Records with Subject: Intelligent Systems
Showing records 1 to 25 of 261. [First] Page: 1 2 3 4 5 Last
A Lightweight Identification Method for Complex Power Industry Tasks Based on Knowledge Distillation and Network Pruning
Wendi Wang, Xiangling Zhou, Chengling Jiang, Hong Zhu, Hao Yu, Shufan Wang
February 10, 2024 (v1)
Keywords: knowledge distillation, network pruning, power industry, service identification
Lightweight service identification models are very important for resource-constrained distribution grid systems. To address the increasingly larger deep learning models, we provide a method for the lightweight identification of complex power services based on knowledge distillation and network pruning. Specifically, a pruning method based on Taylor expansion is first used to rank the importance of the parameters of the small-scale network and delete some of the parameters, compressing the model parameters and reducing the amount of operation and complexity. Then, knowledge distillation is used to migrate the knowledge from the large-scale network ResNet50 to the small-scale network so that the small-scale network can fit the soft-label information output from the large-scale neural network through the loss function to complete the knowledge migration of the large-scale neural network. Experimental results show that this method can compress the model size of the small network and improv... [more]
A Fast Workflow for Automatically Extracting the Apparent Attitude of Fractures in 3-D Digital Core Images
Ying Zhou, Deshuang Chang, Jianxiong Zheng, Douxing Zhu, Xin Nie
January 12, 2024 (v1)
Keywords: digital core images, dip angle, dip direction, fracture apparent attitude, least squares
Fractures play a crucial role as fluid conduits and reservoir spaces in reservoirs. The distribution and characteristics of fractures determine the presence of high-quality reservoirs. To accurately analyze and observe fracture parameters, three-dimensional (3-D) digital cores generated from computed tomography (CT) are utilized. However, the current process of extracting fracture properties from these digital cores is time-consuming and labor-intensive. This paper introduces a new, fast, and automatic workflow for extracting the apparent dip angle and direction of fractures from 3-D digital core images. The proposed workflow involves several steps. Firstly, two perpendicular cross-sections are obtained from the digital core and converted into binary images. Next, the coordinates of four fracture feature points within the core image are automatically extracted. The fracture plane is then fitted using the least squares method based on the extracted coordinates. Finally, the apparent dip... [more]
Explainable Machine Learning-Based Method for Fracturing Prediction of Horizontal Shale Oil Wells
Xinju Liu, Tianyang Zhang, Huanying Yang, Shihao Qian, Zhenzhen Dong, Weirong Li, Lu Zou, Zhaoxia Liu, Zhengbo Wang, Tao Zhang, Keze Lin
November 30, 2023 (v1)
Keywords: explainable algorithm, hydraulic fracturing horizontal wells, machine learning productivity prediction model, PSO-GBDT, shale oil
Hydraulic fracturing is a crucial method in shale oil development, and predicting production after hydraulic fracturing is one of the challenges in shale oil development. Conventional methods for predicting production include analytical methods and numerical simulation methods, but these methods involve many parameters, have high uncertainty, and are time-consuming and costly. With the development of shale oil development, there are more and more sample data on the geological parameters, engineering parameters, and development parameters of shale oil hydraulic fracturing, making it possible to use machine learning methods to predict production after hydraulic fracturing. This article first analyzes the impact of different parameters on initial production and recoverable reserves based on field data from Chang-7 shale oil in the Ordos Basin of China. Then, using the Particle Swarm Optimization (PSO) algorithm and the Gradient Boosting Decision Tree (GBDT) algorithm, machine learning mod... [more]
Remaining Useful Life Prediction for Lithium-Ion Batteries Based on a Hybrid Deep Learning Model
Chao Chen, Jie Wei, Zhenhua Li
September 20, 2023 (v1)
Keywords: channel attention mechanism, lithium-ion batteries, long short-term memory, remaining useful life
