Search results for: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublicationWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Augmenting digital documents with negotiation capability
PublicationActive digital documents are not only capable of performing various operations using their internal functionality and external services, accessible in the environment in which they operate, but can also migrate on their own over a network of mobile devices that provide dynamically changing execution contexts. They may imply conflicts between preferences of the active document and the device the former wishes to execute on. In the...
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Improving all-reduce collective operations for imbalanced process arrival patterns
PublicationTwo new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example...
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Digital Filtering of Railway Track Coordinates in Mobile Multi–Receiver GNSS Measurements
PublicationThe article discusses an important issue in connection with the technique of mobile Global Navigation Satellite System (GNSS) measurements of railway track coordinates, which is digital filtering performed to precisely determine railway track axes. For this purpose, a measuring technique is proposed which bases on the use of a measuring platform with a number of appropriately distributed GNSS receivers, where two of them determine...
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Qualia: About Personal Emotions Representing Temporal Form of Impressions - Implementation Hypothesis and Application Example
PublicationThe aim of this article is to present the new extension of the xEmotion system as a computerized emotional system, part of an Intelligent System of Decision making (ISD) that combines the theories of affective psychology and philosophy of mind. At the same time, the authors try to find a practical impulse or evidence for a general reflection on the treatment of emotions as transitional states, which at some point may lead to the...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublicationAutonomous 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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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublicationIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublicationNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Instructor Presence in Video Lectures: Preliminary Findings From an Online Experiment
PublicationMotivation. Despite the widespread use of video lectures in online and blended learning environments, there is still debate whether the presence of an instructor in the video helps or hinders learning. According to social agency theory, seeing the instructor makes learners believe that s/he is personally teaching them, which leads to deeper cognitive processing and, in turn, better learning outcomes. Conversely, according to cognitive...
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Variable Ratio Sample Rate Conversion Based on Fractional Delay Filter
PublicationIn this paper a sample rate conversion algorithm which allows for continuously changing resampling ratio has been presented. The proposed implementation is based on a variable fractional delay filter which is implemented by means of a Farrow structure. Coefficients of this structure are computed on the basis of fractional delay filters which are designed using the offset window method. The proposed approach allows us to freely...
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A simplified channel estimation procedure for NB-IoT downlink
PublicationThis paper presents a low-complexity channel estimation procedure which is suitable for use in energy-efficient NB-IoT user equipment devices. The procedure is based on the well-established least squares scheme, followed by linear interpolation in the time domain and averaging in the frequency domain. The quality of channel estimation vs. signal-to-noise ratio is evaluated for two channel models and compared with the performance...
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A Universal Gains Selection Method for Speed Observers of Induction Machine
PublicationProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
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Low-Level Music Feature Vectors Embedded as Watermarks
PublicationIn 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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A Novel Approach to the Assessment of Cough Incidence
PublicationIn this paper we consider the problem of identication of cough events in patients suffering from chronic respiratory diseases. The information about frequency of cough events is necessary to medical treatment. The proposed approach is based on bidirectional processing of a measured vibration signal - cough events are localized by combining the results of forward-time and backward-time analysis. The signal is at rst transformed...
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Automatic sound source localization in disturbing conditions using acoustic vector sensors
PublicationA 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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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Engineering education for smart grid systems in the quasi-industrial environment of the LINTE^2 laboratory
PublicationSmart grid systems are revolutionising the electric power sector, integrating advanced technologies to enhance efficiency, reliability and sustainability. It is important for higher education to equip the prospective smart grid professional with the competencies enabling them to navigate through the related complexities and drive innovation. To achieve this, interdisciplinary education programmes are necessary, addressing inter...
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublicationComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...
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1D portable optical coherence tomography system
Publication—Imaging methods are an expanding branch of technology, which involves data acquisition and analysis of images for research and diagnostics. This paper has been devoted to the description of the optical design for a one-dimensional, portable optical coherence tomography (OCT) system. The Mach-Zehnder interferometer has been designed in the presented study. The description of the construction and applied hardware solutions have...
