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Found 6374 publications
Using multi-attribute decision-making technique for the selection of agribots via newly defined fuzzy sets
Publication Name: Aims Mathematics
Publication Date: 2025-01-01
Volume: 10
Issue: 5
Page Range: 12168-12204
Description:
Reference parameter mapping (passing arguments by reference) is a technique where the reference (like to find physical meaning, memory address) of a parameter is passed to a function or procedure, rather than a copy of the parameter’s value. This approach enables changes made to the parameter within the function to affect the original data. In decision-making systems, reference parameter mapping (passing arguments by reference) offers several key advantages that enhance flexibility, consistency, and efficiency. This is especially useful in scenarios where decisions are based on shared data, complex interactions, and iterative updates. In this paper, a new class of fuzzy set was introduced that is known as the (q1 ,q2 )-rung Diophantine fuzzy set, where q1 and q2 are reference parameter mappings. Most of the classical and new generalized fuzzy sets are exceptional classes of (q1 , q2 )-rung Diophantine fuzzy set ((q1 ,q2 )- RDFS) like intuitionistic fuzzy set (IFS), Pythagorean fuzzy Sets (PyFSs) and q-rung Orthopair fuzzy sets (q-ROFSs), linear Diophantine fuzzy sets (LDFS), and so on. It is commonly seen in multi-criteria decision-making (MCDM) scenarios that the presence of imprecise information and ambiguity in the decision maker's judgment affects the resolution technique. Fuzzy models that are now in use are unable to effectively manage these uncertainties to provide an appropriate balance during the decision-making process. Using control (reference) parameter mappings, (q1 , q2 )- RDFSs are potent fuzzy model that can handle these challenging problems. Two more novel ideas are presented in this work: (q1 ,q2 )-rung Diophantine fuzzy averaging and geometric aggregation operators with newly defined score and accuracy functions. An agricultural fieFS robot MCDM framework was proposed, incorporating (q1 ,q2 )-rung Diophantine fuzzy averaging and geometric aggregation operators. This strategy's efficacy and adaptability in addressing real-worFS issues were demonstrated by its application to get more benefits. This study has a lot of potential to handle difficult socioeconomic issues and offer vital information to academic, government, and analysts searching for fresh approaches in a variety of fieFSs.
Open Access: Yes
DOI: 10.3934/math.2025552
Efficacy of Advanced Robotic and Virtual Therapy in the Treatment of Acute and Subacute Stroke Patients: a Feasibility Study
Publication Name: Acta Polytechnica Hungarica
Publication Date: 2025-01-01
Volume: 22
Issue: 10
Page Range: 83-102
Description:
The aim of this study is to compare the effectiveness of advanced robotic therapy, virtual therapy and conventional physiotherapy in the rehabilitation of patients with acute and subacute stroke. In addition, we aim to further demonstrate the importance of an early mobilisation exercise program in the management of acute stroke patients. Participants (first-time ischaemic stroke patients in acute or subacute stages) were randomly divided into three equal groups (n=10 persons/group): a robot-assisted early mobilisation + virtual reality therapy (ROB+VR) group, a robot-assisted early mobilisation + conventional physiotherapy (ROB+FIZ) group, and a conventional physiotherapy (CON) group. Each group performed a 3-week-long training program (1 hour/session, 5 days/week). The results were measured before and after the exercise. The primary outcome measure used was the modified Rankin Scale (mRS) which indicates the severity of disability in daily activities and measures the degree of independence of the individual. The secondary outcomes were measured by the EuroQoL 5 dimensions questionnaire 5 levels version (EQ-5D-5L), the Berg Balance Scale (BBS), the Barthel Index (BI), and the 6-minute walking test (6mWT). All the three groups showed improvements in most outcomes. The scores for BI, EQ-5D-5L, and mRS showed significant improvements in quality of life. Comparing the groups, the ROB+VR group showed the greatest improvement in the scores in almost all of the tests. From the test scores, the 6-minute walk test had the highest improvement at the end of the therapy (94.58% improvement). Our results show that early robotic mobilization, followed by a movement program, combined with a virtual reality therapy, significantly improve both the speed and quality of rehabilitation after a stroke.
Open Access: Yes
One succeeds and the other fails? Criminal justice in times of emergency
Publication Name: Frontiers in Political Science
Publication Date: 2025-01-01
Volume: 7
Issue: Unknown
Page Range: Unknown
Description:
The Government has declared a state of emergency for the whole territory of Hungary for a period of 210 days from 1 November 2022 in view of the armed conflict and humanitarian disaster in Ukraine and to avert and manage the consequences of such conflicts in Hungary. Under the rules of emergency legislation, the Government is thus once again in a constitutional position to suspend the application of certain laws, derogate from statutory provisions and take other extraordinary measures. On the basis of this authorization, Government Decree 3/2023 (I. 12.) on the different application of certain provisions concerning the execution of sentences during a state of emergency was adopted at the beginning of the year, according to which, upon the request of a non-Hungarian convict, the national commander of the penitentiary system shall suspend the execution of the sentence until the transfer of the sentence, provided that certain conditions are met and there are no grounds for exclusion. Based on a detailed analysis of the legislation, it can be concluded that in practice this may also mean the remission of the remaining part of the sentence, since the receiving foreign state must ensure the enforcement of the sentence under Hungarian rules, but it is questionable whether this will be done. This outcome, however, runs counter to the fundamental principle of criminal justice, the principle of proportionate punishment, as it discriminates between offenders based on nationality. How compatible is this solution with the fundamental principles of the rule of law, such as non-discrimination or the principle of the obligation to be punished?