Lithium-ion batteries are widely utilized in various fields, including aerospace, new energy vehicles, energy storage systems, medical equipment, and security equipment, due to their high energy density, extended lifespan, and lightweight design. Precisely predicting the remaining useful life (RUL) of lithium batteries is crucial for ensuring the safe use of a device. In order to solve the problems of unstable prediction accuracy and difficultly modeling lithium-ion battery RUL with previous methods, this paper combines a channel attention (CA) mechanism and long short-term memory networks (LSTM) to propose a new hybrid CA-LSTM lithium-ion battery RUL prediction model. By incorporating a CA mechanism, the utilization of local features in situations where data are limited can be improved. Additionally, the CA mechanism can effectively mitigate the impact of battery capacity rebound on the model during lithium-ion battery charging and discharging cycles. In order to ensure the full valid... [more]
A Novel Cellular Network Traffic Prediction Algorithm Based on Graph Convolution Neural Networks and Long Short-Term Memory through Extraction of Spatial-Temporal Characteristics
Geng Chen, Yishan Guo, Qingtian Zeng, Yudong Zhang
September 20, 2023 (v1)
Keywords: cellular network, graph convolutional neural networks, RMSE, short and long-term memory networks, traffic prediction
In recent years, cellular communication systems have continued to develop in the direction of intelligence. The demand for cellular networks is increasing as they meet the public’s pursuit of a better life. Accurate prediction of cellular network traffic can help operators avoid wasting resources and improve management efficiency. Traditional prediction methods can no longer perfectly cope with the highly complex spatiotemporal relationships of the current cellular networks, and prediction methods based on deep learning are constantly growing. In this paper, a spatial-temporal parallel prediction model based on graph convolution combined with long and short-term memory networks (STP-GLN) is proposed to effectively capture spatial-temporal characteristics and to obtain accurate prediction results. STP-GLN is mainly composed of a spatial module and temporal module. Among them, the spatial module designs dynamic graph data based on the principle of spatial distance and spatial correlation... [more]
Study on Multi-Objective Optimization of Logistics Distribution Paths in Smart Manufacturing Workshops Based on Time Tolerance and Low Carbon Emissions
Chao Wu, Yongmao Xiao, Xiaoyong Zhu, Gongwei Xiao
July 7, 2023 (v1)
Keywords: low carbon emission, path optimization, smart manufacturing, time tolerance, workshop logistics distribution
In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A “time window span” was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of impr... [more]
Framework for the Implementation of Smart Manufacturing Systems: A Case in Point
Muhammad Hammad, Md Shamimul Islam, Mohammad Asif Salam, Ali Turab Jafry, Inayat Ali, Wasim Ahmed Khan
June 7, 2023 (v1)
Keywords: framework, fuzzy DEMATEL, sensitivity analysis, significant attributes, smart manufacturing
Smart manufacturing has become a vital technique for increasing productivity and efficiency. Firms are following a smart manufacturing implementation system to compete in the market. Therefore, it is mandatory to find the crucial factors that enable the implementation of intelligent manufacturing in enterprises. This study proposes the framework for a new model factory based on the three-dimensional model that extends the product lifecycle layer. It also analyzes the significant attributes and interdependence relationships of causes and effects through the fuzzy DEMATEL approach for the selected small and medium enterprises discussed as a case study. The results show that the factors in Region 1 are significant attributes that need to be focused on for the development and establishment of small and medium enterprises under consideration. These attributes include design documentation (A11), intelligently management of small and medium enterprises (A3), visualization and monitoring of lo... [more]
Situational Awareness for Smart Distribution Systems
Leijiao Ge, Jun Yan, Yonghui Sun, Zhongguan Wang
April 28, 2023 (v1)
In recent years, the accelerating climate change and intensifying natural disasters have called for more renewable, resilient, and reliable energy from more distributed sources to more diversified consumers, resulting in a pressing need for advanced situational awareness of modern smart distribution systems [...]
Wireless Rechargeable Sensor Networks
Chang-Wu Yu
April 28, 2023 (v1)
Wireless sensor networks have attracted much attention recently due to their various applications in many fields [...]
