Search Results (250)

The rapid evolution of UAV technology has increased the demand for lightweight airborne perception systems. This study introduces ADG-YOLO, an optimized model for real-time target detection and ranging on UAV platforms. Building on YOLOv11n, we integrate C3Ghost modules for efficient feature fusion and ADown layers for detail-preserving downsampling, reducing the model’s parameters to 1.77 M and computation to 5.7 GFLOPs. The Extended Kalman Filter (EKF) tracking improves positional stability in dynamic environments. Monocular ranging is achieved using similarity triangle theory with known target widths. Evaluations on a custom dataset, consisting of 5343 images from three drone types in complex environments, show that ADG-YOLO achieves 98.4% mAP_0.5 and 85.2% mAP_0.5:0.95 at 27 FPS when deployed on Lubancat4 edge devices. Distance measurement tests indicate an average error of 4.18% in the 0.5–5 m range for the DJI NEO model, and an average error of 2.40% in the 2–50 m range for the DJI 3TD model. These results suggest that the proposed model provides a practical trade-off between detection accuracy and computational efficiency for resource-constrained UAV applications. Full article

This study develops a geomorphological identification methodology for wall reefs in the microcontinental environment of Wangiwangi Island, Indonesia, using medium-resolution Landsat 8 satellite imagery and morphological analysis based on Maxwell’s geomorphological framework. The uniqueness of the wall reef landform lies in the fact that the lagoon elongates on limestone, resulting in a habitat and ecosystem that develops differently from those of other shelf reefs, namely, platform reefs and plug reefs. Using Optimum Index Factor (OIF) optimization and RGB image composites, four reef types were successfully identified: cuspate reefs, open ring reefs, closed ring reefs, and resorbed reefs. A field check was conducted at fifteen observation sites, which included measurements of depth, turbidity, and water quality parameters, as well as an in situ benthic habitat inventory. The analysis results showed a strong correlation between image composites, geomorphological reef classes, and ecological conditions, confirming the successful adaptation of Maxwell’s classification to the Indonesian reef system. This hybrid integrated approach successfully maps the distribution of reefs on a complex continental shelf, providing an essential database for shallow-water spatial planning, ecosystem-based conservation, and sustainable management in the Coral Triangle region. Policy recommendations include zoning schemes for protected areas based on reef landform morphology, strengthening integrative monitoring systems, and utilizing high-resolution imagery and machine learning algorithms in further research. Full article

The axisymmetric geometries of both internal and external profiles of church bells, along with the properties of the bell metal, are of vital importance to their acoustics. The role of “golden geometry” in determining the visual characteristics of the outer profile of a modern English church bell is presented. It is shown that a golden rectangle, a golden triangle, and a golden angle are all important factors. Three angular parameters are identified as measures of these attributes of the bell’s “goldenness”. Two of these features are shown to result from an underlying regular pentagon with one side defined by the bell’s mouth. The centre of this pentagon determines the location of the bell’s shoulders. Further minor features are also shown to be determined by golden geometry. The evolution of the three angular parameters over the previous millennium is included, showing a tendency to trend quickly towards the golden values in all the cases. Ultimately, the angular parameters for the English church bell of focus here are used for comparison with other modern European bells studied previously. The bells considered all displayed at least two of the three major golden features to an agreement of better than 1%. Full article

This paper presents a systematic methodology for identifying optimal scaling regions in segment-based box-counting fractal dimension calculations through a three-phase algorithmic framework combining grid offset optimization, boundary artifact detection, and sliding window optimization. Unlike traditional pixelated approaches that suffer from rasterization artifacts, the method used directly analyzes geometric line segments, providing superior accuracy for mathematical fractals and other computational applications. The three-phase optimization algorithm automatically determines optimal scaling regions and minimizes discretization bias without manual parameter tuning, achieving significant error reduction compared to traditional methods. Validation across the Koch curve, Sierpinski triangle, Minkowski sausage, Hilbert curve, and Dragon curve demonstrates substantial improvements: excellent accuracy for the Koch curve (0.11% error) and significant error reduction for the Hilbert curve. All optimized results achieve $R^2\ge 0.9988$. Iteration analysis establishes minimum requirements for reliable measurement, with convergence by level 6+ for the Koch curve and level 3+ for the Sierpinski triangle. Each fractal type exhibits optimal iteration ranges where authentic scaling behavior emerges before discretization artifacts dominate, challenging the assumption that higher iteration levels imply more accurate results. Application to a Rayleigh–Taylor instability interface (D = 1.835 ± 0.0037) demonstrates effectiveness for physical fractal systems where theoretical dimensions are unknown. This work provides objective, automated fractal dimension measurement with comprehensive validation establishing practical guidelines for mathematical and real-world fractal analysis. The sliding window approach eliminates subjective scaling region selection through systematic evaluation of all possible linear regression windows, enabling measurements suitable for automated analysis workflows. Full article

