Wyniki wyszukiwania dla: Machine design - MOST Wiedzy

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Wyniki wyszukiwania dla: Machine design

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Wyniki wyszukiwania dla: Machine design

  • Examining Influence of Distance to Microphone on Accuracy of Speech Recognition

    The problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...

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  • Efficiency of gas detection algorithms using fluctuation enhanced sensing

    Publikacja

    - Rok 2015

    Efficiency of various gas detection algorithms by applying fluctuation enhanced sensing method was discussed. We have analyzed resistance noise observed in resistive WO3- nanowires gas sensing layers. Power spectral densities of the recorded noise were used as the input data vectors for two algorithms: the principal component analysis (PCA) and the support vector machine (SVM). The data were used to determine gas concentration...

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  • Examination method of the effect of the incidence angle of laser beam on distance measurement accuracy to surfaces with different colour and roughness

    Interest in the influence of the incidence angle of a laser beam to distance measurements can be seen in many areas of science and technology: geodesy, glaciology, archaeology, machine automation, and others. This paper presents results of measurements of the effect of the incidence angle of a laser beam to distance measurements to the surfaces of different colour and roughness by Topcon's electro-optical total station with an...

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  • Deep neural networks approach to skin lesions classification — A comparative analysis

    The paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...

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  • Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms

    Publikacja

    - Rok 2014

    Implementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...

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  • Experimental ultimate strength assessment of stiffened plates subjected to marine immersed corrosion

    Publikacja

    This study experimentally analyses the impact of marine immersed corrosion degradation on the compressive strength of the stiffened plates where the lower degradation levels were considered. The corrosion degradation test was accelerated by controlling the natural corrosion environmental factors, avoiding applying an electric current. Different groups of corrosion degradation levels and initial plate thicknesses were investigated....

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  • Experimental investigations of damage evolution in concrete during bending by continuous micro-CT scanning

    The paper describes experimental investigation results of fracture in notched concrete beams under quasi-static three-point bending. To visualize 3D fracture in concrete under bending, an extended X-ray micro-computed tomography system was used, i.e. the tomography system SkyScan 1173 was connected to the loading machine ISTRON 5569. This combined system enabled to shot images of deforming concrete beams during a continuous deformation...

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  • Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation

    Publikacja

    - SENSORS - Rok 2024

    To date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...

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  • Book Review

    Acting over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...

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  • Total Completion Time Minimization for Scheduling with Incompatibility Cliques

    Publikacja

    - Rok 2021

    This paper considers parallel machine scheduling with incompatibilities between jobs. The jobs form a graph equivalent to a collection of disjoint cliques. No two jobs in a clique are allowed to be assigned to the same machine. Scheduling with incompatibilities between jobs represents a well-established line of research in scheduling theory and the case of disjoint cliques has received increasing attention in recent...

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  • Computing methods for fast and precise body surface area estimation of selected body parts

    Currently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...

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  • Domestic ORC micro-CHP combined with a commercial gas boiler

    Publikacja

    - Rok 2014

    The chapter presents the results of experimental studies conducted during the launch of the first in Poland demonstration prototype of the micro ORC coupled to a domestic gas boiler. The accomplished studies indicated the possibility for the ORC module to work with such boiler (autonomous source of heat) with a prototype single-stage axial micro turbine as the expansion machine. Confirmation of that fact has been delineated in...

  • CUTTING POWER FORECASTING WHILE WOOD SAWING: FRACTURE MECHANICS APPROACH AND AXELSSON’S MODEL COMPARISON

    Publikacja

    - Rok 2014

    In the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. On the other hand, cutting forces (power) could be considered from a point of view of modern fracture mechanics. Another way is to forecast cutting power consumption on...

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  • Processing of acoustical data in a multimodal bank operating room surveillance system

    An 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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  • Z type Observer Backstepping For Induction Machines

    This paper contains a relatively new synthesis method for non-linear objects, named backstepping. This method can be used to obtain the observer structure. The paper presents the structure of the speed observer which is a new proposition of observer backstepping with additional state variables marked Z. The rotor speed can be estimated in three different ways. The first is based on the adaptive approach, the second on the nonadaptive...

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  • Audio-visual surveillance system for application in bank operating room

    An audio-visual surveillance system able to detect, classify and to localize 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 acoustic...

  • Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2015

    In this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...