Intelligent Diagnosis Model of Working Conditions in Variable Torque Pumping Unit Wells Based on an Electric Power Diagram
Ruichao Zhang, Dechun Chen, Nu Lu, Bo Zhang, Yanjie Yang
April 28, 2023 (v1)
Keywords: dynamometer card, eigenvalue extraction, electric power diagram calculation, intelligent, working condition diagnosis
Because of the problems, such as the lack of an electric power diagram atlas under different working conditions and the difficulty in intelligent diagnosis of variable torqued pumping unit wells, this paper proposes a diagnosis model of working conditions based on feature recognition. The mathematical relationship model between the polished rod load and motor output power is derived based on the analysis of geometric structure, motion law, and process of energy transformation and transfer of the variable torque pumping unit. It can calculate the electric power diagram based on a dynamometer card. On this basis, the electric power diagram atlas is created, and the feature analysis and eigenvalue extraction of the electric power diagrams under different working conditions are carried out to realize the direct diagnosis of the working conditions in the variable torque pumping unit wells. The application and analysis of examples show that the electric power diagram atlas created in this pa... [more]
Implementation of “Smart” Solutions and An Attempt to Measure Them: A Case Study of Czestochowa, Poland
Renata Biadacz, Marek Biadacz
April 27, 2023 (v1)
Keywords: intelligent transportation system, smart city, smart mobility
The aim of the study is to present the implemented “smart” solutions and the developed indicators of their measurement in the context of the city of Częstochowa (Poland), as well as a participant in the “Benchmarking—we are looking for the best smart city solutions”. In order to achieve the assumed goal, a traditional review of the literature on the subject in the field of “smart city” was carried out. Then, the methodological assumptions related to developing a model set of indicators for cities participating in the program have been presented. In addition, a comparative analysis of the obtained indicators values for cities, Częstochowa and Bydgoszcz, has been carried out in the scope of one exemplary measure. The proposed research procedure can be used to analyze and evaluate cities in the country, as well as to select alternative solutions in the context of other urban features. Due to the fact that other cities in Poland will also participate in the study, the significance of this... [more]
Improving the Efficiency of Information Flow Routing in Wireless Self-Organizing Networks Based on Natural Computing
Krzysztof Przystupa, Julia Pyrih, Mykola Beshley, Mykhailo Klymash, Andriy Branytskyy, Halyna Beshley, Daniel Pieniak, Konrad Gauda
April 26, 2023 (v1)
Keywords: ant algorithm, k-means, signal-to-noise ratio (SNR), simulated annealing
With the constant growth of requirements to the quality of infocommunication services, special attention is paid to the management of information transfer in wireless self-organizing networks. The clustering algorithm based on the Motley signal propagation model has been improved, resulting in cluster formation based on the criterion of shortest distance and maximum signal power value. It is shown that the use of the improved clustering algorithm compared to its classical version is more efficient for the route search process. Ant and simulated annealing algorithms are presented to perform route search in a wireless sensor network based on the value of the quality of service parameter. A comprehensive routing method based on finding the global extremum of an ordered random search with node addition/removal is proposed by using the presented ant and simulated annealing algorithms. It is shown that the integration of the proposed clustering and routing solutions can reduce the route sear... [more]
Enhancing User Experiences with Cloud Computing via Improving Utilitarian and Hedonic Factors
Juthamon Sithipolvanichgul, Charlie Chen, Judy Land, Peter Ractham
April 26, 2023 (v1)
Keywords: cloud computing, hedonic factors, perceived risk, user experiences, utilitarian factors
This study provides insights into the initial and post-adoption of cloud computing services by integrating information technology adoption, social influence, trust, security, and information systems quality theories. Social influence, hedonicity, and automaticity are hedonic predictors of user satisfaction with cloud computing services. Perceived risks, trust in the provider, and system quality are utilitarian predictors of user satisfaction with cloud computing services. The Partial Least Squares (PLS) was employed to test eight hypotheses on the causal relationships between the variables. Six out of eight hypotheses were supported. Hedonic factors appear to have more influence than the utilitarian factor of increasing user satisfaction with cloud computing services in the school setting. The findings lead to both theoretical and practical implications for improving the initial and post-adoption of cloud computing services.
Computational Intelligent Approaches for Non-Technical Losses Management of Electricity
Rubén González Rodríguez, Jamer Jiménez Mares, Christian G. Quintero M.