This study aimed to develop a non-contact, marker-less machine learning model to estimate forearm pronation–supination angles using 2D hand landmarks derived from MediaPipe Hands, with inertial measurement unit sensor angles used as reference values. Twenty healthy adults were recorded under two camera conditions: medial (in-camera) and lateral (out-camera) viewpoints. Five regression models were trained and evaluated: Linear Regression, ElasticNet, Support Vector machine (SVM), Random Forest, and Light Gradient Boosting Machine (LightGBM). Among them, LightGBM achieved the highest accuracy, with a mean absolute error of 5.61° in the in-camera setting and 4.65° in the out-camera setting. The corresponding R² values were 0.973 and 0.976, respectively. The SHAP analysis identified geometric variations in the palmar triangle as the primary contributors, whereas elbow joint landmarks had a limited effect on model predictions. These results suggest that forearm rotational angles can be reliably estimated from 2D images, with an accuracy comparable to that of conventional goniometers. This technique offers a promising alternative for functional evaluation in clinical settings without requiring physical contact or markers and may facilitate real-time assessment in remote rehabilitation or outpatient care. Full article

Traditional Case-Based Reasoning (CBR) methods face significant methodological challenges, including limited information resources in case databases, methodologically inadequate similarity calculation approaches, and a lack of standardized case revision mechanisms. These limitations lead to suboptimal case matching and insufficient solution adaptation, highlighting critical gaps in the development of CBR methodologies. This paper proposes a novel CBR framework enhanced by generative AI, aiming to improve and innovate existing methods in three key stages of traditional CBR, thereby enhancing the accuracy of retrieval and the scientific nature of corrections. First, we develop an ontology model for comprehensive case representation, systematically capturing scenario characteristics, risk typologies, and strategy frameworks through structured knowledge representation. Second, we introduce an advanced similarity calculation method grounded in triangle theory, incorporating three computational dimensions: attribute similarity measurement, requirement similarity assessment, and capability similarity evaluation. This multi-dimensional approach provides more accurate and robust similarity quantification compared to existing methods. Third, we design a generative AI-based case revision mechanism that systematically adjusts solution strategies based on case differences, considering interdependence relationships and mutual influence patterns among risk factors to generate optimized solutions. The methodological framework addresses fundamental limitations in existing CBR approaches through systematic improvements in case representation, similarity computation, and solution adaptation processes. Experimental validation using actual case data demonstrates the effectiveness and scientific validity of the proposed methodological framework, with applications in risk assessment and emergency response scenarios. The results show significant improvements in case-matching accuracy and solution quality compared to traditional CBR approaches. This method provides a robust methodological foundation for CBR-based decision-making systems and offers practical value for risk management applications. Full article

This study investigates the thermal performance of induction motors powered by multilevel H-bridge inverters using a novel pulse-width phase shift triangle modulation (PSTM-PWM) technique. Conventional PWM methods introduce significant harmonic distortion, increasing copper and iron losses and causing overheating and reduced motor lifespan. Through experimental testing and comparison with standard PWM techniques (LS-PWM and PS-PWM), the proposed PSTM-PWM reduces harmonic distortion by up to 64% compared to the worst one and internal motor losses by up to 5.5%. A first-order thermal model is used to predict motor temperature, validated with direct thermocouple measurements and infrared thermography. The results also indicate that the PSTM-PWM technique improves thermal performance, particularly at a triangular waveform peak value of 3.5 V, reducing temperature by around 6% and offering a practical and simple solution for industrial motor drive applications. The modulation order was set to M = 7 to reduce both the losses in the power inverter and to prevent the generation of very high voltage pulses (high dV/dt), which can deteriorate the insulation of the induction motor windings over time. Full article