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Insights in microbiotechnology: 2022.Editorial
PublicationThis Research Topic serves as an invaluable resource for readers interested in staying updated with the latest progress and developments in the field of microbiotechnology. It spotlights the innovative research conducted by up-and-coming experts in the field, specifically emphasizing the transforming abilities of microorganisms that greatly influence the scientific community. The advent of multi-omic technologies has revolutionized microbiotechnology,...
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Alhassan Ali Ahmed
PeopleAlhassan Ali Ahmed BSc of pharmacy, MSc in Bioinformatics and Biotechnology, and currently doing his PhD in Bioinformatics and Machine Learning. Alhassan has considerable experience in the pharmaceutical industry as he worked before in different positions such as; Community pharmacist, Medical advisor, Antibiotics production specialist, Quality assurance specialist, Key account manager for Immunotherapeutic medications, and currently,...
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublicationW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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Wind Turbines Modeling as the Tool for Developing Algorithms of Processing their Video Recordings
PublicationIn the real world, many factors exist disturbing observation of the examined phenomena and causing various noises and distortions in recorded signals. It very often makes it difficult or even impossible to optimize various signal processing algorithms, through finding appropriate parameters. In this paper, we show an application, that retrieves wind turbine rotor speed from recorded video. Next, we describe the process of reduction...
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Wind Turbines Modeling as the Tool for Developing Algorithms of Processing their Video Recordings
PublicationIn the real world, many factors exist disturbing observation of the examined phenomena and causing various noises and distortions in recorded signals. It very often makes it difficult or even impossible to optimize various signal processing algorithms, through finding appropriate parameters. In this paper, we show an application, that retrieves wind turbine rotor speed from recorded video. Next, we describe the process of reduction...
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Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Frequency based criterion for distinguishing tonal and noisy spectral components
PublicationA frequency-based criterion for distinguishing tonal and noisy spectral components is proposed. For considered spectral local maximum two instantaneous frequency estimates are determined and the difference between them is used in order to verify whether component is noisy or tonal. Since one of the estimators was invented specially for this application its properties are deeply examined. The proposed criterion is applied to the...
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Large dynamic range high frequency fully differential CMOS transconductanceamplifier.
PublicationW pracy zaproponowano nową koncepcję układową w pełni różnicowego wzmacniacza transkonduktancyjnego CMOS o dużym zakresie dynamiki i szerokim pasmie częstotliwości. Przeprowadzone badania teoretyczne i symulacyjne potwierdziły małe zniekształcenia harmoniczne (THD), szerokie pasmo przenoszonych częstotliwości oraz duży zakres dynamiki dla sygnałów różnicowych.
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Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model
PublicationDepth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size...
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How ethics combine with big data: a bibliometric analysis
PublicationThe term Big Data is becoming increasingly widespread throughout the world, and its use is no longer limited to the IT industry, quantitative scientific research, and entrepreneurship, but entered as well everyday media and conversations. The prevalence of Big Data is simply a result of its usefulness in searching, downloading, collecting and processing massive datasets. It is therefore not surprising that the number of scientific...
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Conducted EMI Propagation Paths in DC-AC Hard Switching Converter
PublicationIn order to limit the electromagnetic interference (EMI) in power electronics devices, knowledge about the phenomena connected with EMI generation and propagation is necessary. This papers describes the propagation paths in the 3 phase voltage source inverter using wide-band simulation and laboratory test with the signal processing method Wiener filtering, where the transfer functions between voltage across switches and the perturbation...
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Sensors and System for Vehicle Navigation
PublicationIn recent years, vehicle navigation, in particular autonomous 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, or deep learning, are changing the quality of areas of applications, improving the sensors and systems used. Recently, the influence of artificial intelligence on sensor data processing and...
