Search Results (129)

This study proposes an Improved Whale Migration Algorithm (IWMA) to overcome the shortcomings of the original Whale Migration Algorithm, which suffers from premature convergence and insufficient local exploitation in high-dimensional multimodal optimization. IWMA introduces three enhancements: circle chaotic initialization to improve population diversity, a three-layer cooperative search framework to achieve a stronger balance between exploration and exploitation, and a dynamic adaptive mechanism with t-distribution re-exploration to reinforce both global escaping and local refinement. On the CEC2017 benchmark suite, IWMA demonstrates clear superiority over seven representative algorithms, delivering the best results on 27 out of 29 functions by best, 25 by mean, and 23 by standard deviation in 30 dimensions, and on 25, 18, and 18 functions, respectively, in 50 dimensions. Compared with other migration-based optimizers, its average rank improves by more than 30 percent, while runtime analysis shows only a small additional overhead of 7 to 12 percent. These outcomes, supported by convergence curves, boxplots, radar charts, and Wilcoxon tests, confirm the effectiveness of the proposed improvements. In six multi-UAV path planning scenarios, IWMA reduces the average cost by 14.5 percent compared with WMA and achieves up to 32.1 percent reduction in the most complex case. Overall, its average cost decreases by 27.4 percent across seven competitors, with a 23.6 percent improvement in the best solutions. These results demonstrate that the proposed modifications are effective, enabling IWMA to transfer its performance gains from benchmark tests to practical multi-UAV cooperative mission planning, where it consistently produces safer and smoother trajectories under complex constraints. Full article

Nanopriming with metal nanoparticles (NPs) is a promising strategy for improving seedling quality in horticultural crops. This study evaluated the effects of hydropriming, ZnO, SiO₂, ZnO + SiO₂, a ZnMo nanofertilizer, and two commercial biostimulants (Osmoplant and Codasil) on the early development of Capsicum annuum L. seedlings. Morphological, physiological, and biochemical traits, including biomass, stem architecture, number of leaves, chlorophylls, carotenoids, SPAD index, and nitrate reductase (NR) activity, were measured under controlled conditions. The ZnO and ZnO + SiO₂ treatments promoted stronger root growth, higher pigment content, and higher NR activity. SiO₂ alone and ZnMo showed intermediate improvements, while Osmoplant and Codasil had more limited effects. Multivariate analyses provided complementary information: heat maps revealed correlations between traits, PCA differentiated treatment responses, and radar charts integrated performance profiles. Overall, the results provide promising evidence that seed nanopriming, particularly with ZnO and ZnO + SiO₂, improves seedling vigor and transplant potential in jalapeño peppers. Full article

Performance analysis in elite football still faces significant challenges: traditional descriptive statistics often fail to capture tactical adaptability, and African teams remain underrepresented in the scientific literature despite achieving historic breakthroughs. The FIFA World Cup Qatar 2022 marked a turning point, with Morocco becoming the first African nation to reach the semi-finals. This study systematically analyzed the tactical, physical, and structural performance of the Moroccan national team across seven matches using official FIFA post-match reports. A three-level methodological framework was adopted: (i) descriptive analysis of key performance indicators (KPIs); (ii) visual profiling through radar charts, heatmaps, and passing networks; and (iii) exploratory modelling using principal component analysis (PCA) and clustering. Results revealed consistent defensive organization, low ball possession (<40% in five matches), and effective counter-attacking transitions, with pressing peaks against Spain (288 actions) and France (299 actions). PCA explained 76% of the variance, identifying two principal axes (physical intensity vs. technical mastery; verticality vs. build-up play) and clustering distinguished three match types: low-block defensive games, transition-oriented games, and open matches. These findings highlight Morocco’s tactical adaptability and sustained physical commitment. The study demonstrates how AI-enhanced analytics and multidimensional data visualization can uncover latent performance patterns and support evidence-based decision-making. Practical implications include actionable insights for performance analysts and coaching staff, particularly as Morocco prepares for the 2025 Africa Cup of Nations and the FIFA World Cups in 2026 and 2030. This integrative approach can serve as a model for federations seeking data-driven performance optimization in elite football. Full article

