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Search results for: missing data prediction
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Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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Harmony Search for Data Mining with Big Data
PublicationIn this paper, some harmony search algorithms have been proposed for data mining with big data. Three areas of big data processing have been studied to apply new metaheuristics. The first problem is related to MapReduce architecture that can be supported by a team of harmony search agents in grid infrastructure. The second dilemma involves development of harmony search in preprocessing of data series before data mining. Moreover,...
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Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics
PublicationData-driven surrogates are the most popular replacement models utilized in many fields of engineering and science, including design of microwave and antenna structures. The primary practical issue is a curse of dimensionality which limits the number of independent parameters that can be accounted for in the modelling process. Recently, a performance-driven modelling technique has been proposed where the constrained domain of the...
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Rhamnolipid CMC Prediction
PublicationRelationships between the purity, pH, hydrophobicity (log Kow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure–property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered....
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Coastal Cliffs Monitoring and Prediction of Displacements Using Terrestial Laser Scanning
PublicationCoastal cliffs are very sensitive to degradation caused by erosion and abrasion. Thus, it is very important to monitor susceptibility of the cliffs in terms of slope angles and ground fall resulting from vertical morphology of the cliffs. The results could be used for example to establish the boundaries of the safe investments zone or retreat infrastructure buildings in case of real threat such as degradation of the objects of...
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Electromagnetic interference frequencies prediction model of flyback converter for snubber design
PublicationSnubber design for flyback converters usually requires experimental prototype measurements or simulation based on accurate and complex models. In this study simplified circuit modelling of a flyback converter has been described to dimension snubbers in early stage of design process. Simulation based prediction of the transistor and diode ringing frequencies has been validated by measurements in a prototype setup. In that way obtained...
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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The molecular entities in linked data dataset
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublicationThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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DATA INTEROPERABILITY AND THE OPEN DATA ECOSYSTEM: ROLES AND RESEARCH AREAS
PublicationSustainability and value-creation are considered important parameters to measure the success of an open data system. Unfortunately, existing open data systems are not meeting their promises to achieve a sustainable and value-based open data system. Van Loenen et al. (2021) proposed a sustainable and value-creating open data ecosystem. According to their study, the open data ecosystem needs to be user-driven, inclusive, circular,...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublicationThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Systematic Literature Review on Click Through Rate Prediction
PublicationThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
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Prediction of protein assemblies, the next frontier: The CASP14‐CAPRI experiment
PublicationWe present the results for CAPRI Round 50, the 4th joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 12 targets, including 6 dimers, 3 trimers, and 3 higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly...
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A new index for statistical analyses and prediction of travelling ionospheric disturbances
PublicationTravelling Ionospheric Disturbances (TIDs) are signatures of atmospheric gravity waves (AGWs) observed in changes in the electron density. The analysis of TIDs is relevant for studying coupling processes in the thermosphere–ionosphere system. A new TID index is introduced, which is based on an easy extension of the commonly used approach for TID detection. This TID activity index, which can be applied for individual Global Navigation...
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Integrated information and prediction Web Service WaterPUCK General concept
PublicationIn this paper, general concept of a new method as ‘Integrated information and prediction Web Service WaterPUCK’ for investigation influence of agricultural holdings and land-use structures on coastal waters of the southern Baltic Sea is presented. WaterPUCK Service is focused on determination of the current and future environmental status of the surface water and groundwater located in the Puck District (Poland) and its impact...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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COMPARISON OF BLOOD PRESSURE PREDICTION METHODS
PublicationIn the paper dierent approaches of predicting blood pressure values are presented. Basically, two methods and theirs modifications are considered. In total, seven algorithms have been examined. Tests have been conducted using both synthetic and clinical data. From our study it follows that none of the examined methods is superior to other.
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Induction machine behavioral modeling for prediction of EMI propagation.
PublicationThis paper presents the results of wideband behavioral modeling of an induction machine (IM). The proposed solution enables modeling the IM differential- and common-mode impedance for a frequency range from 1 kHz to 10 MHz. Methods of parameter extraction are derived from the measured IM impedances. The developed models of 1.5 kW and 7.5 kW induction machines are designed using the Saber Sketch scheme editor and simulated in the...
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Missing the sweet spot: one of the two N-glycans on human Gb3/CD77 synthase is expendable
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CORPORATE BANKRUPTCY PREDICTION IN POLAND AGAINST THE BACKGROUND OF FOREIGN EXPERIENCE
PublicationIn highly developed countries, research in the field of bankruptcy risk prediction has been conducted for many years. For example, in the United States, which can be considered a pioneering country, the first publications appeared in the early twentieth century. In Poland, due to political and economic reasons, the interest in this issue dates back to the early 1990s. For this reason, this publication attempts to answer the following...
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CORPORATE BANKRUPTCY PREDICTION IN POLAND AGAINST THE BACKGROUND OF FOREIGN EXPERIENCE
PublicationIn highly developed countries, research in the field of bankruptcy risk prediction has been conducted for many years. For example, in the United States, which can be considered a pioneering country, the first publications appeared in the early twentieth century. In Poland, due to political and economic reasons, the interest in this issue dates back to the early 1990s. For this reason, this publication attempts to answer the following...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublicationWhile to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublicationWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublicationIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.
