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Search results for: IOT, BIG DATA
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Construction of index generation unit using probabilistic data structures
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GBTX Emulation for BM@N/MPD Data Acquisition Systems
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Mining e-mail message sequences from log data
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Method of data anomaly detection in the process of mobile applications installation
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Fusion of data from AIS and tracking radar for the needs of ECDIS
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Advanced camera image data acquisition system for Pi-of-the-Sky
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Versatile prototyping platform for Data Processing Boards for CBM experiment
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Ellipsometric data analysis used in on-line metal passivation monitoring
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Generating training data for SART-2 keystroke analysis module
PublicationAnaliza dynamiki pisania na klawiaturze jest jedną z technik biometrycznych, które uwzględniają cechy behawioralne. Trudność związana z informacja na temat dynamiki pisania na klawiaturzepolega na tym, że są to dane bardzo niestabilne. Artykuł prezentuje krótko rozwiązanie wykorzystane w celu zbierania danych uczących oraz ekstrakcji cech dla systemu uwierzytelniania użytkownika na podstawie sposobu korzystania z klawiatury. Następnie...
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On intermolecular potential determination via equations of state and by acoustic data
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The Analysis of Green Areas’ Accessibility in Comparison with Statistical Data in Poland
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Measures for interoperability of phenotypic data: minimum information requirements and formatting
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Applications of Chebyszehev minimax deconvolution filtering to the estimation of deterended data
PublicationW pracy wyznaczono empirycznie, że sygnał wyjściowy rozplotowego filtru względem nieparzystej pary impulsów Kroneckera , z użyciem minimaksowej normy Czebyszewa, jest bardzo "bliski" pozbawionemu trendu sygnałowi wejściowemu. Obliczenia dla znacząco dużej liczby rzeczywistych danych z rynków kapitałowych i walutowych wykazały, że średnia miara rzeczonej "bliskości" , określona definicją znormalizowanego w L2 współczynnika kowariancji,...
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Nondestructive global corrosion measurement using guided wavefield data
PublicationMetallic structures often face degradation, and corrosion ranks among the most prevalent forms of deterioration. Accurate quantification of corrosion is crucial, especially for structures exposed to harsh environmental conditions, such as marine vessels and offshore installations. Because the traditional measurement methods based on scanning by ultrasonic gauge are time-consuming and provide only rough information on the thickness...
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Processing of point cloud data retrieved from terrestrial laser scanning for structural modeling by Finite Element Method
PublicationFinite Element Method is one most popular contemporary method of strength analysis. The method is an advanced method for solving differential equations, based on discretization, which means that area is divided into finite elements. Each finite element has a solution of the equation approximated by specific functions and performing the actual calculations only for nodes of this division. Finite Element Method is widely used in...
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REVERSE MODELLING OF MICROSEISMIC WAVES PROPAGATION FOR THE INTERPRETATION OF THE DATA FROM HYDRAULIC FRACTURING MONITORING IN POLAND
PublicationA hydraulic fracturing job was performed to stimulate gas flow from a horizontal wellbore located in Poland. The whole operation was overseen by means of microseismic monitoring. For this purpose, an array of 12000 geophones was deployed on ground in form of patches distributed unevenly in a region of 4km from the wellbore. The array was constantly recording seismic signals during whole fracturing processed. Such recorded signals...
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Comprehensive Comparison of a Few Variants of Cluster Analysis as Data Mining Tool in Supporting Environmental Management
PublicationA few variants of hierarchical cluster analysis (CA) as tool of assessment of multidimensional similarity in environmental dataset are compared. The dataset consisted of analytical results of determination of metals (Na, K, Ca, Sc, Fe, Co, Zn, As, Br, Rb, Mo, Sb, Cs, Ba, La, Ce, Sm, Hf and Th) in ambient air dried and kept alive, by the means of hydroponics, moss baskets collected in 12 locations on the area of Tricity (Poland)....
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublicationOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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The Decisional DNA-Based Smart Bike for Internet of Things
PublicationIn this paper, we introduce a novel application of the Internet of Things, the Decisional DNAbased Smart Bike. The Decisional DNA is a domain-independent, flexible and standard knowledge representation structure; it allows its domains to acquire and store experiential knowledge and formal decision events in an explicit way. By using Decisional DNA, the sensor-equipped bicycle is able to learn its user’s weight, riding habits, etc....
