Search Results (148)

Space economy involves all activities and resource allocations that generate additional economic and societal benefits through space exploitation. The development of space infrastructure enables a wider range of economic activities. Regarding economic sustainability and national security, the possession of the launch site within national territory is of utmost importance. This paper presents a methodology for selecting launch sites based on linguistic term evaluation using a Discrete Single-Valued Neutrosophic Number (DSVNN) representation. The existence of support makes the DSVNN interpretable, which is not possible in the case of Single-Valued Neutrosophic Number (SVNN) with only specific values of truth, indeterminacy, and falsity degrees. An ensemble of five widely well-known MCDM methods, namely TOPSIS, CODAS, COPRAS, EDAS, and MOORA, are used in the decision-making process. The whole procedure is then applied to the launch site selection in Thailand. All MCDM methods result in the same top priority location, U-Tapao Rayong–Pattaya International Airport, Chonburi. The weight sensitivity analysis and the method cross-validation are applied to test the robustness of the result. Full article

The increasing complexity of marine spatial management and the rapid growth of nautical tourism require the use of formal and transparent decision-making models. Identifying optimal locations for nautical anchorages is a multi-criteria decision problem (MCDP) in which navigation safety, spatial constraints, and environmental protection often conflict. This study presents an integrated framework combining Geographic Information Systems (GIS) and multi-criteria decision-making (MCDM) methods for the systematic evaluation and ranking of nautical anchorages. As a case study, 86 potential locations in Split-Dalmatia County, Croatia, were analysed based on 18 criteria encompassing hydrological, meteorological, and spatial factors, as well as risk factors relevant to navigation safety. The methodological approach applies six MCDM methods implemented in the R programming language: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), ViseKriterijska Optimizacija I Kompromisno Rjesenje (VIKOR), Multi-Objective Optimisation on the Basis of Ratio Analysis (MOORA), Complex Proportional Assessment (COPRAS), Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS), and Evaluation Based on Distance from Average Solution (EDAS). To reduce methodological bias, a final Consensus rank was calculated to synthesise the results of all applied methods. The stability of the obtained ranking was examined through an analysis of rank agreement between methods, using a diagonal matrix of rank overlaps and the corresponding heatmap visualisation. The results indicate a high level of consistency among individual MCDM methods and strong stability of the final consensus ranking. The proposed model ranks locations from best to worst based on how well they meet the established criteria, while ensuring strict navigational safety and compliance with environmental constraints. These findings confirm that the integrated GIS–MCDM approach is a reliable, repeatable, and scientifically grounded tool for supporting spatial planning and concession allocation in the development of nautical infrastructure. Full article

Soil erosion in arid watersheds poses a significant threat to land productivity, water resources, and long-term sustainability, necessitating spatially explicit and data-driven prioritization frameworks for targeted conservation. This study developed an integrated GIS-based multi-criteria decision-making (MCDM) framework to assess soil erosion susceptibility and prioritize twelve sub-basins (SB) of the Wadi Numan basin (683 km²), Makkah Region, Saudi Arabia. Morphometric analysis was conducted using sixteen parameters derived from a 10 m Digital Elevation Model (DEM), and Land Use/Land Cover (LULC) data were obtained from the Esri Sentinel-2 10 m dataset. Four MCDM techniques—additive ratio assessment (ARAS), complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis (MOORA), and technique for order preference by similarity to ideal solution (TOPSIS)—were applied under the criteria importance through inter-criteria correlation (CRITIC) objective weighting, and their consistency was evaluated using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). MOORA achieved the highest consistency for morphometric analysis (SCCT: 0.982; KTCCT: 0.958), while TOPSIS performed best for LULC analysis (SCCT: 0.800; KTCCT: 0.731). The final combined prioritization used MOORA for morphometric analysis and TOPSIS for LULC analysis, with proportional weighting of 72.7% and 27.3%, respectively. The scheme categorized the sub-basins into five levels of soil erosion priority. The composite ranking classified SB-9 and SB-1 under very high priority (25.94%); SB-2 and SB-3 under high priority (6.40%); SB-5, SB-6, and SB-10 under medium priority (36.37%); SB-4 and SB-8 under low priority (18.11%); and SB-11, SB-12, and SB-7 under very low priority (13.18%). This integrated method provides a practical decision-support tool for identifying and managing sub-basins susceptible to soil erosion, thereby promoting the long-term sustainability of land and water resources. Full article

