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Tytuł:
AI-supported reasoning in physiotherapy
Wnioskowanie w fizjoterapii wspierane sztuczną inteligencją
Autorzy:
Mikołajewski, Dariusz
Mikołajewska, Emilia
Powiązania:
https://bibliotekanauki.pl/articles/41203435.pdf
Data publikacji:
2024
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Tematy:
artificial intelligence
machine learning
clinical reasoning
clinical decision support system
interview
musculoskeletal pain disorders
physiotherapy
usability
recommender system
self-management
mHealth
sztuczna inteligencja
uczenie maszynowe
wnioskowanie kliniczne
system wspomagania decyzji klinicznych
wywiad
zaburzenia bólowe układu mięśniowo-szkieletowego
fizjoterapia
użyteczność
system rekomendacji
samokontrola
mZdrowie
Opis:
Artificial intelligence (AI)-based clinical reasoning support systems in physiotherapy, and in particular data-driven (machine learning) systems, can be useful in making and reviewing decisions regarding functional diagnosis and formulating/maintaining/modifying a rehabilitation programme. The aim of this article is to explore the extent to which the opportunities offered by AI-based systems for clinical reasoning in physiotherapy have been exploited and where the potential for their further stimulated development lies.
Systemy wspomagania wnioskowania klinicznego w fizjoterapii oparte na sztucznej inteligencji, a w szczególności na danych (uczenie maszynowe), mogą być przydatne w podejmowaniu i weryfikacji decyzji dotyczących diagnostyki funkcjonalnej ora formułowania/utrzymywania/modyfikowania programu rehabilitacji. Celem niniejszego artykułu jest zbadanie, w jakim stopniu możliwości oferowane przez systemy oparte na sztucznej inteligencji w zakresie rozumowania klinicznego w fizjoterapii zostały wykorzystane i gdzie leży potencjał ich dalszego stymulowanego rozwoju.
Źródło:
Studia i Materiały Informatyki Stosowanej; 2024, 16, 2; 21-27
1689-6300
Pojawia się w:
Studia i Materiały Informatyki Stosowanej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A COLREGs-compliant decision support tool to prevent collisions at sea
Autorzy:
Martelli, M.
Žuškin, S.
Zaccone, R.
Rudan, I.
Powiązania:
https://bibliotekanauki.pl/articles/24201449.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
analysis of ship collision
collision avoidance
collision avoidance decision making
collision avoidance system
anti-collision maneuvering
autonomous control unit
autonomous ship
autonomous navigation system
Opis:
Groundings and collisions still represent the highest percentage of marine accidents despite the current attention on Maritime Education and Training and the improvement of sensor capability. Most of the time, a collision is caused by a human error with consequences ranging from moderate to severe, with a substantial impact on both environment and life safeguarded at sea. In this paper, a brief statistical data regarding human element as a root cause of marine incidents together with collision regulations misunderstanding is presented as a background chapter. Furthermore, the present work discusses a decision support system architecture to suggest an appropriate action when the risk of a potential collision is detected. The proposed architecture system is based on various modules integrated with proper sensor input data regarding the surrounding navigation area. As a result, the tool can support the Officers of Watch in the decision-making process providing an early suggestion in compliance with the COLlision REGulations. The proposed system is intended to be used onboard independently from the degree of automation of the ship, and it is based on AIS, which is mandatory, making it widely applicable. The proper use of the system can considerably reduce the number of collisions, as demonstrated by the obtained results.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 2; 347--353
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A comparative study on performance of basic and ensemble classifiers with various datasets
Autorzy:
Gunakala, Archana
Shahid, Afzal Hussain
Powiązania:
https://bibliotekanauki.pl/articles/30148255.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
classification
Naïve Bayes
neural network
Support Vector Machine
Decision Tree
ensemble learning
Random Forest
Opis:
Classification plays a critical role in machine learning (ML) systems for processing images, text and high -dimensional data. Predicting class labels from training data is the primary goal of classification. An optimal model for a particular classification problem is chosen based on the model's performance and execution time. This paper compares and analyzes the performance of basic as well as ensemble classifiers utilizing 10-fold cross validation and also discusses their essential concepts, advantages, and disadvantages. In this study five basic classifiers namely Naïve Bayes (NB), Multi-layer Perceptron (MLP), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) and the ensemble of all the five classifiers along with few more combinations are compared with five University of California Irvine (UCI) ML Repository datasets and a Diabetes Health Indicators dataset from Kaggle repository. To analyze and compare the performance of classifiers, evaluation metrics like Accuracy, Recall, Precision, Area Under Curve (AUC) and F-Score are used. Experimental results showed that SVM performs best on two out of the six datasets (Diabetes Health Indicators and waveform), RF performs best for Arrhythmia, Sonar, Tic-tac-toe datasets, and the best ensemble combination is found to be DT+SVM+RF on Ionosphere dataset having respective accuracies 72.58%, 90.38%, 81.63%, 73.59%, 94.78% and 94.01%. The proposed ensemble combinations outperformed the conven¬tional models for few datasets.
