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Wyniki wyszukiwania dla: DEEP LEARNING , CONVOLUTIONAL NEURAL NETWORK , NEURAL ARCHITECTURE SEARCH , NETWORK MORPHISM , MALIGNANT MELANOMA
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Network-aware Data Prefetching Optimization of Computations in a Heterogeneous HPC Framework
PublikacjaRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Organization of BBMRI.pl: The Polish Biobanking Network
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Universal Augmentation Schemes for Network Navigability
PublikacjaRozważano problem uzupełniania grafu (reprezentującego np. sieci społeczne) poprzez dodanie w każdym węźle jednego dodatkowego skierowanego połączenia (długodystansowego). Dokładniej, dla każdego węzła definiuje się listę prawdopodobieństw istnienia połączenia wychodzącego z danego węzła do wszystkich pozostałych węzłów; wartości tych prawdopodobieństw muszą sumować się do jedności. Routing zachłanny w takiej sieci polega na przekazywaniu...
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Network analyses with the use of spatial databases
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Project Management Cycle in the Construction Industry Augmented by Collaborative Innovation Network Software
PublikacjaProject management is a very broad concept that has in recent times is growing rapidly. Management is especially complex in the construction sector, among the other sectors, due to the high uncertainty of workmanship and complexity of construction projects. Proper project management skills are an important factor in the success of projects, leading to reduced costs and shorten the time of investment. Nevertheless, most of the projects...
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Call processing performance in multidomain IMS/NGN architecture
PublikacjaThe Next Generation Network (NGN) architecture, which bases on the IP Multimedia Subsystem (IMS) concept, is a proposition of a telecommunication network dedicated to the needs of the modern information society. The main goal of NGN is to provide Quality of Service (QoS), for which proper network design and dimensioning are necessary. This also requires appropriate traffic models, which should be efficient and not excessively complicated...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublikacjaSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublikacjaThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Geospatial Coverage and Signal Quality Measurements of Terrestrial DAB+ Network in Northern Poland
PublikacjaModern signal coverage maps are prepared based on industry-standard radio propagation models, which take into account a number of parameters, including: type of antenna, distance from the transmitter, type of terrain, etc. However, such simulations are prone to location-specific inaccuracies, and should be verified with in-situ measurements. This paper presents results of a field test of a terrestrial DAB+ (Digital Audio Broadcasting...
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Qualitative Indicators Used to Select the Placement and Parameters of Energy Storage Installed in the Distribution Network
PublikacjaThe technology related to energy storage has developed in recent years. Continuous improvement of the solutions available on the market resulted in wider usability of energy storage. They are also increasingly used in a distribution network. This study contains a synthesised description of physical features of the energy storage used in distribution networks. Several criteria of algorithms used to determine the placement and...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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MODERNIST, 1920S AND 1930S INDUSTRIAL ARCHITECTURE OF THE PORT OF GDYNIA - IN SEARCH OF AN AESTHETIC LANGUAGE FOR UTILITARIAN BUILDINGS OF THE POLISH GATEWAY TO THE WORLD
PublikacjaThe purpose of the article is to present the results of the research on the aspects of the Port of Gdynia modernist architecture aesthetics. Its construction was one of the two major projects carried out in the interwar period in Poland. In the course of analyses it has been attempted to answer the question whether an individual aesthetic language has been created in the 1920s and 1930s for the industrial architecture of the Polish...
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Neural Manoeuvre Detection of the Tracked Target in ARPA Systems
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Adaptive neural voltage controller with tunable activation gain
PublikacjaW artykule przedstawiono model adaptacyjnego neuronowego regulatora napięcia dla turbogeneratora z nastrojonym współczynnikiem wzmocnienia funkcji przynależności. Ten model jest kombinacją klasycznego neuronowego modelu i neuronowego modelu z współczynnikiem wzmocnienia funkcji przynależności zależnym od warunków pracy obiektu.Przedstawiono, także wyniki symulacji mające na celu badania efektywności proponowanego regulatora dla...
