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USŁUGA RÓWNOWAŻENIA OBCIĄŻENIA W SYSTEMIE OPENSTACK
PublicationNiniejszy artykuł ma na celu pokazanie funkcjonowania równoważenia obciążenia dla serwisu Neutron odpowiedzialnego za tworzenie i obsługę usług sieciowych dla użytkowników OpenStack’a. Stanowi on podstawę do zapewnienia komunikacji wewnątrz systemowej, z systemem jak i z wewnętrznymi prywatnymi sieciami systemowymi. W artykule przedstawiono wyniki bazując na edycji Juno, którą zaimplementowano w celu przeprowadzenia badań i analizy...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublicationHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Collision‐Aware Routing Using Multi‐Objective Seagull Optimization Algorithm for WSN‐Based IoT
PublicationIn recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery. The routing protocols...
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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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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Assessing Tram Infrastructure Safety Using the Example of the City of Gdańsk
PublicationAnalysis of Gdańsk’s tram network statistics shows that incidents are quite frequent (about 650 within 5 years) and mostly involve collisions and crashes. As well as reducing the tram systems’ efficiency and reliability, incidents have a nega-tive effect on road safety. As Polish cities extend their tram networks, they must also ensure that their existing networks are safe. This is to be achieved by conducting safety assessments....
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5G/6G optical fronthaul modeling: cost and energy consumption assessment
PublicationIn fifth generation (5G) and the future beyond 5G (6G) radio access networks (RANs), the cost of fronthaul deployment is a main challenge for mobile network operators. Depending on different constraints, there are various solutions to deploy an efficient fronthaul. Fiber-optic-based fronthaul offers long-term support with regard to a rapid increase in capacity demands. When fiber connections, either point-to-point (P2P) or point-to-multipoint...
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The voltage on bus bars of the main switchboard of the ro-ro ship electrical power system during a layover at the port
Open Research DataThe dataset is part of the research results on the quality of supply voltage on bus bars of the main switchboard of the ship's electrical power system in different states of ship exploitation. The attached dataset contains the measurement results carried out onboard a ro-ro ship during a layover at the port.
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The voltage on bus bars of the main switchboard of the car carrier electrical power system at sea trials during a sea voyage
Open Research DataThe dataset is part of the research results on the quality of supply voltage on bus bars of the main switchboard of the ship's electrical power system in different states of ship exploitation. The attached dataset contains the measurement results conducted onboard the car carrier at sea trials. The data were recorded during a sea voyage, under normal...
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Olgun Aydin Dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...
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LLA : A New Anypath Routing Scheme Providing Long Path Lifetime in VANETs
PublicationVehicular ad-hoc networks (VANETs) are a promising solution to improve the road traffic safety, reduce the environmental pollution, or simply provide the on-board infotainment services. However, these actions are often not possible due to high mobility of vehicles causing frequent failures of VANET links. In this paper, we focus on anypath routing to improve the reliability of multihop VANET communications. In particular, the paper...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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New trends in development of micro heat exchangers for ORC's
PublicationIn the paper, new trends in development of micro heat exchangers for CHP are presented. Main attention is concentrated on the question, how channels size and thermal development lenght affect the heat transfer. New types of micro heat exchangers developed at the Institute of Fluid-Flow Machinery PAS and the methoda of their design are presented. The new experimental testing methods of the micro-channel heat exchangers, new algorithms...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Modification of Selected Propagation Models in Terms of Path Loss Estimation in Container Terminal
PublicationIt is particularly important to look for any propagation model that could be useful for designing mobile radio networks in container terminal environment. Selected propagation models have been investigated. Firstly - basing on measurements results - they have been evaluated in this scope and the analysis has shown, that the adjustment is needed. This modification improved significantly the accuracy of path loss modelling. For the...
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Efficiency comparison of selected endoscopic video analysis algorithms
PublicationIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Evolution of Animats Following a Moving Target in an Artificial Ecosystem
PublicationMany biological animals, even microscopically small, are able to track moving sources of food. In this paper, we investigate the emergence of such behavior in artificial animals (animats) in a 2-dimensional simulated liquid environment. These "predators" are controlled by evolving artificial gene regulatory networks encoded in linear genomes. The fate of the predators is determined only by their ability to gather food and reproduce—no...