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  • Sensorless low speed PMSM motor control with cogging torque compensation

    The paper presents sensorless control of a low speed permanent magnet synchronous machine with use of modified state observer. An overview of the PMSM motor used in the research setup was presented. The problem of drive torque ripple, resulting mainly from the occurrence of a significant cogging torque, was discussed. A solution compensating the torque ripple of the PMSM motor was proposed. A start-up procedure of the speed control...

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  • I, Robot: between angel and evil

    Publikacja

    - Rok 2020

    The boosting of most digital innovations within recent technology progress by artificial intelligence (AI) constitutes a growing topic of interest. Besides its technical aspects, increasing research activity may be observed in the domain of security challenges, and therefore of responsibility related to the controlled or hypothetically uncontrolled or autonomous emergence of AI solutions. Consequently, responsibility and ethics...

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  • Analysis of Factors Influencing the Prices of Tourist Offers

    Tourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...

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  • Classification of Sea Going Vessels Properties Using SAR Satellite Images

    Publikacja

    The aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...

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  • Deep Learning: A Case Study for Image Recognition Using Transfer Learning

    Publikacja

    - Rok 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Deep Learning

    Publikacja

    - Rok 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • INFLUENCE OF TACK WELDS DISTRIBUTION AND WELDING SEQUENCE ON THE ANGULAR DISTORTION OF TIG WELDED JOINT

    In this paper the influence of tack welds distribution and welding sequence on angular distortion of the Tungsten Inert Gas (TIG) welded joint was tested. Additionally, the effect of welding current on angular distortion was assessed. For research X2CrTiNb18 (AISI 441) stainless steel (2.5 mm thick) was chosen. During research specimens were prepared with different distributionsof tack...

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  • Lamb wave-based monitoring of shear failure of an adhesive lap joint

    Publikacja

    The paper presents a study on the elastic wave propagation in adhesive joints of steel plates subjected to tensile loading. A single lap joint was chosen for analysis because of its simplicity and plurality of applications. Experimental investigations consisted of the uniaxial extension of prepared specimens. Force and displacement values were recorded by a testing machine. Simultaneously, guided Lamb waves were excited and signals...

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  • Listening to Live Music: Life beyond Music Recommendation Systems

    Publikacja

    - Rok 2018

    This paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...

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  • INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY

    In recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...

  • Trust and distrust in electoral technologies: what can we learn from the failure of electronic voting in the Netherlands (2006/07)

    Publikacja

    - Rok 2024

    This paper focuses on the complex dynamics of trust and distrust in digital government technologies by approaching the cancellation of machine voting in the Netherlands (2006-07). This case describes how a previously trusted system can collapse, how paradoxical the relationship between trust and distrust is, and how it interacts with adopting and managing electoral technologies. The analysis stresses how, although...

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  • Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?

    Publikacja

    - Rok 2022

    In this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...

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  • Nowe możliwości generowania zarysów satelitowych mechanizmów roboczych

    Publikacja

    - Rok 2012

    Planetary hydraulic gear motors have been well known since 70's . first motors were constructed for maritime industry by hydroster from gdansk. the evolution of this type of motors led to an increase of nominal pressure and durability. nowadays the industry needs reliable and efficient motor able to work with alternative hydraulic fluids like water, emulsion and vegetable oil. therefore a new type of motors are being developed...

  • State and control system variables sensitivity to rotor asymmetry in the induction motor drive

    The aim of this paper is to undertake analysis and comparison of the closed-loop and sensorless control systems sensitivity to the broken rotor for diagnostic purposes. For the same vector control system induction motor drive analysis concerning operation with the asymmetric motor, broken rotor fault handling and operation were investigated. Reliability, range of stable operation, fault symptoms and application of diagnosis methods...

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  • A tool for integrating Web Site services over User Interface

    Publikacja

    - Rok 2013

    Companies and organizations are building information systems by integrating previously independent applications, together with new developments. This integration process has to deal with existing applications, which can only be used through their specific interfaces, and often cannot be modified. Integration of web applications running remotely and controlled by separate organizations becomes even more complicated, as their user...

  • Histogram of Gradients with Cell Average Intensity for Human Detection

    Publikacja

    - Rok 2015

    The modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...

  • Problems of analytical determination of journal bearing bush fatigue strength estimates

    Problems connected with determination of stress distribution in sliding layer of thinwalled bearing bushes, investigated in bearing fatigue test rigs, have been presented. Using an example of plain bearings tested in the fatigue machine SMOK (built at the Gdask University of Technology) problems with obtaining a convergence of iterative procedure for determining the fatigue strength estimators of bearing alloy surface layer are...

  • Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations

    Evaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...

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  • Method of selecting the LS-SVM algorithm parameters in gas detection process

    In this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...

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  • Experience-Oriented Knowledge Management for Internet of Things

    Publikacja

    - Rok 2016

    In this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...

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  • Decisional DNA Based Conceptual Framework for Smart Manufacturing

    Publikacja

    - Advances in Intelligent Systems and Computing - Rok 2016

    This paper presents the conceptual framework for systematic knowledge representation, storage and reuse of manufacturing information in a production scenario. This knowledge structure is designed for three levels in a manufacturing set up viz. first at the engineering objects level, second at process and finally at factory level. Virtual engineering object (VEO) deals with knowledge at the individual object/component/machine level...

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  • Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building

    Traffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...

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  • Models of Brushless Synchronous Generator for Studying Autonomous Electrical Power System

    Publikacja

    - Rok 2020

    This is a PhD dissertation. The work presented in this monograph was carried out at the Department of Power Electronics and Electrical Machines, Faculty of Electrical and Control Engineering at the Gdansk University of Technology. Developed during the research models of brushless synchronous generator ware verified using FEM based simulations and measurements conducted on the prototype generator. The main focus of the research...

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  • A Wind Energy Conversion System Based on a Generator with Modulated Magnetic Flux

    Publikacja

    - ENERGIES - Rok 2020

    In this work, the concept of an energy conversion system for wind turbines based on the modified permanent magnet synchronous generator (PMSG) is presented. In the generator, a pair of three-phase windings is used, one of which is connected in a “star” and the second in a “delta” configuration. At the outputs of both windings, two six-pulse uncontrolled (diode) rectifiers are included. These rectifiers are mutually coupled by a...

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  • Comparative Study of Integer and Non-Integer Order Models of Synchronous Generator

    Publikacja

    - ENERGIES - Rok 2020

    This article presents a comparison between integer and non-integer order modelling of a synchronous generator, in the frequency domain as well as in the time domain. The classical integer order model was compared to one containing half -order systems. The half-order systems are represented in a Park d-q axis equivalent circuit as impedances modelled by half-order transmittances. Using a direct method based on the approximation...

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  • Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry

    We describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...

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  • Technique for reducing erosion in large-scale circulating fluidized bed units

    Publikacja
    • J. Grochowalski
    • A. Widuch
    • S. Sładek
    • B. Melka
    • M. L. Nowak
    • A. Klimanek
    • M. Andrzejczyk
    • M. Klajny
    • L. Czarnowska
    • B. Hernik... i 3 innych

    - POWDER TECHNOLOGY - Rok 2023

    This paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...

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  • IFE: NN-aided Instantaneous Pitch Estimation

    Publikacja

    Pitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...

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  • Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents

    Publikacja

    - MOLECULES - Rok 2024

    Solubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...

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  • Deep convolutional neural network for predicting kidney tumour malignancy 

    Publikacja

    - Rok 2021

    Purpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...

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  • Empirical analysis of tree-based classification models for customer churn prediction

    Publikacja
    • F. E. Usman-Hamza
    • A. O. Balogun
    • S. K. Nasiru
    • L. F. Capretz
    • H. A. Mojeed
    • S. A. Salihu
    • A. G. Akintola
    • M. A. Mabayoje
    • J. B. Awotunde

    - Scientific African - Rok 2023

    Customer 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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  • Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

    Publikacja
    • S. Donghui
    • L. Zhigang
    • J. Zurada
    • A. Manikas
    • J. Guan
    • P. Weichbroth

    - KNOWLEDGE AND INFORMATION SYSTEMS - Rok 2024

    The 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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  • “The Guardians of the Truth”: Journalists’ Resistance to the Algorithmization of Journalism

    Publikacja
    • J. Kreft
    • M. Boguszewicz-kreft
    • M. Fydrych

    - ETHOS. KWARTALNIK INSTYTUTU JANA PAWŁA II KUL - Rok 2024

    Regardless of the term used, be it “robot journalism,” “automated journalism,” “algorithmic journalism” or “machine-written journalism,” the process of automatic content creation and distribution is progressing in the newsrooms. Meanwhile, exercising control over the creation and distribution of news is considered a fundamental element of journalists’ professional identity. The article presents the results of research on the perception...

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