As a representative high-performance construction material, ultra-high performance concrete (UHPC) is typically prepared using quartz sand and steel fibers. To alleviate the shortage of building materials in island and reef regions, this study employs coral sand for UHPC preparation and investigates the effects of different fibers on its mechanical properties. This study demonstrates that this approach mitigates brittle failure patterns and enhances the durability of structures. To investigate the enhancement effects of PE and steel fibers on the mechanical properties of coral sand ultra-high performance concrete (CSUHPC), 12 mix designs were formulated, including a plain (no fiber) reference group and PE fiber-reinforced, steel fiber-reinforced, and hybrid fiber combinations. Compressive tests, tensile tests, and three-point bending tests on pre-notched beams were conducted. Key parameters such as 28-day compressive strength, tensile strength, and flexural strength and toughness were measured. A multi-criteria evaluation framework was established to comprehensively assess the integrated performance of each group. The experimental results demonstrated that fiber incorporation significantly enhanced the compressive strength and fracture properties of CSUHPC compared to the plain reference group. Steel fiber-only reinforcement exhibited the most pronounced improvement in compressive strength and fracture properties, while hybrid fiber combinations provided superior tensile performance. Through the established multi-criteria evaluation framework, the optimal comprehensive performance was achieved with a 3% steel fiber dosage, achieving improvements of 0.93 times in compressive strength, 2.80 times in tensile strength, 1.84 times in flexural strength, 192.08 times in fracture energy, and 1.84 times in fracture toughness relative to the control group. Full article

The selection of Data Lifecycle Models (DLMs) in complex data management scenarios necessitates finding a balance between quantitative and qualitative characteristics to ensure regulation, improve performance, and maintain governance requirements. In this context, an interactive web application based on AHP-Express has been developed as a user-friendly tool to facilitate decision-making processes related to DLM. The application facilitates customized decision matrices, organizes various expert interviews with distinct weights, calculates local and global priorities, and delivers final DLM rankings by consolidating sub-criteria scores into weighted macro-category values, accompanied by graphical representations. Key functions encompass consistency checks, sensitivity analysis for macro-category weight variations, and graphical representations (bar charts, radar maps, sensitivity charts) that emphasize strengths, shortcomings, and the robustness of rankings. In a suggested application for sensor-based artifact monitoring at the Museo del Carbone, the tool swiftly selected the most appropriate DLM as the leading contender, exhibiting consistent performance across diverse weight scenarios. The results of the Museo del Carbone case validate that AHP-Express facilitates rapid, transparent, and reproducible DLM selection, reducing cognitive load while maintaining scientific rigor. The tool’s modular architecture and visualization features enable educated decision making for various data management issues. Full article

This study aimed to investigate cattle farmer livelihoods that relate to cattle welfare in the region with the newly emerging Lumpy Skin Disease (LSD) in Indonesia. A semi-structured interview survey was conducted with randomly selected cattle farmers (n = 102), in Riau. Cattle were bled for analysis of LSD-post-vaccinal seroconversion. The Sustainable Livelihood Framework (SLF) was used; data on livelihood assets, activities, and outcomes were analysed using Multiple Correspondence Analysis (MCA), two-step clustering, and the radar chart of asset possessions. The survey showed that vaccination and veterinary services covered 82.4% and 90.2% of farms. Seroconversion was detectable in vaccinated (15.0%, n = 173) and in non-vaccinated animals (23.1%, n = 13). Farmers mostly fed only grass to cattle (92.2%), with neither pastoral management nor ad libitum water provision. The MCA and cluster analyses indicated that cattle shelter roofing and flooring and manure disposal were the most important markers of the community’s livelihood. Poverty among cattle farmers was 23.5%. The cluster with lower income per capita had lower quality of shelter roofing and flooring, a lack of regular manure disposal, jobless second children, and the lowest possession of natural and physical assets. Helping to possess natural and physical assets might improve cattle farmers’ well-being and cattle welfare. Full article

