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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublicationImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wyko-rzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Analiza możliwości wzrostu udziału transportu zbiorowego w wojewódzkich przewozach pasażerskich na przykładzie województwa pomorskiego
PublicationPodział zadań przewozowych pomiędzy dostępne środki transportu jest jednym z kluczowych wyzwań przy opracowaniu Planów Transportowych w regionach. Stan aktualny i prognozy prowadzone na obszarze Unii Europejskiej wskazują, że w najbliższych latach dominującym środkiem transportu pasażerskiego będzie samochód osobowy z zarysowującą się tendencją wzrostową. Dlatego bardzo istotnym działaniem przy budowie zintegrowanego systemu transportu...
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Prognozowanie wpływu drgań komunikacyjnych na budynki mieszkalne za pomocą sztucznych sieci neuronowych i maszyn wektorów wspierających
PublicationDrgania komunikacyjne mogą stanowić duże obciążenie eksploatacyjne budynku, powodując zarysowania i spękania tynków, odpadanie wypraw, zarysowania konstrukcji, pękanie elementów konstrukcji lub nawet zawalenie się budynku. Pomiary drgań na rzeczywistych konstrukcjach są pracochłonne i kosztowne, a co ważne nie w każdym przypadku są one uzasadnione. Celem pracy jest analiza autorskiego algorytmu, dzięki któremu z dużym prawdopodobieństwem...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation
PublicationPrecipitation estimation models are typically sourced by rain gauges, weather radars and satellite observations. A relatively new technique of precipitation estimation relies on the network of Commercial Microwave Links (CMLs) employed for cellular communication networks: the rain-inducted attenuation in the links enables the precipitation estimation. In the paper, it is analysed to what extent the precipitation derived from CML...
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Experimental and theoretical investigation of conformational states and noncovalent interactions in crystalline sulfonamides with a methoxyphenyl moiety
PublicationFour sulfonamide derivatives with a methoxyphenyl moiety, namely N-{4-[(2-methoxyphenyl)sulfamoyl] phenyl}acetamide (1a), N-{4-[(3-methoxyphenyl)sulfamoyl]phenyl}acetamide (1b), 4-amino-N-(2- methoxyphenyl)benzenesulfonamide (2a) and 4-amino-N-(3-methoxyphenyl)benzenesulfonamide (2b), have been synthesized and characterized physiochemically by CHNS, MS, FT-IR, 1H NMR, 13C NMR, PXRD and TG methods. Crystal structures were determined...
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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublicationVast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...
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Personalized nutrition in ageing society: redox control of major-age related diseases through the NutRedOx Network (COST Action CA16112)
PublicationA healthy ageing process is important when it is considered that one-third of the population of Europe is already over 50 years old, although there are regional variations. This proportion is likely to increase in the future, and maintenance of vitality at an older age is not only an important measure of the quality of life but also key to participation and productivity. So, the binomial “nutrition and ageing” has different aspects...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Static Shunt PE Voltage-Quality Controllers
PublicationThis chapter focuses on power electronics (PE)-based solutions used in distribution networks for reduction of supply-voltage-quality deterioration, from long interruptions to the harmonics. Various PE devices and their combinations are addressed for particular or a range of voltage disturbances. A particular solution is applied taking into account demands for voltage quality and network configuration. In general, there are three...
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Feasibility Study of Three-Phase Modular Converter for Dual-Purpose Application in DC and AC Microgrids
PublicationThe modern concept of a universal converter is intended as a power converter (PC) suitable for application in both dc or ac grids using the same external connectors. This novel family was recently proposed to allow easier integration of renewable energy sources and energy storage systems (ESSs), interfacing with dc/ac grids and/or loads with a minimum redundancy of power switches and passive elements. This kind of solution and...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublicationWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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Impact of SDN Controller’s Performance on Quality of Service
PublicationSoftware Defined Networking is a paradigm in network architecture; that is quickly becoming commonplace in modern telecommunication systems. It facilitates network customization for the requirements of different applications and simplifies the implementation of new services. Since its proposal, a significant evolution in its functionality has occurred. However, this development brought along problems of efficiency and performance,...
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Novel Biomass-Based Polymers: Synthesis, Characterization, and Application
PublicationA wide range of polymers were prepared from biomass-derivatives, using different polymerization mechanisms. Well-defined, fully hydroxy-functional polyesters based on aliphatic diols were synthesized, using either conventional metal-based catalysts or the organic superbase 1,5,7-triazabicyclododecene (TBD). Unsaturated polyesters were also made, offering additional functionality to these biobased resins. Metal-catalyzed or enzymatic...
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IoT protocols, architectures, and applications
PublicationThe proliferation of embedded systems, wireless technologies, and Internet protocols have enabled the IoT to bridge the gap between the virtual and physical world enabling the monitoring and control of the environment by data processing systems. IoT refers to the inter-networking of everyday objects that are equipped with sensing, computation, and communication capabilities. These networks can collaboratively interact and perform...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Business continuity management framework for Industry 4.0 companies regarding dependability and security of the ICT and ICS/SCADA system
PublicationThis chapter addresses a business continuity management (BCM) framework for the Industry 4.0 companies including the organizational and technical solutions, regarding the dependability and security of the information and telecommunication technology (ICT), and the industrial control system (ICS) / supervisory control and data acquisition (SCADA) system. These technologies and systems play nowadays important roles in modern advanced...
