Search results for: NETWORK REPRESENTATION OF TIME SERIES
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Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0
PublicationABSTRACT Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel...
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Development of Intelligent Road Signs with V2X Interface for Adaptive Traffic Controlling
PublicationThe objective of this paper is to present a practical project of intelligent road signs, under which a series of new products for the regulation of traffic is being created. The engineering part of the project, described in this paper, was preceded by a series of experimental studies, the results of which were described in another paper accepted for publication at the MTS-ITS conference 2019, entitled "Comparative study on the effectiveness...
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A quasi-2D small-signal MOSFET model - main results
PublicationDynamic properties of the MOS transistor under small-signal excitation are determined by kinetic parameters of the carriers injected into the channel, i.e., the low-field mobility, velocity saturation, mobility at the quiescent-point (Q-point), longitudinal electric field in the channel, by dynamic properties of the channel, as well as by an electrical coupling between the perturbed carrier concentration in the channel and the...
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Time frequency representation of Doppler boold flow recordings
Open Research DataVital signals registration plays a grate role in biomedical engineering and education process. Well acquired data allow future engineers to observe certain physical phenomenons as well learn how to correctly process and interpret the data. This data set was designed for students to learn about Doppler phenomena and to demonstrate correctly and incorrectly...
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Distributed Representations Based on Geometric Algebra: the Continuous Model
PublicationAuthors revise the concept of a distributed representation of data as well as two previously developed models: Holographic Reduced Representation (HRR) and Binary Spatter Codes (BSC). A Geometric Analogue (GAc - ''c'' stands for continuous as opposed to its discrete version) of HRR is introduced - it employs role-filler binding based on geometric products. Atomic objects are real-valued vectors in n-dimensional Euclidean space...
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Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Road safety analysis in Poland using time-series modelling techniques
PublicationA number of international studies argue that there is a correlation between the number of traffic fatalities and the degree of public activity. The studies use the unemployment rate to support that argument. As unemployment grows miles travelled fall, a factor known to affect road safety. This relationship seems to be true for Poland, as well. The model presented in the paper is intended to prove it. It is a structural time-series local...
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THIRD-ORDER EXPONENTIAL INTEGRATOR FOR LINEAR KLEIN–GORDON EQUATIONS WITH TIME AND SPACE-DEPENDANT MASS
PublicationAllowing for space- and time-dependance of mass in Klein–Gordon equations re- solves the problem of negative probability density and of violation of Lorenz covariance of interaction in quantum mechanics. Moreover it extends their applicability to the domain of quantum cosmology, where the variation in mass may be accompanied by high oscillations....
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THIRD-ORDER EXPONENTIAL INTEGRATOR FOR LINEAR KLEIN–GORDON EQUATIONS WITH TIME AND SPACE-DEPENDANT MASS
PublicationAllowing for space- and time-dependance of mass in Klein–Gordon equations re- solves the problem of negative probability density and of violation of Lorenz covariance of interaction in quantum mechanics. Moreover it extends their applicability to the domain of quantum cosmology, where the variation in mass may be accompanied by high oscillations....
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Dispersive Delay Structures With Asymmetric Arbitrary Group-Delay Response Using Coupled-Resonator Networks With Frequency-Variant Couplings
PublicationThis article reports the design of coupled-resonatorbased microwave dispersive delay structures (DDSs) with arbitrary asymmetric-type group delay response. The design process exploits a coupling matrix representation of the DDS circuit as a network of resonators with frequency-variant couplings (FVCs). The group delay response is shaped using complex transmission zeros (TZs) created by dispersive cross-couplings. We also present an...
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Modelling Coarse Particulate Matter PM10 Concentration in the Tricity Area Using GIS
PublicationEnvironmental pollution is an issue of global concern, with Particulate Matter (PM) poisoning being a prime cause of lung cancer. This has led the European Commission to establish strict daily and annual PM concentration limits. The monitoring of air quality in major cities is the responsibility of European Member States. The Tricity, a 414.81 km 2 area in northern Poland, is monitored by a network of only 9 stations operated by...
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Viability of decisional DNA in robotics
PublicationThe Decisional DNA is an artificial intelligence system that uses prior experiences to shape future decisions. Decisional DNA is written in the Set Of Experience Knowledge Structure (SOEKS) and is capable of capturing and reusing a broad range of data. Decisional DNA has been implemented in several fields including Alzheimer’s diagnosis, geothermal energy and smart TV. Decisional DNA is well suited to use in robotics due to the...
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Improving Re-rankCCP with Rules Quality Measures
PublicationRecommender Systems are software tools and techniques which aim at suggesting new items that may possibly be of interest to a user. Context-Aware Recommender Systems exploit contextual information to provide more adequate recommendations. In this paper we described a modification of an existing contextual post-filtering algorithm which uses rules-like user representation called Contextual Conditional Preferences. We extended the...