Background and Objectives: Three-dimensional (3D) scanning is increasingly utilized in medical practice, from orthotics to surgical planning. However, traditional hand measurement techniques remain inconsistent and prone to human error and are often time-consuming. This research evaluates the practicality of a commercial 3D scanning method by comparing the accuracy of scans conducted by two user groups. Materials and Methods: This study evaluated the following two groups: an experimental group (n = 45) and a control group (n = 42). A total of 261 hand scans were captured using the Structure Sensor Pro 3D scanner for iPad (Structure, Boulder, CO, USA). The scans were then evaluated using Meshmixer software (version 3.5.474), analyzing key parameters, such as surface area, volume, number of vertices, and triangles, etc. Furthermore, a digital literacy test and a user experience survey were conducted to support a more comprehensive evaluation of participant performance within the study. Results: The experimental group outperformed the control group on all measured parameters, including surface area, volume, vertices, triangle, and gap count, with large effect sizes observed. User experience data revealed that participants in the experimental group rated the 3D scanner significantly higher across all dimensions, particularly in ease of use, excitement, supportiveness, and practicality. Conclusions: A short 15 min training session can promote scan reliability, demonstrating that even minimal instruction improves users’ proficiency in 3D scanning, fundamental for supporting clinical accuracy in diagnosis, surgical planning, and personalized device manufacturing Full article

This study focuses on the Triangle of Central China and investigates the spatiotemporal evolution, driving factors, and impacts of population aging on regional sustainable development from 2000 to 2020. The study adopts an innovative two-scale analytical framework at the prefecture and district/county level, integrating spatial autocorrelation analysis, the Geodetector model, and geographically weighted regression. The results show a significant acceleration in population aging across the study area, accompanied by pronounced spatial clustering, particularly in western Hubei and the Wuhan metropolitan area. Over time, the spatial distribution has evolved from a relatively dispersed pattern to one of high concentration. Key drivers of the spatial heterogeneity of aging include economic disparities, demographic transitions, and the uneven spatial allocation of public services such as healthcare and education. These aging patterns profoundly affect the region’s potential for sustainable development. Accordingly, the study proposes a multi-scale collaborative governance strategy: At the prefecture level, efforts should focus on promoting the coordinated development of the silver economy and optimizing the spatial redistribution of healthcare resources; At the district and county level, priorities should include strengthening infrastructure, curbing the outflow of young labor, and improving access to basic public services. By integrating spatial analysis techniques with sustainable development policy recommendations, this study provides a basis for scientifically measuring, understanding, and managing demographic transitions. This is essential for achieving long-term socioeconomic sustainability in rapidly aging regions. Full article

This study develops a high-accuracy indoor positioning system using ultra-wideband (UWB) technology and the time-of-arrival (TOA) method. The system is built using Arduino Nano microcontrollers and DW1000 UWB chips to measure distances between anchor nodes and a mobile tag. Three positioning algorithms are tested: the triangle centroid algorithm (TCA), inner triangle centroid algorithm (ITCA), and the proposed intersection midpoint algorithm (IMA). Experiments conducted in a 732 × 488 × 220 cm indoor environment show that TCA performs well near the center but suffers from reduced accuracy at the edges. In contrast, IMA maintains stable and accurate positioning across all test points, achieving an average error of 12.87 cm. The system offers low power consumption, fast computation, and high positioning accuracy, making it suitable for real-time indoor applications such as hospital patient tracking and shopping malls where GPS is unavailable or unreliable. Full article

This study focuses on thermal comfort in residential buildings within the Iron Triangle area of South Australia, examining how indoor conditions influence residents’ comfort and adaptive behaviours. Conducted from June 2023 to February 2024 across 30 homes in Port Pirie, Port Augusta, and Whyalla, the research gathered data from 38 residents, who reported indoor comfort levels in living rooms and bedrooms. A total of 3540 responses were obtained. At the same time, the measurement of indoor conditions in the buildings was performed using a small HOBO MX1104 device. Using the Mean Thermal Sensation Vote (MTSV) concept, it was possible to determine the neutral operative temperature and temperature ranges for thermal comfort categories. According to the defined linear regression formula, the neutral temperature was 23.9 °C. In living rooms, it was slightly lower, at 23.7 °C, and in bedrooms, slightly higher, at 24.4 °C. For comparison, the neutral temperature was calculated based on the average Predicted Mean Vote (MPMV) and equal to 24.3 °C. Comparison of the regression curves showed that in terms of slope, the MPMV curve is steeper (slope 0.282) than the MTSV curve (slope 0.1726), and lies above it. Regarding the residents’ behaviour, a strong correlation was found between the operative temperature T_o and the degree of clothing I_cl in living rooms. Use of ceiling fans was also studied. A clear trend was also observed regarding window and door opening. The findings of the research can be used to inform the design and operation of residential buildings with a view to enhancing thermal comfort and energy efficiency. Full article