This work examines the machining responses of dry turning in ultrasonic-assisted stir-squeeze cast A356 hybrid nanocomposites reinforced with zirconia (ZrO₂) and graphene oxide (GO). Accordingly, flank wear (VBc) ranged from 0.061 to 0.238 mm, influenced by abrasion, adhesion, built-up edge (BUE) formation, and diffusion mechanisms. Cutting speed had the most significant effect on flank wear (65.65%), followed by depth of cut (18.2%) and feed rate (11.13%), supported by a well-fitted regression model (R² = 0.987; p < 0.05). Surface roughness (Ra) ranged from 1.733 to 7.012 μm, with cutting speed, feed rate, and depth of cut contributing 70.42%, 15.43%, and 9.56%, respectively. The cutting temperature was limited to 127 °C, primarily influenced by cutting speed (60.68%), whereas cutting power varied between 0.353 and 0.644 kW, mainly governed by cutting speed (68.71%) and depth of cut (25.92%). The chip morphology showed a segmented sawtooth pattern due to cyclic fracture initiation during material removal. Multi-criteria optimization using complex proportional assessment (COPRAS) identified v = 90 m/min, f = 0.06 mm/rev, and d = 0.1 mm as the optimal parameters, yielding a tool life of 22.6 min and a machining cost of INR 58.69 per item. This research is further focused on the implementation of different cooling lubrication techniques utilizing environmentally friendly cutting fluids, including Minimum-Quantity Lubrication and nano-MQL, among other types of environments. Full article

The growth of advanced cyber threats has inspired organisations to start using powerful cybersecurity platforms, but the process of selection is analytically challenging due to the multidimensional, uncertain, and conflicting character of the evaluation criteria. The prevailing culture of decision-support frameworks is based on unyielding numerical evaluations that cannot reflect the underlying vagueness of expert judgment and the dynamic interplay of macro-environmental factors. This paper presents a combined Fuzzy Multi-Criteria Decision-Making (FMCDM) system, which uses polygonal fuzzy numbers, in particular pentagonal fuzzy representation, and four other complementary methods of MCDM (Fuzzy AHP, Fuzzy TOPSIS, Fuzzy VIKOR, and Fuzzy COPRAS), integrated by a Borda Count consensus system. Sixteen assessment sub-criteria are logically obtained through an analysis of PESTEL (Political, Economic, Social, Technological, Environmental, and Legal) and weighted using the Fuzzy Analytic Hierarchy Process. The model is used to compare six cybersecurity platforms, including Microsoft Security Framework, CrowdStrike Falcon, Cisco Cybersecurity Portfolio, Palo Alto Networks Cortex, Fortinet Security Fabric, and Sophos Central. In this study, Fuzzy AHP demonstrates that the aggregate weight of political factors is the highest (0.4181), followed by cross-border data management, regulatory compliance, and government incentives as the most popular sub-criteria. According to the results from the Fuzzy TOPSIS, Fuzzy VIKOR, and Fuzzy COPRAS methods, Microsoft Security Framework ranks consistently in the first place, and CrowdStrike Falcon and Cisco Cybersecurity Portfolio were ranked second and third, respectively. The framework presented in the study provides decision-makers with a reproducible, uncertainty-conscious basis for cybersecurity platform selection. Full article

One of the most critical challenges in maritime transport decarbonization, as part of the EU greenhouse gas (GHG) neutrality strategy, is the reduction in GHG and harmful emissions from the energy systems of existing vessels. Furthermore, the potential for implementing decarbonization technologies in operating vessels remains significantly more limited compared to newly constructed ships. Selecting appropriate decarbonization measures requires a comprehensive evaluation of technological feasibility, economic viability, and environmental performance, in accordance with the regulatory frameworks established by the IMO and the EU. A major limitation in such decision-making processes is ensuring the representativeness and reliability of expert judgments. In order to improve the reliability of results by expanding and structuring the information base, this study proposes and implements a method based on the integration of SWOT analysis with multi-criteria decision-making (MCDM) methods. The objective of this study was to examine the methodological aspects of testing the integrated application of comprehensive analysis and ranking methods for decarbonization technologies as applied to a prototype oil tanker. Based on the SWOT analysis method, technological solutions that are available for practical application were identified for the medium-term decarbonization period considered in the study, up to 2030–2035. Subsequent rating based on several applied multi-criteria (MCDM) analysis methods (TOPSIS, COPRAS, SAW) allowed us to examine the range, stability and sensitivity of the obtained solutions in relation to the methods themselves and scenarios with variations in the weighting factors of the evaluation criteria. The complete match of the ratings obtained using the TOPSIS and COPRAS methods confirms the stability of the multi-criteria decision-making process (priority-compromise order): CCS, kite, air lubrication, Flettner rotor. The performed sensitivity analysis showed that the technology rankings remain relatively stable when the weighting factor for the CO₂ reduction criterion varies within a range of approximately ±10%, while larger deviations result in an increasing difference between all three MCDM methods. For the TOPSIS method, the change limits for the critical values of the threshold indicators were ±20%, the COPRAS method showed intermediate results, and changing the weighting coefficients within a ±20% range did not alter the selection of the best technology. The results obtained allow for a positive assessment of the effectiveness of the proposed integrated methodology when applied as an alternative in the initial stage of ranking decarbonization methods for in-service ships. Full article

