In this research is presented a new method for determining the weights of criteria called simple weight calculation (SIWEC) method. The steps of this method are presented in the practical example of determining the importance of criteria for the needs of sales of agricultural products in the Semberija region. During the presentation of this method two methods are elaborated the simple SIWEC method which includes numerical ratings and the fuzzy SIWEC method which includes ratings in the form of linguistic value. In the selected example is presented how to use this method in order to determine the importance of criteria and in both cases the criterion of sales reliability is given the greatest weight. The contribution SIWEC method is reflected in its simplicity, which facilitates decision-making. • The method presented in this research apart from others is that it uses the evaluation of the criteria by decision makers, so the criteria should not be ranked and compared, but simply evaluated. • Unlike similar methods, the presented method uses the adjusted steps of the method for ranking the alternatives, and decision makers are given a different importance in the decision-making.

Uncertainty-aware soft sensors in sign language recognition (SLR) integrate methods to quantify and manage the uncertainty in their predictions. This is particularly crucial in SLR due to the variability in sign language gestures and differences in individual signing styles. Managing uncertainty allows the system to handle variations in signing styles, lighting conditions, and occlusions more effectively. While current techniques for handling uncertainty in SLR systems offer significant benefits in terms of improved accuracy and robustness, they also come with notable disadvantages. High computational complexity, data dependency, scalability issues, sensor and environmental limitations, and real-time constraints all pose significant hurdles. The aim of the work is to develop and evaluate a Type-2 Neutrosophic Hidden Markov Model (HMM) for SLR that leverages the advanced uncertainty handling capabilities of Type-2 neutrosophic sets. In the suggested soft sensor model, the Foot of Uncertainty (FOU) allows Type-2 Neutrosophic HMMs to represent uncertainty as intervals, capturing the range of possible values for truth, falsity, and indeterminacy. This is especially useful in SLR, where gestures can be ambiguous or imprecise. This enhances the model’s ability to manage complex uncertainties in sign language gestures and mitigate issues related to model drift. The FOU provides a measure of confidence for each recognition result by indicating the range of uncertainty. By effectively addressing uncertainty and enhancing subject independence, the model can be integrated into real-life applications, improving interactions, learning, and accessibility for the hearing-impaired. Examples such as assistive devices, educational tools, and customer service automation highlight its transformative potential. The experimental evaluation demonstrates the superiority of the Type-2 Neutrosophic HMM over the Type-1 Neutrosophic HMM in terms of accuracy for SLR. Specifically, the Type-2 Neutrosophic HMM consistently outperforms its Type-1 counterpart across various test scenarios, achieving an average accuracy improvement of 10%.

The contribution of Pawel Oclon has been funded by the EU project “Renewable energy system for residential building heating and electricity production–RESHeat”, Grant Agreement #956255. The work of Petar Varbanov has been funded by the Széchenyi István University in Hungary. The authors would like to apologise for any inconvenience caused.

The Solar Combined Cooling, Heating, and Power (S-CCHP) system, distinct from traditional centralised generation, provides clean energy solutions by installing user-side renewable energy capture facilities like solar panels to address the energy crisis and mitigate global warming. Previous research on the design of S-CCHP for buildings has often emphasised self-sufficiency, with less focus on the role of these systems as energy suppliers on the market. However, it is feasible to install scaled-up solar facilities that generate enough power to export to the grid, reducing grid pressure and enhancing the renewable energy mix. This study analyses the optimal design deployment for electricity within the S-CCHP system, based on the Renewable Energy System for Residential Building Heating and Electricity Production (RESHeat) system installed in Limanowa. It aims to optimise owner energy deployment by strategically integrating electricity generation, hybrid storage, and the electricity market to maximise owner benefits. A Life Cycle Assessment is also conducted to explore greenhouse gas emissions across scenarios with different storage facilities and reuse rates. Results show that the optimal deployment of 264 PV panels, each with a rated power of 440 W, generates 105 MWh annually, resulting in the surplus of 90.18 MWh with a selling price of 115 EUR/MWh. Vanadium redox flow batteries offer the highest revenue (4922.01 EUR) with the lowest storage costs, while lithium-ion batteries have the lowest carbon emissions (1.22 t CO2 eq/y). Sensitivity analysis and revenue break-even analysis are further conducted to assess the robustness and financial viability.

Despite the Malaysian government's efforts to promote cogeneration technology, it constitutes a mere 4.2 % of the country's total electricity generation. To address this issue, this review article aims to identify and benchmark global best practices for bolstering cogeneration implementation in Malaysia. While previous studies in this domain have centered on examining government policies within the specific regions, this paper underscores the imperative for an updated and comprehensive literature review to systematically collect and categorise best practices from around the world. This work examines the adoption of cogeneration energy systems within nations characterised by a substantial presence in their energy composition, simultaneously exploring the roles of regulatory frameworks in promoting their uptake. The scope of the literature review includes statistical data, reports, and other relevant scholarly works on cogeneration policies. Based on the findings, the review paper concludes that well-crafted policies are instrumental in encouraging rapid technology advocacy. The legislative landscape pertaining to cogeneration implementation in Malaysia is scrutinised, followed by a comparative analysis against global best practices to identify opportunities for improvement. Three crucial elements emerge as paramount to expediting the adoption: (i) administrative recognition, (ii) financial initiatives, and (iii) regulatory improvements. Several recommendations for the Malaysian cogeneration roadmap are presented. Overall, this paper offers insights into the chronological evolution of cogeneration policy development and provides actionable guidelines for developing effective policies in Malaysia and other South-East Asian countries.

