Currently, the health management for athletes has been a significant research issue in academia. Some data-driven methods have emerged in recent years for this purpose. However, numerical data cannot ...reflect comprehensive process status in many scenes, especially in some highly dynamic sports like basketball. To deal with such a challenge, this paper proposes a video images-aware knowledge extraction model for intelligent healthcare management of basketball players. Raw video image samples from basketball videos are first acquired for this study. They are processed using adaptive median filter to reduce noise and discrete wavelet transform to boost contrast. The preprocessed video images are separated into multiple subgroups by using a U-Net-based convolutional neural network, and basketball players' motion trajectories may be derived from segmented images. On this basis, the fuzzy KC-means clustering technique is adopted to cluster all segmented action images into several different classes, in which images inside a classes are similar and images belonging to different classes are different. The simulation results show that shooting routes of basketball players can be properly captured and characterized close to 100% accuracy using the proposed method.
•An improved local outlier factor algorithm with a rotating search area (LOFR) was developed for ICESat-2 ATLAS data.•The LOFR algorithm can adaptively adjust the search area and direction.•The LOFR ...algorithm was evaluated in four sites across China.•The LOFR performs well for terrain and forest height estimation.
ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) was launched in 2018 with a photon-counting LiDAR (Light Detection and Ranging) system, ATLAS (Advanced Topographic Laser Altimeter System). It is collecting massive earth elevation data all over the world, which has shown the potential of large-scale forest monitoring. However, the energy emitted by the LiDAR system is low, and the received signals are easily affected by noise. Accurate classification of photons is an important step for forest parameter retrieval. Given the limitations of existing photon classification algorithms in areas with complex terrain, we proposed an improved local outlier factor algorithm with a rotating search area (LOFR). First, photons are transformed to the along-track direction, and noise photons are preliminarily filtered out by using the elevation histogram and elevation statistical methods. Next, ground photons are extracted by using the LOF (Local Outlier Factor) with the horizontal ellipse search area algorithm (LOFE) during an initial classification stage to filter photons that are far away from the ground. During the refined classification stage, which is the core of the algorithm, the terrain slope is calculated according to the ground photons extracted during initial classification. The elliptic search area is then rotated to align its long axis with the terrain slope. Finally, the LOFR scores of the photons are calculated to remove noise photons and signal photons are classified into top-of-canopy photons, canopy photons, and ground photons. The results show that the algorithm can effectively classify photons. Both estimated terrain height and canopy height derived using the classified photons are in good agreement with airborne LiDAR data. The mean absolute error (MAE) of the estimated terrain height relative to airborne data was 1.45 m and the root mean square error (RMSE) was 2.82 m. For canopy height validation, the correlation coefficient (R2), MAE, and RMSE at the best study scale (80 m) were 0.86, 1.82 m, and 2.72 m, respectively. These results demonstrated that the proposed LOFR algorithm can improve photon classification over complex terrain without prior knowledge of the terrain. Therefore, it could provide a robust approach for large-scale ATLAS data processing.
We investigate an improved digital back propagation (DBP) method based on a multi-stage perturbation theory to compensate for nonlinear impairments in fiber optic links. In the standard DBP, the ...nonlinear operation only calculates the phase shift based on the power of the current signal sample. In the proposed perturbation-assisted DBP (P-DBP) method, the nonlinear operation calculates nonlinear phase shifts and complex distortions taking into account the correlation among neighboring optical pulses, which significantly improves the accuracy of nonlinear calculation. We obtain analytical expressions to calculate the nonlinear phase shifts due to the self-phase modulation and intra-channel cross-phase modulation effects and the complex distortions due to the intra-channel four wave mixing effect. We experimentally demonstrate that in a 256-Gb/s polarization multiplexed system over a 2,000-km fiber optic link, the P-DBP method using 4 steps shows the same compensation performance as standard DBP using 40 steps. We perform algorithm complexity analysis and show that the P-DBP method reduces the computational complexity up to 82% as compared with the standard DBP for the same gain.