April 25, 2023 (v1)
Keywords: fraud detection, intelligent systems, irregular electricity consumption, non-technical losses
This paper presents an intelligent system for the detection of non-technical losses of electrical energy associated with the fraudulent behaviors of system users. This proposal has three stages: a non-supervised clustering of consumption profiles based on a hybrid algorithm between self-organizing maps (SOM) and genetic algorithms (GA). A second stage for demand forecasting is based on ARIMA (autoregressive integrated moving average) models corrected intelligently through neural networks (ANN). The final stage is a classifier based on random forests for fraudulent user detection. The proposed intelligent approach was trained and tested with real data from the Colombian Caribbean region, where the utility reports energy losses of around 18% of the total energy purchased by the company during the five last years. The results show an average overall performance of 82.9% in the detection process of fraudulent users, significantly increasing the effectiveness compared to the approaches (68%... [more]
An Integrated Fuzzy DEMATEL and Fuzzy TOPSIS Method for Analyzing Smart Manufacturing Technologies
Fawaz M. Abdullah, Abdulrahman M. Al-Ahmari, Saqib Anwar
April 25, 2023 (v1)
Keywords: digitalization, fuzzy DEMATEL, fuzzy TOPSIS, Industry 4.0, manufacturing strategies, MCDM
I4.0 promotes a future in which highly individualized goods are mass produced at a competitive price through autonomous, responsive manufacturing. In order to attain market competitiveness, organizations require proper integration of I4.0 technologies and manufacturing strategy outputs (MSOs). Implementing such a comprehensive integration relies on carefully selecting I4.0 technologies to meet industrial requirements. There is little clarity on the impact of I4.0 technologies on MSOs, and the literature provides little attention to this topic. This research investigates the influence of I4.0 technologies on MSOs by combining reliable MCDM methods. This research uses a combination of fuzzy DEMATEL and fuzzy TOPSIS to evaluate the impact of I4.0 technologies on MSOs. The fuzzy theory is implemented in DEMATEL and TOPSIS to deal with the uncertainty and vagueness of human judgment. The FDEMATEL was utilized to identify interrelationships and determine criterion a’s weights, while the fuzz... [more]
Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
Stanisław Duer, Jan Valicek, Jacek Paś, Marek Stawowy, Dariusz Bernatowicz, Radosław Duer, Marcin Walczak
April 19, 2023 (v1)
Keywords: diagnostic information, diagnostic process, expert system, intelligent systems, knowledge base, low-power solar plant devices, neural networks, servicing process
The article presents the problems of diagnostics of low-power solar power plants with the use of the three-valued (3VL) state assessment {2, 1, 0}. The 3VL diagnostics is developed on the basis of two-valued diagnostics (2VL), and it is elaborated on. In the (3VL) diagnostics, the range of changes in the values of the signals from the 2VL logic was accepted for the serviceability condition: state {12VL}. This range of signal value changes for logic (3VL) was divided into two signal value change sub-ranges, which were assigned two status values in the logic (3VL): {23VL}—serviceability condition and {13VL}—incomplete serviceability condition. The state of failure for both logics applied of the valence of states is interpreted equally for the same changes in the values of diagnostic signals, the possible changes of which exceed the ranges of their permissible changes. The DIAG 2 intelligent system based on an artificial neural network was used in diagnostic tests. For this purpose, the a... [more]
Modeling the Effectiveness of Intelligent Systems in Public Transport That Uses Low-Carbon Energy: A Case Study
Justyna Patalas-Maliszewska, Hanna Łosyk, Jacek Newelski
April 19, 2023 (v1)
Keywords: electric buses, intelligent transportation system, public transport, smart city, smart mobility
Cities have been struggling for many years with many transport problems, including the impact of carbon monoxide emitted by vehicles on the environment, traffic jams, high energy consumption, numerous accidents or high infrastructure costs. There is also a dynamic growth of vehicles on the roads, which is why an increasing number of cities are introducing intelligent transportation systems (ITS), which is part of the concept of smart cities. This paper proposes a new matrix to assess the effects of the ITS implementation in the context of a concept Smart City, which consists of five criteria: (1) movement speed; (2) safety; (3) environmental; (4) economic; (5) satisfaction and amenities for society/passengers. In this new approach the benchmark values of the indicators assigned to the criteria are involved and, therefore, it is possible to determine the level of effectiveness of the ITS in public transport that uses low-carbon energy. This research used literature studies to establish... [more]
Reliability Testing of Wind Farm Devices Based on the Mean Time to Failures