This study explores entertainment consumption patterns in Romania, a transitional digital culture characterized by high digital connectivity but underdeveloped physical infrastructure. Employing a dual qualitative coding methodology, this research combines inductive analysis of consumer focus groups with deductive analysis of expert interviews, enabling a multi-layered interpretation of both overt behaviors and latent emotional drivers. Seven key thematic dimensions, motivational depth, perceived barriers, emotional needs, clarity of preferences, future behavioral intentions, social connection, and identity construction, were analyzed and compared using a Likert-based scoring framework, supported by a radar chart and comparison matrix. Findings reveal both convergence and divergence between consumer and expert perspectives. While consumers emphasize immediate experiences and logistical constraints, experts uncover deeper emotional motivators such as validation, mentorship, and identity formation. This behavioral–emotional gap suggests that, although digital entertainment dominates due to accessibility, it often lacks the emotional richness associated with physical formats, which are preferred but less accessible. This study underscores the importance of triangulated qualitative inquiry in revealing not only stated preferences but also unconscious psychological needs. It offers actionable insights for designing emotionally intelligent and culturally responsive entertainment strategies in digitally saturated yet infrastructure-limited environments. Full article

The recent debate on Environmental, Social, and Governance (ESG) factors has focused primarily on financial decision making and risk management from the perspectives of developed economies. However, in most developing countries, ESG risk models for mortgage lenders are very limited. In most of these countries, ESG-rating providers employ widely varying methodologies and disclosure policies, often resulting in divergent assessments of the same organization. This research develops a pilot statistical-analysis, dual-horizon ESG risk model specific to the Mexican mortgage industry, which provides a better understanding of how ESG risk could evolve over time across financial, operational, regulatory, and reputational dimensions in Mexico. This dual-horizon ESG framework considers a two-year short-term risk assessment and a ten-year long-term risk assessment. This research integrates expert opinions with a scoring system that improves on traditional methods. Dependability and internal consistency are tested using the Intraclass Correlation Coefficient (ICC) and Cronbach’s alpha. Radar chart visualization and cluster analysis are used to visualize the empirical results. The empirical findings show that environmental risk has strong temporal effects, and the perceived severity is 20% higher over the longer time horizon. Furthermore, social risk exhibits high variability, identifying it as a critical risk for financial stability and regulatory compliance. Cluster analysis identifies systematic patterns in expert opinions that determine two groups, making the qualitative findings derived from radar plots more robust. Group 0 (75% of experts) has an institutional view about ESG risks. Group 1 (25% of experts) aligns with an affiliation to large financial institutions. Finally, this research identifies three key sustainability challenges for the mortgage sector in Mexico: exposure to climate-induced stress, fragmented regulatory frameworks, and social inequality. Full article

This article proposes a strategy for the visual characterization of power quality in big data analysis contexts, culminating in the development of a visualization tool based on higher-order statistics, which exhibits an efficiency between 83.33% and 100% in detecting 50 Hz synthetic and real-life simple and hybrid events, showing its significant potential for real-world applications marked by non-linear loads and non-Gaussian behaviors and surpassing the detection of traditional tools such as boxplot by up to 50%. Efficient energy management is closely accompanied by an optimum energy data management (EDM). It implies the acquisition, analysis, and interpretation of data to make decisions regarding the best energy usage with subsequent cost reductions. Through a study of indicators, including higher-order statistics, crest factor, SNR and THD, the article establishes nominal values and behavioral patterns, expanding the previous knowledge of these parameters. The indicators are presented as vertices in a radar-type charting tool, providing a multidimensional spatial visualization from individual indices that allows the behavioral pattern associated with each type of disturbance to be characterized combined with a decision tree. In addition, boxplots reflecting data processing are included, which facilitates the comparison and discussion of both visualization instruments: radar chart and boxplot. Full article

