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Wyniki wyszukiwania dla: LEARNING
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Freelance technical writing application for a job which I did not get.
PublikacjaIn this essay I am going to explore the different ways in which developments in engineering technology and materials science have improved the quality of learning and at the same time somewhat diminished students innate intellectual ability which came as the result of what we know as A.I. According to wikipedia.org the word "education" comes from the conjunction of a Latin words "I lead" or "duco" meaning "I...
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Examining Statistical Methods in Forecasting Financial Energy of Households in Poland and Taiwan
PublikacjaThis paper examines the usefulness of statistical methods in forecasting the financial energy of households. The study’s objective is to create the innovative ratios that combine both financial and demographic information of households and implement them in the forecasting models. To conduct this objective, six forecasting models are developed using three different methods—discriminant analysis, logit analysis, and decision trees...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublikacjaShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublikacjaRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Sensors and System for Vehicle Navigation
PublikacjaIn recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications. New technologies, such as multisensory data fusion, big data processing, or deep learning, are changing the quality of areas of applications, improving the sensors and systems used. Recently, the influence of artificial intelligence on sensor data processing and...
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Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublikacjaThis study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly...
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublikacjaAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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Tacit Knowledge Sharing and Project Performance. Does the Knowledge Workers' Personal Branding Matter?
PublikacjaTacit knowledge sharing is the real challenge for knowledge management today. Network economy has completely changed the role of knowledge workers who now become independent tacit knowledge producers. Bearing this fact in mind, the author studied how tacit knowledge sharing affects the process of building a personal brand and project performance. For this purpose, the authors conducted a study among Polish professionals with different...
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Path-based methods on categorical structures for conceptual representation of wikipedia articles
PublikacjaMachine learning algorithms applied to text categorization mostly employ the Bag of Words (BoW) representation to describe the content of the documents. This method has been successfully used in many applications, but it is known to have several limitations. One way of improving text representation is usage of Wikipedia as the lexical knowledge base – an approach that has already shown promising results in many research studies....
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Experience-Oriented Intelligence for Internet of Things
PublikacjaThe Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate...
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High-quality academic teachers in business school. The case of The University of Gdańsk, Poland
PublikacjaThe Bologna process, the increasing number of higher education institutions, the mass education and the demographic problems make the quality of education and quality of the academic teachers a subject of wide public debate and concern. The aim of the paper is to identify the most preferred characteristics of a teacher working at a business school. The research problem was: What should a high-quality business school academic teacher...
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Cross-Cultural Interactions between Expatriates and Local Managers in the Light of Positive Organizational Behaviour
PublikacjaThe main purpose of this article is to identify the ‘individual positive deviance’ presented by expatriates and local managers in their mutual cooperation. The theoretical basis for the publication is the discussion of the Positive Organizational Behaviour (POB) essence and the application of this approach in the area of expatriation. Attitudes, behaviour, working style and personality traits of employees of different nationalities...
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Studia podyplomowe dla nauczycieli przez Internet na przykładzie Gdańska i Warszawy
PublikacjaW artykule przedstawiono studia podyplomowe dla nauczycieli przez Internet realizowane przez Politechnikę Gdańską w ramach współpracy Wydziału Elektroniki, Telekomunikacji i Informatyki oraz Centrum Edukacji Niestacjonarnej. Zaproponowano model kształcenia zintegrowanego, który pozwala na lepsze wykorzystanie materiałów pomocniczych (biblioteki zasobów, linki, testy kontrolne, przykładowe prace dyplomowe z lat poprzednich) oraz...
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Chat GPT Wrote It: What HCI Educators Can Learn from their Students?
PublikacjaRecently students, teachers, and researchers equally have become impressed by Generative AI (GenAI) tools, with ChatGPT at the top. However, numerous concerns about the GenAI-related threats to academic integrity and the validity of learning outcomes are emerging. This problem is also vivid in Human-Computer Interaction (HCI) education since students can use GenAI tools to rapidly generate ideas, user interface templates, screen...
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Civil liability for artificial intelligence products versus the sustainable development of CEECs: which institutions matter?
PublikacjaThe aim of this paper is to conduct a meta-analysis of the EU and CEECs civil liability institutions in order to find out if they are ready for the Artificial Intelligence (AI) race. Particular focus is placed on ascertaining whether civil liability institutions such as the Product Liability Directive (EU) or civil codes (CEECs) will protect consumers and entrepreneurs, as well as ensure undistorted competition. In line with the...
