ANALYSIS OF FIELDER STARTS AND BENCH ABILITY ON AMERICAN PROFESSIONAL BASEBALL PLAYERS

The development of athletes or players depends on two aspects: nature and nurture. The former is the talent and qualification of the players themselves, while the latter is the training that consumes human, material and financial resources. Take professional baseball players as an example. Matching the talents of players and referring to the relevant starting rules of the professional baseball league, when the up-and-coming players are first discovered, focused training are used on them. By doing so, the value of the players would be effectively enhanced and the players are helped to seek a better way out. This can form a virtuous circle: the pellets get quality players, and the players get better results. That is to say, strengthening the training for the shortcomings of the players with the potential of the starting players can avoid unnecessary training and huge training expenses behind them, and greatly reduce the risk of career, so that the players have higher security in their short career, and get a win-win-win situation. This study is aimed at the schedule information of the American Baseball League teams. Through feature selection of data mining, this study analyzes the main relationships and key differences between starting player and bench player of second baseman and shortstop in League of Nations teams. It is found that the on base percentage and speed of the infielders is an important ability indicator for the starting position; whereas, the second baseman emphasizes on the attack and the shortstop focuses on fielding. This feature is verified by comparing the opinions of experts and commentators.  Article visualizations

Factors of Employee’s E-Learning Effectiveness: A Multi-Level Study Based on Socio-Technical Systems Theory

Application of e-learning in enterprises provides the advantages of lower training cost, richer learning content, higher information consistency, and easier update of content. Despite the fact that enterprises have the intention to introduce e-learning, there is not a complete framework to which they can refer to ensure the benefits of e-learning for employee training or learning and understand which important factors affect employee’s e-learning effectiveness. Relative to the difficulties of introducing e-learning in management practice, the academic achievements in this aspect also seem very limited. Most the existing papers are focused on discussion and survey of e-learning in school, and very few of them are dedicated to empirical research of e-learning in corporate environment. Besides, these studies discuss e-learning only at the technical or the individual level without a comprehensive investigation into the factors affecting e-learning effectiveness with multi-level theoretic framework. This paper applies the socio-technical systems theory to review and integrate theories about employee e-learning from a macro view. To make up the insufficiency of related research, literature review and case research are conducted first. Based on the interview results, an analysis model is constructed to thoroughly explore factors affecting employee’s e-learning effectiveness. Later, through a questionnaire survey on employees’ adoption of e-learning and subsequent multi-level data analysis, hypotheses on the relationship of the influencing factors and the research model are verified. Results show that e-learning effectiveness (usefulness of e-learning, continuance intention to use, and e-learning performance) is simultaneously or alternately affected by direct or moderating factors of the technical system and the social system at the work environment level and the individual level. Compared with the existing research, this paper uses a more comprehensive system view to construct the theoretical model and empirically verify it. The results can be a reference for future researchers and managers of e-learning in enterprises

Modeling Knowledge Sharing and Interemployee Helping From a Perspective of Flow Theory: A Survey of Online Knowledge Works

This study proposes a model based on flow theory by postulating key antecedents as the critical drivers of knowledge sharing and interemployee helping. In the model, knowledge sharing is influenced by flow experience directly and also indirectly via the mediation of interemployee helping. Accordingly, the flow experience is influenced simultaneously by four exogenous factors related to individuals’ perception about their work: work skills, self-fulfillment in challenges, perceived control, and vividness. The empirical findings of this study confirm the applicability of flow theory in business organizations by investigating online knowledge workers from business organizations. This study contributes to the knowledge management literature by extending flow theory to the area of knowledge sharing and interemployee helping, by validating idiosyncratic antecedent drivers of the flow theory, and by performing a practical operationalization of the flow experience. This research also provides managerial implications and limitations

Understanding the Impact of Service Failure and Recovery Justice on Consumers’ Satisfaction and Repurchase Intention

