Search Results (32)

Access to clean cooking remains a major challenge in rural and off-grid areas where traditional fuels are costly, harmful, or scarce. Solar cooking offers a sustainable solution, but many existing systems suffer from fixed positioning and low efficiency. This study presents a low-cost, dual-axis solar tracking parabolic dish cooker designed for such regions, featuring adjustable pot holder height and portability for ease of use. The system uses an Arduino UNO, LDR sensors, and a DC gear motor to automate sun tracking, ensuring optimal alignment throughout the day. A 0.61 m parabolic dish with ≥97% reflective silver-coated mirrors concentrates sunlight to temperatures exceeding 300 °C. Performance tests in April, June, and November showed boiling times as low as 3.37 min in high-irradiance conditions (7.66 kWh/m²/day) and 6.63 min under lower-irradiance conditions (3.86 kWh/m²/day). Compared to fixed or single-axis systems, this design achieved higher thermal efficiency and reliability, even under partially cloudy skies. Built with locally available materials, the system offers an affordable, clean, and effective cooking solution that supports energy access, health, and sustainability in underserved communities. Full article

This study explores the predictive factors influencing sport coaches’ perceived performance levels following an 18-month mentor-based education program. The study employed a quasi-experimental, pre-test/post-test control group design to assess changes in perceived coach performance over time. The experimental group participated in six group gatherings and at least 15 individual mentoring sessions over 18 months, while the control group received no intervention. Participants were recruited from a non-formal coach education program run by the Norwegian Olympic Sports Center (NOSC), requiring recommendations from their respective sport federations. Of the 159 coaches who applied, 73 were selected for the program and invited to participate, along with 29 additional coaches from specialized high schools for elite sports, forming a total sample of 98 coaches (69 in the experimental group, 29 in the control group) at pre-test. The sample consisted of 61 males (62%) and 37 females (38%), aged 26 to 71 years (M = 38.3, SD = 8.3), representing over 20 sports, with handball (15.3%), cross-country skiing (10.2%), soccer (7.1%), and track and field (7.1%) being the most common. Data collection included an online questionnaire measuring perceived coach performance, coaching hours, age, and dimensions of the coach–athlete working alliance (task, bond, and goal development). After 18 months, 75 coaches completed the study, yielding a response rate of 73.5%. Hierarchical regression analyses revealed that coaches’ ages, weekly coaching hours, baseline perceived performance, and task development within the coach–athlete working alliance positively predicted their performance perception post-test. Participation in the mentor-based program also had a significant positive effect. However, neither bond nor goal development in the working alliance predicted performance perception. These findings underscore the importance of mentoring, structured self-reflection, and task-focused coaching strategies in enhancing coaching effectiveness. The results have implications for coach education programs seeking to foster professional growth and performance development. Full article

Psychological preparation has taken on a crucial role in today’s sports practice. Effective resolutions to the challenges inherent in athletes’ psychological preparation require a comprehensive understanding of the key components that constitute the psychological preparation process. This quasi-experimental study aims to first, assess the interrelationships among imagery abilities, physical self-efficacy, and sport performance among a sample of alpine skiers. Secondly, this study sought to assess the effect of a psychological intervention on imagery and self-efficacy, and its impact on their task performance. The proposed hypothesis suggests that integrating imagery and self-efficacy interventions into the training process of alpine skiers will enhance athletes’ achievements on the slalom ski track. Seven leading Latvian youth alpine skiers with an average age of M = 17.14 (SD = 1.77) participated in a three-month psychological skill intervention targeting imagery and self-efficacy enhancement, alongside control training sessions on a slalom ski track to evaluate its effectiveness on sport performance. Pre- and post-intervention assessments were conducted using questionnaires, revealing significant improvements in imagery abilities and self-efficacy (p < 0.05). Notably, positive interrelationships between imagery abilities, self-efficacy, and sport performance were observed. These findings underscore the efficacy of integrating psychological interventions into the athlete training process and highlight the importance of psychological readiness in optimizing athletic achievements, particularly in dynamic sports like alpine skiing. The study results provide novel theoretical and practical psychological insights into the training process of athletes in sports. Full article

