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A novel genetic approach to provide differentiated levels of service resilience in IP-MPLS/WDM networks
PublikacjaThis paper introduces a novel class-based method of survivable routing for connection-oriented IP-MPLS/WDM networks, called MLS-GEN-H. The algorithm is designed to provide differentiated levels of service survivability in order to respond to varying requirements of end-users. It divides the complex problem of survivable routing in IP-MPLS/WDM networks into two subproblems, one for each network layer, which enables finding the...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Formation of Protein Networks between Mucins: Molecular Dynamics Study Based on the Interaction Energy of the System
PublikacjaMolecular dynamics simulations have been performed for a model aqueous solution of mucin. As mucin is a central part of lubricin, a key component of synovial fluid, we investigate its ability to form cross-linked networks. Such network formation could be of major importance for the viscoelastic properties of the soft-matter system and crucial for understanding the lubrication mechanism in articular cartilage. Thus,the inter- and...
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Optimum Choice of Randomly Oriented Carbon Nanotube Networks for UV-Assisted Gas Sensing Applications
PublikacjaWe investigated the noise and photoresponse characteristics of various optical transparencies of nanotube networks to identify an optimal randomly oriented network of carbon nanotube (CNT)-based devices for UV-assisted gas sensing applications. Our investigation reveals that all of the studied devices demonstrate negative photoconductivity upon exposure to UV light. Our studies confirm the effect of UV irradiation on the electrical...
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Efficient handover scheme for Mobile IPv4 over IEEE 802.11 networks with IEEE 802.21 triggers.
PublikacjaEfektywność przełączania jest bardzo istotnym parametrem, decydującym o pracy sieci bezprzewodowych, realizujacych usługi multimedialne na wysokim poziomie jakości. Użytkownicy takich sieci oczekują ciągłej obsługi podczas procesu przemieszczania się. Okazuje się, że istotnym źródlem opóźnień są nieefektywne procedury przełączania w warstwach drugiej i trzeciej, wynikający częściowo z postulatu o separacji funkcji realizowanych...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublikacjaThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublikacjaA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublikacjaThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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Application of Bayesian Networks in risk diagnostics arising from the degree of urban regeneration area degradation
PublikacjaUrban regeneration as a complex project, generates many extremely specific threats affecting the increase of investment risk. Its unique nature causes that probability parameter, normally applied in the process of risk quantification, is extremely difficult to estimate. Due to lack of historical data urban regeneration related activities are therefore associated with uncertainty. According to the authors, a useful tool for resolving...
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Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations
PublikacjaThe technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate...
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Nodal cooperation equilibrium analysis in multi-hop wireless ad hoc networks with a reputation system
PublikacjaMotivated by the concerns of cooperation security, this work examines selected principles of state-of-the-art reputation systems for multi-hop ad hoc networks and their impact upon optimal strategies for rational nodes. An analytic framework is proposed and used for identification of effective cooperation-enforcement schemes. It is pointed out that optimum rather than high reputation can be expected to be sought by rational nodes.
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublikacjaOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Multipath routing for quality of service differentiation and network capacity optimization in broadband low-earth orbit systems
PublikacjaThis paper shows the importance of employing multiple different paths for routing in Inter-Satellite Link (ISL) networks in broadband Low-Earth Orbit (LEO) satellite systems. A theoretical analysis is presented and a routing concept is proposed to demonstrate three facts that make multipath routing especially important in broadband LEO networks: (1) differences in the propagation delays have a much greater impact on end-to-end...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Modelling of a medium-term dynamics in a shallow tidal sea, based on combined physical and neural network methods
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Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis
PublikacjaEndometrial cancer (EC) is the second most common cancer in women. A large number of human cancers exhibit dysregulation of microRNA expression including EC. MiR-15b/16–2 is one of the best-known miRNA clusters that is expressed in many types of cancer tissues. Herein, we analyzed the expression of individual miR-15b/16–2 cluster members, its paralogues, and their target network analysis, as well as their prognostic significance...
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Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis
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<title>Recurrent neural network application to image filtering: 2-D Kalman filtering approach</title>
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Interdyscyplinary collaboration of Polish universities. The case of egocentric network analysis of the West Pomeranian University of Technology in Szczecin
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CLEPSYDRA Data Aggregation and Enrichment Framework: Design, Implementation and Deployment in the PIONIER Network Digital Libraries Federation
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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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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Method to solve the non-linear systems of equations for steady gradually varied flow in open channel network.
PublikacjaW artykule omówiono rozwiązanie systemu równań nieliniowych opisujacych przepływ ustalony wolnozmienny w sieci kanałów otwartych. Niewiadomymi są glębokości w poszczególnych przekrojach oraz natężenia przepływów w poszczególnych gałęziach systemu. Układ musi być rozwiązywany iteracyjnie. Klasyczne metody Picarda i Newtona mogą okazać się nieskuteczne ze względu na oscylacje rozwiązania w kolejnych iteracjach i związany z tym brak...
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The pollutant transport equation for a steady, gradually varied flow in an open channel network: a solution of high accuracy
PublikacjaW pracy przedstawiono metodę rozwiązania jednowymiarowego równania adwekcji-dyfuzji opisującego transport zanieczyszczeń w warunkach przepływu ustalonego wolnozmiennego w sieci kanałów otwartych. Zastosowano technikę dekompozycji. Zlineoryzowane równanie adwekcji-dyfuzji rozwiązano stosując całkę Duhamela, zaś równanie zacierające człon źródłowy-metodą różnic skończonych. Metoda zapewnia bardzo dużą dokładność rozwiązania nawet...
