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Search results for: APACHE SPARK,YARN, BIG DATA, GREEN COMPUTING, SENTINEL, TERA SORT, WORDCOUNT, BENCHMARKS, SCHEDULET
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International Journal of Image and Data Fusion
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International Journal of Data Warehousing and Mining
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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
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International Journal of Data Mining and Bioinformatics
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Japanese journal of statistics and data science
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International Journal of Data and Network Science
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Journal of Statistics and Data Science Education
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European Data Protection Law Review
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Annual Review of Biomedical Data Science
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SIAM Journal on Mathematics of Data Science
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International Journal of Data Science and Analytics
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JOURNAL OF PHYSICAL AND CHEMICAL REFERENCE DATA
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International Journal of Population Data Science
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U.S. Geological Survey Data Series
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Evaluation of the efficiency of the duty cycle of refuse collection vehicle based on real-world data
PublicationIn this paper a method of the efficiency evaluation of the duty cycle of Refuse Collection Vehicle is presented. Using real world data, two representative duty cycles were analysed. Total cycle efficiency was calculated, as well as the efficiency of particular cycle phases. Then, energy needed to collect and compact the waste and energy from fuel were compared. Measured and calculated values were shown on the diagrams illustrating...
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Successive cytotoxicity control by evolutionary surface decorated electronic push-pull green ZnCr-LDH nanostructures: Drug delivery enlargement for targeted breast cancer chemotherapy
PublicationThe reason for the increasing bioavailability and biocompatibility of the porous nanomaterials in the presence of different (bio)molecules is still unknown. The role of difference functional groups and their interactions with the potential bioavailability and biocompatibility is of great importance. To investigate the potential contribution of the electronic effects (especially on the surface of the porous nanomaterials) on their...
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A Fail-Safe NVRAM Based Mechanism for Efficient Creation and Recovery of Data Copies in Parallel MPI Applications
PublicationThe paper presents a fail-safe NVRAM based mechanism for creation and recovery of data copies during parallel MPI application runtime. Specifically, we target a cluster environment in which each node has an NVRAM installed in it. Our previously developed extension to the MPI I/O API can take advantage of NVRAM regions in order to provide an NVRAM based cache like mechanism to significantly speed up I/O operations and allow to preload...
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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublicationOpen Access scholarly literature is scientific output free from economic barriers and copyright restrictions. Using a case study approach, data mining methods and qualitative analysis, the scholarly output and the meta-data of the Open Access eJournal of e-Democracy and Open Government during the time interval 2009–2020 was analysed. Our study was able to identify the most prominent research topics (defined as thematic clusters)...
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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublicationOpen Access scholarly literature is scientific output free from economic barriers and copyright restrictions. Using a case study approach, data mining methods and qualitative analysis, the scholarly output and the meta-data of the Open Access eJournal of e-Democracy and Open Government during the time interval 2009–2020 was analysed. Our study was able to identify the most prominent research topics (defined as thematic clusters)...
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Oznaczanie śladowych ilości związków organicznych w próbkach o złożonych matrycach zgodne z regułami ''zielonej chemii analitycznej''. Krótkołańcuchowe kwasy karboksylowe = Increasingly green approaches to the determination of selected trace organic in complex matrices. Short chain carboxylic acids
PublicationNowadays the great stress is put on environment protection and the activities to minimize the effect of chemical analyses on the environment are discussed. When environmentally friendly methodologies of analytes determination are applied the term "green analytical chemistry" is used. In general, the determination of organic compounds in complex matrices, which is a frequent analytical task, requires separation of sample components...
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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublicationThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...
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Parametric versus nonparametric modelling of dynamic susceptibility contrast enhanced MRI based data
PublicationDynamic tracking of a bolus of a paramagnetic agent (dynamic susceptibility contract - DSC) in MRI (magnetic resonance imaging) measurements is successfully used for assessment of the tissue perfusion and the other features and functions of the brain (i.e. cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). The parametric and nonparametric approaches to the identification of MRI models are presented...
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Cavitation based cleaner technologies for biodiesel production and processing of hydrocarbon streams: A perspective on key fundamentals, missing process data and economic feasibility – A review
PublicationThe present review emphasizes the role of hydrodynamic cavitation (HC) and acoustic cavitation in clean and green technologies for selected fuels (of hydrocarbon origins such as gasoline, naphtha, diesel, heavy oil, and crude oil) processing applications including biodiesel production. Herein, the role of cavitation reactors, their geometrical parameters, physicochemical properties of liquid media, liquid oxidants, catalyst loading,...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Integration of Multi-Source Geospatial Data from GNSS Receivers, Terrestrial Laser Scanners, and Unmanned Aerial Vehicles
PublicationThe analysis based on geospatial data from different measurement systems now constitutes a complex numerical and practical enterprise. The dynamic development of modern technologies enables rapid and precise acquisition of such data. Nonetheless, the diversity of reference systems is today one of the main challenges for their correct interpretation. The combined use of the processed measurement results and archival data in paper...
