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Search results for: INTEL
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Artificial Intelligence-Based Weighting Factor Autotuning for Model Predictive Control of Grid-Tied Packed U-Cell Inverter
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Signal Receiving and Processing Platform of the Experimental Passive Radar for Intelligent Surveillance System Using Software Defined Radio Approach
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Intelligent and active furcellaran-gelatin films containing green or pu-erh tea extracts: Characterization, antioxidant and antimicrobial potential
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Correction: Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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High-efficiency hybrid PV-TEG system with intelligent control to harvest maximum energy under various non-static operating conditions
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Development of a new generation of unmanned surface and underwater vehicles using the advanced technologies and achievements towards the application of control systems by the artificial intelligence AI.
PublicationThe operation of offshore structures at sea requires implementation of the advanced systems of permanent monitoring of work of such the installations. Novel solutions concerning such the systems should be associated with application of unmanned maritime surface and underwater platforms. The unmanned maritime platforms are and will be based on application of the newest achievements of some important technologies. Between these technologies...
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Archives of civil engineering. Intelligent graphic modeler integrating FE analisys of transient heat transfer with early computer-aided design of energy-efficient buildings
PublicationW pracy zaprezentowano nowatorski Modeler Rozmyty, w którym zaimplementowano unikalną koncepcję rozpoznawania. Modeler Rozmyty dokonuje ekstrakcji danych geometrycznych poprzez rozpoznanie i identyfikację niedokładnych i niejednorodnych rysunków, złożonych z prostych obiektów graficznych.
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Monitorowanie i mapowanie zanieczyszczenia powietrza atmosferycznego przez związki z grupy BTEX na obszarze aglomeracji Trójmiejskiej (próba zastosowania technik sztucznej inteligencji do prognozowania poziomów stężeń związków z grupy BTEX).
PublicationW efekcie przeprowadzonych badań potwierdzono przydatności techniki dozymetrii pasywnej wykorzystywanej na etapie izolacji i wzbogacania analitów do uzyskania długoterminowej (długofalowej) informacji o poziomie stężeń zanieczyszczeń z grupy BTEX w powietrzu atmosferycznym na terenie aglomeracji Trójmiejskiej.Stwierdzono iż stężenia monitorowanych związków uzyskane z wykorzystaniem techniki dozymetrii pasywnej na etapie pobierania...
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Sprawozdanie naukowe z badania nośności pala CFA Nr T13 mm metodą próbnego obciążenia statycznego z pomiarem rozkładu siły osiowej wzdłuż trzonu na terenie budowy Inteligentnego Centrum Logistycznego w Pustyni k. Dębicy
PublicationOpracowanie wyników badania nośności pala wierconego świdrem ciągłym CFA ∅630 mm, nr T13, wykonanego na terenie budowy Inteligentnego Centrum Logistycznego dla Nutrifarm Sp. z o.o., zlokalizowanego w miejscowości Pustynia k. Dębicy. Badanie pala wykonano metodą próbnego obciążenia statycznego z pomiarem rozkładu siły osiowej wzdłuż trzonu pala, zrealizowanym za pomocą ekstensometrów strunowych.
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PREDICTING CORPORATE BANKRUPTCIES IN POLAND AND LITHUANIA – COMPARATIVE ANALYSIS
PublicationThe research on predicting bankruptcies of enterprises constitutes one of the most important areas of financial management. In developed countries, the first publications on the subject appeared in the early 20th century. The situation is different in the countries of Eastern Europe, which introduced the market system already at the beginning of the 1990s, which resulted in first corporate bankruptcies. The article...
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CHALLENGES TO NATIONAL ECONOMIES OF SELECTED EU COUNTRIES IN THE CONTEXT OF DEMOGRAPHIC CHANGES IN SOCIETY
PublicationThe countries of Central and Eastern Europe, which acceded to the EU in 2004, are facing a great challenge related to transformations in the level and demographic structure of the population. The observed adverse demographic developments require taking decisive actions aimed at curbing the negative trend. The purpose of this paper is to present changes in the level and demographic structure of population and their impact on...
