Search results for: CLASSIFICATION
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State of the art in the field of emission reduction of sulphur dioxide produced during coal combustion
PublicationThe need for clean coal technologies to reduce the adverse environmental impact of coal combustion products has been grounded. The article deals with information concerning present and future technologies, directed towards the struggle against air pollution by SO2, produced during coal combustion. Their classification and critical rating from economical and technological points of views (including those developed by authors) have...
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Spike patterns and chaos in a map-based neuron model
PublicationThe work studies the well-known map-based model of neuronal dynamics introduced in 2007 by Courbage, Nekorkin and Vdovin, important due to various medical applications. We also review and extend some of the existing results concerning β-transformations and (expanding) Lorenz mappings. Then we apply them for deducing important properties of spike-trains generated by the CNV model and explain their implications for neuron behaviour....
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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New polish catalogue of typical flexible and semi-rigid pavements
PublicationThe paper covers the following topics important for the development of the new Polish Catalogue of typical flexible and semi-rigid pavements: reasons for preparing the new issue of the Catalogue of typical flexible and semi-rigid pavements, items introduced in the new issue, organise the terminology related to pavements, design traffic calculations and new equivalent axle load factors,...
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Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions
PublicationIncreased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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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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Thermal Energy Storage with PCMs in Shell-and-Tube Units: A Review
PublicationThe paper presents a survey of the experimental and numerical studies of shell-and-tube systems in which phase change material (PCM) is used. Due to the multitude of design solutions for shell-and-tube systems, the emphasis is placed on double-tube (DT), triplex-tube (TT), and multitube (MT) units. Additionally, only single-pass systems are considered. Particular attention is paid to the method of heat transfer intensification....
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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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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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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Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublicationThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 20132014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification a protected Natura 2000 habitat (code 7230) using remote sensing technologies. High resolution airborne true colour (RGB) and...
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Tools for road infrastructure safety management in Poland
PublicationThe objective of road safety infrastructure management is to ensure that when roads are planned, designed, built and used road risks can be systematically identified, assessed, removed and mitigated. There are a number of approaches to road safety management. European Union Directive 2008/96/EC requires EU member states to use four basic tools of road safety infrastructure management. An overview of the methods in these countries...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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External Validation Measures for Nested Clustering of Text Documents
PublicationAbstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
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Modelling of Diffusing Capacity Measurement Results in Lung Microangiopathy Patients. A novel Diagnostic Suppport
PublicationLung microangiopathy is a little known negative influence of diabetes mellitus on the functioning of the lungs. The aim of this study is to design a supportive method for diagnosing lung microangiopathy. This will be based on routinely performed pulmonary measurements as well as on investigation process modelling and data processing. A model of the diffusion of oxygen from the alveoli to the blood has been described with a set...
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Recognizing emotions on the basis of keystroke dynamics
PublicationThe article describes a research on recognizing emotional states on the basis of keystroke dynamics. An overview of various studies and applications of emotion recognition based on data coming from keyboard is presented. Then, the idea of an experiment is presented, i.e. the way of collecting and labeling training data, extracting features and finally training classifiers. Different classification approaches are proposed to be...
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Vibroflotation Control of Sandy Soils using DMT and CPTU
PublicationVibroflotation is a typical improvement method for the cohesionless deposits of high thickness. The compaction method was applied to densify sandy deposits in Gdynia Port. Compaction control was verified with CPTU and DMT tests. Some examples of interpretation of soundings in pre-treated and compacted sands are shown. The classification diagrams are given for pre-treated and compacted sand. The stress history of the deposits is...
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An Analysis of the Relationship between the Architecture and the Structure of a Vessel on the Example of the Reconstruction Design Process of the Historical Sailing Yacht "General Zaruski" Carried Out between 2009 and 2012
PublicationThe article analyzes the relation between architecture and structure of a vessel on the example of the reconstruction design of a wooden sailing yacht "General Zaruski" built in Ekanӓs, Sweden in 1939. Based on the documentation of "Kaparen" (sister yacht), "Mloda Gwardia" (ex "General Zaruski") and the reconstruction classification project made by the authors, the impact of functional, spatial and aesthetic design objectives (e.g....
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Rynek inwestowania w sztukę jako przykład inwestycji alternatywnej
PublicationW opracowaniu przedstawiono klasyfikację inwestycji emocjonalnych jako jednej z kategorii inwestycji alternatywnych. Ocenie poddano wpływ inwestorów chińskich na kondycję rynku sztuki. Zbadano zmienność stopy zwrotu dla wybranych krajowych rynków sztuki. Obliczono podstawowe miary statystyczne dla analizowanych inwestycji alternatywnych. Wskazano na potencjalne możliwości obniżenia ryzyka portfela inwestycyjnego poprzez odpowiednią...