Long-term acclimation to monochromatic lights emerges in seaweeds. In this study, analysis based on physiological characteristics and transcriptome sequencing were employed to investigate the ...long-term acclimation of thalli of rhodophyte
Pyropia haitanensis
grown under white light (WL) and monochromatic blue light (BL), green light (GL), and red light (RL). The net photosynthesis of synchronically cultured thalli was highest under WL, while the net photosynthesis was significantly higher under GL and RL compared with BL, indicating the low utilization efficiency of BL and relatively high ones of GL and RL. Compared with WL, the PE/Chl.
a
ratio was significantly higher in BL-acclimated thalli and lower in both GL- and RL-acclimated thalli. The C/N ratio was decreased in BL-acclimated thalli and drastically increased in GL- and RL-acclimated thalli. Only a small amount of starch grains were observed in WL-acclimated thallus cells, and no starch grain was found in BL-acclimated thallus cells, whereas numerous starch grains were found in GL- and RL-acclimated thallus cells. These findings implied roles of pigments and allocation of carbon between carbohydrates and phycobiliproteins during monochromatic light acclimation. Transcriptome analysis showed that DEGs involving protein synthesis were mainly upregulated by BL, whereas DEGs involving energy-yielding carbohydrate catabolism were mainly downregulated by GL and RL. Besides, genes encoding light-harvesting complex, ferredoxin-NADP reductase, and key enzymes of carbon and nitrogen assimilation were upregulated by BL, yet downregulated by GL and RL. Those results indicated that
P. haitanensis
thalli could compensate for the low utilization efficiency of BL via the increase in phycoerythrin accumulation through upregulating enzymes acting on carbon and nitrogen assimilation, consequently activating downstream of protein synthesis. Mechanisms of photoacclimation under GL and RL might include the reduction in light energy absorption and photosynthetic electron transfer chain activity via downregulating genes encoding nitrogen assimilating enzymes, light-harvesting complexes and ferredoxin-NADP reductases, and the attenuation in accumulation and catabolism of photosynthates to avoid excessive energy-yielding that might cause a burden on metabolism.
Category:
Midfoot/Forefoot
Introduction/Purpose:
The aim of this study was to introduce a new surgical procedure defined as revolving scarf osteotomy (RSO) and compare the clinical and radiological ...results of RSO and double metatarsal osteotomy (DMO) performed for treating severe hallux valgus (HV) with an increased distal metatarsal articular angle (DMAA).
Methods:
First metatarsal osteotomies were performed in 56 patients (62 feet) with severe HV with an increased DMAA in Honghui Hospital from January 2015 to December 2017. RSO was performed in 32 feet and DMO was performed in 30 feet. Clinical assessments were performed using the American Orthopaedic Foot & Ankle Society (AOFAS) score and visual analog scale (VAS) score. Radiographic evaluations of the hallux valgus angle (HVA), intermetatarsal angle (IMA), DMAA, and first metatarsal length (FML) were compared preoperatively and postoperatively in the two groups, and the rates of complications were also compared.
Results:
The mean AOFAS score, VAS score, HVA, IMA, and DMAA showed significant improvements in both groups after surgery, but with no significant differences between the two groups. The postoperative FML was significantly larger in the RSO group than in the DMO group (p<0.001). One of the 30 feet (3.3%) in the DMO group exhibited transfer metatarsalgia at 12 months postoperatively, while another foot (3.3%) in same group had avascular necrosis of the metatarsal head. One of the 30 feet (3.1%) in the RSO group had hallux varus.
Conclusion:
No differences in the clinical and radiographic results were observed between the two groups with severe HV and an increased DMAA. However, RSO may reduce postoperative complications compared to DMO. A long-term, randomized, controlled prospective study with a larger sample would provide higher-level evidence for confirming the clinical efficacy and safety of RSO.
In power-limited trans-oceanic submarine systems, the electrical-to-optical (E/O) power conversion efficiency determines the amount of optical signal power generated by repeaters, which governs the ...cable capacity. In contrast to conventional submarine systems, recent single mode fiber spatial division multiplexing (SDM) systems operate at a lower channel power and support a larger number of optical fibers. Moreover, pump sharing technology is used in SDM systems to enhance cable capacity and system reliability, where a group of pump lasers are combined to feed a group of fiber pairs. The repeater E/O power conversion efficiency is directly related with cable capacity, as well as capacity per power and cost per capacity analysis. Therefore, it is important to understand the characteristics of repeater E/O efficiency. We developed a model to analyze the repeater E/O efficiency in submarine SDM systems. Experimental measurement data of pump lasers and numerical simulation results of Erbium doped fiber amplifiers (EDFAs) were used as input information to the model to analyze repeater E/O efficiency in various system designs. Based on the E/O efficiency model results, we investigated cable capacity using the Gaussian noise (GN) model. Moreover, cable capacity per power was calculated and compared based on three different power metrics: (i) electrical supply power, (ii) pump optical power and (iii) EDFA output power. With the aid of the repeater E/O efficiency model, one can analyze the efficiency of submarine systems using the direct metric of cable capacity per electrical supply power.
