Search results for: algorithms - Bridge of Knowledge

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Search results for: algorithms

Search results for: algorithms

  • From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition

    Publication

    Recently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...

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  • Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System

    Bluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in...

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  • Gesture-based computer control system applied to the interactive whiteboard

    In the paper the gesture-based computer control system coupled with the dedicated touchless interactive whiteboard is presented. The system engineered enables a user to control any top-most computer application by using one or both hands gestures. First, a review of gesture recognition applications with a focus on methods and algorithms applied is given. Hardware and software solution of the system consisting of a PC, camera, multimedia...

  • Gesture-based computer control system applied to the interactive whiteboard

    Publication

    - Year 2010

    In the paper the gesture-based computer control system coupled with the dedicated touchless interactive whiteboard is presented. The system engineered enables a user to control any top-most computer application by using one or both hands gestures. First, a review of gesture recognition applications with a focus on methods and algorithms applied is given. Hardware and software solution of the system consisting of a PC, camera, multimedia...

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  • SONIC - Self-optimizing narrowband interference canceler: comparison of two frequency tracking strategies

    Publication

    This paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time linear stable plant with unknown and possibly time-varying dynamics. It is assumed that both the instantaneous frequency of the sinusoidal disturbance and its amplitude may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. The proposed disturbance...

  • NVRAM as Main Storage of Parallel File System

    Modern cluster environments' main trouble used to be lack of computational power provided by CPUs and GPUs, but recently they suffer more and more from insufficient performance of input and output operations. Apart from better network infrastructure and more sophisticated processing algorithms, a lot of solutions base on emerging memory technologies. This paper presents evaluation of using non-volatile random-access memory as a...

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  • Performance improvement of NN based RTLS by customization of NN structure - heuristic approach

    Publication

    - Year 2015

    The purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...

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  • Autonomous Robot for Efficient Indoor RF Measurements

    Publication

    In this paper, we addresses the emergence of autonomous and semi-autonomous radio frequency (RF) measurements as a vital application for robots, particularly in indoor environments where traditional methods are labor-intensive and error-prone. We propose a method utilizing Autonomous Mobile Robots (AMRs) equipped with Light Detection and Ranging (LiDAR) and RGB-D cameras to conduct precise and repetitive RF signal measurements...

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  • Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data

    Publication

    - Year 2024

    This paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...

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  • A review of explainable fashion compatibility modeling methods

    Publication

    The paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’...

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  • Reconfigurable Antennas for Trustable Things

    Publication

    In modern applications, the Internet of Things plays a significant role in increasing the productivity, effectiveness or safety and security of people and assets. Additionally, the reliability of Internet of Things components is crucial from the application point of view, where a resilient and low-latency network is needed. This can be achieved by utilizing reconfigurable antennas to enhance the capabilities of the wireless sensor...

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  • Neural networks and deep learning

    Publication

    - Year 2022

    In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...

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  • Determination of API content in a pilot-scale blending by near-infrared spectroscopy as a first step method to process line implementation

    Near infrared (NIR) spectroscopy was used for estimation of powder blend homogeneity and manufacturing control of a medicinal product powder mixture containing active pharmaceutical ingredient (API). Aiming at initiating a Process Analytical Technology (PAT) activity, the first step was a stationary mode atline evaluation. In this, the content of pharmaceutical active compound in the powder mixtures intended to the direct tabletting...

  • Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing

    Publication

    Solution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...

  • Statistically efficient smoothing algorithm for time-varying frequency estimation

    The problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...

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  • Discovering patterns of Web Page Visits from Associaton Rules Viewpoint

    Publication

    The popularity of the Internet results from the almost unlimited resources of information stored in it. At the same time, Internet portals have become a widespread source of information and note very large number of visits. The list of web pages opened by users is stored in web servers' log files. Extraction of knowledge on the navigation paths of users has become carefully analyzed problem. Currently, there are a number of algorithms...

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  • Acoustic Processor of the Mine Countermeasure Sonar

    This paper presents the concept of an acoustic processor of the mine countermeasure sonar. Developed at the Department of Marine Electronics Systems, Gdansk University of Technology, the acoustic processor is an element of the MG-89, an underwater acoustic station. The focus of the article is on the modules of the processor. They are responsible for sampling analogue signals and implementing the algorithms controlling the measurement...

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  • Sparse autoregressive modeling

    Publication

    - Year 2012

    In the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation...