Lithium (Li)-rich continental brines found in the Lithium Triangle region in South America are a natural resource of paramount importance. In the present research, the analytical performance of laser-induced breakdown spectroscopy (LIBS) technology was assessed for the quantitative analysis of Li in natural brines aimed at enhancing the efficient exploration of salt flats (called salars). Brine samples were collected from different salars located in the Puna plateau (Northwest Argentina) and analyzed by LIBS in the form of solid pressed pellets. Broadband emission spectra (180–900 nm) were recorded and spectrally analyzed by specially designed computational algorithms. The laser-induced plasmas were characterized by calculating the electron density and the temperature. The Li elemental concentrations in the brines were determined through univariate calibration with the Li I emission line at 670.77 nm by using a suitable set of standards with Li concentrations up to 1300 $\mathsf{\mu }$g/g. The calculated limit of detection was LoD = 0.2 ± 0.1 $\mathsf{\mu }$g/g. The Li content in the brines determined with LIBS showed a good agreement (normalized standard deviation: σ_N = 25%) with the concentrations measured with atomic absorption spectroscopy. The results demonstrated the feasibility of the LIBS technique for the quantitative analysis of Li in natural brines, thus contributing to advancing the exploration of Li-rich resources. Full article

Transforaminal lumbar interbody fusion (TLIF) is a commonly employed surgical technique for managing lumbar degenerative disease and spinal instability. While it offers advantages over posterior lumbar interbody fusion (PLIF), traditional TLIF often involves prolonged recovery and morbidity due to muscle retraction. To improve outcomes, several alternative techniques have emerged, including minimally invasive TLIF (MIS-TLIF), trans-Kambin percutaneous TLIF (PE-TLIF), and transfacet TLIF (TF-TLIF). Each approach presents distinct anatomical and technical advantages, yet no standardized framework exists to guide their selection based on individual patient anatomy. In this study, we review the evolution of TLIF techniques and propose a novel algorithm that integrates patient-specific imaging, anatomical variability, and segmentation data to guide surgical decision-making. By analyzing the surgical corridors, indications, and limitations of each approach, and presenting representative clinical cases, we demonstrate how this algorithm can be applied in practice. For instance, TF-TLIF may be optimal in patients requiring direct decompression without major deformity, while PE-TLIF may be appropriate for those with Kambin’s triangles measuring ≥ 9 mm, allowing for indirect decompression. This tailored framework aims to optimize outcomes and reduce complications. Further prospective validation and incorporation of AI-driven segmentation tools are needed to support broader clinical implementation. Full article

The paper investigates an alternative approach to measuring and compensating reactive power in electric machines, particularly under non-sinusoidal voltage and current waveforms. Traditional power definitions, such as those introduced by Budeanu and Fryze, as well as the power triangle, are discussed alongside integral definitions of reactive power, which account for waveform distortions. This approach is novel and has not been previously applied in the context of electric machines. A digital algorithm for reactive power calculation, based on the integral definition, is proposed. It requires minimal computational resources and is easy to implement. Experimental measurements conducted on a single-phase induction motor demonstrate the impact of capacitive compensation on current waveforms. The results confirm the validity of the adopted definition of reactive power. With full reactive power compensation, the RMS value of the current drawn by the motor is minimized, which is not always the case with the classical approach to improving the power factor. The findings highlight the importance of accurate reactive power measurement and compensation in enhancing the performance and energy efficiency of electrical machines. The proposed approach is applicable not only to single-phase motors but also more broadly in determining the reactive power drawn by electric machines and in measuring electric energy, particularly in the presence of distorted voltages and currents. Full article

Background/Objectives: The hypoglossal nerve plays a crucial role in cervical surgery, requiring precise anatomical knowledge to prevent iatrogenic injury. This study examined its position relative to key structures using cadaveric dissections and assessed ChatGPT-4’s reliability in providing anatomical insights. Methods: Ten cadavers were dissected to identify the hypoglossal nerve’s course in relation to the internal jugular vein, carotid arteries, thyro-linguo-facial trunk, hyoid bone, and digastric muscle. Measurements were taken, and ChatGPT was queried for anatomical guidance and surgical recommendations. Results: The hypoglossal nerve was consistently medial to the internal jugular vein and lateral to the carotid arteries. The measured distances to the surrounding structures showed notable variability, particularly with the thyro-linguo-facial trunk. ChatGPT accurately described major landmarks but overlooked lesser-known anatomical triangles and provided no additional dissection guidance. It primarily suggested intraoperative monitoring and preoperative imaging. Conclusions: The carotid and submandibular triangles serve as reliable landmarks for identifying the hypoglossal nerve. This study highlights an unreported variability in its relationship with the thyro-linguo-facial trunk. ChatGPT, while informative, lacked detailed surgical applicability for dissection. Full article