This paper mainly focuses on efficient schemes for simulating propagation in optical fibers. Various schemes based on split-step Fourier techniques to solve the nonlinear Schrödinger equation ...(NLSE), which describes the propagation in optical fibers, are compared. In general, the schemes in which the loss operator is combined with nonlinearity operator are found to be more computationally efficient than the schemes in which the loss is combined with dispersion. When the global error is large, the schemes with variable step size outperform the ones with uniform step size. The schemes based on local error and/or minimum area mismatch (MAM) further improve the computational efficiency. In this scheme, by minimizing the area mismatch between the exponential profile and its stepwise approximation, an optimal step size distribution is found. The optimization problem is solved by the steepest descent algorithm. The number of steps to get the desired accuracy is determined by the local error method. The proposed scheme is found to have higher computational efficiency than the other schemes studied in this paper. For QPSK systems, when the global error is 10 -8 , the number of fast Fourier transforms (FFTs) needed for the conventional scheme (loss combined with dispersion and uniform step size) is 5.8 times that of the proposed scheme. When the global error is 10 -6 , the number of FFTs needed for the conventional scheme is 3.7 times that of the proposed scheme.
With the rapid development of the mobile Internet, people's demand for information is increasing, and the traditional fitness model is unable to meet the development needs of society. In this study, ...mobile Internet technology is used to build a new type of green intelligent fitness system. The system can collect users’ fitness data and upload the data to the cloud server. And users can obtain their exercise data and their ranks at any time through mobile APP to realize data sharing. At the same time, WebSocket technology is used to realize real-time updates of data, and a collaborative filtering recommendation algorithm is used to analyze users’ rating data and recommend intelligent fitness equipment for users. It is found that the system constructed in this study uses the computing power of multiple nodes in the cluster to analyze the fitness data on the cluster rapidly. Based on the collaborative filtering algorithm, the analysis of users is realized, and the recommendation accuracy is up to 89%. This study first puts forward the combination of mobile Internet and traditional fitness industry, which provides a reliable way to promote the development of national fitness.
The primary research purpose lies in studying the intelligent detection of movements in basketball training through artificial intelligence (AI) technology. Primarily, the theory of somatosensory ...gesture recognition is analyzed, which lays a theoretical foundation for research. Then, the collected signal is denoised and normalized to ensure that the obtained signal data will not be distorted. Finally, the four algorithms, decision tree (DT), naive Bayes (NB), support vector machine (SVM), and artificial neural network (ANN), are used to detect the data of athletes' different limb movements and recall. The accuracy of the data is compared and analyzed. Experiments show that the back propagation (BP) ANN algorithm has the best action recognition effect among the four algorithms. In basketball training athletes' upper limb movement detection, the average accuracy rate is close to 93.3%, and the average recall is also immediate to 93.3%. In basketball training athletes' lower limb movement detection, the average accuracy rate is close to 99.4%, and the average recall is immediate to 99.4%. In the detection of movements of upper and lower limbs: the recognition method can efficiently recognize the basketball actions of catching, passing, dribbling, and shooting, the recognition rate is over 95%, and the average accuracy of the four training actions of catching, passing, dribbling, and shooting is close to 98.95%. The intelligent basketball training system studied will help basketball coaches grasp the skilled movements of athletes better to make more efficient training programs and help athletes improve their skill level.
The spectral clustering method has notable advantages in segmentation. But the high computational complexity and time consuming limit its application in large-scale and dense airborne Light Detection ...and Ranging (LiDAR) point cloud data. We proposed the Nyström-based spectral clustering (NSC) algorithm to decrease the computational burden. This novel NSC method showed accurate and rapid in individual tree segmentation using point cloud data. The K-nearest neighbour-based sampling (KNNS) was proposed for the Nyström approximation of voxels to improve the efficiency. The NSC algorithm showed good performance for 32 plots in China and Europe. The overall matching rate and extraction rate of proposed algorithm reached 69% and 103%. For all trees located by Global Navigation Satellite System (GNSS) calibrated tape-measures, the tree height regression of the matching results showed an value of 0.88 and a relative root mean square error (RMSE) of 5.97%. For all trees located by GNSS calibrated total-station measures, the values were 0.89 and 4.49%. The method also showed good performance in a benchmark dataset with an improvement of 7% for the average matching rate. The results demonstrate that the proposed NSC algorithm provides an accurate individual tree segmentation and parameter estimation using airborne LiDAR point cloud data.
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