THE CHARTERISTICS OF LOWER LIMB MOMENTS IN BASEBALL PITCHING

The aim of this study was to examine the characteristics of lower limb moments in baseball pitching. Ten senior high school pitchers participated in this study (age: 16.7±0.7 yr; height: 179.1±5.8 cm; body mass: 73.7±8.9 kg). Ten VICON cameras (200Hz) and two Kistler force plates (1000Hz) fixed on a pitching mound were used to collect 3-D kinematic and GRF data. Three successful trials for each subject were used to compute lower limbs joint moments. The results indicated, for the pivot leg, ankle plantarflexor moment, knee and hip adductor moment are the key moments to transform energy to trunk and upper extremities by driving and rotating the knee. For the lead leg, ankle plantarflexor moment and hip flexor moment are the main joint moments to brake upper extremities by a knee extention during baseball pitching

KINEMATICS ANALYSIS OF THE UPPER EXTREMITY DURING THE TWOHANDED BACKHAND DRIVE VOLLEY FOR FEMALE TENNIS PLAYERS

The purpose of this study was to discuss the motion characteristics of the arms in the two-handed backhand drive volley. Five elite female tennis players participated in this study, their two-handed backhand drive volley strokes were analysed, and all participants are right handed. Motion Analysis System with 10 Eagle Digital inferred high speed cameras at 200Hz were used for this study. The results show a similar elbow and wrist speed strategy in x-axis between two-handed ground stroke and drive volley, our study also found that the rear arm dominates the stroke and mainly provide the topspin that is required for the skill of the drive volley. In order to create better stroke efficiency, the right elbow reached peak velocity first, followed by the right wrist before racket impact with the ball

What Factors Satisfy E-Book Platform Customers? Development of A Model to Evaluate E-Book User Behavior and Satisfaction

The use of e-book readers has become increasingly widespread; however, there are few studies to evaluate e-book user behavior and satisfaction on e-book platforms, and even fewer approaches the subject from the perspective of task-technology fit. In order to fill this gap, this study adopts task-technology fit theory to explore the factors that affect the behavior satisfaction of users on commercial e-book platforms. Our research model excludes utility and performance from task-technology fit theory to focus on individual user satisfaction measurement because general e-book platform users are not concerned about work performance issues in leisure activities. The results show that functional service, convenience, and searching task are important factors that influence users\u27 task-technology fit behavior. Moreover, task-technology fit may improve users\u27 satisfaction, flow and scanpath. Finally, satisfaction is affected by task-technology fit and flow factors. An analysis of the research explained 61 percent of the variance in users’ task-technology fit, and 59 percent of the variance in satisfaction to use e-book platform. These results provide a new perspective to e-book researchers and can help e-book platform managers and designers in making policies and designing platforms

Mining association language patterns using a distributional semantic model for negative life event classification

AbstractPurposeNegative life events, such as the death of a family member, an argument with a spouse or the loss of a job, play an important role in triggering depressive episodes. Therefore, it is worthwhile to develop psychiatric services that can automatically identify such events. This study describes the use of association language patterns, i.e., meaningful combinations of words (e.g., <loss, job>), as features to classify sentences with negative life events into predefined categories (e.g., Family, Love, Work).MethodsThis study proposes a framework that combines a supervised data mining algorithm and an unsupervised distributional semantic model to discover association language patterns. The data mining algorithm, called association rule mining, was used to generate a set of seed patterns by incrementally associating frequently co-occurring words from a small corpus of sentences labeled with negative life events. The distributional semantic model was then used to discover more patterns similar to the seed patterns from a large, unlabeled web corpus.ResultsThe experimental results showed that association language patterns were significant features for negative life event classification. Additionally, the unsupervised distributional semantic model was not only able to improve the level of performance but also to reduce the reliance of the classification process on the availability of a large, labeled corpus

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Alleviating Interference through Cognitive Radio for LTE-Advanced Network

In the LTE-Advanced network, some femtocells are deployed within a macroecell for improving throughput of indoor user equipments (UEs), which are referred to as femtocell UEs (FUEs). Cross-tier interference is an important issue in this deployment, which may significantly impact signal quality between Macrocell Base Stations (MBSs) and Macrocell User Equipments (MUEs), especially for MUEs near the femtocell. To relieve this problem, the Third Generation Partnership Project Long Term Evolution-Advanced (3GPP LTE-Advanced) de fined the cognitive radio enhanced femtocell to coordinate interference for LTE-Advanced Network. Cognitive radio femtocells have the ability to sense radio environment to obtain radio parameters. In this paper, we investigated the performance of existing schemes based on fractional frequency reuse. Therefore, we proposed a scheme with cognitive radio technology to improve the performance of fractional fre-quency reuse scheme. Simulation results showed that our scheme can effectively enhance average downlink throughput of FUEs as well as the total downlink throughput in LTE-Advanced Networks

KINETIC DIFFERENCES IN LOWER EXTREMITY BETWEEN BASEBALL PITCHING FROM PITCHER’S MOUND AND FLAT-GROUND

The purpose of this study was to investigate the kinetic differences in lower extremity between pitching from a mound and flat-ground. A motion capture system and two force plates were used simultaneously to collect the dynamic data of 8 baseball male pitchers. The results revealed that pitching from the mound generated higher propulsive force at the trailing leg as well as greater braking force and vertical ground reaction force at the lead leg (p< .05). The trailing leg in the mound condition generated greater knee posterior joint force while the lead leg had greater axial joint force at ankle and knee, as well as greater extension moment at ankle, knee and hip (p< .05). It was concluded that pitching from the mound generated higher ground reaction force, which resulted in higher joint forces and moments and thus might increase stresses at lower extremity

Prognostic factors of candidemia among nonneutropenic adults with total parenteral nutrition

BackgroundImmediate removal of central venous catheters (CVCs) is not possible in patients with candidemia requiring total parenteral nutrition (TPN). This study analyzed the possible prognostic factors for survival time after onset of candidemia among nonneutropenic adults requiring TPN.MethodsWe conducted a retrospective analysis from September 2003 to August 2005.ResultsA total of 59 nonneutropenic adults with candidemia and requiring TPN were identified retrospectively. All Candida isolates were susceptible to flucytosine and amphotericin B. With the exception of one C glabrata isolate, all other isolates were susceptible to fluconazole and itraconazole. The only predictor of 30-day survival rate after onset of candidemia identified in our analysis was an Acute Physiology and Chronic Health Evaluation II (APACHE II) score of 23 points or less. Adults with higher APACHE II scores, who did not have their CVCs changed, did not receive antifungal treatment, or who had thrombocytopenia had shorter survival times after the onset of candidemia.ConclusionsAPACHE II scores, thrombocytopenia, antifungal agents, and CVCs changes are associated with survival time in nonneutropenic adults requiring TPN after the onset of candidemia