Artificial intelligence is developing at a rapid pace, with examples of machine learning already being used in aviation to improve efficiency. In the coming decade, it is likely that intelligent assistants (IAs) will be deployed to assist aviation personnel in the cockpit, the air traffic control center, and in airports. This will be a game-changer and may herald the way forward for single-pilot operations and AI-based air traffic management. Yet in aviation there is a core underlying tenet that ‘people create safety’ and keep the skies and passengers safe, based on a robust industry-wide safety culture. Introducing IAs into aviation might therefore undermine aviation’s hard-won track record in this area. Three experts in safety culture and human-AI teaming used a validated safety culture tool to explore the potential impacts of introducing IAs into aviation. The results suggest that there are indeed potential negative outcomes, but also possible safety affordances wherein AI could strengthen safety culture. Safeguards and mitigations are suggested for the key risk owners in aviation organizations, from CEOs to middle managers, to safety departments and frontline staff. Such safeguards will help ensure safety remains a priority across the industry. Full article

This study explores the comprehensive understanding of taekwondo, the application of fourth industrial revolution technologies in various kinds of sports, the development of taekwondo through artificial intelligence (AI), and essential technology in the fourth industrial revolution while suggesting advanced science directions through a literature review. Literature was sourced from six internet search electronic databases, consisting of three English databases and three Korean databases, from January 2016 to August 2023. The literature indicated cases of sports convergence with the application of fourth industrial revolution technologies, such as the game of go, golf, table tennis, soccer, American football, skiing, archery, and fencing. These sports not only use big data but also virtual reality and augmented reality. Taekwondo is a traditional martial art that originated in Republic of Korea and gradually became a globally recognized sport. Since taekwondo’s competition analysis is an analysis in which researchers manually write events, it takes a very long time to analyze, and the scale of the analysis varies depending on the researcher’s tendencies. This study presented the development of an AI Taekwondo performance improvement analysis and evaluation system and a metaverse-based virtual Taekwondo pumsae/fighting coaching platform through an AI-based motion tracking analysis method. Full article

New environmental extremes are currently underway and are much greater than those in previous records. These are mostly regional, singular events that are caused by global change/local weather combinations and are larger than the impact of linear temperature increases projected using climate models. These new states cannot easily be assigned probabilities because they often have no historical analogs. Thus, the term super climate extremes is used. Examples are the loss of sea ice and ecosystem reorganization in northern marine Alaska, heatwave extreme in western Canada, and the loss of snow in Greenland. New combined extreme occurrences, which are reported almost daily, lead to a new, higher level of climate change urgency. The loss of sea ice in 2018–2019 was a result of warmer Arctic temperatures and changes in the jet stream. They resulted in a chain of impacts from southerly winds, the northward movement of predatory fish, and the reduction of food security for coastal communities. Record temperatures were measured in southwestern British Columbia following previous drought conditions, a confluence of two storm tracks, and warming through atmospheric subsidence. Greenland’s losses had clear skies and jet stream events. Such new extremes are present indicators of climate change. Their impacts result from the interaction between physical and ecological processes, and they justify the creation of a new climate change category based on super climate extremes. Full article

Mature civil engineering software and platforms can provide a dynamic correlated situation of the road design, generate a quick and accurate grading design in terrain model making, and, most importantly, improve the design efficiency and calculation accuracy and reduce the workload of designers in the construction project. However, the application of existing platforms in complex site engineering for the design of ski tracks has not been well developed. The design process of ski tracks requires consideration of elaborate requirements in complex environmental conditions. In this study, we aim to simplify digital elevation model (DEM) data, optimize ski track contour lines, and localize the design expression of the ski track designs based on the experience of the construction of the National Alpine Ski Center in the Yanqing Competition Zone for the Beijing 2022 Winter Olympic Games. This study examines the feasibility of the optimal digital approach combining mathematics and computer science based on the case study of the warm-up and training ski track of the south area in the Yanqing Competition Zone. This study will contribute to the optimal design of skiing tracks in construction projects and help to improve designers’ workload efficiency for the design and construction of ski tracks in the future. Full article