Źródło:
Applied Computer Science; 2023, 19, 1; 107-132
1895-3735
2353-6977
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial Neural Networks as a Tool for Supporting a Moulding Sand Control System Based on the Dependency between Selected Moulding Sand Properties
Autorzy:
Mrzygłód, Barbara
Jakubski, Jarosław
Opaliński, Andrzej
Regulski, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/24201264.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
artificial neural network
decision support
green moulding sand
compactibility
Opis:
The article presents the potential for using artificial neural networks to support decisions related to the rebonding of green moulding sand. The basic properties of the moulding sand tested in foundries are discussed, especially compactibility as it gives the most information about the quality of green moulding sand. First, the data that can predict the compactibility value without the need for testing are defined. Next, a method for constructing an artificial neural network is presented and the network model which produced the best results is analysed. Additionally, two applications were designed to allow the investigation results to be searchable by determining the range of values of the moulding sand parameters.
Źródło:
Journal of Casting & Materials Engineering; 2023, 7, 2; 15--21
2543-9901
Pojawia się w:
Journal of Casting & Materials Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combining predictive distributions of electricity prices : does minimizing the CRPS lead to optimal decisions in day-ahead bidding?
Autorzy:
Nitka, Weronika
Weron, Rafał
Powiązania:
https://bibliotekanauki.pl/articles/27315321.pdf
Data publikacji:
2023
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
decision support
day-ahead electricity bidding
predictive distribution
combining forecast
CRPS learning
Opis:
Probabilistic price forecasting has recently gained attention in power trading because decisions based on such predictions can yield significantly higher profits than those made with point forecasts alone. At the same time, methods are being developed to combine predictive distributions, since no model is perfect and averaging generally improves forecasting performance. In this article, we address the question of whether using CRPS learning, a novel weighting technique minimizing the continuous ranked probability score (CRPS), leads to optimal decisions in day-ahead bidding. To this end, we conduct an empirical study using hourly day-ahead electricity prices from the German EPEX market. We find that increasing the diversity of an ensemble can have a positive impact on accuracy. At the same time, the higher computational cost of using CRPS learning compared to an equal-weighted aggregation of distributions is not offset by higher profits, despite significantly more accurate predictions.
Źródło:
Operations Research and Decisions; 2023, 33, 3; 105--118
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decision-Making Supporting Models Concerning the Internal Security of the State
Autorzy:
Kovalchuk, Oleg
Kasianchuk, Mykhailo
Karpinski, Mikolaj
Shevchuk, Ruslan
Powiązania:
https://bibliotekanauki.pl/articles/27311918.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
information security of the state
decision-making
information and analytical support
internal security
model
Opis:
In the digital society, states’ information security has become one of the key elements of ensuring the competitiveness and sustainable development of the state, guaranteeing its integrity and security in general. An important component of state security is the internal security of the state, which must ensure the personal and public safety of its citizens. Modern Ukraine is building a new system of criminal justice, which requires a new information system for risk assessment and support for optimal decision-making. Today, applied research and the development of information and analytical software for the internal security of the state have acquired a special meaning. In the paper, there is built a set of models for providing operational information for decision-making in criminal justice. This is a cluster model for creating criminal profiles of convicts, and a scoring model for identifying individual characteristics of criminals that have the greatest impact on their propensity to reoffend. The obtained models can provide reliable support for decision-making in the field of criminal justice and become part of the information support system for the internal security of Ukraine in general.