  • Detection and localization of selected acoustic events in acoustic field for smart surveillance applications

    A method for automatic determination of position of chosen sound events such as speech signals and impulse sounds in 3-dimensional space is presented. The evens are localized in the presence of sound reflections employing acoustic vector sensors. Human voice and impulsive sounds are detected using adaptive detectors based on modified peak-valley difference (PVD) parameter and sound pressure level. Localization based on signals...

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  • Decisional DNA and Optimization Problem

    Publication

    - Year 2013

    Many researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...

  • Audio-visual surveillance system for application in bank operating room

    An audio-visual surveillance system able to detect, classify and to localize acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic...

  • Examining Quality of Hand Segmentation Based on Gaussian Mixture Models

    Publication

    Results of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...

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  • Reconstruction Methods for 3D Underwater Objects Using Point Cloud Data

    Publication

    Existing methods for visualizing underwater objects in three dimensions are usually based on displaying the imaged objects either as unorganised point sets or in the form of edges connecting the points in a trivial way. To allow the researcher to recognise more details and characteristic features of an investigated object, the visualization quality may be improved by transforming the unordered point clouds into higher order structures....

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  • Comparison of various speech time-scale modificartion methods

    The objective of this work is to investigate the influence of the different time-scale modification (TSM) methods on the quality of the speech stretched up using the designed non-uniform real-time speech time-scale modification algorithm (NU-RTSM). The algorithm provides a combination of the typical TSM algorithm with the vowels, consonants, stutter, transients and silence detectors. Based on the information about the content and...

  • Automatic sound source localization in disturbing conditions using acoustic vector sensors

    A concept, practical realization and applications of a passive acoustic radar to automatic localization and tracking of sound sources in disturbing conditions were presented in the paper. The device consists of the new kind of multichannel miniature sound intensity sensors and a group of digital signal processing algorithms. The sensitivity of the realized acoustic radar was examined in free sound field. Several kinds of sound...

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  • Detection and localization of selected acoustic events in 3D acoustic field for smart surveillance applications

    A method for automatic determination of position of chosen sound events such as speech signals and impulse sounds in 3-dimensional space is presented. The events are localized in the presence of sound reflections employing acoustic vector sensors. Human voice and impulsive sounds are detected using adaptive detectors based on modified peak-valley difference (PVD) parameter and sound pressure level. Localization based on signals...

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  • Identification of models and signals robust to occasional outliers

    Publication

    In this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...

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  • Non-invasive blood glucose monitoring with Raman spectroscopy: prospects for device miniaturization

    Publication

    - Year 2015

    The number of patients with diabetes has reached over 350 million, and still continues to increase. The need for regular blood glucose monitoring sparks the interest in the development of modern detection technologies. One of those methods, which allows for noninvasive measurements, is Raman spectroscopy. The ability of infrared light to penetrate deep into tissues allows for obtaining measurements through the skin without its...

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  • Facial emotion recognition using depth data

    Publication

    - Year 2015

    In this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...

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  • Mobile navigation system for visually impaired users in the urban environment

    This paper describes the prototype version of a mobile application supporting independent movement of theblind. Its objective is to improve the quality of life of visually impaired people, providing them with navigationalassistance in urban areas. The authors present the most important modules of the application. The module forprecise positioning using DGPS data from the ASG-EUPOS network as well as enhancements of positioning...

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  • Processing of acoustical data in a multimodal bank operating room surveillance system

    An automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...

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  • Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2015

    In this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...

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  • PROPERTIES OF PARAMETRIC ALGORITHMIC DESIGN OF RESIDENTIAL HOUSES IN URBAN CONTEXT

    Publication

    - Year 2016

    Design explorations of architectural avant-garde resulted in the development of digital techniques that allow solving very complex and demanding contemporary design challenges. In the architectural discourse the new design workshop seems to be symbolized mainly by the projects of sports facilities, cultural, administrative or multifunctional high-rise buildings. However for the quality of society life is more important to exploit...

  • Identification of models and signals robust to occasional outliers

    Publication

    In this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...

  • Finite Element Method Applied in Electromagnetic NDTE: - A Review

    The paper contains an original comprehensive review of finite element analysis (FEA) applied by researchers to calibrate and improve existing and developing electromagnetic non-destructive testing and evaluation techniques, including but not limited to magnetic flux leakage (MFL), eddy current testing, electromagnetic-acoustic transducers (EMATs). Premium is put on the detection and modelling of magnetic field, as the vast majority...

