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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Multicast Traffic Throughput Maximization through Dynamic Modulation and Coding Scheme Assignment in Wireless Sensor Networks
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublikacjaThis paper presents the design, realization and measurements of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Risk Modelling with Bayesian Networks - Case Study: Construction of Tunnel under the Dead Vistula River in Gdansk
PublikacjaThe process of decision-making in public procurement of construction projects during the preparation and implementation phases ought to be supported by risk identification, assessment, and management. In risk assessment one has to take into account factors that lead to risk events (background info), as well as the information about the risk symptoms (monitoring info). Typically once the risks have been assessed a decision-maker...
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Fabrication of toughened plastic using styrene butadiene rubber-poly (methyl methacrylate) interpenetrating polymer networks
PublikacjaA standard set of interpenetrating polymeric networks (IPNs) has been contrived using an elastomerstyrene butadiene rubber and a thermoplastic poly (methyl methacrylate) through sequential polymerization protocol. This low-cost material can be hopefully engaged as a toughened plastic with cocontinuous morphology. Different morphological protocols including Raman imaging are effectively utilized to envisage the effect of blend ratio...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublikacjaFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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<title>Selection of GRNN network parameters for the needs of state vector estimation of maneuvering target in ARPA devices</title>
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Radioimmunotherapy Confers Long-Term Survival to Lymphoma Patients with Acceptable Toxicity: Registry Analysis by the International Radioimmunotherapy Network
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Using Statistical Methods to Estimate The Worst Case Response Time of Network Software Running on Indeterministic Hardware Platforms
PublikacjaIn this paper we investigate whether the statistical Worst Case Execution Time (WCET) estimation methods devised for embedded platforms can be successfully applied to find the Worst Case Response Time (WCRT) of a network application running on a complex hardware platform such as a contemporary commercial off-the-shelf (COTS) system. Establishing easy-to-use timing validation techniques is crucial for real-time applications and...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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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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Modeling of TEC Variations Based on Signals from Near Zenith GNSS Satellite Observed by Dense Regional Network
PublikacjaCurrently the substantial successes in high-resolution ionospheric mapping is declared in many publications. Nevertheless, up to now there are no examples of dynamic visualization of TEC disturbances on regional scale with as high resolution as tropospheric models. Over the years, ionosphere has been modeling basing on the simple assumption, that it is a thin layer, which surrounds the Earth at some arbitrary height. However, the...
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublikacjaAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublikacjaThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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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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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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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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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublikacjaThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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The possibility of estimating the height of the ionospheric inhomogeneities based on TEC variations maps obtained from dense GPS network
PublikacjaA state of the ionosphere can be effectively studied using electromagnetic signals received from global navigation satellite systems (GNSS). Utilization of the dual frequency observations allows estimating values of the total electron content (TEC). They can be used for a number of scientific studies such as detection and monitoring of traveling ionospheric disturbances or plasma bubbles. Moreover, maps of TEC variations allow...
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Contact force network evolution in active earth pressure state of granular materials: photo‑elastic tests and DEM
PublikacjaArtykuł omawia ewolucję sieci sił kontaktowych w materiałach granulowanych podczas quasi-statycznego stanu aktywnego. Doświadczenia foto sprężyste zostały wykonane dla kulek szklanych. Doświadczenia zostały symulowane stosując metodę elementów dyskretnych (DEM). Model DEM prawidłowo przewidział strukturę sił kontaktowych i ich wielkość, lokalizację odkształceń oraz obszary zmian fazowych.
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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A new fuzzy model of multi-criteria decision support based on Bayesian networks for the urban areas' decarbonization planning
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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A new approach to inter-layer sharing providing differentiated protection services in survivable IP-MPLS/WDM networks
PublikacjaArtykuł omawia zagadnienie ochrony transmisji o charakterze połączeniowym w sieciach wielowarstwowych IP-MPLS/WDM. W szczególności prezentuje nową metodę współdzielenia międzywarstwowego zasobów ścieżek zabezpieczających gwarantującą szybkie odtwarzanie uszkodzonych połączeń (nawet o 40% szybciej w porównaniu z powszechnie stosowaną metodą).