It has long been understood that diversity is a key aspect of what makes a landscape attractive but to what degree of diversity and how is it experienced? Many forest landscapes are generally monotonous in character or are broken up by forest management activities such as clear cutting, which may negatively impact their potential for recreation and psychological well-being benefits. We conducted a virtual reality experiment where people were taken on a trip along a simulated cross country skiing track in an Estonian forest. Participants followed a route at simulated speeds typical of cross-country skiing. The route was long enough to experience several minutes passing through one type of forest landscape with a series of small variations in character followed by several minutes passing through a notably different forest landscape. The restorative experience obtained by the visit was measured periodically in each version of the landscape. Univariate general linear modelling analysis was statistically significant (r² = 0.651, F(198, 965) = 9.108, p < 0.001) and showed that while respondents preferred less-dense forest in general (B = 0.189, p = 0.001)—an expected result—a comparable amount of positive restorative response could also be attributed to prominent changes in forest character, regardless of the type of forest (B = 0.401, p < 0.001). We hypothesise that respondents were reacting favourably to sudden changes in forest appearance after prolonged exposure to one forest type—that diversity is important in maintaining interest, reducing boredom, and in providing a restorative experience. The implications are, firstly, that a virtual experience can detect restorative effects and, secondly, that recreational trails should be designed to pass through varied landscapes offering continually changing diverse experiences—the impact of which can be tested in the virtual setting because there is control of all variables. Full article

To address the long-term statistical problem of ski-track area in the construction and operation of ski resorts, we propose a new ski-track point cloud boundary extraction method that improves the accuracy of boundary extraction and minimizes the offset of the area error. In this method, all point clouds are first projected onto the fitting plane using the random sample consensus (RANSAC) method. An improved point cloud boundary extraction algorithm is used to triangulate and extract the high-precision ski-track boundary. A discrete Green formula is then used to calculate and count the ski track’s exact area. It is demonstrated through five sets of test experiments that the error offset of the method proposed in this paper is smaller than that of other classical methods, which confirms its benefits and feasibility. Full article

With tracking systems becoming more widespread in sports research and regular training and competitions, more data are available for sports analytics and performance prediction. We analyzed 2523 ski jumps from 205 athletes on five venues. For every jump, the dataset includes the 3D trajectory, 3D velocity, skis’ orientation, and metadata such as wind, starting gate, and ski jumping hill data. Using this dataset, we aimed to predict the expected jump length (xLength) inspired by the expected goals metric in soccer (xG). We evaluate the performance of a fully connected neural network, a convolutional neural network (CNN), a long short-term memory (LSTM), and a ResNet architecture to estimate the xLength. For the prediction of the jump length one second after take-off, we achieve a mean absolute error (MAE) of 5.3 $\mathrm{m}$ for the generalization to new athletes and an MAE of 5.9 $\mathrm{m}$ for the generalization to new ski jumping hills using ResNet architectures. Additionally, we investigated the influence of the input time after the take-off on the predictions’ accuracy. As expected, the MAE becomes smaller with longer inputs. Due to the real-time transmission of the sensor’s data, xLength can be updated during the flight phase and used in live TV broadcasting. xLength could also be used as an analysis tool for experts to quantify the quality of the take-off and flight phases. Full article

Stereo tracking of clouds from multiple satellites permits the simultaneous retrieval of an atmospheric motion vector (“wind”) and its height in the atmosphere. The direct measurement of height is a major advantage of stereo methods over observations made from a single satellite where the height must be inferred from infrared brightness temperatures. A pair of operational geostationary satellites over the Americas provides stereo coverage where their two fields of view intersect. Stereo coverage can be extended to nearly a full hemisphere with a third satellite. We demonstrate this configuration with the operational GOES-R constellation of GOES-16 (east) and GOES-17 (west) augmented by GOES-18 in its central test slot and use the 500-m resolution Advanced Baseline Imager Band 2. We examine the consistency of the pairwise products created from GOES-18 and -16 versus GOES-18 and -17 and create a fused triple-GOES product that spans nearly the full hemisphere seen from GOES-18. We also examine the retrieval of ground points observed under clear skies and compare their retrievals to zero speed and known terrain heights. The results are compatible with a wind accuracy about 0.1 m/s with height assignment uncertainty of 175 m. Full article

Eleven world elite ski-mountaineering (Ski-Mo) athletes were evaluated for pronounced echocardiographic physiological remodeling as the primary aim of our feasibility speckle tracking study. In this context, sports-related cardiac remodeling was analyzed by performing two-dimensional echocardiography, including speckle tracking analysis of the left atrium (LA), right ventricle (RV) and left ventricular (LV) global longitudinal strain (LV-GLS) at rest and post-peak performance. The feasibility echocardiographic speckle tracking analysis was performed on eleven elite Ski-Mo athletes, which were obtained in 2022 during the annual medical examination. The obtained data of the professional Ski-Mo athletes (11 athletes, age: 18–26 years) were compared for different echocardiographic parameters at rest and post-exercise. Significant differences were found for LV-GLS mean (p = 0.0036) and phasic LA conduit strain pattern at rest and post-exercise (p = 0.0033). Furthermore, negative correlation between LV mass and LV-GLS (p = 0.0195, r = −0.69) and LV mass Index and LV-GLS (p = 0.0253, r = −0.66) at rest were elucidated. This descriptive reporting provided, for the first time, a sport-specific dynamic remodeling of an entire elite national team of the Ski-Mo athlete’s left heart and elucidated differences in the dynamic deformation pattern of the left heart. Full article

