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Search results for: GRAPH NEURAL NETWORK
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublicationIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Software Agents for Computer Network Security
PublicationThe chapter presents applications of multi-agent technology for design and implementation of agent-based systems intended to cooperatively solve several critical tasks in the area of computer network security. These systems are Agent-based Generator of Computer Attacks (AGCA), Multi-agent Intrusion Detection and Protection System (MIDPS), Agent-based Environment for Simulation of DDoS Attacks and Defense (AESAD) and Mobile Agent...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Similarities and Differences Between the Vertex Cover Number and the Weakly Connected Domination Number of a Graph
PublicationA vertex cover of a graph G = (V, E) is a set X ⊂ V such that each edge of G is incident to at least one vertex of X. The ve cardinality of a vertex cover of G. A dominating set D ⊆ V is a weakly connected dominating set of G if the subgraph G[D]w = (N[D], Ew) weakly induced by D, is connected, where Ew is the set of all edges having at least one vertex in D. The weakly connected domination number γw(G) of G is the minimum cardinality...
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Direct electrical stimulation of the human brain has inverse effects on the theta and gamma neural activities
PublicationObjective: Our goal was to analyze the electrophysiological response to direct electrical stimulation (DES) systematically applied at a wide range of parameters and anatomical sites, with particular focus on neural activities associated with memory and cognition. Methods: We used a large set of intracranial EEG (iEEG) recordings with DES from 45 subjects with electrodes...
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Model of control plane of ASON/GMPLS network
PublicationASON (Automatic Switched Optical Network) is a concept of optical network recommended in G.8080/Y.1304 by ITU-T. Control Plane of this network could be based on GMPLS (Generalized Multi-Protocol Label Switching) protocols. This solution, an ASON control plane built on GMPLS protocols is named ASON/GMPLS. In the paper, we decompose the control plane problem and show the main concepts of ASON network. We propose a hierarchical architecture...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublicationIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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Simulator for Performance Evaluation of ASON/GMPLS Network
PublicationThe hierarchical control plane network architecture of Automatically Switched Optical Network with utilization of Generalized Multi-Protocol Label Switching protocols is compliant to next generation networks requirements and can supply connections with required quality of service, even with incomplete domain information. Considering connection control, connection management and network management, the controllers of this architecture...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublicationMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Epoxy/Ionic Liquid-Modified Mica Nanocomposites: Network Formation–Network Degradation Correlation
PublicationWe synthesized pristine mica (Mica) and N-octadecyl-N’-octadecyl imidazolium iodide (IM) modified mica (Mica-IM), characterized it, and applied it at 0.1–5.0 wt.% loading to prepare epoxy nanocomposites. Dynamic differential scanning calorimetry (DSC) was carried out for the analysis of the cure potential and kinetics of epoxy/Mica and epoxy/Mica-IM curing reaction with amine curing agents at low loading of 0.1 wt.% to avoid particle...
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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A better practical algorithm for distributed graph coloring
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Interval vertex-coloring of a graph with forbidden colors
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Interval Vertex-Coloring of a Graph With Forbidden Colors
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The smallest hard-to-color graph for algorithm DSATUR
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Interval edge coloring of a graph with forbidden colors
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The smallest hard-to-color graph for the SL algorithm
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Graph Approach to the Computation of the Homology of Continuous Maps
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Distributed largest-first algorithm for graph coloring.
PublicationW artykule zaprezentowano rozproszony, probabilistyczny algorytm kolorowania grafów. Kolorowanie uzyskane jest optymalne lub prawie optymalne dla takich klas grafów jak koła dwudzielne, gąsienice czy korony. Udowodniono, że algorytm ten działa w czasie O(D^2 log n) rund dla dowolnego grafu n wierzchołkowegoo stopniu maksymalnym D.
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An experimental study of distributed algorithms for graph coloring.
PublicationW pracy podano algorytm rozproszonego kolorowania grafówi porównano ze znanym wcześniej algorytmem.
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Packing three-vertex paths in a subcubic graph
PublicationW pracy rozważany jest problem pakowania scieżek P3 w grafach podkubicznych, pokazano oszacowania dolne na ilość ścieżek w zależności od stopnia spójności grafu oraz minimalnego stopnia.
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Graph decomposition for improving memoryless periodic exploration
PublicationW ostatnich latach często badanym problem jest eksploracja anonimowych grafów z lokalnymi etykietami portów przy każdym wierzchołku. Niedawno pokazano [Czyzowicz et al., Proc. SIROCCO'09], że dla każdego grafu istnieje poetykietowanie prowadzące do eksploracji przez automat bezpamięciowy z okresem co najwyżej 13n/3. W niniejszej pracy poprawiamy to ograniczenie do 4n-2, stosując całkowicie nową technikę dekompozycji grafu.