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Rearrangeable clos networks C(n,r_1,n^2-1,n,r_2) with certain restrictions for connections
PublikacjaW pracy została zaproponowana nowa metoda sprawdzania przestrajalności pól Closa dla połączeń jeden do wiele. W rozważaniach zakładamy grupowanie połączeń.In the article we will propose new method of checking rearrangeability of multicast Clos networks. In the literature there is no precise method for checking rearrangeability. We focused on three-stage Clos networks without any constraints about fan-out capability. We show the...
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ADAPTIVE PREDICTIONS OF THE EURO/ZŁOTY CURRENCY EXCHANGE RATE USING STATE SPACE WAVELET NETWORKS AND FORECAST COMBINATIONS
PublikacjaThe paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day- ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space...
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Service time distribution influence on end-to-end call setup delay calculation in networks with Session Initiation Protocol
PublikacjaThe most important GoS parameter for networks with SIP protocol is end-to-end call setup delay. So far there were no coherent models allowing calculation of these parameters for networks with SIP protocol. Few models were developed but they are insufficient. In the paper we propose model which allows end-to-end call setup delay calculation for networks with SIP protocol. The model is using chain of M/G/1/K models and is applicable...
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A robust optimization model for affine/quadratic flow thinning: A traffic protection mechanism for networks with variable link capacity
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublikacjaW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Frequency-Variant Double-Zero Single-Pole Reactive Coupling Networks for Coupled-Resonator Microwave Bandpass Filters
PublikacjaIn this work, a family of frequency-variant reactive coupling (FVRC) networks is introduced and discussed as new building blocks for the synthesis of coupled-resonator bandpass filters with real or complex transmission zeros (TZs). The FVRC is a type of nonideal frequency-dependent inverter that has nonzero elements on the diagonal of the impedance matrix, along with a nonlinear frequency-variation profile of its transimpedance...
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Practical Trial for Low-Energy Effective Jamming on Private Networks With 5G-NR and NB-IoT Radio Interfaces
PublikacjaFourth-generation (4G) mobile networks are successively replaced by fifth-generation (5G) ones, based on the new releases of the 3rd Generation Partnership Project (3GPP) standard. 5G generation is dedicated to civilian users and the conducted analytical work shows that it has numerous technological gaps that prevent its direct implementation in military communications systems. However, the recent armed world conflicts showed that...
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INTER-LAYER SHARING OF BACKUP PATH CAPACITIES PROVIDING FAST SERVICE RECOVERY IN IP-MPLS/WDM NETWORKS
PublikacjaIn this paper, we investigate the issue of providing the transmission continuity in IP-MPLS/WDM networks in the presence of failures of nodes/links. Special focus is put on assuring fast restoration of flows affected after a failure in a scenario assuming sharing the backup path capacities in order to decrease the overall bandwidth consumption. In particular, we propose a new approach to inter-layer sharing of link capacity reserved...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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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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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublikacjaTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
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Planowanie rozwoju sieci dystrybucji energii elektrycznej na obszarach miejskich = Planning of development of the urban electricity distribution network
PublikacjaReferat przedstawia opis rozwiązania problemu planowania rozwoju sieci dystrybucji energii elektrycznej na obszarach miejskich. Rozwiązanie uzyskuje się w drodze zaprogramowania rozwoju z wykorzystaniem algorytmu genetycznego. Uwzględniane są dane o zawodności istniejącej infrastruktury i jej ograniczenia przesyłowe. Podjęto również próbę odwzorowania możliwych do wyboru tras prowadzenia linii kablowych. Funkcja zdatności rozwiązania...
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Stromal-Epithelial Cross-Talk in the Intestinal Stem Cell Niche is Mediated by a Regulatory Network that Involves TGF-Beta and CTGF
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A diode rectifier with a Special Coupled Reactor and additional Active Power Filter in the Marine Local Power Network Supply Conditions
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