accuracy of classification ….
Vasiliy S. Kireev, Ivan S. Smirnov and Victor S. Tyunyakov. Automatic Fuzzy Cognitive Map Building Online System.
Under the present-day global crisis, global economy regionalization and technological areas redistribution there has been seen an unprecedented uncertainty growth along with various risks, which makes it harder to take managing decisions. The scenario approach appears to be one of the most popular when it comes to modelling weakly-structured subject fields and complex problems. Fuzzy cognitive maps have good prospects in the field, as they enable us to describe both the structure and the dynamic of the area under study. This paper goes along the topical automated data science and focuses on ….
Sergey V. Kosikov, Viacheslav E. Wolfengagen and Larisa Yu. Ismailova. The presentation of evolutionary concepts in problems of information support to implement the best available technologies.
The paper considers an approach to solving the problem of supporting the semantic stability of information system (IS) objects. A set of IS objects is addressed as a semantic network consisting of concepts and frames. The interpretation that assigns intensional (meaning) and extensional (value) characteristics to network designs is connected to the constructions of the semantic network. The interpretation in the general case depends on the interpreting subject, time, context, which can be considered as parameters. The possibility to preset a consistent interpretation for a given semantic ….
Hidemoto Nakada and Yuuji Ichisugi Ichisugi. Context-Dependent Robust Text Recognition using Large-scale Restricted Bayesian Network.
We have been proposing a computational model of the cerebral cor- tex called BESOM, which models the cerebral cortex as restricted Bayesian net- works based on recent findings in the neuroscience area. Since BESOM is based on Bayesian network, it inherently allows bi-directional information flow, meaning that it can naturally merge information extracted from concrete data with highly- abstract prior knowledge. As an example of such kind of tasks, we report robust text recognition task with context information. We show that word spelling knowledge and word n-gram could be represented as a ….
Alexey Artamonov, Dmitry Kshnyakov, Valeriya Danilova, Ilya Galin and Andrey Cherkasskiy. Methodology for the Development of Dictionaries for Automated Classification System.
The paper describes a relevant task for research area specialists to define categories for the incoming information and scientific materials by using automated systems (software) and the methodology of developing of dictionaries for such systems. The methodology is based on studying of existing classification codes and developing dictionaries, which contain the most relevant and frequent keywords..
Thomas Collins and Wei-Min Shen. A Robust Cognitive Architecture for Learning from Surprises.
Learning from surprises is a cornerstone for building bio-inspired cognitive architectures that can autonomously learn from interactions with their environments. However, distinguishing true surprises — from which useful information can be extracted to improve an agent’s world model — from environmental noise arising from uncertainty is a fundamental challenge. This paper proposes a new and robust approach for actively learning a predictive model of discrete, stochastic, partially-observable environments based on a concept called the Stochastic Distinguishing Experiment (SDE). SDEs are ….
Dmitry Filin and Aleksandr I. Panov. Applying a neural network architecture with spatio-temporal connections to the maze exploration.
We present a model of Reinforcement Learning, which consists of modified neural-network architecture with spatio-temporal connections, known as Temporal Hebbian Self-Organizing Map (THSOM). A number of experiments were conducted to test the model on the maze solving problem. The algorithm demonstrates sustainable learning, building a near to optimal routes. This work describes an agents behavior in the mazes of different complexity and also influence of models parameters at the length of formed paths..
Nikolay Bazenkov, Dmitry Vorontsov, Varvara Dyakonova, Liudmila Zhilyakova, Oleg Kuznetsov and Dmitri Sakharov. Discrete Modeling of Multi-Transmitter Neural Networks with Neuron Competition.
We propose a novel discrete model of central pattern generators (CPG), neuronal ensembles generating rhythmic activity. The model emphasizes the role of nonsynaptic interactions and the diversity of neuronal phenotypes in nervous systems. Neurons in the model release different neurotransmitters into the shared extracellular space (ECS) so each neuron with the appropriate set of receptors can receive signals from other neurons. We consider neurons of different membrane phenotypes represented as finite-state machines functioning in discrete time steps. Discrete modeling is aimed to provide a ….
Arthur Chubarov and Daniil Azarnov. Modeling Behavior of Virtual Actors: A Limited Turing Test for Social-Emotional Intelligence.
This work presents the design, implementation and study of (1) a videogame -like virtual environment simulator, enabling social interaction of avatars controlled by human participants and by virtual actors; (2) a set of virtual actors with varying forms and degree of social-emotional intelligence, based on the eBICA cognitive architecture; and (3) a limited Turing test for social-emotional intelligence, involving human participants and virtual actors. The virtual environment simulator allows for various forms of ….
Sergey Kosikov, Viacheslav Wolfengagen and Larisa Ismailova. The type system to provide compositional thinking about data flows in support tasks for the implementation of best available technologies.
The paper considers the approach to solving the problem of preventing the information system vulnerability that arises due to the insertion and / or performance of a semantically incorrect script (XSS-vulnerability). The solution of this task suggests modeling the information exchange between active objects (agents), including the information containing code fragments. Modeling is supposed to be carried out within the framework of the basic applicative computing system, in which the code fragments can be modeled by applicative objects. An important part of the task is to check the …