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Next generation ITS implementation aspects in 5G wireless communication network
PublicationIn the paper the study of Intelligent Transportation systems implementation in the 5G wireless communication network is presented. Firstly, small-cell concept in Ultra Dense Heterogeneous network was analyzed. Secondly, the 5G network requirements were presented which are important from the point of view of transportation systems development. Next, the study on the 5G network architectures proposals dedicated to the ITS systems...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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The Performance of ASON/GMPLS Network with Hierarchical Control Plane Structure
PublicationThe paper regards the problem of ASON/GMPLS network performance with hierarchical control plane structure in condition of incomplete domain network information. The authors propose the hierarchical ASON/GMPLS control plane architecture, which fulfills the requirements of modern optical networks and allows to control the multidomain network with requirement quality of service. The authors examine the scalability and properties of...
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Paweł Burdziakowski dr inż.
PeoplePaweł Burdziakowski, PhD, is a professional in low-altitude aerial photogrammetry and remote sensing, marine and aerial navigation. He is also a licensed flight instructor and software developer. His main areas of interest are digital photogrammetry, navigation of unmanned platforms and unmanned systems, including aerial, surface, underwater. He conducts research in algorithms and methods to improve the quality of spatial measurements...
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Khadijeh Askaripour dr
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Alicja Lizut-Ambroziak inż.
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Efekty egoistycznych ataków na poziomie mac w sieciach ad hoc o topologii wieloskokowej
PublicationStacje sieci ad hoc mogą manipulować parametrami dostępu do medium transmisyjnego dla osiągnięcia nienależnie wysokiej jakości usług. Dla środowiska sieci ad hoc o topologii wieloskokowej rozważane są ataki na mechanizmy odłożenia transmisji i klasyfikacji ruchu, przeprowadzane zarówno w stosunku do przepływów źródłowych jak i tranzytowych. Wyniki pozwalają wstępnie ocenić efekty takich ataków oraz skuteczność mechanizmów obronnych.
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Sterowanie optyczną siecią wielodomenową z hierarchiczną strukturą płaszczyzn sterowania
PublicationW artykule przedstawiono problem sterowania wielodomenową siecią optyczną z hierarchiczną strukturą płaszczyzn sterowania. Autorzy proponują wykorzystanie koncepcji sieci ASON/GMPLS, która spełnia wymagania nowoczesnych sieci optycznych, a jednocześnie umożliwia sterowanie wielodomenową siecią z gwarancją jakości usług. W artykule zaproponowano algorytm sterowania z gwarancją jakości, którego efektywność zweryfikowano metodą symulacji...
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Influence of the jitter buffer on the quality of service VoIP.
PublicationVoIP (Voice over IP) is a modern service with enormous potential for yet further growth. It uses the already available and universally implemented IP transport platform. One significant problem, however, is ensuring the Quality of Service, abbreviated QoS. This paper addresses exactly that issue. In an extensive investigation the influence of jitter buffers on QoS is being examined in depth. Two implementations, namely a passive...
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Firing map of an almost periodic input function
PublicationIn mathematical biology and the theory of electric networks the firing map of an integrate-and-fire system is a notion of importance. In order to prove useful properties of this map authors of previous papers assumed that the stimulus function f of the system ẋ = f(t,x) is continuous and usually periodic in the time variable. In this work we show that the required properties of the firing map for the simplified model ẋ = f(t) still...
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All graphs with paired-domination number two less than their order
PublicationLet G=(V,E) be a graph with no isolated vertices. A set S⊆V is a paired-dominating set of G if every vertex not in S is adjacent with some vertex in S and the subgraph induced by S contains a perfect matching. The paired-domination number γp(G) of G is defined to be the minimum cardinality of a paired-dominating set of G. Let G be a graph of order n. In [Paired-domination in graphs, Networks 32 (1998), 199-206] Haynes and Slater...