With the increasing air traffic flow, the workload of air traffic controllers is also growing, and their proficiency directly impacts civil aviation safety and efficiency. To address the lack of clear training objectives and inconsistent evaluation methods in the initial controller training at the Southwest Air Traffic Management Bureau, this study aimed to develop and validate a core competency model for initial air traffic controllers. Referencing ICAO Document 10056, the study first defined core competencies. Subsequently, using job analysis, the behavioral event interview (BEI) method, and expert panels, a core competency model tailored to the training objectives of the Southwest ATMB was constructed. The key findings of this research include: first, the defined structure of the developed model, comprising seven competency dimensions, 21 elements, and 26 observable behaviors (OBs); second, the determination of combined weights for each dimension and indicator using questionnaire surveys, the Analytic Hierarchy Process (AHP), and the Entropy Weight Method; and third, the successful application and validation of the model. Specifically, in its application, the weighted TOPSIS method was employed to evaluate trainees in a specific group. This not only provided a ranking of trainee abilities but also facilitated in-depth analysis through radar charts of competency dimensions and box plots of OB items. These application results demonstrate the model’s effectiveness and practicality. Full article

Crops in greenhouses located in cold climates are frequently affected by high relative humidity (RH). This study presents the design, testing, and analysis of a dehumidifier based on thermoelectric cooling. Thermoelectric dehumidifiers (TEDs) are capable of dehumidifying greenhouses in cold regions while recovering heat for indoor air heating. The design of a TED is based on the specific characteristics of thermoelectric coolers (TECs). A TED consists of a cabinet, four heat exchangers, a duct fan, a water pump, and auxiliary components. The TED performance was evaluated in a Chinese solar greenhouse (CSG) with a volume of approximately 160 m³. The input voltage of the TECs, fan airflow rate, and cold-side fin area affected the TED performance, with their influence varying in magnitude. The radar chart results show that the optimal operating parameters are as follows: a fan airflow rate of 300 m³/h, a TEC input voltage of 15 V, and a cold-side fin area of 0.15 m². With the TED running for 120 min under the optimal parameters, the RH in the CSG decreased by 25.5%, while the air temperature increased by 3.4 °C. The installation of the TED at the bottom of the CSG improved the growing environment of the crops, particularly in the vertical range between 0.2 m and 1.5 m height inside the greenhouse. These findings provide a valuable reference for applying thermoelectric cooling technology in the greenhouse field. Full article

The utilization of coral aggregates in the preparation of Ultra-High Performance Concrete (UHPC) effectively addresses the material scarcity challenges in island and reef construction environments, thereby advancing the sustainable development of building materials technology. This research systematically investigates the physical and mechanical properties of Coral Sand UHPC (CSUHPC) with varying fiber contents through uniaxial compression tests, splitting tensile tests, and stress–strain curve tests under compression. The experimental results demonstrate that the incorporation of fibers significantly enhances both the mechanical strength and ductility of CSUHPC. The test data indicate that CSUHPC specimens with a steel fiber volume fraction of 3% exhibit the highest performance, attaining a compressive strength of 131.9 MPa and a splitting tensile strength of 18.5 MPa. The compressive stress–strain curve tests reveal that the incorporation of fibers induces a failure mode transition in CSUHPC specimens from brittle to ductile. Furthermore, a constitutive equation for CSUHPC was proposed, and a multi-dimensional assessment system based on the radar chart, which encompasses compressive strength, splitting tensile strength, peak strain, compressive toughness, and an energy dissipation coefficient. The optimal fiber combination was determined as a hybrid fiber system comprising 2% steel fibers and 1% polyethylene (PE) fibers, which demonstrates superior comprehensive performance. Full article

