Search Results (15)

Background/Objectives: Semi-active prosthetic feet present a promising solution that enhances adaptability while maintaining modest size, weight, and cost. We propose a semi-active Two-Keel Variable-Stiffness Foot (VSF-2K), the first prosthetic foot where both the hindfoot and forefoot stiffness can be independently and actively modulated. We present a model-based analysis of the effects of different VSF-2K settings on prosthesis characteristics and gait metrics. Methods: The study introduces a simulation model for the VSF-2K: (1) one sub-model to optimize the design of the keels of VSF-2K to maximize compliance, (2) another sub-model to simulate the stance phase of walking with different stiffness setting pairs and ankle alignment angles (dorsiflexion/plantarflexion), and (3) a third sub-model to simulate the keel stiffness of the hindfoot and forefoot keels comparably to typical mechanical testing. We quantitatively analyze how the VSF-2K’s hindfoot and forefoot stiffness settings and ankle alignments affect gait metrics: Roll-over Shape ($ROS$), Effective Foot Length Ratio ($EFLR$), and Dynamic Mean Ankle Moment Arm ($DMAMA$). We also introduce an Equally Spaced Resampling Algorithm (ESRA) to address the unequal-weight issue in the least-squares circle fit of the Roll-over Shape. Results: We show that the optimal-designed VSF-2K successfully achieves controlled stiffness that approximates the stiffness range observed in prior studies of commercial prostheses. Our findings suggest that stiffness modulation significantly affects gait metrics, and it can mimic or counteract ankle angle adjustments, enabling adaptation to sloped terrain. We show that $DMAMA$ is the most promising metric for use as a control parameter in semi-active or variable-stiffness prosthetic feet. We identify the limitations in $ROS$ and $EFLR$, including their nonmonotonic relationship with hindfoot/forefoot stiffness, insensitivity to hindfoot stiffness, and inconsistent trends across ankle alignments. We also validate that the angular stiffness of a two-independent-keel prosthetic foot can be predicted using either keel stiffness from our model or from a standardized test. Conclusions: These findings show that semi-active variation of hindfoot and forefoot stiffness based on single-stride metrics such as $DMAMA$ is a promising control approach to enabling prostheses to adapt to a variety of terrain and alignment challenges. Full article

We have proposed a multi-strategy enhanced particle swarm optimization (PSO) algorithm to optimize the antenna spacing distribution of an optical phased array (OPA). The global search capability is improved by incorporating circle chaotic mapping initialization and an updated strategy based on adaptive inertia weights and dynamic learning factors. We used the peak side-lobe level (PSLL) at different steering angles as the fitness function, which effectively suppresses the rapid degradation of PSLL during scanning. Based on this approach, 32- and 64-channel aperiodic OPAs were designed with a scanning range of ±60°, with improvements of the PSLL of 1.94 and 2.05 dB at 60°, respectively. In addition, the analytical and numerical simulation results are in good agreement. We also analyzed the influence of spacing deviations on PSLL and found that the obtained OPAs exhibit sufficient robustness. Full article

A high-quality optical path alignment is essential for achieving superior image quality in optical biological microscope (OBM) systems. The traditional automatic alignment methods for OBMs rely heavily on complex masker-detection techniques. This paper introduces an innovative, image-sensor-based optical path alignment approach designed for low-power objective (specifically 4×) automatic OBMs. The proposed method encompasses reference objective (RO) identification and alignment processes. For identification, a model depicting spot movement with objective rotation near the optical axis is developed, elucidating the influence of optical path parameters on spot characteristics. This insight leads to the proposal of an RO identification method utilizing an edge gradient and edge position probability. In the alignment phase, a symmetry-based weight distribution scheme for concentric arcs is introduced. A significant observation is that the received energy stabilizes with improved alignment precision, prompting the design of an advanced alignment evaluation method that surpasses conventional energy-based assessments. The experimental results confirm that the proposed RO identification method can effectively differentiate between 4× and 10× objectives across diverse light intensities and exposure levels, with a significant numerical difference of up to 100. The error–radius ratio of the weighted circular fitting method is maintained below 1.16%, and the fine alignment stage’s evaluation curve is notably sharper. Moreover, tests under various imaging conditions in artificially saturated environments indicate that the alignment estimation method, predicated on critical saturation positions, achieves an average error of 0.875 pixels. Full article