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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublicationDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Rheology of liquid crystalline polymers
PublicationLiquid crystallinity was invented in the 19th century. It was sometimes called the fourth state of matter because of the ability of macromolecules to generate liquid crystal phases. The main classification divided liquid crystalline polymers (LCPs) into lyotropic and thermotropic types. Interpretation of the rheological behavior of LCP is more complicated than for other polymers. Ordinary polymers are characterized by a normal...
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Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe paper describes an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an expert...
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Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe presentation is about an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT 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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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Tools for road infrastructure safety management – Polish experiences
PublicationThe objective of road safety infrastructure management is to ensure that when roads are planned, designed, built and used road risks can be systematically identified, assessed, removed and mitigated. There are a number of approaches to road safety management. European Union Directive 2008/96/EC requires EU member states to use four basic tools of road safety infrastructure management. An overview of the methods in these countries...
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Bringing Bathymetry LiDAR to Coastal Zone Assessment: A Case Study in the Southern Baltic
PublicationOne of the major tasks in environmental protection is monitoring the coast for negative impacts due to climate change and anthropopressure. Remote sensing techniques are often used in studies of impact assessment. Topographic and bathymetric procedures are treated as separate measurement methods, while methods that combine coastal zone analysis with underwater impacts are rarely used in geotechnical analyses. This study presents...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Multi-Stage Video Analysis Framework
PublicationThe chapter is organized as follows. Section 2 presents the general structure of the proposed framework and a method of data exchange between system elements. Section 3 is describing the low-level analysis modules for detection and tracking of moving objects. In Section 4 we present the object classification module. Sections 5 and 6 describe specialized modules for detection and recognition of faces and license plates, respectively....
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Efficiency comparison of selected endoscopic video analysis algorithms
PublicationIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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The structure of the control system for a dynamically positioned ship
PublicationThe article discusses functions and tasks of dynamic positioning (DP) systems for ships. The analysed issues include ship steering, in particular stabilisation of ship position and direction of motion (real course) at low manoeuvring speeds, and commonly used DP ship models. Requirements imposed by classification societies on DP ships are quoted. A multi-layer structure of the DP control system is presented, with special attention...
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ECG-based prediction of ventricular fibrillation by means of the PCA
PublicationA Sudden Cardiac Death (SCD) is a death resulting from cardiac failure with no significant symptoms earlier than one hour before occurrence. It is the cause of for approximately 400000 deaths per year in United States and millions of deaths worldwide. The proposed system, including two-stage algorithm and wearable diagnostic device allows for SCD risk estimation and continuous monitoring of high risk patients. A single channel...
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublicationThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Use of Sensory Analysis Methods to Evaluate the Odor of Food and Outside Air
PublicationSensory analysis is applied in many areas of daily life. It is used to carry out the sensory evaluation of foodstuffs or other products and to evaluate the properties of odors present in the environment. The authors attempt to summarize the knowledge on the classification and application of sensory analysis methods to evaluate the odor nuisance of air, which allows the identification of sensory impressions and determination of...
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Music Genre Recognition in the Rough Set-Based Environment
PublicationThe aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...
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Method of Decision-Making Logic Discovery in the Business Process Textual Data
PublicationGrowing amount of complexity and enterprise data creates a need for novel business process (BP) analysis methods to assess the process optimization opportunities. This paper proposes a method of BP analysis while extracting the knowledge about Decision-Making Logic (DML) in a form of taxonomy. In this taxonomy, researchers consider the routine, semi-cognitive and cognitive DML levels as functions of BP conceptual aspects of Resources,...
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Związki biologicznie aktywne w żywności i napojach
PublicationJuż od dłuższego czasu daje się zauważyć wzrost zainteresownia związkami biologicznie aktywnymi w żywności (szczególnie pochodzenia roślinnego) oraz napojach i sokach. W wielu ośrodkach naukowych trwają badania ukierunkowane na określenie aktywności przeciwutleniającej badanych próbek oraz oznaczenie zawartości polifenoli i innych związków o właściwościach przeciwutleniających (m.in. witaminy C oraz tokoferoli). W pracy przedstawiono...
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Generowanie modeli symulacyjnych na potrzeby systemu ekspertowego wspomagającego projektowanie układów automatyki statku
PublicationOmówiono automatyczne generowanie modeli symulacyjnych na potrzeby systemu ekspertowego wspomagającego projektowanie układów automatyki statków. Na podstawie przyjętych założeń projektowych system ekspertowy zleca badania wybranych struktur podsystemów elektroenergetycznych statków. Aplikacja symulacyjna pobiera z biblioteki modele matematyczne elementów składowych struktur, a następnie zestawia modele symulacyjne, wykonuje badania...