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A universal IT system architecture for servicing, collecting, storing, processing and presenting data from wireless devices
PublicationIn the article we present a universal IT system architecture, which allows one to develop, based on mobile and multiplatform JAVA language, applications capable of working with many different wireless systems in an easy and effective way. Modular system architecture supports efficient data processing and enables convenient presentation of chosen parameters. Additionally, proposed IT system architecture provides easy adoption to...
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublicationAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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WETI (Data Engineering) - Mathematics 2023/24 (E.Kozłowska-Walania)
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublicationOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Secure access control and information protection mechanisms in radio system for monitoring and acquisition of data from traffic enforcement cameras
PublicationThe study presents the architecture of the Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short: RSMAD), particularly concerning access control and protection of confidential data. RSMAD security structure will be discussed in relation to network security issues. Additionally, the paper presents the results of the work associated with the modelling of potential threats to system security.
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Open extensive IoT research and measurement infrastructure for remote collection and automatic analysis of environmental data.
PublicationInternet of Things devices that send small amounts of data do not need high bit rates as it is the range that is more crucial for them. The use of popular, unlicensed 2.4 GHz and 5 GHz bands is fairly legally enforced (transmission power above power limits cannot be increased). In addition, waves of this length are very diffiult to propagate under field conditions (e.g. in urban areas). The market response to these needs are the...
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Mobile inventory system for hydrotechnical objects using data from multiple sensors operating simultaneously
PublicationThe knowledge of the location, shape and other characteristics of spatial objects in the coastal areas has a significant impact on the functioning of ports, shipyards, and other water-infrastructure facilities, both offshore and inland. Therefore, measurements are taken of the underwater part of the waterside zone, which means the bottom of water and other underwater objects (e.g. breakwaters, docks, etc.), and objects above the...
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The impact of shipping 4.0 on controlling shipping accidents: A systematic literature review
PublicationMaritime shipping, with a significant role in global trade, confronts various accidents leading to loss of lives, properties, and the environment. Shipping 4.0 technologies are scaling up to address this problem by employing real-time data-driven technologies, including cyber-physical systems, advanced tracking and tracing, intelligent systems, and big data analytics. Despite growing attention, there is a general lack of clarity...
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MATCHED FILTER APPROACH FOR MICROSEISMIC SIGNAL PROCESSING OF REAL DATA FROM EAST POMERANIA SHALE GAS
PublicationThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing (HF)process. An array of several hundred geophones is placed on the surface to record little ground tremors induced by fracturing process. Filtration and summation of signals from geophones is essential to identify and locate fracturing events from underground. Authors propose a method of matched filtering, that is usually...
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Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
PublicationIn this study, illustrating and comparing the performances of count data models such as Poisson, negative binomial (NB), Hurdle and zero-inflated models for the determination of factors affected housing sales in Dubai. Model comparisons are made via Akaike’s information criterion (AIC), the Vuong test and examining the residuals. Main purpose of this study is building reliable statistical model for relationship between Dubai housing...
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Rapid on-line method of wastewater parameters estimation by electronic nose for control and operating wastewater treatment plants toward Green Deal implementation
PublicationIn order to comply with legal regulations related to wastewater quality, the operational mode of facilities at wastewater treatment plant (WWTP) should be properly adjusted according to parameters of influents, however it is very difficult without frequently performed measurements. Currently there are known many techniques and devices for assesment of wastewater parameters such as chemical oxygen demand, biochemical oxygen demand,...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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GaMRed – adaptive filtering of high-throughput biological data
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New distributional data on bryophytes of Poland and Slovakia, 9
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New distributional data on bryophytes of Poland and Slovakia, 3
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Scientific tools for collecting and analysing medical data in rhinology.
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Wireless data transmission for fiber optical sensor system
PublicationW artykule opisano możliwość wykorzystania bezprzewodowego systemu transmisji danych do transmisji sygnałów z czujników światłowodowych.
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M-Split Estimation in Laser Scanning Data Modeling
PublicationPublikacja traktuje o wykorzystaniu estymacji M-Split do modelowania danych pozyskanych w wyniku skaningu laserowego. Autorzy prezentują rozwiązanie w oparciu o detekcję krawędzi dwóch płaszczyzn.
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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K-means clustering for SAT-AIS data analysis
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Manganese Distribution in CdMnTeSe Crystals. EXAFS Data Analysis
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Realistic visualization of real terrain based on GIS Data.
PublicationArtykuł prezentuje projekt realistycznej wizualizacji terenu rzeczywistego na podstawie danych pochodzących z Geograficznych Systemów Informacyjnych (GIS). Opisano w nim koncepcję projektu, wskazano trudności w jego realizacji i wskazano drogi ich przezwyciężenia.
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublicationThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...