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- Publikacje 1706 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: DEEP NEURAL NETWORKS
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublikacjaArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Experimental tests of reinforced concrete deep-beams
PublikacjaThe paper presents results of experimental research of the reinforced concrete deep beam with a spatial arrangement. Tested structural elements consist of the cantilever deep beam loaded on the height and transverse deep beam with hanging on it another one. The analysis includes crack morphology, effort of steel and load distribution. The article verified effectiveness of two different kind of reinforcement in both tested deep...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublikacjaThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Neural Modelling of Steam Turbine Control Stage
PublikacjaThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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EXPERIMENTAL AND THEORETICAL FLOW OF THE FORCES IN DEEP BEAMS WITH CANTILEVAR
PublikacjaThis article presents the results of experimental research carried out on deep beams with cantilever which was loaded throughout the depth. The main deep beam was directly simply supported on the one side. On the other side the deep beam was suspended in another deep member situated at right angles. All deep beams created a spatial arrangement. The paper is focused on the analysis of the cracks morphology and flow of the internal...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublikacjaIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Neural Development
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Neural Computation
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Grade of service determination methodology in IP networks with SIP protocol
PublikacjaAlthough Grade of Service is very important in VoIP providers evaluation, We wasn't able to find any paper regarding the topic of measuring GoS variables for IP networks utilizing SIP, which are defined like for PSTN/ISDN/GSM networks (post-selection delay, answering delay, release delay, or probability of end-to-end blocking). Due to the lack of research in this field, it was necessary to start from defining measures and cover...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublikacjaIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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A Closed Bipolar Electrochemical Cell for the Interrogation of BDD Single Particles: Electrochemical Advanced Oxidation
PublikacjaA closed bipolar electrochemical cell containing two conductive boron-doped diamond (BDD) particles of size 250 – 350 m, produced by high-pressure high-temperature (HPHT) synthesis, has been used to demonstrate the applicability of single BDD particles for electrochemical oxidative degradation of the dye, methylene blue (MB). The cell is fabricated using stereolithography 3D printing and the BDD particles are located at either...
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Adding Interpretability to Neural Knowledge DNA
PublikacjaThis paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublikacjaA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublikacjaOne 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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Resilient Routing in Communication Networks
PublikacjaThis important text/reference addresses the latest issues in end-to-end resilient routing in communication networks. The work highlights the main causes of failures of network nodes and links, and presents an overview of resilient routing mechanisms, covering issues related to the Future Internet (FI), wireless mesh networks (WMNs), and vehicular ad-hoc networks (VANETs). For each of these network architectures, a selection of...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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WIRELESS NETWORKS
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Towards a classification of networks with asymmetric inputs
PublikacjaCoupled cell systems associated with a coupled cell network are determined by (smooth) vector fields that are consistent with the network structure. Here, we follow the formalisms of Stewart et al (2003 SIAM J. Appl. Dyn. Syst. 2, 609–646), Golubitsky et al (2005 SIAM J. Appl. Dyn. Syst. 4, 78–100) and Field (2004 Dyn. Syst. 19, 217–243). It is known that two non-isomorphic n-cell coupled networks can determine the same sets of...
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The reliability of tree and star networks.
PublikacjaOne of the important parameters characterizing the quality of computer networks is the network's reliability with respect to failures of the communication links and nodes. This chapter investigated the reliability of tree and star networks. The tree and star topology is used in centralized computer networks. In centralized computer networks all communication must take place through some central computer. Following measures of network...
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Communication Networks in the Service of the Environmental Monitoring
PublikacjaIn the paper selected issues relating to communication networks in the services of the environmental monitoring (EM) have been described. It is divided into three main parts: introduction, wire and wireless networks. At the beginning of the basic definitions were explained. The wire part focuses on a plain old telephone service (POTS), an integrated services digital network (ISDN), a digital subscriber line (DSL) and a fiber-optic...
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Journal of Deep Space Exploration
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Deep Eutectic Solvents and Their Uses for Air Purification
PublikacjaChemical compounds released into the air by the activities of industrial plants and emitted from many other sources, including in households (paints, waxes, cosmetics, disinfectants, plastic (PVC) flooring), may affect the environment and human health. Thus, air purification is an important issue in the context of caring for the condition of the environment. Deep eutectic solvents (DESs) as liquids with environmentally friendly...