Źródło:
International Journal of Electronics and Telecommunications; 2023, 69, 2; 301--307
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Designing Smart Antennas Using Machine Learning Algorithms
Autorzy:
Samantaray, Barsa
Das, Kunal Kumar
Roy, Jibendu Sekhar
Powiązania:
https://bibliotekanauki.pl/articles/27312957.pdf
Data publikacji:
2023
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
artificial neural network
decision tree
ensemble algorithm
machine learning
smart antenna
support vector machine
Opis:
Smart antenna technologies improve spectral efficiency, security, energy efficiency, and overall service quality in cellular networks by utilizing signal processing algorithms that provide radiation beams to users while producing nulls for interferers. In this paper, the performance of such ML solutions as the support vector machine (SVM) algorithm, the artificial neural network (ANN), the ensemble algorithm (EA), and the decision tree (DT) algorithm used for forming the beam of smart antennas are compared. A smart antenna array made up of 10 half-wave dipoles is considered. The ANN method is better than the remaining approaches when it comes to achieving beam and null directions, whereas EA offers better performance in terms of reducing the side lobe level (SLL). The maximum SLL is achieved using EA for all the user directions. The performance of the ANN algorithm in terms of forming the beam of a smart antenna is also compared with that of the variable-step size adaptive algorithm.
Źródło:
Journal of Telecommunications and Information Technology; 2023, 4; 46--52
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Developing a Decision Support System for Supply Chain Component
Autorzy:
Andry, Johanes Fernandes
Nurprihatin, Filscha
Liliana, Lydia
Powiązania:
https://bibliotekanauki.pl/articles/24200510.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
decision support system
extreme programming
furniture manufacture industry
supply chain
Opis:
Increased competition has led businesses to compete with each other in streamlining supply chain processes, especially in the manufacturing sector. Supply Chain Management (SCM) determines the success of industrial business processes because it regulates product flow regarding integration, performance, and information. However, several problems have emerged in the supply chain process, such as a lack of coordination in the production queue, difficulties in forecasting trending products, and suboptimal production capacity. To address these issues, the role of information technology is crucial for implementing a Decision Support System (DSS). This study aims to develop a DSS to improve the supply chain processes. The research method used is Extreme Programming (XP) with a qualitative approach through a questionnaire. The research process involves collecting data, defining boundaries and problems, and designing, coding, and testing the system. As a final step, evaluation is carried out by distributing surveys to obtain valid satisfaction results. This research produces a DSS that has applicability in marketing, accounting, and production processes. The application of DSS in the furniture manufacturing industry can help manage the movement of resources, optimize strategic networks, and assist decision-making in the supply chain process.
Źródło:
Management and Production Engineering Review; 2023, 14, 2; 124--133
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy Multi-criteria Decision Model to Support Product Quality Improvement
Autorzy:
Siwiec, Dominika
Gawlik, Remigiusz
Pacana, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/24200512.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
production engineering
decision support
quality
FAHP
FTOPSIS
multi-criteria decision making
Opis:
Improving product quality while making decisions remains a challenge. The objective of this research was to develop a model that supports the precise enhancement of product quality through comprehensive analysis of possibilities, product incompatibilities, root causes, and recommended improvement actions. The model incorporated various tools and methods such as the SMARTER method, expert team selection, brainstorming, Ishikawa diagram, 5M+E rule, FAHP, and FTOPSIS methods. The study demonstrated that integrating quality management tools and decision-making methods into a unified model enables the accurate prioritization of activities for product quality management. This integrated approach represents the novelty of this research. The model was evaluated using a mechanical seal made of 410 alloy. The research findings can be valuable to enterprises seeking to enhance product quality at any stage of production, particularly for modified or new products.
Źródło:
Management and Production Engineering Review; 2023, 14, 2; 134--149
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Integration test procedures for a collision avoidance decision support system using STPA
Autorzy:
Dugan, S.
Skjetne, R.
Wróbel, K.
Montewka, J.
Gil, M.
Utne, J. B.