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Metrisability of managing of stream-systemic processes
PublicationTo achieve the planned goal, in order to properly describe the manufacturing system management, six process stream functions were introduced. Non-dimensional flows of these functions in time can be empirically defined during the manufacturing process. They are interpreted as non-dimensional expenses. Maximum values for these functions in properly-managed processes equal one. Also, a global management function was introduced, being...
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Objective selection of minimum acceptable mesh refinement for EMC simulations
PublicationOptimization of computational electromagnetics (CEM) simulation models can be costly in both time and computing resources. Mesh refinement is a key parameter in determining the number of unknowns to be processed. In turn, this controls the time and memory required for a simulation. Hence, it is important to use only a mesh that is good enough for the objectives of the simulation, whether for direct handling of high-fidelity EM...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublicationVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublicationThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
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Rapid dimension scaling of compact microwave couplers with power split correction
PublicationIn this paper, a technique for rapid re-design ofcompact microwave couplers with respect to operating frequency is discussed. Our methodology involves an inverse surrogate model setup using several reference designs optimized (at the level of equivalent circuit representation of the coupler) for a set of operating frequencies within a range of interest. The surrogate establishes the relationship between the operating frequency...
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Time-series analysis of road safety trends aggregated at national level in Europe for 2000-2010
PublicationThe reader will find in this study road safety modelling theory and time-series analysis techniques, applications to long period data of injury accidents and casualities, aggregared at national level
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A LUMPED-CIRCUIT MODEL OF CIRCULAR PISTON TRANSDUCER FOR MODELING ITS PERFORMANCE IN DUAL FREQUENCY OPERATING MODES
PublicationThe paper presents novel network equivalent circuit of piezoceramic circular disc transducer that takes into account thickness and ra dial mode of vibrations. The starting point of the analysis is 4-port description of circular disc element representing the solution of wave equation set in radial and thickness directions. Th e approximate solution for harmonic case is represented in the form of 4x4 matrix, which is syn thesized...
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Secondary arc modelling for single pole reclosing analyses
PublicationThe paper discusses two evaluation methods of single pole auto-reclosing process effectiveness in HV transmission lines. Secondary arc current and recovery voltage calculation results obtained by load flow calculation are compared to the results obtained by the time domain simulations. Moreover, a nonlinear secondary arc model implementation is presented. The paper presents the study results for the three types of EHV transmission...
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Time series of Doppler blood flow recordings
Open Research DataVital signals registration plays a grate role in biomedical engineering and education process. Well acquired data allow future engineers to observe certain physical phenomenons as well learn how to correctly process and interpret the data. This data set was designed for students to learn about Doppler phenomena and to demonstrate correctly and incorrectly...
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Smart Decisional DNA Technology to Enhance Industry 4.0 Environment in Conjunction with Conventional Manufacturing
PublicationKnowledge-based support has become an indispensable part not only to the traditional manufacturing set-ups but also to the new fast-emerging Industry 4.0 scenario. In this regard, successful research has been performed and extensively reported to develop Decisional DNA based knowledge representation models of engineering object and engineering process called Virtual engineering object (VEO), Virtual engineering process (VEP) and...
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Affective computing and affective learning – methods, tools and prospects
PublicationEvery teacher knows that interest, active participation and motivation are important factors in the learning process. At the same time e-learning environments almost always address only the cognitive aspects of education. This paper provides a brief review of methods used for affect recognition, representation and processing as well as investigates how these methods may be used to address affective aspect of e-education. The paper...
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Time series - the tool for traffic safety analysis
PublicationGłównym celem artykułu jest przedstawienie sposobu modelowania i modeli stosowanych w analizach i prognozowaniu odnośnie zmian śmiertelności w wypadkach drogowych w Polsce. W tym celu zastosowano teorię modeli strukturalnych szeregów czasowych przy założeniu, że zarówno ruch drogowy, jak i bezpieczeństwo na drogach są procesami dynamicznymi, w których przeszłość ma znaczący wpływ na teraźniejszość i przyszłość systemu.
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Traffic fatalities modelling using time-series.
PublicationReferat zawiera opis jednaj z metod analizowania trendów bezpieczeństwa ruchu drogowego opartej na teorii szeregów czasowych. Przedstawiono w nim aplikację tej metody do badania związku pomiędzy liczbą śmiertelnych ofiar wypadków drogowych w Polsce w latach 1991-2003 a wielkością bezrobocia w tym czasie.
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Traffic risk modelling using time-series
PublicationW referacie przedstawiono metodę prognozowania ryzyka w ruchu drogowym powstałą na bazie analizy szeregów czasowych. W jej oparciu dla danych o liczbie śmiertelnych ofiar wypadków drogowych w Polsce w latach 1989-2000 zbudowano model i wykonano prognozę rozwoju trendu w przyszłości.
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Short-Period Information in GPS Time Series
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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Time Synchronization between the eNBs in E-UTRAN under the Asymmetric IP Network
PublicationIn this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The...