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Optimal detection observers based on eigenstructure assignment. W: FaultDiagnosis. Models, artificial intelligence, applications. Ed. J. Korbicz, J.M. Kościelny, Z. Kowalczuk, W. Cholewa. Berlin: Springer Verlag**2004 s. 219-259, 7 rys. bibliogr. 41 poz. Optymalne obseratory detekcyjne oparte na strukturze własnej.
PublicationPraca dotyczy analitycznych metod syntezy algorytmów detekcji uszkodzeń. De-finiując wektor resztowy jako ważony błąd uzyskanej oceny wyjścia danego o-biektu, poszukuje się takich obserwatorów stanu, dostarczających owych osza-cowań, dla których wektor resztowy jest w możlwie wysokim stopniu niezależnyod niemierzalnych zakłóceń oddziałujących na obiekt oraz od niemierzalnychszumów w torach pomiarowych. Rozważa się algorytmy...
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Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines: Complexity and Algorithms
PublicationIn this paper, the problem of scheduling on parallel machines with a presence of incompatibilities between jobs is considered. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. The paper provides several results concerning schedules, optimal or approximate with respect to the two most popular criteria of optimality:...
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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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How to deal with knowledge in small companies? Defining emergent KM approach
PublicationThis paper examines the concept of emergent KM approach in small companies. The origins of consideration are grounded in the theory of strategic management literature and in particular in the distinction between deliberate versus emergent approach towards strategic planning. Using the methodology of case study, we carried out an explorative research to analyse the characteristics of KM approach in two small companies located in...
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Towards trustworthy multi‐modal motion prediction: Holistic evaluation and interpretability of outputs
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An agent-based framework for distributed learning
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Deep learning approach for delamination identification using animation of Lamb waves
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublicationIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
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Interpretation and modeling of emotions in the management of autonomous robots using a control paradigm based on a scheduling variable
PublicationThe paper presents a technical introduction to psychological theories of emotions. It highlights a usable ideaimplemented in a number of recently developed computational systems of emotions, and the hypothesis thatemotion can play the role of a scheduling variable in controlling autonomous robots. In the main part ofthis study, we outline our own computational system of emotion – xEmotion – designed as a key structuralelement in...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Instance segmentation of stack composed of unknown objects
PublicationThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Feature-based generation of machining process plans for optimised parts manufacture
PublicationPrzedstawiono aktualne zagadnienia związane z integracją systemów CAD/CAM/CAPP. Opracowano model informacyjny danych dla systemu CAPP w postaci zapisu macierzowego. Zawarto algorytm tworzenia rozwiązań wariantowych i wyboru optymalnego procesu technologicznego obróbki. Proponowany algorytm działania zweryfikowano na rzeczywistym przykładzie z praktyki przemysłu.
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Fluent Editor and Controlled Natural Language in Ontology Development
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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A survey of neural networks usage for intrusion detection systems
PublicationIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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Awareness evaluation of patients in vegetative state employing eye-gaze tracking system
PublicationApplication of eye-gaze tracking system to awareness evaluation is demonstrated. Hitherto awareness evaluation methods are presented. The assumptions of proposed method based on analysis of visual activity of patients in vegetative state are demonstrated. The eye-gaze tracking system ''Cyber-Eye'' developed at the Multimedia Systems Department employed to conducted experiments is presented. Research described in the paper indicates...
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Parametrization and Correlation Analysis Applied to Music Mood Classification .
PublicationThe paper presents a study on music mood categorization. First, a review of music mood models is presented. Then, the preparation of a set of music excerpts to be used in the experiments and music parametrization is described. Next, some listening tasks performed to obtain mood descriptors are introduced. Finally,the correlation between mood descriptors and features extracted from parameters is discussed. The paper concludes with...