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Supramolecular deep eutectic solvents and their applications
PublikacjaIn recent years, the growing awareness of the harmfulness of chemicals to the environment has resulted in the development of green and sustainable technologies. The compromise between economy and environmental requirements is based on the development of new efficient and green solutions. Supramolecular deep eutectic solvents (SUPRADESs), a new deep eutectic solvent (DES) subclass characterized by inclusion properties, are a fresh...
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublikacjaExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublikacjaIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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Discussion:Horizontal stress increase induced by deep vibratory compaction
PublikacjaDeep compaction control of granular material using the results of field tests. The analysis include the CPTU and DMT tests terformed before and after compaction works.
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Adding Intelligence to Cars Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...
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Magnetic deep eutectic solvents – Fundamentals and applications
PublikacjaMagnetic deep eutectic solvents (MDES), a relatively new subclass of conventional deep eutectic solvents (DES) containing additional paramagnetic components in their structure. MDES exhibit a strong response toward external magnetic fields, thus they can improve many industrial and analytical applications. In addition, this new group of solvents present unique physicochemical properties that can be easily tuned by selecting the...
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Cost minimization in wireless networks with a bounded and unbounded number of interfaces
PublikacjaPraca dotyczy problemu minimalizacji energii poprzez selektywne odłączanie urządzeń komunikacyjnych w wielointerfejsowych sieciach bezprzewodowych w taki sposób, by zapewnić realizację wymaganego grafu połączeń. Sformułowano problem optymalizacyjny, podano wyniki dotyczące jego trudności i zaproponowano algorytmy optymalizacyjne. Rozważono zarówno wariant, w którym liczba interfejsów komunikacyjnych jest parametrem stałym (narzuconym...
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Deep compaction control of sandy soils
PublikacjaVibroflotation, vibratory compaction, micro-blasting or heavy tamping are typical improvement methods for the cohesionless deposits of high thickness. The complex mechanism of deep soil compaction is related to void ratio decrease with grain rearrangements, lateral stress increase, prestressing effect of certain number of load cycles, water pressure dissipation, aging and other effects. Calibration chamber based interpretation...
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Overview of Scalability and Reliability Problem in SDN Networks
PublikacjaIn the paper an overview of scalability and reliability in the SDN (Software Defined Networks) networks has been presented. Problems and limitations for guaranteeing scalability and reliability in SDN networks have been indicated. Known methods for assuring scalability and reliability in SDN networks have been described. Projects from research communities for resolving issues with scalability and reliability in SDN networks have...
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The reliability of tree and star networks
PublikacjaThis paper investigated the reliability of tree and star networks. Following measures of network reliability are assumed: the expected number of nodes, that can communicate with the central node; the expected number of node pairs, that are connected by a path through the central node; the expected number of node pairs communicating.
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublikacjaPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Application of deep eutectic solvents in bioanalysis
PublikacjaThe application of deep eutectic solvents (DESs) is sharply surging as a green alternative to conventional solvents due to their unique properties in terms of simplicity of preparation, designability and low cost. A great deal of attention has been paid to the application of these green solvents in analytical chemistry in recent years, and a lot of interesting work has been reported. This review summarizes the most relevant applications...
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Protection in elastic optical networks
PublikacjaIn this article, we analyze gains resulting from the use of EON architectures with special focus on transportation of cloud-ready and content-oriented traffic in the context of network resilience. EONs are a promising approach for future optical transport networks and, apart from improving the network spectral efficiency, bring such new capabilities as squeezed protection, which reduces resource requirements in failure scenarios....
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Adrian Bekasiewicz dr hab. inż.
OsobyAdrian Bekasiewicz received the MSc, PhD, and DSc degrees in electronic engineering from Gdansk University of Technology, Poland, in 2011, 2016, and 2020, respectively. In 2014, he joined Engineering Optimization & Modeling Center where he held a Research Associate and a Postdoctoral Fellow positions, respectively. Currently, he is an Associate Professor with Gdansk University of Technology, Poland. His research interests include...