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METHOD FOR SHIP'S ROLLING PERIOD PREDICTION WITH REGARD TO NON-LINEARITY OF GZ CURVE
PublicationThe paper deals with the problem of prediction of the rolling period. A special emphasis is put on the practical application of the new method for rolling period prediction with regard to non-linearity of the GZ curve. The one degree-of-freedom rolling equation is applied with using the non-linear stiffness moment and linear damping moment formulas. A number of ships are considered to research the discrepancies between the pending...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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NUMERICAL ESTIMATION OF HULL HYDRODYNAMIC DERIVATIVES IN SHIP MANOUVERING PREDICTION
PublicationOperating in crowded waterways pose a risk of accidents and disasters due to maneuvering limitations of the ship. In order to predict ship’s maneuvering characteristics at the design stage, model tests are often executed as the most accurate prediction tool. Two approaches can be distinguished here: free running model tests and numerical simulations based on planar motion model with the use of hydrodynamic derivatives obtained...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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ColorNephroNet: Kidney tumor malignancy prediction using medical image colorization
PublicationRenal tumor malignancy classification is one of the crucial tasks in urology, being a primary factor included in the decision of whether to perform kidney removal surgery (nephrectomy) or not. Currently, tumor malignancy prediction is determined by the radiological diagnosis based on computed tomography (CT) images. However, it is estimated that up to 16% of nephrectomies could have been avoided because the tumor that had been...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Processing of LiDAR and Multibeam Sonar Point Cloud Data for 3D Surface and Object Shape Reconstruction
PublicationUnorganised point cloud dataset, as a transitional data model in several applications, usually contains a considerable amount of undesirable irregularities, such as strong variability of local point density, missing data, overlapping points and noise caused by scattering characteristics of the environment. For these reasons, further processing of such data, e.g. for construction of higher order geometric models of the topography...
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Methods for quality improvement of multibeam and LiDAR point cloud data in the context of 3D surface reconstruction
PublicationPoint cloud dataset is the transitional data model used in several marine and land remote-sensing applications. During further steps of processing, the transformation of point cloud spatial data to more complex models containing higher order geometric structures like edges and facets may be possible, if an appropriate quality level of input data is provided. Point cloud datasets usually contain a considerable amount of undesirable...
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublicationThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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Vibro piles performance prediction using result of CPT
PublicationVibro piles belong to the group of full displacement piles with an expanded base, characterised by a very high load capacity, especially in non-cohesive soils. The problem is to adopt a reliable method for the determination of full load–settlement (Q–s) curve. A frequent difficulty is the determination of the load capacity limit based on the static load test because the course of the load–settlement curve is of a linear nature....
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BIG PROBLEMS WITH BIG DATA
PublicationThe article presents an overview of the most important issues related to the phenomenon called big data. The characteristics of big data concerning the data itself and the data sources are presented. Then, the big data life cycle concept is formulated. The next sections focus on two big data technologies: MapReduce for big data processing and NoSQL databases for big data storage.
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublicationThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Shales Leaching Modelling for Prediction of Flowback Fluid Composition
PublicationThe object of the paper is the prediction of flowback fluid composition at a laboratory scale, for which a new approach is described. The authors define leaching as a flowback fluid generation related to the shale processing. In the first step shale rock was characterized using X-ray fluorescence spectroscopy, X-ray diractometry and laboratory analysis. It was proven that shale rock samples taken from the selected sections of horizontal...
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Data on the identification of microsatellite markers in Eisenia fetida and Eisenia andrei
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Prediction of consumer electricity needs based on Internet weather forecasts
PublicationElectrical energy is considered both as an important driver for producing and transporting goods in companies, as well as a good in itself which requires planning and management for generating and delivering it to consumers in proper time and amounts. Weather information can be considered to convey part of the data on energy delivery needs of consumers. Free meteorological data sources on the Web do not offer consistent data to...
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A Stand for Measurement and Prediction of Scattering Properties of Diffusers
PublicationIn this paper we present a set of solutions which may be used for prototyping and simulation of acoustic scattering devices. A system proposed is capable of measuring sound field. Also a way to use an open source solution for simulation of scattering phenomena occurring in proximity of acoustic diffusers is shown. The result of our work are measurement procedure and a prototype of the simulation script based on FEniCS - an open source...
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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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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublicationIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Low-Level Aerial Photogrammetry as a Source of Supplementary Data for ALS Measurements
PublicationThe development of laser scanning technology ALS allows to make high-resolution measurements for large areas result-ing in significant reduction of costs. The main stakeholders at heights data received from the airborne laser scanning is mainly state administration. The state institutions appear among projects such as ISOK. Each point is classified in ac-cordance with the standard LAS 1.2, our research focuses on the class 6 -...
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Electrochemical simulation of metabolism for antitumor-active imidazoacridinone C-1311 and in silico prediction of drug metabolic reactions
PublicationThe metabolism of antitumor-active 5-diethylaminoethylamino-8-hydroxyimidazoacridinone (C-1311) has been investigated widely over the last decade but some aspects of molecular mechanisms of its metabolic transformation are still not explained. In the current work, we have reported a direct and rapid analytical tool for better prediction of C-1311 metabolism which is based on electrochemistry (EC) coupled on-line with electrospray...
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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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Sensitivity of the Baltic Sea level prediction to spatial model resolution
Publicationhe three-dimensional hydrodynamic model of the Baltic Sea (M3D) and...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...