Powiązania:
https://bibliotekanauki.pl/articles/24201452.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Opis:
The transition from conventionally manned to autonomous ships is accompanied by the development of enhanced Decision Support Systems (DSS) for navigators. Such systems need to consider interactions among hardware, software, and humans and their potential effects on system performance, which require rigorous testing to verify the system's safe decision-making ability and operational limits. Testing requirements for verification are aimed at 1) assessing the system's reliability and failure handling performance, and 2) integration testing. This work uses the System-Theoretic Process Analysis (STPA) to develop integration tests for a novel DSS. STPA is a structured methodology to identify hazards from multiple sources, including hardware or software failures, system interactions, and human errors. The objectives of the study are to develop and assess the feasibility of integration test procedures based on STPA. The stability monitoring subsystem from the DSS is analyzed as a case study. The results are used to suggest functional and performance integration test procedures.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 2; 375--381
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-criteria decision support methods for the selection of the optimum contractor: A case study of a passenger transfer centre
Autorzy:
Łopatka, Paweł
Tłuczak, Agnieszka
Jadach, Robert
Powiązania:
https://bibliotekanauki.pl/articles/27324304.pdf
Data publikacji:
2023
Wydawca:
Fundacja Centrum Badań Socjologicznych
Tematy:
TOPSIS
logistics projects
passenger transfer centre
Opis:
Purpose: The main purpose of the paper is to apply the TOPSIS method for selecting the optimal contractor for a passenger transfer center. Methodology: The methodology is based on the use of TOPSIS, which determines the distance of decision alternatives from the ideal and anti-ideal solutions using evaluation criteria. Results: Two different contractor rankings were obtained depending on the weights of the criteria. With equal weights, the best contractor is number 5, while with weights determined by formula (8), the best is number 4. Theoretical Contribution: The paper contributes to the field of investment project management by demonstrating how the TOPSIS method can aid in decision-making for optimal contractor selection, thereby reducing the risk of erroneous decisions. Practical Implications: The practical implications of this research are significant for investment projects, as the demonstrated methodology can be directly applied to the contractor selection process, potentially leading to more successful project outcomes.
Źródło:
Journal of Sustainable Development of Transport and Logistics; 2023, 8, 2; 219--228
2520-2979
Pojawia się w:
Journal of Sustainable Development of Transport and Logistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multifaceted decision support analysis of risk assessment in the process of transporting feed by rail transport using the FMEA method
Autorzy:
Krześniak, Mirosław
Szaciłło, Lucyna
Powiązania:
https://bibliotekanauki.pl/articles/38955608.pdf
Data publikacji:
2023
Wydawca:
Politechnika Warszawska, Wydział Transportu
Tematy:
FMEA
freight process
GMP+ System
proces spedycji
Opis:
The article presents selected aspects regarding transporting goods intended for animal feeding. The transport of this type of cargo must meet trade safety requirements and be monitored at every stage of the transport chain. The safety of transport of this type of goods is given priority because possible contamination of feed could affect the quality of food products and threaten human health. The authors referred to the reasons for creating an international procedure regarding, among others, the transport of this group of goods, limiting the risks mentioned above. The proposed procedure is a response to various incidents of feed contamination. It was introduced as an internal system and then developed internationally. The article points to the multi-threaded nature of topics related to the risk management process during the transport of feed intended for animal feeding by rail. This article presents an approach to this issue that considers a multi-aspect analysis of decision support. Risk assessment in transporting feed by rail is an essential factor influencing safety in trade. The article presents the FMEA method, which enables decision support analysis considering non-compliance risk. The recommended method that enables the examination of transport processes for this group of goods is the analysis of the types and effects of possible errors. The task solved using the FMEA method is fed by historical data, the transport task, and the FMEA methodology. Three elements are analyzed - the significance of non-compliance, the risk of non-compliance, and the possibility of detecting non-compliance. They enable quantification and determination of a risk priority number. If the acceptable risk level is exceeded, changes are made to the transport task. The article broadly refers to aspects of risk analysis, which allows you to manage the transport process.
Źródło:
WUT Journal of Transportation Engineering; 2023, 137; 115-131
1230-9265
Pojawia się w:
WUT Journal of Transportation Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of Selected Mechanical Properties in Austempered Ductile Iron with Different Wall Thickness by the Decision Support Systems
Autorzy:
Jaśkowiec, Krzysztof
Opaliński, Andrzej
Kustra, Piotr
Jach, D.