How to acquire the exact center of a circular sample is an essential task in object recognition. Present algorithms suffer from the high time consumption and low precision. To tackle these issues, we propose a novel circle center location algorithm based on sample density and adaptive thresholding. After obtaining circular contours through image pre-processing, these contours were segmented using a grid method to obtain the required coordinates. Based on the principle of three points forming a circle, a data set containing a large number of samples with circle center coordinates was constructed. It was highly probable that these circle center samples would fall within the near neighborhood of the actual circle center coordinates. Subsequently, an adaptive bandwidth fast Gaussian kernel was introduced to address the issue of sample point weighting. The mean shift clustering algorithm was employed to compute the optimal solution for the density of candidate circle center sample data. The final optimal center location was obtained by an iteration algorithm. Experimental results demonstrate that in the presence of interference, the average positioning error of this circle center localization algorithm is 0.051 pixels. Its localization accuracy is $64.1\%$ higher than the Hough transform and $86.4\%$ higher than the circle fitting algorithm. Full article

The traditional measurement method (e.g., field survey) of tree diameter circumference often has high labor costs and is time-consuming. Mobile laser scanning (MLS) is a powerful tool for measuring forest diameter at breast height (DBH). However, the accuracy of point cloud registration seriously affects the results of DBH measurements. To address this issue, this paper proposes a new method for extracting tree DBH parameters; it achieves the purpose of efficient and accurate extraction of tree DBH by point cloud filtering, single-tree instance segmentation, and least squares circle fitting. Firstly, the point cloud data of the plantation forest samples were obtained by a self-constructed unmanned vehicle-mounted mobile laser scanning system, and the ground point cloud was removed using cloth simulation filtering (CSF). Secondly, fast Euclidean clustering (FEC) was employed to segment the single-tree instances, and the point cloud slices at breast height were extracted based on the point sets of single-tree instances, which were then fitted in two dimensions using the horizontally projected point cloud slices. Finally, a circle fitting algorithm based on intensity weighted least squares (IWLS) was proposed to solve the optimal circle model based on 2D point cloud slices, to minimize the impact of misaligned point clouds on DBH measures. The results showed that the mean absolute error (MAE) of the IWLS method was 2.41 cm, the root mean square error (RMSE) was 2.81 cm, and the relative accuracy was 89.77%. Compared with the random sample consensus (RANSAC) algorithm and ordinary least squares (OLS), the MAE was reduced by 36.45% and 9.14%, the RMSE was reduced by 40.90% and 12.26%, and the relative accuracy was improved by 8.99% and 1.63%, respectively. The R² value of the fitted curve of the IWLS method was the closest to 1, with the highest goodness of fit and a significant linear correlation with the true value. The proposed intensity weighted least squares circle-fitting DBH extraction method can effectively improve the DBH extraction accuracy of mobile laser scanning point cloud data and reduce the influence of poorly aligned point clouds on DBH fitting. Full article

This study presents a methodology to prevent the overdesign of electric dispensers for dental impression materials by analyzing the necessary load and determining the appropriate pressurization speed and drive motor capacity. We derived an equation to calculate the required torque and rotational speed of the motor based on the extrusion load and the speed of the impression material. A specialized load measurement system was developed to measure the load necessary to extrude the impression material. Through experiments and image processing, we measured the radius of curvature of the trajectory of the impression material and correlated it with the pressurization speed. Techniques such as position coordinate plotting, curve fitting, and circle fitting were employed to determine the pressurization speed that aligns with the manufacturer’s recommended curvature radius. These findings led to a substantial decrease in the necessary motor torque and rotational speed compared with the current standards. This research provides a systematic approach to sizing drive motors using extrusion load and pressurization speed, aiming to reduce overdesign, power consumption, and the weight and size of the motor and battery, thereby contributing to the development of more efficient and compact dental impression material dispensers. Full article

In substation lightning rod meter reading data taking, the classical object detection model is not suitable for deployment in substation monitoring hardware devices due to its large size, large number of parameters, and slow detection speed, while is difficult to balance detection accuracy and real-time requirements with the existing lightweight object detection model. To address this problem, this paper constructs a lightweight object detection algorithm, YOLOv5-Meter Reading Lighting (YOLOv5-MRL), based on the improved YOLOv5 model’s speed while maintaining accuracy. Then, the YOLOv5s are pruned based on the convolutional kernel channel soft pruning algorithm, which greatly reduces the number of parameters in the YOLOv5-MRL model while maintaining a certain accuracy loss. Finally, in order to facilitate the dial reading, the dial external circle fitting method is proposed to calculate the dial reading using the circular angle algorithm. The experimental results on the self-built dataset show that the YOLOv5-MRL object detection model achieves a mean average precision of 96.9%, a detection speed of 5 ms/frame, and a model weight size of 5.5 MB, making it better than other advanced dial reading models. Full article