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<title>Synchronous optical transmission data link integrated with FPGA for TESLA FEL SIMCON system: long data vector optical transceiver module tests</title>
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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublicationThe GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network...
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Innovative Web-Based Geographic Information System for Municipal Areas and Coastal Zone Security and Threat Monitoring Using EO Satellite Data
PublicationThe paper presents a novel design of a Web-based Safe City & Coastal Zone GIS (SCCZ-GIS). The system integrates data acquired from different remote sensing and geospatial data sources for the purpose monitoring the security of the coastal zone, its inhabitants and Critical Infrastructure. The system utilises several innovative technologies and solutions, and is capable of direct co-operation with different remote sensing data sources...
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The Impact of Direct Normal Irradiation on the Solar Tower Power Plant Performance based on Real and Satellite Data: Analysis on Algerian Regions
PublicationThe present paper presents a deep study on the possibility of implementing Concentrated Solar Power (CSP) plants in Algeria for the production of the electrical energy. Indeed, this paper focusses mainly on the main parameters, which can have an important impact on the choice of the location, the dimension and the available thermal energy storage system. In this study, three main parameters are investigate...
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublicationProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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TRANSPORT POSSIBILITY FOR MPEG-4/AVC- AND MPEG-2-ENCODED VIDEO DATA IN IPTV: A COMPARISON STUDY
PublicationIPTV (Television over IP) is a modern service with a great potential to expand. It uses the IP transport platform, that is already in worldwide operation. At the time of writing, two techniques are used to transport the video and audio data of IPTV: MPEG-2 TS and Native RTP. The two techniques quite definitely have an influence on both quality of service (QoS) and quality of experience (QoE). This paper sets out to demonstrate...
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Correlation between in vitro and in vivo data on food digestion. What can we predict with static in vitro digestion models?
PublicationDuring the last decade, there has been a growing interest in understanding food's digestive fate in order to strengthen the possible effects of food on human health. Ideally, food digestion should be studied in vivo on humans but this is not always ethically and financially possible. Therefore, simple in vitro digestion models mimicking the gastrointestinal tract have been proposed as alternatives to in vivo experiments. Thus,...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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NUMERICAL MODEL QUALITY ASSESSMENT OF OFFSHORE WIND TURBINE SUPPORTING STRUCTURE BASED ON EXPERIMENTAL DATA
PublicationAs a structure degrades some changes in its dynamical behavior can be observed, and inversely, observation and evaluation of these dynamical changes of the structure can provide information of structural state of the object. Testing of the real structure, besides of being costly, can cover only limited working states. It is particularly considerable in case of hardly accessible, and randomly/severely dynamically loaded offshore...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Experience-Oriented Intelligence for Internet of Things
PublicationThe Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate...
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Processing of acoustical data in a multimodal bank operating room surveillance system
PublicationAn 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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Numerical weather prediction - data fusion to GIS systems and potential applications
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Effective Data-Centric Reputation Systems for MANETs: A Novel Evaluation Framework
PublicationZaprezentowano datacentryczny system reputacyjny dla sieci bezprzewodowej ad hoc z transmisją wieloskokową oraz metodę jego oceny opartą na wskaźniku efektywności. Wskaźnik ten odzwierciedla wymienność pomiędzy odróżnialnością węzłów egoistycznych od pozostałych oraz stopniem wykazywanego przez nie egoizmu. Dla przyjętego modelu sieci przedyskutowano analitycznie znaczenie znajomości tras i metryk reputacyjnych przez węzły.
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Cardiovascular data analysis using electronic wearable eyeglasses-preliminary study
Publicationhe paper presents an alternative approach to the monitoring of the cardiovascular system. The study depicts configurations of the utilized system and preliminary results of electrical and mechanical parameters of the cardiac system which can be measured using a head-worn device.
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Daily Radiation Budget of the Baltic Sea Surface from Satellite Data
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Use of Satellite Data in Monitoring of Hydrophysical Parameters of the Baltic Sea Environment
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Comparison of Selected Reduction Methods of Bathymetric Data Obtained by Multibeam Echosounder
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An Approach to Imbalanced Data Classification Based on Instance Selection and Over-Sampling
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Impact of Clustering on a Synthetic Instance Generation in Imbalanced Data Streams Classification
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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Optimization of river network representation data models for web-based systems
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Structural Model of the Bilitranslocase Transmembrane Domain Supported by NMR and FRET Data
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Analysis of Isocratic-Chromatographic-Retention Data using Bayesian Multilevel Modeling
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