Open Access: Yes
Hybrid Data-Fusion Model for Solar-Powered Smart Irrigation with Predictive Decision-Making
Publication Name: Chemical Engineering Transactions
Publication Date: 2025-01-01
Volume: 121
Issue: Unknown
Page Range: 139-144
Description:
The proposed system addresses inefficient water use in agriculture by integrating an Arduino microcontroller, sensors, and data analysis. It irrigates only when needed, using weather forecasts and soil moisture sensors to optimize water delivery. The system conserves water, improves irrigation and resource management, enhances crop productivity, and reduces environmental impact. It features a user-friendly interface for remote monitoring and control and uses a Weather Forecast API to obtain real-time and forecast data from Open Weather via the REST protocol, including temperature, humidity, wind speed, and rain probability. This weather data is combined with soil moisture sensor readings in a Hybrid Fusion Algorithm, which checks both current and predicted conditions to decide when to irrigate. For instance, if the soil is dry but rain is likely, the system delays irrigation to save water. If the soil is dry and no rain is expected, irrigation starts automatically. By combining soil and weather data, the system can make more informed and sustainable decisions. In tests, this approach reduced water use by 27 % and cut unnecessary operations by 18 % compared to traditional systems. The system operates on solar energy, ensuring a sustainable and self-sufficient solution. This system represents an innovative advancement in agricultural technology, supporting more efficient and sustainable farming practices.
Open Access: Yes
DOI: 10.3303/CET25121024
Policy priorities for improving Global Innovation Index score and innovative performance in upper-middle-income countries: Implications for Armenia
Publication Name: Problems and Perspectives in Management
Publication Date: 2025-01-01
Volume: 23
Issue: 1
Page Range: 569-583
Description:
As an upper-middle-income country, Armenia should develop and implement targeted policies, such as increased R&D investments, education reforms, and industry-academia collaboration, to enhance its innovation performance. Strengthening these areas is expected to contribute to higher Global Innovation Index (GII) rankings, reflecting improved national innovation capacity. This study aims to estimate the impact of various GII components (including pillars, sub-indices, and sub-pillars) on the overall GII and pillar scores for upper-middle-income countries. Based on these findings, the study seeks to identify Armenia’s key policy priorities and provide targeted recommendations for enhancing its innovation performance. This study employs a cross-sectional regression to analyze the factors influencing GII scores in upper-middle-income countries, assessing the impact of sub-indices, pillars, and sub-pillars. The analysis reveals that market sophistication and creative outputs strongly influence GII scores among upper-middle-income countries, contributing significantly to national innovation performance. Additionally, knowledge and technology outputs, human capital and research, and infrastructure pillars show a statistically significant impact at the 5% level. Notably, even minor improvements in innovation output sub-index scores account for substantial variations in GII rankings. These findings suggest that Armenia should prioritize targeted education reforms, increase R&D investment, and strengthen university-industry linkages to enhance its innovation ecosystem and improve its global competitiveness.
Open Access: Yes
Multi-Stage Centralized Energy Management for Interconnected Microgrids: Hybrid Forecasting, Climate-Resilient, and Sustainable Optimization
Publication Name: CMES Computer Modeling in Engineering and Sciences
Publication Date: 2025-01-01
Volume: 145
Issue: 3
Page Range: 3783-3811
Description:
The growing integration of nondispatchable renewable energy sources (PV, wind) and the need to cut CO2 emissions make energy management crucial. Microgrids provide a framework for RES integration but face challenges from intermittency, fluctuating loads, cost optimization, and uncertainty in real-time balancing. Accurate short-term forecasting of solar generation and demand is vital for reliable and sustainable operation. While stochastic and machine learning methods are used, they struggle with limited data, complex temporal patterns, and scalability. Key challenges include capturing seasonal to weekly variations and modeling sudden fluctuations in generation and consumption. To address these issues, this paper presents a novel three-stage centralized EMS for interconnected microgrids. The first stage involves comprehensive data analysis to extract meaningful patterns. The second stage introduces a hybrid forecasting framework that integrates stochastic (Prophet) with machine learning (BiLSTM) techniques to improve prediction accuracy under uncertainty. In the third stage, a modified linear programming approach leverages the improved short-term forecasts to optimize energy sharing between microgrids, with the aim of reducing operational costs, minimizing carbon emissions, and improving system stability under climate variability. The proposed EMS is designed to accommodate diverse microgrid configurations while maintaining computational efficiency. Four scenarios are considered to evaluate the proposed energy management strategy. The obtained results demonstrate that the proposed EMS significantly improves both forecasting accuracy and operational performance. The combined methods achieve the best performance among all tested models, with an RMSE of 0.0070, MAE of 0.0043, and R2 of 0.9988, corresponding to improvements of ΔRMSE = −0.2122 and ΔR2 = +0.7126 relative to Prophet. These substantial gains in predictive accuracy translate into more precise battery scheduling, reduced grid dependency, and optimized power dispatching, thereby significantly enhancing system efficiency, reliability, and sustainability. Overall, the results highlight the effectiveness of integrating hybrid forecasting with optimization-based EMS, providing a viable pathway toward high penetration of renewable energy sources in future power systems.