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Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublikacjaThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
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Safety assessment of ships in critical conditions using a knowledge-based system for design and neural network system
PublikacjaW pracy opisano wybrane elementy metody oceny bezpieczeństwa statków w stanie uszkodzonym, ukierunkowanej na ocenę osiągów statku i ocenę ryzyka. Metoda analizy osiągów i zachowania się statku w stanie uszkodzonym została wykorzystana do oceny charakterystyk hydromechanicznych statku uszkodzonego. Do oceny ryzyka wykorzystano elementy metodyki Formalnej Oceny Bezpieczeństwa. System ekspertowy został wykorzystany do analziy podziału...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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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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Relay-aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT utilizing ESPAR Antennas
PublikacjaIndustrial Internet of Things (IIoT) applicationsrequire reliable and efficient wireless communication. Assumingdense Wireless Sensor Networks (WSNs) operating in a harshenvironment, a concept of a Time Division Multiple Access(TDMA) based WSN enriched with Electronically SteerableParasitic Array Radiator (ESPAR) antennas is proposed andexamined in this work. The utilized...
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Cross-layer integration of network mechanisms for increasing efficiency of multimedia session support in IEEE 802.11s environment
PublikacjaWith an IEEE 802.11 wireless networks operating in Point-to-Multipoint mode being the most popular WLAN access technology employed today, it can be expected that a Wireless Mesh Network (WMN) based on the technology can provide significant advantages for such network systems. The IEEE 802.11s standard amendment provides the comprehensive set of mechanisms required to implement and deploy a WMN utilizing this widely popular technology....
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A reactive algorithm for deducing nodal forwarding behavior in a multihop ad-hoc wireless network in the presence of errors
PublikacjaA novel algorithm is presented to deduce individual nodal forwarding behavior from standard end-to-end acknowledgments. The algorithm is based on a well-established mathematical method and is robust to network related errors and nodal behavior changes. The proposed solution was verified in a network simulation, during which it achieved sound results in a challenging multihop ad-hoc network environment.
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublikacjaThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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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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Network design for surface water quality monitoring in a road construction project using Gamma Test theory
PublikacjaRoad construction has a negative environmental impact on the surrounding aquatic environment, requiring the continuous monitoring of surface water quality. Here, optimization of the water quality monitoring network (WQMN) is an essential step in supporting the sustainable development of road construction projects. This study introduces Gamma Test theory (GTT) as a practical method for optimizing the WQMN of surface waters during...
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A Method of Fast and Simultaneous Calibration of Many Mobile FMCW Radars Operating in a Network Anti-Drone System
PublikacjaA market for small drones is developing very fast. They are used for leisure activities and exploited in commercial applications. However, there is a growing concern for accidental or even criminal misuses of these platforms. Dangerous incidents with drones are appearing more often, and have caused many institutions to start thinking about anti-drone solutions. There are many cases when building stationary systems seems to be aimless...
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Biotrickling filtration of n-butanol vapors: process monitoring using electronic nose and artificial neural network
PublikacjaBiotrickling filtration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for biofiltration process monitoring in terms of reduction in n-butanol concentration and odour intensity of treated air. The study...
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Effect of User Mobility upon Trust Building among Autonomous Content Routers in an Information-Centric Network
PublikacjaThe capability of proactive in-network caching and sharing of content is one of the most important features of an informationcentric network (ICN). We describe an ICN model featuring autonomous agents controlling the content routers. Such agents are unlikely to share cached content with other agents without an incentive to do so. To stimulate cooperation between agents, we adopt a reputation and trust building scheme that is able...
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The mechanisms of technological innovation in SMEs: a Bayesian Network Analysis of EU regional policy impact on Polish firms.
PublikacjaWe study the underlying mechanisms of technological innovation in SMEs in the context of ex-post evaluation of European Union’s regional policy. Our aim is to explain the observed change in firms’ innovativeness after receiving EU support for technological investment. To do so, we take an approach that is novel in innovation studies: a Bayesian Network Analysis to assess the effectiveness of EU policy instrument for technological...
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Rapid Design Tuning of Miniaturized Rat-Race Couplers Using Regression-Based Equivalent Network Surrogates
PublikacjaA simple technique for fast design tuning of compact rat-race couplers is presented. Our approach involves equivalent circuit representation, corrected by nonlinear functions of frequency with coefficients extracted through nonlinear regression. At the same time, the tuning process connects two levels of coupler representation: EM simulation of the entire circuit and re-optimization of the coupler building blocks (slow-wave cells...
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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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Pedestrian protection, speed enforcement and road network structure the key action for implementing Poland's Vision Zero
PublikacjaSince 1991 Poland's road safety has been systematically improving with a 60% reduction in road deaths. Despite the progress Poland continues to be one of the European Union' worst performing countries. The country's main road safety problems remain unchanged: dangerous behaviour of road users, underdeveloped system of road safety management and low quality of road infrastructure. This is why subsequent road safety programmes (implemented...
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Synthesis and photoelectrochemical behaviour of hydrogenated titania nanotubes modified with conducting polymer infiltrated by redox active network
PublikacjaIn this work, we show preparation of ordered inorganic-organic composite electrode material where hydrogenated titania nanotubes H-TiO2 with tubularly developed surface modified with poly(3,4-ethylenedioxythiophene) matrix permeated by Prussian Blue (PB) inorganic redox network in order to reach highly photoactive heterojunction. The polymer deposition was realized via two subsequent processes covering: i) potentiostatic polymerization...
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublikacjaArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublikacjaThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...