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Artificial Neural Networks in Microwave Components and Circuits Modeling
PublikacjaArtykuł dotyczy wykorzystania sztucznych sieci neuronowych (SNN) w projektowaniu i optymalizacji układów mikrofalowych.Zaprezentowano podstawowe zasady i założenia modelowania z użyciem SNN. Możliwości opisywanej metody opisano wykorzystując przykładowyprojekt anteny łatowej. Przedstawiono różne strategie modelowania układów, które wykorzystują możliwości opisywanej metody w połączeniu zwiedzą mikrofalową. Porównano również dokładność...
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Neural networks in the diagnostics of induction motor rotor cages.
PublikacjaW środowisku Lab VIEW została stworzona aplikacja służąca do pomiaru, prezentacji i zapisu przebiegów widma prądu stojana z uwzględnieniem potrzeb pomiarowych występujących podczas badania wirników silników indukcyjnych przy użyciu sieci neuronowych. Utworzona na bazie zbioru uczącego sieć Kohonena z powodzeniem rozwiązała stawiany przed nią problem klasyfikacji widm prądu stojana, a co za tym idzie również diagnozy stanu...
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Applications of neural networks and perceptual masking to audio restoration
PublikacjaOmówiono zastosowania algorytmów uczących się w dziedzinie rekonstruowania nagrań fonicznych. Szczególną uwagę zwrócono na zastosowanie sztucznych sieci neuronowych do usuwania zakłócających impulsów. Ponadto opisano zastosowanie inteligentnego algorytmu decyzyjnego do sterowania maskowaniem perceptualnym w celu redukowania szumu.
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Application of neural networks for turbine rotor trajectory investigation.
PublikacjaW pracy przedstawiono rezultaty badań sieci neuronowych przewidujących trajektorię wirnika turbinowego uzyskanych ze stanowiska turbiny modelowej. Badania wykazały, iż sieci neuronowe wydają się być z powodzeniem zastosowane do przewidywania trajektorii ruchu wirnika turbiny. Najważniejszym zadaniem wydaje się poprawne określenie wektorów sygnałów wejściowych oraz wyjściowych jak również prawidłowe stworzenie sieci neuronowej....
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Problems in toxicity analysis - application of fuzzy neural networks
PublikacjaPraca dotyczy zastosowania sztucznych sieci neuronowych do przygotowywania danych do szacowania toksyczności (wody powierzchniowe). Przygotowanie to polega na sztucznym zagęszczaniu zbioru danych, które następnie mogą być wykorzystane do szacowania/modelowania wartości toksyczności na ich podstawie.
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QUASI-DISTRIBUTED NETWORK OF LOW-COHERENCE FIBER-OPTIC FABRY-PÉROT SENSORS WITH CAVITY LENGTH-BASED ADDRESSING
PublikacjaDistributed measurement often relies on sensor networks. In this paper, we present the construction of low coherent fiber-optic Fabry-Pérot sensors connected into a quasi-distributed network. We discuss the mechanism of spectrum modulation in this type of sensor and the constraints of assembly of such sensors in the network. Particular attention was paid to separate the signals from individual sensors, which can be achieved by...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive
PublikacjaWe argue that network methods are successful in detecting nonlinear properties in the dynamics of autonomic nocturnal regulation in short-term variability. Two modes of visualization of networks constructed from RR-increments are proposed. The first is based on the handling of a state space. The state space of RR-increments can be modified by a bin size used to code a signal and by the role of a given vertex as the representation...
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Modified Inductive Multi-Coil Wireless Power Transfer Approach Based On Z-Source Network
PublikacjaThis article presents a non-conventional approach to a multi-coil wireless power transfer system based on a Z-source network. The novelty of the approach lies in the use of a Z-source as a voltage source for energy transmission through the wireless power transfer coils. The main advantage is in a reduced number of semiconductors. This paper provides the design approach, simulation and experimental study. Feasibility and possible...
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Impact of R/X ratio of distribution network on selection and control of energy storage units
PublikacjaThe interest in energy storage is still increasing. Energy storage units are installed in high voltage networks, medium voltage networks and low voltage distribution networks as well. These units are often used to improve power quality. One of the criteria for improving power quality is reducing voltage deviations. Depending on the type of network and specifying its R/X ratio, this criterion can be fulfilled by control of active...