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Background: PT (Patellar Tendinopathy) is a degenerative disorder of the tendons induced via extended overstretching or overuse of the tendons instead than usual inflammation. In the past, humans have centered on a number of strategies of treating PT such as ultrasound and surgical treatment. However, they did no longer genuinely consider the effectiveness of eccentric, isometric, or HSR (Heavy Slow Resistance Training) education for PT; They did now not really outline the stage of PT to beautify the uniformity of the find out about participants; They did no longer immediately examine the affects of isometric, eccentric, and HSR training. This systematic assessment chosen eccentric, isometric, and heavy gradual resistance coaching for the remedy of patellar tendinopathy and their respective prognostic effects will supply valuable, top notch evidence-based insights as properly as vital facts and advice for future scientific administration of patellar tendinopathy. Methods: A thorough and comprehensive search was conducted across the Web of Science, PubMed, and Scopus databases, encompassing a wide range of relevant journals and sources, in order to perform a rigorous systematic review and network meta-analysis, ensuring the inclusion of all pertinent and high-quality studies. The selected studies satisfied predetermined eligibility requirements, which included: (1) PT patients included in the studies; (2) use of eccentric, isometric, and heavy slow resistance training as interventions; and (3) evaluation of VISA-P (Victorian Institute of Sport Assessment Patella Questionnaire) outcome measures. The effect magnitude was measured using the standard mean difference. The risk of bias inherent in each of the studies that were meticulously selected and included in the comprehensive analysis was rigorously evaluated and assessed using the well-established Cochrane Collaboration Risk of Bias Assessment Tool, ensuring the robustness and reliability of the research findings. Results: Three scientific databases yielded a total of 1460 studies, of which 7 were included in the final analysis. The findings indicated that eccentric training (0.01 in Rank 1 and 0.06 in Rank 8) is the worst method for increasing VISA-P level in patients with patellar tendinopathy, while moderate resistance slow training (0.25) and Rank 1 and Rank 8 are the best options. Conclusions: While heavy slow resistance is more suited for attaining long-term improvements in knee function, progressive tendon-loading exercises combined with isometric training or moderate slow resistance training are more beneficial than eccentric training alone. Eccentric training gives a greater range of exercise venues and doesn't require any additional training equipment. The inability to directly compare the effects of heavy slow, eccentric, and isometric resistance training constitutes a significant drawback of this review. This limitation stems from the scarcity of research that compares the outcomes of these various therapeutic approaches. To address this constraint, future research endeavors should strive to conduct comparative studies of these strategies. By doing so, they can aim to bridge this evaluation gap and facilitate a more effective and comprehensive assessment of their respective efficacies.

The rubber wood furniture industry chain, including planting and manufacturing subsystems, emits significant greenhouse gases (GHGs), meanwhile, has huge carbon emission reduction potential. However, quite few studies have taken the whole industry chain GHGs into consideration, especially assessing and predicting those from rubber tree planting to furniture manufacturing. We took the rubber wood furniture of Hainan province as the case, explored its whole life cycle GHGs from cradle-to-gate and predicted the potential GHGs from 2031 to 2062. This study is fully based on field survey and sampling data, including that of the rubber tree planting (40-year cycle) and furniture manufacturing. The results reveal: (1) Whole industry chain of rubber wood furniture emits 3.27 × 10⁶ kgCO2-eq GHGs per 20,000 t rubber logs consuming, where the planting accounts the most (88.20%). Transport and electricity consumption are the main GHGs sources of planting and manufacturing subsystems respectively; (2) The whole life-cycle GHGs of rubber wood furniture in 2023 of Hainan is 2.07 × 10⁷ kgCO2-eq, which mainly come from Danzhou (24.74%), Haikou (19.55%), and Qiongzhong (15.79%); (3) The total GHGs from the rubber wood furniture industry in Hainan from 2031 to 2062 are 210 MtCO2-eq and 129 MtCO2-eq respectively, without or with felling restriction. The changes of GHGs from 2051 to 2062 are caused by the regional center shift of planting gravity; (4) Improving energy use efficiency and optimizing the location of furniture factories would reduce GHGs. This study can provide empirical support for the low carbon sustainable transformation of the rubber wood furniture industry worldwide.

The development of electric motors for automotive applications requires precise material models to simulate structural strength and NVH (Noise, Vibration, and Harshness) properties. Modeling the behavior of lamination stacks, composed of stacked steel plates, presents significant challenges. This study conducted dynamic and quasi-static experiments at various preload levels on an unmodified automotive lamination stack. Significant discrepancies were identified between stiffness values obtained from static and dynamic measurements. Consequently, using dynamically obtained stiffness values in static models, and vice versa, leads to inaccuracies and should be avoided. These results enhance the precision and efficiency of simulations used in the design and optimization of electric motors.