Open Access: Yes
Strategic Innovation for Sustainability: A Conceptual Model Linking Digitalization, Social Dynamics, and Climate Change Mitigation
Publication Name: Business Strategy and the Environment
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
This study addresses a significant research gap in the literature by systematically reviewing and synthesizing the interplay between social dynamics, environmental changes, and organizational innovation. Although prior research has explored these dimensions in isolation, the integrative framework remains lacking. To address this, we conducted an integrative review that combined bibliometric and content analyses of 845 peer-reviewed articles, following the PRISMA guidelines for methodological rigor. Our study reveals that digitalization, social innovation, and technological advancement collectively empower firms to navigate complex social and environmental challenges, fostering sustainable innovation and resilience. Theoretical contributions are grounded in the Triple Bottom Line, Innovation Diffusion Theory, and Resource-Based View theory, offering a robust framework for understanding how organizations balance their economic, social, and environmental performance. Key findings highlight the pivotal role of communication, collaboration, and knowledge sharing in driving innovation, as well as the importance of integrating social and environmental responsiveness into strategic resource management. This study advances the literature by presenting a comprehensive framework that incorporates organizational innovation with broader sustainability outcomes, thereby informing both academic research and practical strategies for sustainable business transformation.
Open Access: Yes
DOI: 10.1002/bse.70471
Municipal Household Waste Management Methodologies in the EU Countries: A Reverse Logistics Benchmarking Approach
Publication Name: Lecture Notes on Multidisciplinary Industrial Engineering
Publication Date: 2025-01-01
Volume: Part F4026
Issue: Unknown
Page Range: 100-109
Description:
Through the application of a reverse logistics benchmark approach, this paper aims to investigate prevailing waste management practices in the European Union (EU) countries. In detail, it will analyze existing waste management practices, identify successful efforts, and identify areas for improvement within the EU region, in order to answer how can different collection waste management practices promote sustainability and integrate with reverse supply network? In this article, a structured literature review is carried out to examine the existing literature background, and public reports are collected and analyzed published by EU nations on waste management. The aim of the article is to understand their current state and evaluate the applicability of reverse logistics techniques in enhancing waste collection, recycling, and disposal. By answering the research question, the examination can provide valuable insights and recommendations for policymakers, as well as those involved in managing waste or stakeholders with an interest in enhancing the sustainability and efficiency of waste management practices in EU countries.
Open Access: Yes
Computational Assessment of Energy Supply Sustainability Using Picture Fuzzy Choquet Integral Decision Support System
Publication Name: Computers Materials and Continua
Publication Date: 2025-01-01
Volume: 85
Issue: 1
Page Range: 1311-1337
Description:
For any country, the availability of electricity is crucial to the development of the national economy and society. As a result, decision-makers and policy-makers can improve the sustainability and security of the energy supply by implementing a variety of actions by using the evaluation of these factors as an early warning system. This research aims to provide a multi-criterion decision-making (MCDM) method for assessing the sustainability and security of the electrical supply. The weights of criteria, which indicate their relative relevance in the assessment of the sustainability and security of the energy supply, the MCDM method allow users to express their opinions. To overcome the impact of uncertainty and vagueness of expert opinion, we explore the notion of picture fuzzy theory, which is a more efficient and dominant mathematical model. Recently, the theory of Aczel-Alsina operations has attained a lot of attraction and has an extensive capability to acquire smooth approximated results during the aggregation process. However, Choquet integral operators are more flexible and are used to express correlation among different attributes. This article diagnoses an innovative theory of picture fuzzy set to derive robust mathematical methodologies of picture fuzzy Choquet Integral Aczel-Alsina aggregation operators. To prove the intensity and validity of invented approaches, some dominant properties and special cases are also discussed. An intelligent decision algorithm for the MCDM problem is designed to resolve complicated real-life applications under multiple conflicting criteria. Additionally, we discussed a numerical example to investigate a suitable electric transformer under consideration of different beneficial key criteria. A comparative study is established to capture the superiority and effectiveness of pioneered mathematical approaches with existing methodologies.
Open Access: Yes
