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Search results for: DATA ANNOTATION
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Multi-Label Classification for AIS Data Anomaly Detection Using Wavelet Transform
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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Machine Learning and data mining tools applied for databases of low number of records
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Artificial intelligence and productivity: global evidence from AI patent and bibliometric data .
PublicationIn this paper we analyse the relationship between technological innovation in the artificial intelligence (AI) domain and macroeconomic productivity. We embed recently released data on patents and publications related to AI in an augmented model of productivity growth, which we estimate for the OECD countries and compare to an extended sample including non-OECD countries. Our estimates provide evidence in favour of the modern...
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The Scalable Distributed Two-layer Content Based Image Retrieval Data Store
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An accurate assignment test for extremely low‐coverage whole‐genome sequence data
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An accurate assignment test for extremely low-coverage whole-genome sequence data
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Performance analysis of data transmission in MC-CDMA radio interface with turbo codes
PublicationMulti-carrier code division multiple access (MC-CDMA) technique is a combination of two radio access techniques: CDMA and orthogonal frequency division multiplexing and has the advantages of both techniques. The paper presents the design of transmitter and receiver for MC-CDMA radio interface. It also presents encoders and decoders of turbo codes which were used in simulation of the MC-CDMA technique. Two turbo codes with 8-state...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Experimental Study of Polish Sausage Drying Kinetics and Contraction by Image Data Analysis
PublicationThe goal of this paper has been to add an experimental data set for drying a meat product and provide a comparison with well-established thin-layer drying models. This article presented experimental investigations on the convective drying of Polish sausage slices at a temperature of 40°C. Slices have been in the thickness of 3 to 8mm. Measurements of mass loss and size change were performed. The data have been presented in the...
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Fault detection in the marine engine using a support vector data description method
PublicationFast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection...
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Automated hearing loss type classification based on pure tone audiometry data
PublicationHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Solvation of N-methylformamide by ethanol: a comparison of molecular dynamics calculations with the experimental data
PublicationWykonano obliczenia metodami dynamiki molekularnej dla tytułowego układu. Rezultaty porównano z uzyskanymi wcześniej wynikami pomiarów termodynamicznych oraz wnioskami z nich wyciągniętymi.
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Kalman filtering for 3d real time data visualisation of multibeam sonar records.
PublicationPrzedstawiono zastosowanie filtracji Kalmana do korekcji błędów systematycznych występujących w danych pochodzących z systemu wielozwiązkowego. Zaproponowano dwuetapową filtrację danych dla każdego wachlarza danych, która realizowana jest w czasie rzeczywistym. Zaprezentowano rezultaty wizualizacji dna morskiego przed i po filtracji.
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THE CONCEPT OF INTEGRATED SYSTEM FOR COLLECTING GEOGRAPHIC AND HYDROGRAPHIC DATA FOR NAVIGATION PURPOSES IN RIS
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Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublicationOpen government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles,...
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Reversible data hiding in encrypted DICOM images using sorted binary sequences of pixels
PublicationIn this paper, a novel reversible data hiding method for encrypted DICOM images is proposed. The method utilizes binary decomposition of the input data paired with a sorting process of the obtained binary sequences to ensure efficient data embedding in each predefined data block for specific most significant bit (MSB) planes while exploiting the properties of run-length encoding. The proposed scheme is lossless, and based on the...
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Digitalization Process and Its Impact on Economic Growth A Panel Data Study for Developing Countries
PublicationThis book analyses the impact of Information and Communication Technologies (ICTs) on economic development. It contains theoretical and empirical studies, including panel studies on various issues facing developing countries, such as education, corruption, economic growth, government expenditure, financial inclusion, foreign direct investment, infrastructure, economic and social welfare, and inequality. Each chapter offers a well-conceived...
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Analysis of Transformation Methods of Hydroacoustic and Optoelectronic Data Based on the Tombolo Measurement Campaign in Sopot
PublicationMeasurements in the coastal zone are carried out using various methods, including Global Navigation Satellite Systems (GNSS), hydroacoustic and optoelectronic methods. Therefore, it is necessary to develop coordinate transformation models that will enable the conversion of data from the land and marine parts to one coordinate system. The article presents selected issues related to the integration of geodetic and hydrographic data....