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FPGA-Based Real-Time Implementation of Detection Algorithm for Automatic Traffic Surveillance Sensor Network
PublicationArtykuł opisuje sprzętową implementację w układzie FPGA algorytmu wykrywającego pojazdy, przeznaczonego do zastosowania w autonomicznej sieci sensorowej. Zadaniem algorytmu jest detekcja poruszających się pojazdów w obrazie z kamery pracującej w czasie rzeczywistym. Algorytm ma na celu oszacowanie parametrów ruchu ulicznego, takich jak liczba pojazdów, ich kierunek ruchu i przybliżona prędkość, przy wykorzystaniu sprzętu sieci...
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublicationArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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EEG data recorded in three mental states
Open Research DataElectroencephalographic (EEG) signals were acquired from 17 (14 males, 3 females) participants aged between 20 and 30 years.
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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublicationThis paper considers complexity and accuracy of data processing for gas detection using resistance fluctuation data observed in resistance gas sensors. A few selected methods were considered (Principal Component Analysis – PCA, Support Vector Machine – SVM). Functions like power spectral density or histogram were used to create input data vector for these algorithms from the observed resistance fluctuations. The presented considerations...
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A Triplet-Learnt Coarse-to-Fine Reranking for Vehicle Re-identification
PublicationVehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the challenges of lower intra-class and higher inter-class similarities. Motivated by deep...
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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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Importance of artificial intelligence to support the process of anaerobicdigestion of kitchen waste with bioplastics / Znaczenie sztucznej inteligencji we wspomaganiu procesu beztlenowej fermentacji odpadów kuchennych zawierających bioplastiki
PublicationArtificial intelligence (AI) and machine learning were used to obtain more effective methods for conducting the digestion process and achieving final products. Data acquisition was carried out by an automatic monitoring and anal. research. The knowledge describing the anaerobic digestion process was summarized in the form of rules: IF (premise) THEN (conclusion). The compiled set of rules created a knowledge base of the expert...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublicationLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases
PublicationThis paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements...
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Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies
PublicationThis guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...
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Mohsan Ali Master of Science in Computer Science
PeopleMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
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Unveiling the electron-induced ionization cross sections and fragmentation mechanisms of 3,4-dihydro-2H-pyran
PublicationThe interactions of electrons with molecular systems under various conditions are essential to interdisciplinary research fields extending over the fundamental and applied sciences. In particular, investigating electron-induced ionization and dissociation of molecules may shed light on the radiation damage to living cells, the physicochemical processes in interstellar environments, and reaction mechanisms occurring in combustion...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Manufacturing Data Analysis in Internet of Things/Internet of Data (IoT/IoD) Scenario
PublicationComputer integrated manufacturing (CIM) has enormous benefits as it increases the rate of production, reduces errors and production waste, and streamlines manufacturing sub-systems. However, there are some new challenges related to CIM operating in the Internet of Things/Internet of Data (IoT/IoD) scenarios associated with Industry 4.0 and cyber-physical systems. The main challenge is to deal with the massive volume of data flowing...
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Multimedia polysensory integration training system dedicated to children with educational difficulties
PublicationThis paper aims at presenting a multimedia system providing polysensory train- ing for pupils with educational difficulties. The particularly interesting aspect of the system lies in the sonic interaction with image projection in which sounds generated lead to stim- ulation of a particular part of the human brain. The system architecture, video processing methods, therapeutic exercises and guidelines for children’s interaction...
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Analysis of server-side and client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and geoportal
PublicationThe last decade has seen a rapid evolution of processing, analysis and visualization of freely available geographic data using Open Source Web-GIS. In the beginning, Web-based Geographic Information Systems employed a thick-client approach which required installation of platform-specific browser plugins. Later on, research focus shifted to platform-independent thin client solutions in which data processing and analysis was performed...
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Applications of Raman spectroscopy for detection of selected substances in tissues
PublicationThis dissertation explores the applications of Raman spectroscopy for biological tissue analysis. Basics of Raman and surface-enhanced Raman spectroscopy (SERS) are described, along with an analysis of the literature on biodetection and non-invasive blood analysis with emphasis on glucose detection. Instrumentation for Raman measurements is described. The sources of noise and interferences occurring in biological tissue measurements...