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NATURAL DEEP EUTECTIC SOLVENTS IN EXTRACTION PROCESS
PublikacjaDeveloping new, eco-friendly solvents which would meet technological and economic demands is perhaps the most popular aspects of Green Chemistry. Natural deep eutectic solvents (NADES) fully meet green chemistry principles. These solvents offer many advantages including biodegradability, low toxicity, sustainability, low costs and simple preparation. This paper provides an overview of knowledge regarding NADES with special emphasis...
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THE UNSUSTAINABILITY OF PUBLIC-SECTOR ORGANIZATIONAL NETWORKS: A CASE STUDY OF VOLUNTARY COURT NETWORKS
PublikacjaPurpose: The purpose of this study is to identify the problem of sustainability of public-sector 12 organizational networks on the example of common courts and what it implies for further 13 research. Methodology: The study used qualitative research tools in the form of structured 14 interviews. Interviews were conducted with 36 presidents and directors of common courts. 15 After conducting and transcribing each interview, their...
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Antifungal activity of propolis extracts produced with deep eutectic solvents.
Dane BadawczeThis dataset contains results of our investigation aiming in determination of antimicrobial potential of the propolis extracts produced with deep eutectic solvents. The activity was determined against C. albicans and C. glabarat strains. On the basis of these results MIC values can be calculated. Three samples of propolis were tested.
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Exploiting Multi-Interface Networks: Connectivity and Cheapest Paths
PublikacjaRozważano zagadnienie minimalizacji energii w sieciach bezprzewodowych bez infrastruktury, w których niektóre węzły są wyposażone w więcej, niż jeden interfejs. W przyjętym modelu sieci podano nowe algorytmy przybliżone oraz wyniki dotyczące złożoności obliczeniowej dla dwóch problemów: aktywacji najtańszej spójnej podsieci spinającej oraz aktywacji ścieżki pomiędzy ustaloną parą węzłów.
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An efficient approach to optimization of semi‐stable routing in multicommodity flow networks
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The influence of reinforcement on load carrying capacity and cracking of the reinforced concrete deep beam joint
PublikacjaThe paper presents the results of experimental research of the spatial reinforced concrete deep beam systems orthogonally reinforced and with additional inclined bars. Joint of the deep beams in this research was composed of the longitudinal deep beam with a cantilever suspended at the transversal deep beam. The cantilever deep beam was loaded throughout the depth and the transversal deep beam was loaded at the mid-span by longitudinal...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublikacjaIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Karol Flisikowski dr inż.
OsobyKarol Flisikowski jest profesorem uczelni w Katedrze Statystyki i Ekonometrii, Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Jest odpowiedzialny jest za prowadzenie zajęć ze statystyki opisowej i matematycznej (w języku polskim i angielskim), a także badań naukowych w zakresie statystyki społecznej. Był uczestnikiem wielu konferencji o zasięgu krajowym, jak i międzynarodowym, gdzie prezentował wyniki prowadzonych przez...
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Rearrangeability in multicast Clos networks is NP-complete
PublikacjaPrzestrajalność w polach Closa z połączeniami jeden do jeden jest problemem wielomianowym. W pracy pokazano, że w polach z połączeniami jeden do wiele problem ten jest NP zupełny.Three-stage elos networks are commutation networks with circuit switching. So far, graph theory has been very useful tool for solving issues related to these networks with unicast connections. This is so because if elos network is represented as a bipartite...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Controlling computer by lip gestures employing neural network
PublikacjaResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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Cooperative Data Transmission in Wireless Vehicular Networks
PublikacjaThe paper presents issues related to the cooperative transmission in wireless vehicular networks. Cooperative transmission involves the use of mobile terminals as relay stations to improve the transmission quality, improve network performance and reduce energy consumption. The paper presents the methods used to implement cooperative transmission and the types of cooperative networks.
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IET Networks
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SOCIAL NETWORKS
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant 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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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublikacjaIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Optimization of Wireless Networks for Resilience to Adverse Weather Conditions
PublikacjaIn this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...
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Topology recognition and leader election in colored networks
PublikacjaTopology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublikacjaDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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CRVG - a new model for wireless networks topology generation
PublikacjaThis paper presents a new model of wireless network topology generator. Its main advantage is the possibility of relatively sparse networks generation. Because no iteration is needed, the model can be used for massive generation of networks for testing. The topological properties of produced graphs place them in the class of scale free networks, resembling real ones.