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  • Low-Level Music Feature Vectors Embedded as Watermarks

    In this paper a method consisting in embedding low-level music feature vectors as watermarks into a musical signal is proposed. First, a review of some recent watermarking techniques and the main goals of development of digital watermarking research are provided. Then, a short overview of parameterization employed in the area of Music Information Retrieval is given. A methodology of non-blind watermarking applied to music-content...

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  • Selection Pressure in the Evolutionary Path Planning Problem

    This article compares an impact of using various post-selection methods on the selection pressure and the quality of the solution for the problem of planning the path for a moving object using the evolutionary method. The concept of selection pressure and different methods of post-selection are presented. Article analyses behaviour of post-selection for four options of evolutionary algorithms. Based on the results achieved, waveform...

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  • State of the art and prospects of methods for determination of lipophilicity of chemical compounds

    Lipophilicity of the compounds is useful to (i) explain their distribution in biological systems, which is different in plant and in animal organisms, (ii) predict the possible pathways of pollutant transport in the environment, and (iii) support drug discovery process and select optimal composition in terms of bioactivity and bioavailability. The lipophilic properties can be determined by two main approaches, experimental, which...

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  • Sensors and Sensor’s Fusion in Autonomous Vehicles

    Publication

    - SENSORS - Year 2021

    Autonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...

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  • OPTIMISING RIG DESIGN FOR SAILING YACHTS WITH EVOLUTIONARY MULTIOBJECTIVE ALGORITHM

    The paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used...

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  • Composition Patterns of Contemporary Polish Residential Building Facades

    This study aims to define the types of composition patterns of contemporary Polish multi-family building facades. The authors define the compositional patterns to determine their frequency. Analyses carried out on the basis of photos and visualizations of 113 examples of architecture from Poland identified groups of common features of facades. Statistical analyses of these features resulted in six types of compositions. Clear differences...

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  • On Accelerated Metaheuristic-Based Electromagnetic-Driven Design Optimization of Antenna Structures Using Response Features

    Development of present-day antenna systems is an intricate and multi-step process requiring, among others, meticulous tuning of designable (mainly geometry) parameters. Concerning the latter, the most reliable approach is rigorous numerical optimization, which tends to be re-source-intensive in terms of computing due to involving full-wave electromagnetic (EM) simu-lations. The cost-related issues are particularly pronounced whenever...

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  • Voice command recognition using hybrid genetic algorithm

    Publication

    Abstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...

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  • Obliczanie przesunięć osi toru przy modernizacji łuków parabolicznych na liniach kolejowych

    Podstawowym zadaniem modernizacji linii kolejowych jest właściwe zaprojektowanie nowego układu geometrycznego, który będzie spełniał założone kryteria związane z parametrami eksploatacyjnymi danej linii. Dążąc do spełnienia przyjętych warunków nałożonych na projektowany układ, projektant najczęściej koryguje podstawowe parametry geometryczne, tj. przechyłkę, promień łuku kołowego oraz długości krzywych przejściowych. W artykule...

  • PROJEKTOWANIE WIELOWYMIAROWEGO REGULATORA BACKSTEPPING W UKŁADZIE DYNAMICZNEGO POZYCJONOWANIA STATKU

    W komercyjnych systemach dynamicznego pozycjonowania statku, pomimo znacznego wzrostu poziomu automatyzacji, wykorzystywane jest nadal sterowanie typu PID. Poprawę jakości procesu pozycjonowania może umożliwić wykorzystanie bardziej efektywnych algorytmów, oferujących zaawansowane nieliniowe techniki sterowania. W artykule przedstawiono zagadnienie projektowania regulatora pozycji i kursu dla układu dynamicznego pozycjonowania...

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  • Elgold partial: Job offers

    Open Research Data

    The dataset contains 34 English texts scrapped from the web portals offering job offers. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity...

  • Elgold partial: Automotive blogs

    Open Research Data

    The dataset contains 34 English texts scrapped from automotive blogs. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and...

  • Elgold partial: Scientific papers' abstracts

    Open Research Data

    The dataset contains 87 Scientific papers' abstracts in English randomly chosen from the folowing scientific disciplines: Biomedicine, Life Sciences, Mathematics, Medicine, Science, Humanities, Social Science.

  • Elgold partial: Movie reviews

    Open Research Data

    The dataset contains 37 English texts with movie reviews. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.

  • Elgold partial: Amazon product reviews

    Open Research Data

    The dataset contains 34 Amazon product reviews in English. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.