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total number and biomass of bacteria in drinking water distribution systems.
PublicationIn the vast water supply network using traditional methods of treatment it is often impossible to maintain a constant and acceptable microbiological quality of water. In Poland the main reason of bacterial re-growth is presence of organic matter and nutrients in the circulating water and prolonged water retention in the network systems due to the decrease of water consumption, which has been observed for the last 20 years. In the...
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RNDM 2016 Workshop and 2nd Meeting of COST CA15127-RECODIS: Highlights from the Resilience Week in Halmstad, Sweden
PublicationLeading network resilience researchers took part in the Resilience Week on Sept. 12-15, 2016 at Halmstad University, SE by Prof. Magnus Jonsson from the Centre for Research on Embedded Systems (CERES), Halmstad University, SE, and Prof. Jacek Rak from Gdansk University of Technology, PL. It included two major events: - The 2nd Meeting of COST CA15127–RECODIS Action (Resilient Communication Services Protecting End-user Applications...
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Comparison of selected electroencephalographic signal classification methods
PublicationA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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Modelling the malware propagation in mobile computer devices
PublicationNowadays malware is a major threat to the security of cyber activities. The rapid develop- ment of the Internet and the progressive implementation of the Internet of Things (IoT) increase the security needs of networks. This research presents a theoretical model of malware propagation for mobile computer devices. It is based on the susceptible-exposed- infected-recovered-susceptible (SEIRS) epidemic model. The scheme is based on...
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SIMULATION MODEL OF ASON/GMPLS ARCHITECTURE
PublicationGrowing demands of information society concerned with sophisticated applications could be satisfied by ASON/GMPLS architecture comprehended as Automatically Switched Optical Network (ASON) with Generalized Multi-Protocol Label Switching (GMPLS). The ASON/GMPLS proposition represents the future direction of Next Generation Network (NGN) architecture. Therefore considerable work has to be done to examine this solution. In this aspect...
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Resilience of 5G Mobile Communication Systems to Massive Disruptions
PublicationThis chapter discusses vital techniques to enhance the resilience of 5G systems. It starts with dependability assessment of 5G networks. Next, it describes (a) the frequency fallback technique to improve availability and survivability of 5G services, (b) segment interleaving scheme to enhance communications resilience between base stations and the remaining part of the network and (c) multi-operator protection to address the resilience...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublicationIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublicationThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
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ANN for human pose estimation in low resolution depth images
PublicationThe paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed....
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Classifying Emotions in Film Music - A Deep Learning Approach
PublicationThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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The Use of Cluster Analysis to Evaluate the Impact of COVID-19 Pandemic on Daily Water Demand Patterns
PublicationProper determination of unitary water demand and diurnal distribution of water consumption (water consumption histogram) provides the basis for designing, dimensioning, and all analyses of water supply networks. It is important in the case of mathematical modelling of flows in the water supply network, particularly during the determination of nodal water demands in the context of Extended Period Simulation (EPS). Considering the...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Zastosowanie sieci neuronowych do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu
PublicationDetekcja impulsów w odebranym sygnale radiowym, zwłaszcza w obecności silnego szumu oraz trendu, jest trudnym zadaniem. Artykuł przedstawia propozycje rozwiązań wykorzystujących sieci neuronowe do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu. Na potrzeby realizacji tego zadania zaproponowano dwie architektury. W pracy przedstawiono wyniki badań wpływu kształtu impulsu, mocy zakłóceń szumowych oraz trendu...
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Analiza wpływu transmisji danych na jakość działania rozproszonych systemów sterowania
PublicationW artykule przedstawiono zagadnienia związane z transmisją danych w rozproszonych systemach sterowania. Opisano cechy charakterystyczne przemysłowych sieci i protokołów informatycznych. Utworzono model rozproszonego systemu sterowania poziomem cieczy w zbiorniku, w którym komunikacja oparta została na protokole Modbus RTU. Na podstawie zmian parametrów transmisji danych wykazano, że poprawna komunikacja pomiędzy elementami systemu...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wykorzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...