Recent progress in real-time tracking of knee bone structures from fluoroscopic imaging using CT templates has opened the door to studying knee kinematics to improve our understanding of patellofemoral syndrome. The problem with CT imaging is that it exposes patients to extra ionising radiation, which adds to fluoroscopic imaging. This can be solved by segmenting bone templates from MRI instead of CT by using a deep neural network architecture called 2.5D U-Net. To train the network, we used the SKI10 database from the MICCAI challenge; it contains 100 knee MRIs with their corresponding annotated femur and tibia bones as the ground truth. Since patella tracking is essential in our application, the SKI10 database was augmented with a new label named UofA Patella. Using 70 MRIs from the database, a 2.5D U-Net was trained successfully after 75 epochs with an excellent final Dice score of 98%, which compared favourably with the best state-of-the-art algorithms. A test set of 30 MRIs were segmented using the trained 2.5D U-Net and then converted into 3D mesh templates by using a marching cube algorithm. The resulting 3D mesh templates were compared to the 3D mesh model extracted from the corresponding labelled data from the augmented SKI10. Even though the final Dice score (98%) compared well with the state-of-the-art algorithms, we initially found that the Euclidean distance between the segmented MRI and SKI10 meshes was over 6 mm in many regions, which is unacceptable for our application. By optimising many of the hyper-parameters of the 2.5D U-Net, we were able to find that, by changing the threshold used in the last layer of the network, one can significantly improve the average accuracy to $0.2$ mm with a variance of $0.065$ mm for most of the MRI mesh templates. These results illustrate that the Dice score is not always a good predictor of the geometric accuracy of segmentation and that fine-tuning hyper-parameters is critical for improving geometric accuracy. Full article

Monitoring and gathering data on sporting activities holds significant promise for athletes, equipment developers, and physical fitness clinicians. Wireless Body Area Networks are being used in sporting environments as a means of gathering data, providing feedback, and helping to gain understanding of athletic activities. Applying WBANs to skiing situations, which have higher vibration, velocities, and damp environments than many other sports, can open up opportunities to understand the dynamics of skiing equipment behaviors, skiing routes on mountains, and how individuals react when skiing. To support these outcomes, a prototype WBAN-style off the shelf component system called SkiMon was proposed, implemented, and tested. The SkiMon system uses inexpensive ESP8266, Raspberry Pi, and sensor devices to gather high quality motion and location tracking data on skiers in real-world skiing conditions. By using IEEE 802.11b/g/n wireless networks, SkiMon is able to sample data at a minimum of 50 Hz, which is enough to model most ski vibration behaviors. These data results are shown to reflect ground truth 3D maps and the acceleration data comports with earlier works on ski vibration testing. Overall, a WBAN-based commodity components solution shows promise as a high quality sensor platform for tracking and modeling skiing activities. Full article

Externally focused attention is known to induce superior results in the movement outcome, whereas focusing attention on the moving body (internal focus) causes conscious control and constrains action. The study investigated effects on knee trajectory and whole-body movement complexity when addressing knee alignment using externally (EF) vs. internally (IF) focused instructions. Young ski racers, n = 24 (12 male), performed landings with subsequent jumps to submaximal height. Movements were tracked and analyzed during the ground contact phase. Sets of jumps were executed without instruction (CON), followed by EF and IF instructions on knee alignment in a random order. Medial–lateral displacement of the knee in landing quantified task achievement, and whole-body principal component analysis was used to compute movement complexity. Knee alignment instructions led to a significantly lower medial knee displacement compared to CON (p = 0.001, η_p² = 0.35). EF vs. IF did not reach significance. EF, as well as IF instructions increased the prominence of the first movement pattern (p = 0.01, η_p² = 0.22) with a reduction of higher-order patterns (p = 0.002, W = 0.11), suggesting a strategy of freezing degrees of freedom. Both instructions addressing the movement form positively influenced knee displacement during landing, and both led to a freezing strategy, simplifying whole-body coordination. Full article