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Nonlinear secondary arc model use for evaluation of single pole auto-reclosing effectiveness
PublicationPurpose – The purpose of this paper is to discuss two evaluation methods of single pole autoreclosing process effectiveness in HV transmission lines. Secondary arc current and recovery voltage results obtained by load flow calculation are compared to the results obtained by the time domain simulations. Moreover, a nonlinear secondary arc implementation is presented. Design/methodology/approach – A computer simulation studies were...
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Source-related Wavefields in Fluids and Dielectrics: A new way of Thinking about Medium Dynamics
PublicationAcoustic and electromagnetic wave phenomena may seem to have a proper formal representation in field theory dating from the 19th century, founded on the mathematics of complex functions. This paper shows, however, that when replacing the classical spectrum-domain approach related to the assumption of harmonic timeform of signals, with a time-domain approach imposingnorestrictionastotheclassoftimeevolutionofsourceandfieldsignals,...
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Virtual Engineering Factory: Creating Experience Base for Industry 4.0
PublicationABSTRACT In recent times, traditional manufacturing is upgrading and adopting Industry 4.0, which supports computerization of manufacturing by round-the-clock connection and communica- tion of engineering objects. Consequently, Decisional DNA- based knowledge representation of manufacturing objects, processes, and system is achieved by virtual engineering objects (VEO), virtual engineering processes (VEP), and virtual engineering...
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Implementation of Addition and Subtraction Operations in Multiple Precision Arithmetic
PublicationIn this paper, we present a digital circuit of arithmetic unit implementing addition and subtraction operations in multiple-precision arithmetic (MPA). This adder-subtractor unit is a part of MPA coprocessor supporting and offloading the central processing unit (CPU) in computations requiring precision higher than 32/64 bits. Although addition and subtraction operations of two n-digit numbers require O(n) operations, the efficient...
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Noise Analysis of Continuous GPS Time Series of Selected EPN Stations to Investigate Variations in Stability of Monument Types
PublicationThe type of monument that a GPS antenna is placed on plays a significant role in noise estimation for each permanent GPS station. In this research 18 Polish permanent GPS stations that belong to the EPN (EUREF Permanent Network) were analyzed using Maximum Likelihood Estimation (MLE). The antennae of Polish EPN stations are placed on roofs of buildings or on concrete pillars. The analyzed data covers a period of 5 years from 2008...
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Road Safety Trends at National Level in Europe: A Review of Time-series Analysis Performed during the Period 2000–12
PublicationThis paper presents a review of time-series analysis of road safety trends, aggregatedat a national level, which has been performed in the period 2000 – 12 and applied to Europeannational data sets covering long time periods. It provides a guideline and set of best practices inthe area of time-series modelling and identifies the latest methods and applications of nationalroad safety trend analysis...
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Comparison of reproduction strategies in genetic algorithm approach to graph searching
Publicationgenetic algorithms (ga) are a well-known tool used to obtain approximate solutions to optimization problems. successful application of genetic algorithm in solving given problem is largely dependant on selecting appropriate genetic operators. selection, mutation and crossover techniques play a fundamental role in both time needed to obtain results and their accuracy. in this paper we focus on applying genetic algorithms in calculating...
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Semantic OLAP with FluentEditor and Ontorion Semantic Excel Toolchain
PublicationSemantic technologies appear as a step on the way to creating systems capable of representing the physical world as real time computational processes. In this context, the paper presents a toolchain for an ontology based knowledge management system. It consists of the ontology editor, FluentEditor and the distributed knowledge representation system, Ontorion. FluentEditor is a comprehensive tool for editing and manipulating complex...
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Decisional-DNA Based Smart Production Performance Analysis Model
Publicationn order to allocate resources effectively according to the production plan and to reduce disturbances, a framework for smart production performance analysis is proposed in this article. Decisional DNA based knowledge models of engineering objects, processes and factory are developed within the proposed framework. These models are the virtual representation of manufacturing resources, and with help of Internet of Things, are capable...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Entropy of Financial Time Series Due to the Shock of War
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Excited state properties of a series of molecular photocatalysts investigated by time dependent density functional theory.
PublicationTime dependent density functional theory calculations are applied on a series of molecular photocatalysts of the type [(tbbpy)2M1(tpphz)M2X2]2+ (M1 = Ru, Os; M2 = Pd, Pt; X = Cl, I) in order to provide information concerning the photochemistry occurring upon excitation of the compounds in the visible region. To this aim, the energies, oscillator strengths and orbital characters of the singlet and triplet excited states are investigated....
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Journal of Time Series Econometrics
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JOURNAL OF TIME SERIES ANALYSIS
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Special forms of echo visual representation in an ahead looking sonar.
PublicationThe paper discusses ways to organise visual representation in a multi-beam ahead looking sonars whose function is to detect objects on the bottom and in pelagic zones. Forms of visual representation are shown and illustrated on the basic screen (panoramic representation and setting, alarms) and on the auxiliary screen (type A, B and special). Special forms of visual representation are mainly used in detecting objects in difficult...
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Optimization of river network representation data models for web-based systems
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublicationThis 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...