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A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
PublikacjaIn recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones,...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy
PublikacjaEfficient structural reliability analysis method is crucial to solving reliability analysis of complex structural problems. High-computational cost and low-failure probability problems greatly limit the efficiency in structural reliability analysis problems, causing the safety and reliability of the structure to be questioned. In this work, a highly efficient structural reliability analysis method coupling active Kriging algorithm...
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Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublikacjaThis work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...
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Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?
PublikacjaThe estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...
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MOST Wiedzy jako narzędzie promocji otwartych zasobów nauki
PublikacjaRośnie znaczenie wiedzy zgromadzonej w różnego rodzaju systemach, w tym w kursach on-line. Połączenie systemów je przetwarzających z Internetem w znaczącym stopniu usprawniło rozprzestrzenianie informacji i zwiększyło jej dostępność. Coraz szersze uznanie zyskują ruchy Otwartego Dostępu (ang. Open Access). Politechnika Gdańska w ramach projektu Multidyscyplinarny Otwarty System Transferu Wiedzy – MOST Wiedzy buduje platformę o...
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ANALIZA STANU TECHNICZNEGO RUROCIĄGÓW: WODY PRZeMYSŁOWEJ I SOLANKI
PublikacjaPracę wykonano na zlecenie Przedsiębiorstwa Badawczo-Wdrożeniowego "HYDRO-POMP" Sp. z o.o. ul. Wróblewskiego 19, 93-578 Łódź. Wykonawcą zlecenia jest Politechnika Gdańska, Wydział Chemiczny, Katedra Elektrochemii, Korozji i Inżynierii Materiałowej, 80-233 Gdańsk, ul. G. Narutowicza 11/12. Celem pracy była analiza stanu technicznego i badania dwóch rurociągów: solanki oraz wody przemysłowej. Badania wykonywano w warunkach terenowych...
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To Survive in a CBRN Hostile Environment: Application of CAVE Automatic Virtual Environments in First Responder Training
PublikacjaThis paper is of a conceptual nature and focuses on the use of a specific virtual reality environment in civil-military training. We analyzed the didactic potential of so-called CAVE automatic virtual environments for First Responder training, a type of training that fills the gap between First Aid training and the training received by emergency medical technicians. Since real training involves live drills based on unexpected situations,...
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublikacjaThe 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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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublikacjaMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Enabling Deeper Linguistic-based Text Analytics – Construct Development for the Criticality of Negative Service Experience
PublikacjaSignificant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights...
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Advantageous conditions of saccharification of lignocellulosic biomass for biofuels generation via fermentation processes
PublikacjaProcessing of lignocellulosic biomass includes four major unit operations: pre-treatment, hydrolysis, fermentation and product purifcation prior to biofuel generation via anaerobic digestion. The microorganisms involved in the fermentation metabolize only simple molecules, i.e., monosugars which can be obtained by carrying out the degradation of complex polymers, the main component of lignocellulosic biomass. The object of this...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublikacjaThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions
PublikacjaAbstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...
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Online sound restoration system for digital library applications
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Neural network agents trained by declarative programming tutors
PublikacjaThis paper presents an experimental study on the development of a neural network-based agent, trained using data generated using declarative programming. The focus of the study is the application of various agents to solve the classic logic task – The Wumpus World. The paper evaluates the effectiveness of neural-based agents across different map configurations, offering a comparative analysis to underline the strengths and limitations...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublikacjaThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublikacjaModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublikacjaHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Otwarte zasoby edukacyjne - przegląd inicjatyw w Polsce i na świecie
PublikacjaOtwarte zasoby edukacyjne (OZE) to materiały szkoleniowe oraz narzędzia wspierające zarówno uczenie, jak i nauczanie. Zjawisko to nierozerwalnie łączy się z szerszym pojęciem otwartej edukacji (OE), które postuluje zniesienie barier w nauczaniu tak, aby uczący się mogli zdobywać wiedzę zgodnie ze swoimi potrzebami edukacyjno-szkoleniowymi. Celem artykułu jest zapoznanie czytelników z zagadnieniem otwartych zasobów edukacyjnych,...
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Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje
PublikacjaGeneratywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...
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Smartphones as tools for equitable food quality assessment
PublikacjaBackground: The ubiquity of smartphones equipped with an array of sophisticated sensors, ample processing power, network connectivity and a convenient interface makes them a promising tool for non-invasive, portable food quality assessment. Combined with the recent developments in the areas of IoT, deep learning algorithms and cloud computing, they present an opportunity for advancing wide-spread, equitable and sustainable food...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublikacjaThis 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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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...