Stanisław Duer, Marek Woźniak, Jacek Paś, Konrad Zajkowski, Arkadiusz Ostrowski, Marek Stawowy, Zbigniew Budniak
April 18, 2023 (v1)
Keywords: diagnostic process, expert system, intelligent systems, knowledge base, Mean Time to Failure (MTTF), reliability, servicing process, wind farm device
Nowadays, one of the main sources of renewable energy is wind energy; therefore, a wind farm’s electricity system must be effective. As a result, wind farm (WF) equipment must continuously operate without failure or damage. To achieve this, it is necessary to regularly monitor and assess the reliability of WF systems at every point of their “life”, including design, implementation, and continued use. Three key goals are presented in the article. First, a theory of fundamental theoretical quantities that can be used in reliability and maintenance analysis is presented. The second is to put forth a theoretical reliability link between mean time to failure and WF system fitness probability (Mean Time to Failures (MTTF—Mean time between failures. MTTF = t1 + t2 + … + tn/m, where: m—the number of all failures at time T, ti—i—ty time to failure)). The third goal is to analyze the time to failure as a function of service life and to assess the dependability of the WF under consideration as a... [more]
Innovation Management in Polish Real Estate Developers in the Renewable Energy Sources Context
Marcin Sitek, Manuela Tvaronavičienė
April 14, 2023 (v1)
Keywords: green building, housing projects management, innovations, real estate developers, renewable energy sources, sustainable construction
This paper analyses innovative activities, including renewable energy sources (RES) in the housing market, the motivations for their introduction, effectiveness, benefits, limitations and management—which are open and current problems of Polish and international sustainable construction. This problem is part of a research gap concerning, among others, the role of developers and entities responsible for introducing energy innovations into housing construction. The aim of the paper is to analyse innovations, with particular emphasis on RES, introduced by residential developers in Poland in the context of global trends. The work is based on the results of surveys conducted among developers of the primary housing market. The research of 130 questionnaires received from entities such as multi-storey buildings and multi-family houses in Poland, was carried out on a nationwide sample using the CATI Computer Assisted Telephone Interview method. The results of the survey research were summarize... [more]
Development of an Intelligent System for Distance Relay Protection with Adaptive Algorithms for Determining the Operation Setpoints
Olga Akhmedova, Anatoliy Soshinov, Farit Gazizov, Svetlana Ilyashenko
April 13, 2023 (v1)
Keywords: external environmental parameters, failure, Fault Detection, overhead power transmission lines, power systems, relay protection
The drastic consequences of emergencies force us to look for ways to increase the stability of the device operation at overhead power transmission lines (OHPTL). It can be achieved by developing new algorithms for determining the protection operation setpoints and detecting the damage location. Fault detection at OHPTL of 10 kV and above is mainly carried out by the devices based on the measurement of emergency mode parameters. For fault detecting one should analyze the parameters of not only current and voltage at the accident time, but also of the overhead power line. Specific active resistance, specific reactance, specific active conductivity and specific reactive conductivity are used to characterize the overhead power transmission lines. As a rule, these parameters are normalized to the unit of length of the overhead line (OHL) and linear values are used in the calculations. When analyzing power lines, tabular approximate values of longitudinal and transversal parameters in equiva... [more]
Intelligent Systems for Power Load Forecasting: A Study Review
Ibrahim Salem Jahan, Vaclav Snasel, Stanislav Misak
April 4, 2023 (v1)
Keywords: load forecasting, off-grid system, renewable energy sources, smart system, weather data
The study of power load forecasting is gaining greater significance nowadays, particularly with the use and integration of renewable power sources and external power stations. Power forecasting is an important task in the planning, control, and operation of utility power systems. In addition, load forecasting (LF) aims to estimate the power or energy needed to meet the required power or energy to supply the specific load. In this article, we introduce, review and compare different power load forecasting techniques. Our goal is to help in the process of explaining the problem of power load forecasting via brief descriptions of the proposed methods applied in the last decade. The study reviews previous research that deals with the design of intelligent systems for power forecasting using various methods. The methods are organized into five groups—Artificial Neural Network (ANN), Support Vector Regression, Decision Tree (DT), Linear Regression (LR), and Fuzzy Sets (FS). This way, the revi... [more]
Toward Sustainable Energy-Independent Buildings Using Internet of Things