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Hydrophobic deep eutectic solvents in microextraction techniques–A review
PublikacjaOver the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...
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Hydrogen bonding part sigma profile of deep eutectic solvents and pure components
Dane BadawczeThe set includes raw data of hydrogen bonding part sigma profiles of deep eutectic solvents and pure components generated by the ADF COSMO-RS software (SCM, Netherlands).
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The networking of the justice system as part of public court networks
PublikacjaThe goal of this paper is to look at the organizational structure of the justice system and provide the answer to the basic question of the possible network relations, their force, and imapct. As part od the paper, I have defined public inetrorganisational court network, dividing them into regulatory inter-organisational networks nad voluntary inetrorganisational networks. Emphasis has also been placed on the benefits and threats...
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Frontiers in Neural Circuits
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NEURAL COMPUTING & APPLICATIONS
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Neural Regeneration Research
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Neural Network World
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NEUROREHABILITATION AND NEURAL REPAIR
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NEURAL PROCESSING LETTERS
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Statistical significance of displacements in heterogeneous control networks
PublikacjaThis paper proposes a modification of the classical process for evaluating the statistical significance of displacements in the case of heterogeneous (e.g. linear-angular) control networks established to deformation measurements and analysis. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal control...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for nitrogen dioxide sensing
Dane BadawczeNetworks consisting of randomly oriented carbon nanotubes (CNN) were investigated toward nitrogen dioxide detection by means of electrical and low-frequency noise measurements. UV-activation of CNN layers improved gas sensitivity and reduced the limit of detection, especially by employing 275 nm-LED. This data set includes DC resistance measurements...
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Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes
PublikacjaIn recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublikacjaIn 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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A Bayesian regularization-backpropagation neural network model for peeling computations
PublikacjaA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Hybrid DUMBRA: an efficient QoS routing algorithm for networks with DiffServ architecture
PublikacjaDynamic routing is very important issue of current packet networks. It may support the QoS and help utilize available network resources. Unfortunately current routing mechanisms are not sufficient to fully support QoS. Although many research has been done in this area no generic QoS routing algorithm has been proposed that could be used across all network structures. Existing QoS routing algorithms are either dedicated to limited...
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Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublikacjaNowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...
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Trust Management Method for Wireless Sensor Networks
PublikacjaA Wireless Sensor Network (WSN) is a network of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data to the main location. The first wireless network that bore any real resemblance to a modern WSN is the Sound Surveillance System (SOSUS), developed by the United States Military in the 1950s to detect and track Soviet...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Application of wavelength division multiplexing in sensor networks
PublikacjaOver the past few years the need to acquire data on various parameters from a number of sensors grew. The need that led to the development of a network of sensors which enables simultaneous control and measurement in a wide range of applications. The aim of this article is to discuss a possibility of connecting a variety of sensors in a network that would utilize WDM technology. Wavelength Division Multiplexing is commonly used...
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Split-beam echosounder data from Gdansk Deep Summer 2019
Dane BadawczeThe acoustic data was collected in 2019, in the Gdansk Deep, in the season: Summer. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected while the ship was sailing. To ensure data quality, echosounders were calibrated and passive...
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublikacjaThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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Traffic Remapping Attacks in Ad Hoc Networks
PublikacjaAd hoc networks rely on the mutual cooperation of stations. As such, they are susceptible to selfish attacks that abuse network mechanisms. Class-based QoS provisioning mechanisms, such as the EDCA function of IEEE 802.11, are particularly prone to traffic remapping attacks, which may bring an attacker better QoS without exposing it to easy detection. Such attacks have been studied in wireless LANs, whereas their impact in multihop...
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Intelligent turbogenerator controller based on artifical neural network
PublikacjaThe paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...
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Application of deep eutectic solvents (DES) in analytical chemistry
PublikacjaRecent years have been associated with efforts to reduce the impact on the natural environment. A greener approach has been introduced in various areas of science, including analytical chemistry. One of the basic procedures for preparing a sample for analysis is its extraction. Traditional methods involve the use of large amounts of organic compounds, often toxic, with an unfavorable impact on the environment. A representative...