Wilk-Kołodziejczyk, Dorota
Powiązania:
https://bibliotekanauki.pl/articles/27314159.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
ADI
austempered ductile iron
mechanical properties
prediction
decision support systems
decision tree
żeliwo sferoidalne
właściwości mechaniczne
prognozowanie
systemy wspomagania decyzji
Opis:
The structure of Austempered Ductile Iron (ADI) is depend of many factors at individual stages of casting production. There is a rich literature documenting research on the relationship between heat treatment and the resulting microstructure of cast alloy. A significant amount of research is conducted towards the use of IT tools for indications production parameters for thin-walled castings, allowing for the selection of selected process parameters in order to obtain the expected properties. At the same time, the selection of these parameters should make it possible to obtain as few defects as possible. The input parameters of the solver is chemical composition Determined by the previous system module. Target wall thickness and HB of the product determined by the user. The method used to implement the solver is the method of Particle Swarm Optimization (PSO). The developed IT tool was used to determine the parameters of heat treatment, which will ensure obtaining the expected value for hardness. In the first stage, the ADI cast iron heat treatment parameters proposed by the expert were used, in the next part of the experiment, the settings proposed by the system were used. Used of the proposed IT tool, it was possible to reduce the number of deficiencies by 3%. The use of the solver in the case of castings with a wall thickness of 25 mm and 41 mm allowed to indication of process parameters allowing to obtain minimum mechanical properties in accordance with the PN-EN 1564:2012 standard. The results obtained by the solver for the selected parameters were verified. The indicated parameters were used to conduct experimental research. The tests obtained as a result of the physical experiment are convergent with the data from the solver.
Źródło:
Archives of Foundry Engineering; 2023, 23, 2; 137--144
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Single-channel EEG processing for sleep apnea detection and differentiation
Autorzy:
Prucnal, Monika A.
Polak, Adam G.
Powiązania:
https://bibliotekanauki.pl/articles/27311744.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
single-channel EEG
sleep apnea detection
optimization of signal processing
medical decision support
Opis:
Sleep apnea syndrome is a common sleep disorder. Detection of apnea and differentiation of its type: obstructive (OSA), central (CSA) or mixed is important in the context of treatment methods, however, it typically requires a great deal of technical and human resources. The aim of this research was to propose a quasi-optimal procedure for processing single-channel electroencephalograms (EEG) from overnight recordings, maximizing the accuracy of automatic apnea or hypopnea detection, as well as distinguishing between the OSA and CSA types. The proposed methodology consisted in processing the EEG signals divided into epochs, with the selection of the best methods at the stages of preprocessing, extraction and selection of features, and classification. Normal breathing was unmistakably distinguished from apnea by the k-nearest neighbors (kNN) and an artificial neural network (ANN), and with 99.98% accuracy by the support vector machine (SVM). The average accuracy of multinomial classification was: 82.29%, 83.26%, and 82.25% for the kNN, SVM and ANN, respectively. The sensitivity and precision of OSA and CSA detection ranged from 55 to 66%, and the misclassification cases concerned only the apnea type.
Źródło:
Metrology and Measurement Systems; 2023, 30, 2; 323--336
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sustainability assessment of the energy generation systems
Autorzy:
Drożdż, Wojciech
Vovk, Yuriy
Widera, Katarzyna
Łopatka, Agnieszka
Gawlik, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/27324310.pdf
Data publikacji:
2023
Wydawca:
Fundacja Centrum Badań Socjologicznych
Tematy:
sustainable energy
energy generation systems
European Union
multi-criteria decision analysis
policy support
Opis:
Purpose: This paper aims to assess the sustainability of energy generation systems in various European Union countries. It seeks to understand the diverse challenges and opportunities these countries face in transitioning to sustainable energy. Methodology: The study employs a multi-criteria decision analysis (MCDA) approach, considering economic, environmental, and social aspects. Data from various databases, including Eurostat, the International Energy Agency, and the World Bank, were analyzed. Results: The results reveal significant variations in sustainability performance across different countries and regions. With strong policy support and high public awareness, Scandinavian countries generally performed well across all sustainability indicators. In contrast, Eastern European countries faced more challenges due to their heavy reliance on fossil fuels. Theoretical Contribution: This study contributes to the ongoing discourse on sustainable energy by providing a comprehensive assessment of the sustainability of energy generation systems. It underscores the complex and multifaceted nature of sustainability and the various factors that influence it. Practical Implications: The findings provide valuable insights for policymakers and energy providers. They highlight the importance of policy support, public awareness, and acceptance in promoting sustainable energy. They also underscore the need for continued efforts and interventions to address the challenges faced by countries heavily reliant on fossil fuels.
Źródło:
Journal of Sustainable Development of Transport and Logistics; 2023, 8, 2; 249--258
2520-2979
Pojawia się w:
Journal of Sustainable Development of Transport and Logistics
Dostawca treści:
Biblioteka Nauki
Artykuł
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