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Modeling a Traffic Remapping Attack Game in a Multi-hop Ad Hoc Network
PublikacjaIn multi-hop ad hoc networks, selfish nodes may unduly acquire high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets. Such traffic remapping attacks (TRAs) are cheap to launch, impossible to prevent, hard to detect, and harmful to non-selfish nodes. While studied mostly in single-hop wireless network settings, TRAs have resisted analysis in multi-hop settings. In this paper...
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Active Learning Based on Crowdsourced Data
PublikacjaThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Harmony Search for Data Mining with Big Data
PublikacjaIn this paper, some harmony search algorithms have been proposed for data mining with big data. Three areas of big data processing have been studied to apply new metaheuristics. The first problem is related to MapReduce architecture that can be supported by a team of harmony search agents in grid infrastructure. The second dilemma involves development of harmony search in preprocessing of data series before data mining. Moreover,...
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Architecture and Basic Assumptions of RSMAD
PublikacjaThe study presents the architecture of Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short RSMAD) which is used for transmission (realized using GSM, UMTS or TETRA networks, and through the Internet network), archiving and exploring image data of traffic offenses. The paper also presents selected basic assumptions of the RSMAD system, which are relevant to the implemented by the system...
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Bilateral power supply of the traction network as a first stage of Smart Grid technology implementation in electric traction
PublikacjaSince 2001, trolleybus system in Gdynia has been involved in many activities related to the reduction of power consumption, both in terms of implementation and research and development. In PKT, in cooperation with SESTO company, started applications of Smart Grid technologies in supply network: the bilateral supply. The paper presents results of this this novel investment.
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse
Publikacjahe development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm....
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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AGAR a Microbial Colony Dataset for Deep Learning Detection
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Photovoltaic bulk heterojunctions with interpenetrating network based on semiconducting polymers
PublikacjaPhotovoltaic cells are supposed to be the most common generators of useful electricity in the nearest future as they utilize inexhaustible carriers of renewable energy called photons. Despite the fact that 95% of worldwide applied photovoltaic devices are based on inorganic semiconductors the area of organic photovoltaics grows successively due to possibility of considerable reduction of manufacturing costs. Since the Heeger's...
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Context Search Algorithm for Lexical Knowledge Acquisition
PublikacjaA Context Search algorithm used for lexical knowledge acquisition is presented. Knowledge representation based on psycholinguistic theories of cognitive processes allows for implementation of a computational model of semantic memory in the form of semantic network. A knowledge acquisition using supervised dialog templates have been performed in a word game designed to guess the concept a human user is thinking about. The game,...
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Adaptive Algorithm for Interactive Question-based Search
PublikacjaPopular web search engines tend to improve the relevanceof their result pages, but the search is still keyword-oriented and far from "understanding" the queries' meaning. In the article we propose an interactive question-based search algorithm that might come up helpful for identifying users' intents. We describe the algorithm implemented in a form of a questions game. The stress is put mainly on the most critical aspect of this...
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Novel Adaptive Method for Data Streams Allocation Based on the Estimate of Radio Channel Parameters in Heterogeneous WBAN Network
PublikacjaThe new adaptive method for data streams allocation in heterogeneous Wireless Body Area Networks and meas-urement equipment is presented. The results obtained using the developed method compared with the selected algorithms likely to be used in those networks. The pro-posed adaptive data streams allocation method based on radio channel parameters makes it even twice as efficient to use in terms of resources usage in a WBAN heterogeneous...
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On-line Search in Two-Dimensional Environment
PublikacjaWe consider the following on-line pursuit-evasion problem. A team of mobile agents called searchers starts at an arbitrary node of an unknown network. Their goal is to execute a search strategy that guarantees capturing a fast and invisible intruder regardless of its movements using as few searchers as possible. As a way of modeling two-dimensional shapes, we restrict our attention to networks that are embedded into partial grids:...
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublikacjaLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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Network oscillations modulate interictal epileptiform spike rate during human memory
PublikacjaEleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in...
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Network heat is the comfort in winter and summer - TRIGENERATION
PublikacjaPrzedstawiono międzynarodowe uwarunkowania prawne oraz techniczne stosowania kogeneracji w aspekcie wykorzystania ciepła sieciowego na potrzeby ogrzewania i klimatyzacji obiektów.
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Intelligent thermal imaging camera with network interface
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Chromatographic Examinations in the Gas Network Odourised by Tetrahydrothiophene
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