Naser Hossein Motlagh, Ali Khatibi, Alireza Aslani
April 4, 2023 (v1)
Keywords: building energy management, intelligent system, internet of things, nearly zero-energy buildings, photovoltaic panel, smart homes, solar systems
Buildings are one of the primary consumers of energy. In addition to the electricity grids, renewable energies can be used to supply the energy demand of buildings. Intelligent systems such as the Internet of Things (IoT) and wireless sensor technologies can also be applied to manage the energy consumption in buildings. Fortunately, integrating renewable energies with these intelligent systems enables creating nearly zero-energy buildings. In this paper, we present the results of our experimentation to demonstrate forming such a building and showing the benefits for building users and the society. We create a system by integrating photovoltaic (PV) technology with an IoT-based control mechanism to supply and consume energy. We further illustrate “how the integration of IoT and PV technology can bring added value to the users?”. To this end, we evaluate the performance of our system against conventional ways of energy supply and consumption for a lighting use case in a dairy store. We a... [more]
Neural Methods Comparison for Prediction of Heating Energy Based on Few Hundreds Enhanced Buildings in Four Season’s Climate
Tomasz Szul, Krzysztof Nęcka, Thomas G. Mathia
April 3, 2023 (v1)
Keywords: building energy consumption, building load forecasting, Energy Efficiency, Machine Learning, neural methods, smart intelligent systems, thermal improved of buildings
Sustainable development and the increasing demand for equitable energy use as well as the reduction of waste of energy are the author’s social and scientific motivations. This new paradigm is the selection of a pertinent methodology to evaluate the efficiency of habitat thermomodernization, which is one of the scientific tasks of the presented study. In order to meet the social and scientific requirements, 380 buildings from the end of the last century (made of large plate technology), which were thermally improved at the beginning of the XXI century, were designed for a comparative analysis of the predictive modelling of heating energy consumption. A specific set of important variables characterizing the examined buildings has been identified. Groups of variables were used to estimate the energy consumption in such a way as to achieve a compromise between the difficulty of obtaining them and the quality of forecast. To predict energy consumption, the six most appropriate neural method... [more]
Review on the Status of the Research on Power-to-Gas Experimental Activities
Andrea Barbaresi, Mirko Morini, Agostino Gambarotta
March 28, 2023 (v1)
Keywords: Energy Storage, Hydrogen, methanation, power-to-gas, project overview, smart energy systems
In recent years, power-to-gas technologies have been gaining ground and are increasingly proving their reliability. The possibility of implementing long-term energy storage and that of being able to capture and utilize carbon dioxide are currently too important to be ignored. However, systems of this type are not yet experiencing extensive realization in practice. In this study, an overview of the experimental research projects and the research and development activities that are currently part of the power-to-gas research line is presented. By means of a bibliographical and sitographical analysis, it was possible to identify the characteristics of these projects and their distinctive points. In addition, the main research targets distinguishing these projects are presented. This provides an insight into the research direction in this regard, where a certain technological maturity has been achieved and where there is still work to be done. The projects found and analyzed amount to 87,... [more]
Residents’ Attitudes and Social Innovation Management in the Example of a Municipal Property Manager
Judyta Kabus, Michał Dziadkiewicz
March 28, 2023 (v1)
Keywords: corporate social responsibility, management, municipal manager, social innovation
Corporate responsibility is an effective management strategy which, through conducting social dialogue at the local level, contributes to increasing the competitiveness of enterprises at a global level and simultaneously shaping favourable conditions for social and economic development. A review of the literature on the subject provided the theoretical motivation to undertake an emirical study of the implemented social innovations by the property manager and their reception by resource residents. The main aim of this study was to diagnose the attitudes of residents towards the implementation of social innovations by the municipal property manager. The research presented in the above article has been conducted in the first and second quarter of 2021 among residents of the Department of Housing “TBS” (ZGM TBS) in Częstochowa, Silesian voivoideship, Poland. The research was conducted using the survey method. The measurement instrument was a prepared questionnaire. The survey was completed... [more]
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