The aim of this study is to identify logistics supply chain criteria by considering the sustainability factor and to conduct a performance evaluation based on these criteria. The application analyzes 15 sub-criteria under the five main criteria of sustainable logistics: procurement logistics, production logistics, reverse logistics, distribution logistics, and disposal logistics. Accordingly, the importance weights of the logistics criteria were determined using the Fuzzy AHP (Analytic Hierarchy Process) method. Based on the determined criterion weights, an integrated model for performance evaluation was proposed using the Spherical Fuzzy MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the Full Multiplicative Form) and Heuristic Fuzzy COPRAS (Complex Proportional Assessment) methods. The application ranked the sustainable logistics performance of three major logistics firms, and the results obtained from both methods were consistent. The findings highlight that the three criteria with the highest importance levels are, in order, as follows: green purchasing strategies (0.356), green design (0.151), and integration of supplier into environmental management processes (0.125). This demonstrates that firms aim to foster environmental responsibility not only in their internal processes but also throughout the supply chain. This study provides a reliable model for evaluating and improving sustainable logistics performance, contributing both to the academic literature and to practical applications in logistics firms. Full article

The rapid proliferation of Conversational Artificial Intelligence Assistants (CAIs) has transformed access to mental health information through freely accessible web interfaces, mobile applications, and public APIs (Application Programming Interfaces), yet systematic methodologies for their evaluation remain limited. This paper introduces SELCAI-MH, a multicriteria framework for CAI evaluation and selection. This framework integrates four complementary multicriteria methods: Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment Method (COPRAS), and Combinative Distance-based Assessment (CODAS), capturing distance-based, compromise-based, proportional, and negative-ideal logics, and proposes SOLAG, an aggregation method that produces a consensus ranking across methods. SELCAI-MH employs a dual evaluation mechanism combining psychiatric expert assessment with AI-based scoring, expert-derived criterion weights, and domain-relevant conversational datasets. The framework is applied to nine internet-accessible CAIs: proprietary platforms (ChatGPT 5.2, Claude Sonnet 4.5, Gemini 1.5 Flash, Perplexity Sonar, Bing AI/Copilot) and open-source Llama variants deployed via cloud inference endpoints. Using a set of anxiety-related questions and CAI responses, evaluated across seven criteria, Claude Sonnet 4.5 emerged optimal, followed by ChatGPT 5.2 and Gemini 1.5 Flash. SOLAG produced highly consistent rankings across the four multicriteria decision-making (MCDM) methods (Spearman ρ ≥ 0.98). Overall, SELCAI-MH provides a structured and reproducible decision-support framework for selecting accessible CAIs in sensitive mental health contexts. Full article

The growing urgency of resource-efficient construction in water-stressed and rapidly urbanizing regions necessitates integrated decision support frameworks that move beyond isolated sustainability metrics. This study operationalizes the water-energy nexus within building design evaluation by developing a structured hybrid multi-criteria decision-making (MCDM) framework tailored to the Indian construction context. Unlike conventional sustainability assessments that treat water and energy independently, the proposed approach integrates life cycle-based water consumption, operational and embodied energy demand, environmental impacts, economic feasibility, and project constraints within a unified analytical hierarchy. A Delphi-validated criterion structure comprising five main criteria and twenty sub-criteria is weighted using the Analytic Hierarchy Process (AHP), and ranked using the VIKOR compromise solution method. To strengthen methodological robustness, ranking outcomes are validated across three independent MCDM logics including TOPSIS, PROMETHEE, and COPRAS. The framework evaluates four representative building strategies aligned with Indian regulatory and certification systems (NBC, ECBC, IGBC/GRIHA, and net-zero water-energy design). Using expert-informed weights derived from a Delphi–AHP involving a panel of experienced practitioners, the VIKOR compromise ranking consistently identifies the net-zero alternative as the most favorable option within the evaluated framework. The results are therefore interpreted as an expert-informed assessment demonstrating the applicability of the proposed decision support methodology rather than as statistically generalizable priorities for the entire Indian construction sector. The study contributes by (i) embedding nexus-based resource interdependence into building-level MCDM modeling, (ii) enhancing transparency through explicit benefit-cost classification and decision matrix disclosure, and (iii) demonstrating ranking stability across multiple validation techniques. The proposed framework provides a transferable methodological approach that can be adapted to different regional contexts through locally derived expert inputs. Full article