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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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Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities
PublicationWide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Fast synchronous distribution network of data streams for RPC Muon Trigger in CMS experiment
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Changes in the addiction prevalence in Polish population between 1990-2019: Review of available data
PublicationThe 1989 collapse of the socialist political system in Poland initiated an avalanche of modifications regarding healthcare policy resulting with new institutions and programs dedicated to monitoring and preventing addiction. In the current article, we look at the available data allowing to track changes in (1) the prevalence of exposure to addictive substances and behaviors, and (2) changes of addictions prevalence in Poland...
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Sea surface temperature retrieval from MSG/SEVIRI data in the Baltic Sea area
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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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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks
PublicationClimate change caused by human activities can influence the lives of everybody onthe planet. The environmental concerns must be taken into consideration by all fields of studyincludingICT. Green Computing aims to reduce negative effects of IT on the environment while,at the same time, maintaining all of the possible benefits it provides. Several Big Data platformslike Apache Spark orYARNhave become widely used in analytics and...
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Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data
PublicationInundation area time series are important for wetlands monitoring and hydrological model validation. This study is conducted in Biebrza floodplain, which is a natural wetland with complex inundation generation processes. In order to map 2014-2018 series of inundation in the floodplain we test our automatic thresholding method on Sentinel 1 data. The threshold value is optimized using correlation of the inundation area with observed...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Use of Data from Satellite Navigation System in Operational and Strategic Management of Transport in Cities
PublicationThe article presents the possibilities of using data from the Global Positioning System for the development of traffic models and examples of use this data in the transport management. Traffic models are useful tools in planning and evaluation of transport solutions, but also can be used for current, operational transport management.
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Using LSTM networks to predict engine condition on large scale data processing framework
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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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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Energetic model of hydraulic system of refuse collection vehicle based on simulation and experimental data
PublicationThis paper presents an energetic model of hydraulic system of a refuse collection vehicle. First, benefits resulting from implementation of an energetic model in the industry and operation of a Refuse Collection Vehicle are briefly explained. Then, components of the energy consumption in hydraulic circuits of compactor and lifting device are described and combined into a comprehensive model that can be evaluated using basic measurement...
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Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublicationIt is proposed, developed, investigated, and validated by experiments and modelling for the first time in worldwide terms new data processing technologies, higher order spectral multiple correlation technologies for fault identification for electromechanical systems via electrical data processing. Investigation of the higher order spectral triple correlation technology via modelling has shown that the proposed data processing technology...
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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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Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
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Deduplication of Tracked Objects Position Data at Single Observation Point of a Vessel Monitoring System
PublicationVessel Monitoring System (VMS) play a major role in safety navigation. In most cases they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Integration of data obtained from these sources is an important problem, which needs to be solved in order to ensure the correct performance of a given VMS. In this paper basic functions which should be implemented in a tracked...
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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublicationIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublicationThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 20132014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification a protected Natura 2000 habitat (code 7230) using remote sensing technologies. High resolution airborne true colour (RGB) and...
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A strategy for GPS data processing in a precise local network during high solar activity
PublicationThis paper presents the analyses connected with reduction of errors from ionospheric refraction using GPS data from local satellite networks. This is particularly essential during rising solar activity. The Bernese GPS Software v. 4.2 was used, as an analytical tool. The test data included measurements from a geodynamic network SUDETES situated in the Sudety Mountains across the border between the Czech Republic and Poland. A local...
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Research and analysis of high-speed data transmission radio link designed for maritime environment
PublicationIn these article the realization of digital radio link for high-speed data transmission was presented. Its concept and practical realization, using USRP devices from National Instruments, were described. Developed software for generation and reception of digital signals in baseband, including description of modulation types, and time and frequency synchronization mechanisms, was presented. Moreover, an operation of designed radio...
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MAPSERVER – INFORMATION FLOW MANAGEMENT SOFTWARE FOR THE BORDER GUARD DISTRIBUTED DATA EXCHANGE SYSTEM
PublicationIn this paper the architecture of the software designed for management of position and identification data of floating and flying objects in Maritime areas controlled by Polish Border Guard is presented. The software was designed for managing information stored in a distributed system with two variants of the software, one for a mobile device installed on a vessel, an airplane or a car and second for a central server. The details...
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Global Value Chains and Wages: International Evidence from Linked Worker-Industry Data
PublicationUsing a rich dataset on over 110,000 workers from nine European countries and the USA we study the wage response to industry dependence on foreign value added. We estimate a Mincerian wage model augmented with an input-output interindustry linkages measure accounting for task heterogeneity across workers. Low and mediumeducated workers and those performing routine tasks experience (little) wage decline due to major dependency of...