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The Central European GNSS Research Network (CEGRN) dataset
PublicationThe Central European GNSS Research Network (CEGRN) collects GNSS data since 1994 from contributors which today include 42 Institutions in 33 Countries. CEGRN returns a dataset of coordinates and velocities computed according to international standards and the most recent processing procedures and recommendations. We provide a dataset of 1229 positions and velocities resulting from 3 or more repetitions of coordinate measurements...
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Artificial Intelligence Aided Architectural Design
PublicationTools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools...
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Electrical Stimulation Modulates High Gamma Activity and Human Memory Performance
PublicationDirect electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation...
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Technical State Assessment of Charge Exchange System of Self-Ignition Engine, Based On the Exhaust Gas Composition Testing
PublicationThis paper presents possible use of results of exhaust gas composition testing of self - ignition engine for technical state assessment of its charge exchange system under assumption that there is strong correlation between considered structure parameters and output signals in the form of concentration of toxic compounds (ZT) as well as unambiguous character of their changes. Concentration of the analyzed ZT may be hence considered...
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Bandwidth Dependence of the Propagation Channel in Circular Metallic BAN Environments
PublicationIn this paper, the bandwidth dependence of the propagation channel for Body Area Networks (BANs) in circular metallic environments is addressed and models are proposed to evaluate the appropriate short-term fading margins that should be considered as a function of the system bandwidth. The deployment of BANs in metallic indoor environments, such as ships, factories, warehouses and other similar environments, involves additional...
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Feasibility Study of Three-Phase Modular Converter for Dual-Purpose Application in DC and AC Microgrids
PublicationThe modern concept of a universal converter is intended as a power converter suitable for application in both dc or ac grids using the same external connectors. This novel family was recently proposed to allow an easier integration of renewable energy sources and energy storage systems, interfacing with dc/ac grids and/or loads with a minimum redundancy of power switches and passive elements. This kind of solution and applications...
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Akustyczna analiza natężenia ruchu drogowego dla systemów zarządzania ruchem
PublicationW pracy przybliżono wybrane zagadnienia z dziedziny zarządzania transportem drogowym w Polsce i na świecie. W tym kontekście pzredstawiono potrzeby rynkowe, wymagania jak i możliwości w zakresie pozyskiwania informacji o aktualnym stanie sieci drogowych. Zaproponowano akustyczną metodę nadzorowania ruchu drogowego i jej możliwości w kontekście systemów zarządzania ruchem. Przedstawiono schemat akwizycji sygnału wraz z danymi odniesienia....
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Pedofilia: istota, rodzaje, zapobieganie. Paedophilia: essence, types, prevention.
PublicationPrzedmiotowa monografia opisuje zagadnienie kryminalizacji czynu zabronionego, polegającego na seksualnym wykorzystywaniu nieletnich poniżej piętnastego roku życia – zarówno w aspekcie obecnie obowiązujących rozwiązań, jak i od strony historycznej. Niniejsze opracowanie zwraca uwagę na fakt, iż współczesna typizacja pedofilii w rodzimym porządku normatywnym bierze pod uwagę ujęcie cybernetyczne, gdzie nawiązanie kontaktu pomiędzy...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship
PublicationThe arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne 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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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublicationOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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What do hashtags afford in digital fashion communication? An exploratory study on Gucci-related hashtags on Twitter and Instagram.
PublicationBeing enmeshed in a digital environment, we daily produce internet-mediated texts – encompassing several different semiotic codes – accessible on a global scale. Posts on different networks usually contain hashtags, which can be understood as affordances or behavior opportunities. These affordances allow specific actions both from the part of the writer and the reader. They can also be “behavior triggers,” which invite certain...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublicationIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...
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Relay-aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT utilizing ESPAR Antennas
PublicationIndustrial 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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Study of the Performance of DSSS UAC System Depending on the System Bandwidth and the Spreading Sequence
PublicationA signal transmitted in an Underwater Acoustic Communication (UAC) system operating in a shallow-water channel suffers from strong time dispersion due to multipath propagation. This causes the Inter-Symbol Interference (ISI) observed in the received signal, which significantly limits the communication system’s reliability and transmission rate. In such propagation conditions, the Direct-Sequence Spread Spectrum (DSSS) method is...
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BPL-PLC Voice Communication System for the Oil and Mining Industry
PublicationApplication of a high-efficiency voice communication systems based on broadband over power line-power line communication (BPL-PLC) technology in medium voltage networks, including hazardous areas (like the oil and mining industry), as a redundant mean of wired communication (apart from traditional fiber optics and electrical wires) can be beneficial. Due to the possibility of utilizing existing electrical infrastructure, it can...
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Looking for the Optimal Location of an Eco-District within a Metropolitan Area: The Case of Tricity Metropolitan Area
PublicationCompact housing structures located in city centers are considered to be the most energy and environmentally eective, mainly due to the access to services, transport networks and municipal infrastructures. There is the question of why so many of the acknowledged ecological housing complexes are located on the outskirts of cities or suburbs. Numerous cities decide to introduce strategies either to densify city centers, hoping to...
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Pedestrian detection in low-resolution thermal images
PublicationOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...