In order to provide clinically significant evidence on the long-term functional performance of CAD/CAM provisional materials, especially 3D-printed and milled resins, accurate tribologically in vitro wear tests that integrate wear parameters and surface topography analysis are necessary. The goal of the study was to assess the wear resistance of several CAM-obtained dental crown materials and the relationship between wear and the manufacturing process, distinctive postprocessing, microhardness, microroughness, and surface topography. A standardized ball-on-flat tribological protocol was applied to (n = 70) CAD/CAM-fabricated PMMA specimens (four 3D-printed groups with distinct post-processing protocols (Optiprint) and three milled materials (TelioCAD, Shaded PMMA, Copra Temp Symphony)) to quantify wear parameters micro- and nanoroughness (Ra, Rz, Sa, Sy), and Vickers microhardness, followed by comprehensive statistical analysis (t-tests, Pearson correlations) to elucidate material- and process-dependent differences in wear behaviour. Nanoroughness was carried using atomic force microscopy evaluation. Wear testing showed that most materials, particularly the 3D-printed groups, developed limited wear, whereas the milled materials evolved toward groove-dominated wear topographies. Wear statistics showed that the printed resins consistently had an advantage, meaning that the degree and rate of wear are significantly influenced by the manufacturing process. Hardness has a central role in governing the wear performance of interim resin materials, while nanoroughness acts as a secondary factor. Optimised post-processing of printed materials, particularly a prolonged post-curing period, yields a beneficial combination of low wear and specific topography, thereby providing a significant clinical advantage. Full article

E-commerce has been a rapidly growing sales channel in recent years, with a strong trend toward further expansion. However, logistics companies face significant challenges in the preparation and sorting of orders when delivering shipments purchased through e-commerce platforms. In this process, order pickers play a pivotal role, as their efficiency directly impacts both the operational performance of logistics companies and the quality of service provided to customers. During peak periods of high order volumes, it is common for order pickers to exceed the prescribed work norm, making them eligible for performance-based bonuses. This study aims to develop a model for evaluating order picker efficiency, ranking them, and determining the optimal allocation of bonuses. It addresses a critical gap in the existing literature, as only a handful of studies have explored this issue in depth. To assess the efficiency of 56 order pickers, the DEA method was applied, incorporating three input and five output variables. The analysis identified 18 order pickers as fully efficient. These individuals were then ranked using the IMF SWARA and COPRAS methods, where IMF SWARA was employed to determine the weights of nine evaluation criteria, while COPRAS was used for the final ranking process. Based on the ranking results, a structured bonus allocation model was developed, encompassing four distinct scenarios. Furthermore, a sensitivity analysis and model validation were conducted to ensure the robustness and reliability of the proposed approach. Full article

This study aimed to determine the ileal digestibility of amino acids (AA) in various protein sources for 21-day-old broilers. A total of 448 Ross 308 male broilers were allocated to eight dietary treatments with eight replicates in a randomized complete block design. Experimental diets included one nitrogen-free diet and seven test diets, each containing one of the following feed ingredients—dehulled soybean meal (SBM), fermented SBM (FSBM), rapeseed meal (RM), copra meal (CM), palm kernel meal (PKM), corn distillers dried grains with solubles (DDGS), and fish meal (FM), as the sole source of AA. On day 21, all birds were euthanized and subsequently ileal digesta was collected from the distal two-thirds of the ileum, extending from Meckel’s diverticulum to 1 cm proximal to the ileocecal junction. The ileal digestibility of AA in the FM was the greatest, followed by the SBM. The ileal digestibility for AA in the SBM was greater than that in the RM. The ileal AA digestibility in the RM was greater than or not different from that in the FSBM, except for Val and Pro, and superior to the CM and the PKM. The ileal digestibility of AA in the FSBM was greater than or not different from those in corn DDGS, except for Met and Cys. Corn DDGS exhibited greater or not different ileal digestibility of AA compared to that of the CM and the PKM, except for Val and Asp, and the PKM was the lowest. In conclusion, the ileal digestibility of AA was the greatest in the FM, followed by the SBM, FSBM, the RM, corn DDGS, the CM, and the PKM. Furthermore, the results underscore the necessity for continuous evaluation of ileal AA digestibility in various protein sources. Full article