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Efficient parallel query processing by graph ranking
PublicationW artykule analizujemy przybliżony algorytm dla problemu szukania drzewa spinającego o minimalnym uporządkowanym indeksie chromatycznym, co znajduje zastosowanie w równoległym przetwarzaniu zapytań w relacyjnych bazach danych. Podajemy nowe oszacowanie uporządkowanego indeksu chromatycznego drzewa, które prowadzi do uzyskania lepszej funkcji dobroci wspomnianego algorytmu.
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublicationThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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Robustness in Compressed Neural Networks for Object Detection
PublicationModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
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Network effects—do they matter for digital technologies diffusion?
PublicationPurpose The main research target of this paper is to capture the network effects using the case of mobile cellular telephony, identified in European telecommunication markets, and its determinants enhancing the process of digital technologies diffusion. Design/methodology/approach This research relies on panel and dynamic panel regression analysis. The empirical sample covers 30 European countries, and the period for the analysis...
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DWDM Network Laboratory Solution for Telecommunication Education Engineering
PublicationDevelopment of network architectures in the field of optical telecommunications technologies is an indicator of changes in telecommunication education engineering. Conducting didactic classes requires hardware infrastructure and research in terms of teaching needs. In the paper we present DWDM network laboratory solution for telecommunication education engineering on the basis of the ADVA Optical Networking equipment. We have to...
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Information-driven network resilience: Research challenges and perspectives
PublicationInternet designed over 40 years ago was originally focused on host-to-host message delivery in a best-effort manner. However, introduction of new applications over the years have brought about new requirements related with throughput, scalability, mobility, security, connectivity, and availability among others. Additionally, convergence of telecommunications, media, and information technology was responsible for transformation...
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Outlier detection method by using deep neural networks
PublicationDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Transmission protocol simulation framework for the resource-constrained sensor network
PublicationIn this paper the simulation framework for simulation of the sensor network protocol is presented. The framework enables the simultaneous development of the sensor network software and the protocol for the wireless data transmission. The advantage of using the framework is the convergence of the simulation with the real software, because the same software is used in real sensor network nodes and in the simulation framework. The...
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Methods of Network Resource Provisioning for the Future Internet IIP Initiative
PublicationIn this paper, we present specification, design and implementation aspects of a network resource provisioning module introduced for the Polish Initiative of Future Internet called System IIP. In particular, we propose a set of novel LP optimization models of network resource provisioning designed to minimize the network resource consumption, either bandwidth or node’s computational power, as well as to maximize the residual capacity....
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Full Network Coverage Monitoring Solutions – The netBaltic System Case
PublicationThis paper defines the problem of monitoring a specific network, and more precisely – part of reporting process, which is responsible for the transport of data collected from network devices to station managers. The environment requires additional assumptions, as a specific network related to the netBaltic Project is to be monitored. Two new monitoring methods (EHBMPvU and EHBMPvF) are proposed, which priority is full network coverage....
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The secure transmission protocol of sensor Ad Hoc network
PublicationThe paper presents a secure protocol of radio Ad Hoc sensor network. This network operates based on TDMA multiple access method. Transmission rate on the radio channel is 57.6 kbps. The paper presents the construction of frames, types of packets and procedures for the authentication, assignment of time slots available to the node, releasing assigned slots and slots assignment conflict detection.
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Generalized access control in hierarchical computer network
PublicationThe paper presents the design of the security layer for a distributed system located in the multizone hierarchical computer network. Depending on the zone from which a client’s request comes to the system and the type of the request, it will be either authorized or rejected. There is one common layer for the access to all the business services and interactions between them. Unlike the commonly used RBAC model, this system enforces...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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CAUSALITY IN MODELS OF THERMAL PROCESSES IN SHIP ENGINE ROOMS WITH THE USE OF BOND GRAPH (BG) METHOD
PublicationWith a single approach to modeling elements of different physical nature, the method of Bond Graph (BG) is particularly well suited for modeling energy systems consisting of mechanical, thermal, electrical and hydraulic elements that operate in the power system engine room. The paper refers to the earlier presented new concept of thermal process modeling using the BG method. The authors own suggestions for determining causality...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Self-Organizing Wireless Nodes Monitoring Network
PublicationThe concept of data monitoring system and self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the wireless monitoring system for containers, and the second is the mobile monitoring system for gas air pollution measurements.
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublicationBearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect...
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Cognitive network model dedicated to transport system telematics
PublicationThe paper defines the concept of cognitive radio, in the context of transport systems, with particular emphasis on modern ecological concept of “green cognitive radio”. In addition, in the paper a modified cognitive network model dedicated to transport system telematics is proposed and presented. Algorithms to support the functioning of the cognitive radio are discussed. Sensors necessary to use the network to support cognitive...
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Accuracy Investigations of Turbine Blading Neural Models Applied to Thermal and Flow Diagnostics
PublicationPossibility of replacing computional fluid dynamics simulations by a neural model for fluid flow and thermal diagnostics of steam turbines is investigated. Results of calculations of velocity magnitude of steam for 3D model of the stator of steam turbine is presented.
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...