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Model of Rules for IT Organization Evolution
PublicationThe aim of this paper is to introduce the Model of Rules for IT Organization Evolution which shall be in compliance with the Generic IT Organization Evolution Model. Due to its general nature, a set of practical adjustments is proposed in order to adapt the Generic Model to the IT Service Management domain. Further, two sets of rules describing the evolution of the IT Service Management area are defined based on two types of rules...
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Implementation of Business Processes in Smart Cities Technology
PublicationThe goal of the paper is to present the results of studies concerning the development of a method of implementation of business processes in Smart Cities systems. The method has been developed during studies carried out within the building of a Smart Cities system for Gdańsk, and is based on basic development project management mechanisms (drawing from best practices, and in particular from the RUP methodology) and business-oriented...
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Ontology of the Design Pattern Language for Smart Cities Systems
PublicationThe paper presents the definition of the design pattern language of Smart Cities in the form of an ontology. Since the implementation of a Smart City system is difficult, expensive and closely linked with the problems concerning a given city, the knowledge acquired during a single implementation is extremely valuable. The language we defined supports the management of such knowledge as it allows for the expression of a solution...
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Model of an Integration Bus of Data and Ontologies of Smart Cities Processes
PublicationThis paper presents a model of an integration bus used in the design of Smart Cities system architectures. The model of such a bus becomes necessary when designing high-level architectures, within which the silo processes of the organization should be seen from the perspective of its ontology. For such a bus to be used by any city, a generic solution was proposed which can be implemented as a whole or in part depending on the requirements...
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Smart Cities System Design Method Based on Case Based Reasoning
PublicationThe objective of this paper is to present the results of research carried out to develop a design method for Smart Cities systems. The method is based on the analysis of design cases of Smart Cities systems in cities, the selection of the city appropriate to the requirements for implementation and application. The Case Based Reasoning method was used to develop the proposed design methodology, along with mechanisms of the conversion...
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High-Level Model for the Design of KPIs for Smart Cities Systems
PublicationThe main goal of the paper is to build a high-level model for the design of KPIs. Currently, the development and processes of cities have been checked by KPI indicators. The authors realized that there is a limited usability of KPIs for both the users and IT specialists who are preparing them. Another observation was that the process of the implementation of Smart Cities systems is very complicated. Due to this the concept of a...
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Designing Aggregate KPIs as a Method of Implementing Decision-Making Processes in the Management of Smart Cities
PublicationThe aim of the paper is to present a concept of measuring the performance of city management processes by use of a concept of aggregate KPIs. In the management of organizations and, as a consequence of the use of a common design framework also in the management of cities, silo KPIs are commonly used to show the statuses of the processes of organizations/cities. Thus the question arises as to what extent aggregate KPIs, as proposed...
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Learning from examples with data reduction and stacked generalization
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Data reduction and stacking for imbalanced data classification
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Issue of reliability–exploitation evaluation of electronic transport systems used in the railway environment with consideration of electromagnetic interference
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Gaze-tracking based audio-visual correlation analysis employing quality of experience methodology
PublicationThis paper investigates a new approach to audio-visual correlation assessment based on the gaze-tracking system developed at the Multimedia Systems Department (MSD) of Gdansk University of Technology (GUT). The gaze-tracking methodology, having roots in Human-Computer Interaction borrows the relevance feedback through gaze-tracking and applies it to the new area of interests, which is Quality of Experience. Results of subjective...
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Smart Pen - new multimodal computer control tool for graphomotorical therapy
PublicationW sytuacji, gdy około 15% populacji uczniów wykazuje cechy dyslektyczne, koniecznością staje się wyposażenie szkół w efektywne narzędzia do diagnozy i terapii tego rodzaju zaburzeń. Dzięki wykorzystaniu tabletu i specjalnie skonstruowanego długopisu wyposażonego w czujniki nacisku uzyskano możliwość monitorowania wielu parametrów, które do tej pory były dla terapeutów całkowicie niedostępne (np. pomiar nacisku na podłoże czy ścisku...