The aquafeed industry is currently facing severe challenges such as increasingly tight supply and price fluctuations of traditional high-quality protein ingredients like fish meal and soybean meal. Therefore, actively exploring and developing new, stable, efficient, and sustainable feed protein sources to replace fish meal and soybean meal has become an urgent task and an important strategic direction for ensuring the sustainable development of the aquaculture industry. Copra meal is a widely available plant protein source with lower cost compared to fish meal and soybean meal, demonstrating good application potential. However, copra meal has disadvantages including low protein content, imbalanced amino acid profile, high crude fiber content, numerous anti-nutritional factors, and low digestibility. These issues can be addressed through certain treatments (e.g., fermentation or water soaking) to enhance its nutritional value. Currently, research on copra meal in aquafeed is still relatively scarce. To enable the broader and more effective application of this promising feed ingredient in aquafeed, this review systematically summarizes the current research progress on the nutritional characteristics, appropriate inclusion levels, processing improvement technologies, and the effects of copra meal on the growth and health of aquatic animals, aiming to provide references for promoting resource diversification and sustainable development in the aquafeed industry. Full article

The development of high-performance, sustainable biocomposites requires biodegradable matrices and optimized natural reinforcements. In this study, flax fiber-reinforced polylactic acid (PLA) hybrid biocomposites incorporating waste pistachio nut shells (WPNS), waste tea leaf fiber (WTLF), and waste quail eggshell (WQES) were developed and evaluated, with direct comparison to previously reported jute-based hybrid systems to assess the benefits of fiber substitution. The composites were fabricated via compression molding and characterized for their mechanical, thermal, acoustic, surface, and moisture-related properties. Replacing the jute with flax resulted in a consistent performance enhancement. Among the hybrids, the flax–WPNS composite exhibited the highest tensile and flexural performance, achieving tensile strength improvements of approximately 30–40% over neat PLA due to effective stress transfer and crack deflection. The flax–WTLF composite showed superior acoustic behavior, attaining a maximum sound absorption coefficient of approximately 0.65–0.70 at mid-to-high frequencies, attributed to its porous microstructure. In contrast, the flax–WQES composite demonstrated the highest thermal conductivity (0.54 W/(mK)) and apparent density (2.24 g/cm³), reflecting dense packing and the presence of CaCO₃-rich particles. Scanning electron microscopy revealed distinct microstructural mechanisms governing these property-specific responses, including differences in interfacial bonding, void distribution, and filler packing efficiency. An integrated fuzzy CRITIC–COPRAS multicriteria decision-making approach identified the flax–WPNS hybrid as the optimal overall formulation. The results clearly demonstrate that flax fibers outperform jute as a reinforcement in PLA-based hybrid biocomposites, and that targeted combinations of flax and waste-derived fillers enable multifunctional performance optimization for sustainable engineering applications. Full article

Effective management of Environmental, Social, and Governance (ESG) practices within the framework of transparency and accountability in businesses is crucial for enhancing their compliance capacity in the face of regulatory pressures and contributing to the early detection of environmental and social risks. This study aims to evaluate the ESG disclosure-based performance of businesses operating in the textile, clothing, and leather sectors in Turkey by examining their ESG indicators from a transparency and accountability perspective. The CRITIC (Criteria Importance Through Intercriteria Correlation) method was used to determine the relative importance levels of the indicators, while the MABAC (Multi-Attributive Border Approximation Area Comparison) and COPRAS (Complex Proportional Assessment) methods were used to rank the performance of businesses within the framework of these indicators. Finally, clustering analysis was used to classify businesses with similar characteristics. The findings show that corporate governance principles are the most important indicator, and that Kordsa Teknik Tekstil A.Ş. and Söktaş Tekstil Sanayi ve Ticaret A.Ş. exhibit a significant and positive difference in terms of transparency and accountability in their ESG practices compared to other businesses. The combined use of CRITIC, MABAC, COPRAS, and cluster analysis offers an innovative, robust decision-making approach and holistic methodological integration for assessing ESG disclosure-based performance in the context of transparency and accountability for businesses. Full article