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Are deep eutectic solvents useful in chromatography? A short review
PublikacjaA literature update has been done concerning Deep Eutectic Solvents (DES) use in chromatography applications. The literature survey was based on the period from 2010 till 2020 and manuscripts reported in the data bases Web of Science and Scopus. The use of DES as mobile phase and mobile phase additives, stationary phases and solid phase modifiers and the use of DES as reaction solvents for chromatography use, were evaluated. Emphasis...
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The impact of institutions on innovation networks: empirical evidence from Poland
PublikacjaInnovation networks may accelerate and improve the innovation process, while institutional pathologies may hamper it. This study employs the Kruskal-Wallis H test and regression analysis to determine if the relationship between institutions and innovation networks does exist among the investigated variables. The purpose of the study was to find out whether cooperation with special local institutions influences the innovative behaviour...
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Jarosław Sadowski dr hab. inż.
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The role of water in deep eutectic solvent-base extraction
PublikacjaDeep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...
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Interdependence between Power Grids and Communication Networks: A Resilience Perspective
PublikacjaPower network resilience is increasingly dependent on communication networks. Besides traditional generation, power networks need to accommodate increasingly high penetration levels of dispersed micro generation, mostly based on renewable sources, and increasing and challenging demand, such as electric vehicles. At the same time the deployment of enabling technologies throughout the power grid makes available new demand resources...
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Remarks on use of the term “deep eutectic solvent” in analytical chemistry
PublikacjaAbout 20 years ago, Abbott and co-workers researched new solvents that were based on mixtures of choline chloride with urea and carboxylic acids and that were liquid at ambient temperature. The term “deep eutectic solvent” (DES) was later adopted for similar mixtures. As DESs have a number of interesting features, they quickly attracted the attention of researchers and found application in various branches of chemical and materials...
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Traffic Modeling in IMS-based NGN Networks
PublikacjaIn the modern world the need for accurate and quickly delivered information is becoming more and more essential. In order to fulfill these requirements, next generation telecommunication networks should be fast introduced and correctly dimensioned. For this reason proper traffic models must be identified, which is the subject of this paper. In the paper standardization of IMS (IP Multimedia Subsystem) concept and IMS-based NGN...
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Novel “acid tuned” deep eutectic solvents based on protonated L-proline
PublikacjaThe paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...
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Deep eutectic solvents vs ionic liquids: Similarities and differences
PublikacjaDeep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...
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A METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS
PublikacjaThe research problem considered in this paper is how to protect wireless sensor networks (WSN) against cyber-threats by applying trust management and how to strengthen network resilience to attacks targeting the trust management mechanism itself. A new method, called WSN Cooperative Trust Management Method (WCT2M), of distributed trust management in multi-layer wireless sensor networks is proposed and its performance is evaluated....
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Force transfer and stress distribution in short cantilever deep beams loaded throughout the depth with a various reinforcement
PublikacjaDeep beams used as the main reinforced concrete structural elements which taking over the load and stiffening construction are often found in high-rise buildings. The architecture of these buildings is sometimes sophisticated and varied, arouse the admiration of the majority of recipients, and thus causing an engineering challenge to correctly design the structural system and force transfer. In such structures is important to shape...
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Application of deep eutectic solvents in atomic absorption spectrometry
PublikacjaAtomic absorption spectrometry (AAS) is a widely applied technique for metal quantification due to its practicality, easy use and low cost. However, to improve the metrological characteristics of AAS, in particular the sensitivity and the detection limit, sample pretreatment is commonly used before the detection step itself. In consideration of the principles of Green Analytical Chemistry, new solvents are being introduced into...
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A Novel Multicast Architecture of Programmable Networks
PublikacjaIn the paper a multicast architecture for programmable networks based on separation of group management and network control tasks is proposed. Thanks to this separation, services which want to make use of multicast communications no longer have to implement low-level network functionalities and their operation is greatly simplified. Abstracting service’s view of the network into a fully connected cloud enables us to transparently...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Eventual Convergence of the Reputation-Based Algorithm in IoT Sensor Networks
PublikacjaUncertainty in dense heterogeneous IoT sensor networks can be decreased by applying reputation-inspired algorithms, such as the EWMA (Exponentially Weighted Moving Average) algorithm, which is widely used in social networks. Despite its popularity, the eventual convergence of this algorithm for the purpose of IoT networks has not been widely studied, and results of simulations are often taken in lieu of the more rigorous proof....