In a three-dimensional (3D) disaster rescue mission environment, multi-drone mission assignments and path planning are challenging. Aiming at this problem, a mission assignment method based on adaptive genetic algorithms (AGA) and a path planning method using sine–cosine particle swarm optimization (SCPSO) are proposed. First, an original 3D digital terrain model is constructed. Second, common threat sources in disaster rescue environments are modeled, including mountains, transmission towers, and severe weather. Third, a cost–revenue function that considers factors such as drone performance, demand for mission points, elevation cost, and threat sources, is formulated to assign missions to multiple drones. Fourth, an AGA is employed to realize the multi-drone mission assignment. To enhance convergence speed and optimize performance in finding the optimal solution, an AGA using both the roulette method and the elite retention method is proposed. Additionally, the parameters of the AGA are adjusted according to the changes in the fitness function. Furthermore, the improved circle algorithm is also used to preprocess the mission sequence for AGA. Finally, based on the sine–cosine function model, a SCPSO is proposed for planning the optimal flight path between adjacent task points. In addition, the inertia and acceleration coefficients of linear weights are designed for SCPSO so as to enhance its performance to escape the local minimum, explore the search space more thoroughly, and achieve the purpose of global optimization. A multitude of simulation experiments have demonstrated the validity of our method. Full article

Due to the presence of numerous surface defects, the inadequate contrast between defective and non-defective regions, and the resemblance between noise and subtle defects, edge detection poses a significant challenge in dimensional error detection, leading to increased dimensional measurement inaccuracies. These issues serve as major bottlenecks in the domain of automatic detection of high-precision metal parts. To address these challenges, this research proposes a combined approach involving the utilization of the YOLOv6 deep learning network in conjunction with metal lock body parts for the rapid and accurate detection of surface flaws in metal workpieces. Additionally, an enhanced Canny–Devernay sub-pixel edge detection algorithm is employed to determine the size of the lock core bead hole. The methodology is as follows: The data set for surface defect detection is acquired using the labeling software lableImg and subsequently utilized for training the YOLOv6 model to obtain the model weights. For size measurement, the region of interest (ROI) corresponding to the lock cylinder bead hole is first extracted. Subsequently, Gaussian filtering is applied to the ROI, followed by a sub-pixel edge detection using the improved Canny–Devernay algorithm. Finally, the edges are fitted using the least squares method to determine the radius of the fitted circle. The measured value is obtained through size conversion. Experimental detection involves employing the YOLOv6 method to identify surface defects in the lock body workpiece, resulting in an achieved mean Average Precision ($mAP$) value of 0.911. Furthermore, the size of the lock core bead hole is measured using an upgraded technique based on the Canny–Devernay sub-pixel edge detection, yielding an average inaccuracy of less than 0.03 mm. The findings of this research showcase the successful development of a practical method for applying machine vision in the realm of the automatic detection of metal parts. This achievement is accomplished through the exploration of identification methods and size-measuring techniques for common defects found in metal parts. Consequently, the study establishes a valuable framework for effectively utilizing machine vision in the field of metal parts inspection and defect detection. Full article

The wafer pre-aligner is a crucial component in the lithography process to correct the wafer center and notch orientation. To improve the precision and the efficiency of pre-alignment, a new method to calibrate the center and the orientation of a wafer based on the weighted Fourier series fitting of circles (WFC) method and the least squares fitting of circles (LSC) method, respectively, is proposed. The WFC method effectively suppressed the influence of the outliers and had high stability compared with the LSC method when fitted to the center of the circle. While the weight matrix degenerated to the identity matrix, the WFC method degenerated into the Fourier series fitting of circles (FC) method. The fitting efficiency of the FC method is 28% higher than that of the LSC method, and the fitting accuracy of the center of the FC method is the same as that of the LSC method. In addition, the WFC method and the FC method perform better than the LSC method in radius fitting. The pre-alignment simulation results showed that the absolute position accuracy of the wafer was ±2 µm, the absolute direction accuracy was 0.01°, and the total calculation time was less than 3.3 s in our platform. Full article

The basic principle of photogrammetry is mature and widely used in engineering. For gantry cranes, the base of which is usually a cylinder, the measurement of the center of the cylinder cross section is difficult, but its coordinates have an important impact on the safety evaluation of cranes. Aiming at the problem of measuring the center of a circle, an optimization method of fitting the center of a circle based on photogrammetry and the Hough transform is proposed. In this algorithm, the effect of image point distortion on the measurement accuracy is considered, and the similarity between ideal and actual midperpendicular is compared in the Hough space. The similarity is taken as the weight of the midperpendicular, and the space coordinates of the center of the circle are fitted again. This process needs to iterate repeatedly until convergence, and the fitting accuracy of the equal weighted midperpendicular fitting algorithm and the weighted midperpendicular fitting algorithm is compared. Finally, according to the characteristics of the algorithm, a theoretical verification experiment and an engineering experiment are carried out. The experimental results show that the proposed weighted midperpendicular fitting algorithm has a better effect than the equal weighted midperpendicular fitting algorithm, which obviously improves the fitting accuracy of the center of the circle and has high engineering value. In both experiments, the relative error was less than one percent. Especially in the engineering experiments, the weighted midperpendicular algorithm improved accuracy by an order of magnitude. Therefore, the proposed algorithm significantly improves the fitting accuracy of the center of the circle and effectively solves the difficulty that the center of the circle cannot be directly measured on the construction machinery. Full article