Using coal gangue in highway base construction provides a sustainable and high-value solid waste recycling approach. This research focused on the mechanical and durability properties of coal gangue from tunneling operations. Six experimental tests, such as unconfined compressive strength (UCS), flexural–tensile strength (FTS), etc., were carried out. The impact of aggregate gradation on coal gangue mixtures’ performance was systematically evaluated. XRD and SEM were used to explore the microstructural mechanisms in cement-stabilized coal gangue–gravel mixtures (CGM). An improved evaluation model, the Delphi–entropy weight–TOPSIS (DET) method, integrating Delphi and entropy weighting, was proposed. Together with an advanced radar chart, it evaluates eight performance criteria, including mechanical, durability, economic, and environmental aspects. The results show that increasing the coal gangue content in mixtures decreases UCS, dynamic compressive rebound modulus (DCRM), FTS, fatigue life, and drying shrinkage performance. Coarse aggregates relieve drying shrinkage, while fine ones improve long-term mechanical properties. Gradation T1~3 promotes the formation of C–S–H gel and AFt crystals, enhancing compactness. Based on the DET model’s quantitative evaluation, T1~3 was determined as the optimal mix for expressway bases, achieving a balance between mechanical performance, durability, and sustainability. Full article

In this study, we explored the use of surface plasmon resonance (SPR) and Mach–Zehnder interferometry for detecting compounds in complex mixtures separated by supercritical fluid chromatography. Each molecule was individually injected and analyzed by supercritical fluid chromatography (SFC) in a 10% alcoholic solution. The fingerprints obtained via the sensors were then compared to the fingerprints of the same molecules present in a lemon essential oil (EO) at the same dilution. The results show a remarkable correlation between UV sensors and electronic noses (e-nose), enabling compound detection. The obtained signals are normalized and presented as radar charts to visualize the specific olfactory signatures of each molecule. The olfactory profiles of monoterpenes C₁₀H₁₆ such as α-pinene and limonene show notable differences, as do the C₁₀H₁₆O isomers (citral, geranial, and neral). Mach–Zehnder interferometry also allows for the discrimination of limonene enantiomers, a challenging task for current chromatography techniques. Statistical analysis confirms the ability of these technologies to differentiate compounds, including isomers. Even if UV detection is more sensitive than SPR, e-noses (SPR and Mach–Zehnder interferometers) offer the unique advantage of providing specific signatures for each compound, facilitating real-time identification. This study demonstrates the effectiveness of combining e-noses with SFC for rapid, non-destructive detection of volatile compounds. This concept can be extended to other terpenoids and volatile compounds, and hybridization with gas chromatography could be a future potential development. Full article

In light of the challenges confronting urban areas due to increasing populations and spatial constraints, urban green infrastructure is vital for fostering environmental balance, enhancing community well being, and promoting sustainable urban development. This situation underscores the necessity for strategies that reconcile the escalating demand for constructed environments with the enhancement of urban green infrastructure in urban areas. This study seeks to empirically investigate an integrated spatial analysis approach that synthesises the quality of urban green infrastructure and land characteristics by incorporating diverse perspectives, utilising the Altstetten-Albisrieden district of Zurich as a case study. It systematically evaluates factors including development density, green surface coverage, leaf area, green ratio and connectivity, and the accessibility of public green spaces within the studied district. A 10-m rectangular grid was employed to visualise and integrate the evaluation results from different perspectives. Furthermore, clustering algorithms were utilised to generate spatial patterns indicative of unique land characteristics. By comparing the results from various clustering algorithms, this study adopted the fifteen clusters derived from the K-Means method, employing radar charts to describe the characteristics of each cluster, and partitioned the district into five zones to provide recommendations regarding the provision and optimisation of urban green infrastructure within the district. Ultimately, it highlighted the necessity of increasing community gardens and green spaces in densely built areas and leveraging existing structures to augment vegetation and plant life for the enhancement of ecological benefits. Full article