This study documents evaluation of the Her Tribe and His Tribe Aboriginal-designed empowerment pilot programs. The programs were designed to support Victorian Aboriginal people to strengthen mental health, social and emotional wellbeing, community connection, and to reduce psychological distress. A second aim was to explore participants’ experiences of the programs, including the feasibility and acceptability of the evaluation component. Her Tribe ran for 16 weeks and His Tribe for 12 weeks. In total, 43 women and 26 men completed assessments at pre- and post-program completion, and 17 and 10, respectively, participated in yarning circles at the 6-month follow up. For both programs, there were significant increases in participants’ access to personal strengths and resources, relationship–community–cultural strengths and resources, and decreases in psychological distress. These changes were associated with small to moderate effects that were maintained at the 6-month follow up. There was a significant increase in aerobic fitness for female but not male participants, and no significant changes in weight for either group. Participants described a range of benefits from the programs, including positive elements and areas for improvement. They also viewed the evaluation as feasible and acceptable, and the findings of value. The outcomes from both pilot programs provide evidence that Aboriginal-designed programs, with a focus on physical and cultural activities, can help to strengthen mental health and wellbeing, community connection, and reduce psychological distress in Victorian Aboriginal communities. Full article

To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved. Full article

The purpose of the present study was to provide an empirical verification of the Circle of Discontent with an assessment of its relationship to restrained and uncontrolled eating among children and adolescents. This study examined whether our results confirm a new hypothesized model. The total sample comprised 282 children and adolescents (148 girls and 134 boys; 141 participants with normal body weight and 141 with obesity). The mean age was 12.23 years (SD = 2.80), and the average BMI (body mass index) was 23.29 kg/m² (SD = 6.27). The following were used: Positive and Negative Affect Scale for Children, Children’s Body Image Scale, Figure Rating Scale, Three-Factor Eating Questionnaire and Eating Disorders in Youth. The obtained values of the model fit indices proved the goodness of fit. Our findings show that obesity accompanies body dissatisfaction and uncontrolled and restrictive eating. Moreover, the higher the level of restrictive eating, the lower the level of uncontrolled eating. The relationships between body dissatisfaction, negative affect and restrictive eating, as well as that between uncontrolled eating and high-energy consumption, are significant and positive. Other relationships are non-significant. The above-mentioned relationships established in the Circle of Discontent, as well as relationships of restrained and uncontrolled eating with variables described in the circle, were confirmed. Based on our results, preventive strategies and psychological interventions can be created and may include changes in body image, eating behaviors and emotional functioning. Full article

Community-based and Indigenous-led health and wellness approaches have been widely advocated for Indigenous peoples. However, remarkably few Indigenous designed and led interventions exist within the field. The purpose of this study was to evaluate an Indigenous-led and community-based health and wellness intervention in a remote and rural Indigenous community. This protocol was designed by and for Indigenous peoples based on the aspirations of the community (established through sharing circles). A total of 15 participants completed a 13-week walking and healthy lifestyle counselling program (incorporating motivational interviewing) to enhance cardiometabolic health. Measures of moderate-to-vigorous physical activity (MVPA; 7-day accelerometry and self-report), predicted maximal aerobic power (VO₂max; 6-min walk test), resting heart rate and blood pressure, and other health-related physical fitness measures (musculoskeletal fitness and body composition) were taken before and after the intervention. The intervention led to significant (p < 0.05) improvements in VO₂max (7.1 ± 6.3 % change), with the greatest improvements observed among individuals with lower baseline VO₂max (p < 0.05, r = -0.76). Resting heart rate, resting systolic blood pressure, and resting diastolic blood pressure decreased significantly (p < 0.05) after the intervention. Self-reported and accelerometry-measured frequency of MVPA increased significantly (p < 0.05), and the total MVPA minutes (~275 min/week) were above international recommendations. Change in VO₂max was significantly correlated with change in self-reported (r = 0.42) and accelerometry-measured (r = 0.24) MVPA minutes. No significant changes were observed in weight, body mass index, waist circumference, body fat (via bioelectrical impedance), grip strength, and flexibility. These findings demonstrate that a culturally relevant and safe, community-based, Indigenous-led, health and wellness intervention can lead to significant and clinically relevant improvements in cardiometabolic health and physical activity behaviour, with the greatest changes being observed in the least active/fit individuals. Full article