This research attempts to explore the impacts of different types of justice and their interactions on the satisfaction toward service failure recovery. We attempt to classify justices into hygiene, motivator, or asymmetric variable, based on the concept of asymmetric effect and two factors theory proposed by Herzberg. Specifically, we predict that procedural and distributive justices are hygiene or performance factor and interpersonal justice is motivator. In addition, based on expectancy-disconfirmation theory (EDT), we also attempt to understand the interaction between paired justices by arguing that motivator can generate more effect when hygiene factor or performance factors meet initial expectation. An experiment, with 3x2x2 between-subjects factorial design consisting of three factors to represent different levels of justice provided by online retailer, will be conducted to test the proposed hypotheses. A two-step approach will be used to (1) confirmation the types (hygiene, performance, or motivator) that each justice dimension belongs to, (2) understand the impact of each justice on satisfaction, and (3) test whether motivator will generate more effect when hygiene and performance factor are satisfied

Charge-Trapping Devices Using Multilayered Dielectrics for Nonvolatile Memory Applications

Charge-trapping devices using multilayered dielectrics were studied for nonvolatile memory applications. The device structure is Al/Y2O3/Ta2O5/SiO2/Si (MYTOS). The MYTOS field effect transistors were fabricated using Ta2O5 as the charge storage layer and Y2O3 as the blocking layer. The electrical characteristics of memory window, program/erase characteristics, and data retention were examined. The memory window is about 1.6 V. Using a pulse voltage of 6 V, a threshold voltage shift of ~1 V can be achieved within 10 ns. The MYTOS transistors can retain a memory window of 0.81 V for 10 years

Transformer-based Variable-rate Image Compression with Region-of-interest Control

This paper proposes a transformer-based learned image compression system. It is capable of achieving variable-rate compression with a single model while supporting the region-of-interest (ROI) functionality. Inspired by prompt tuning, we introduce prompt generation networks to condition the transformer-based autoencoder of compression. Our prompt generation networks generate content-adaptive tokens according to the input image, an ROI mask, and a rate parameter. The separation of the ROI mask and the rate parameter allows an intuitive way to achieve variable-rate and ROI coding simultaneously. Extensive experiments validate the effectiveness of our proposed method and confirm its superiority over the other competing methods.Comment: Accepted to IEEE ICIP 202

TransTIC: Transferring Transformer-based Image Compression from Human Visualization to Machine Perception

This work aims for transferring a Transformer-based image compression codec from human vision to machine perception without fine-tuning the codec. We propose a transferable Transformer-based image compression framework, termed TransTIC. Inspired by visual prompt tuning, we propose an instance-specific prompt generator to inject instance-specific prompts to the encoder and task-specific prompts to the decoder. Extensive experiments show that our proposed method is capable of transferring the codec to various machine tasks and outshining the competing methods significantly. To our best knowledge, this work is the first attempt to utilize prompting on the low-level image compression task

Engulfing cells promote neuronal regeneration and remove neuronal debris through distinct biochemical functions of CED-1

Two important biological events happen coincidently soon after nerve injury in the peripheral nervous system in C. elegans: removal of axon debris and initiation of axon regeneration. But, it is not known how these two events are co-regulated. Mutants of ced-1, a homolog of Draper and MEGF10, display defects in both events. One model is that those events could be related. But our data suggest that they are actually separable. CED-1 functions in the muscle-type engulfing cells in both events and is enriched in muscle protrusions in close contact with axon debris and regenerating axons. Its two functions occur through distinct biochemical mechanisms; extracellular domain-mediated adhesion for regeneration and extracellular domain binding-induced intracellular domain signaling for debris removal. These studies identify CED-1 in engulfing cells as a receptor in debris removal but as an adhesion molecule in neuronal regeneration, and have important implications for understanding neural circuit repair after injury

Ray Tracing Simulation in Nonspherically Symmetric Atmosphere for GPS Radio Occultation

A three-dimensional ray tracing model with aiming algorithms for global positioning system (GPS) signal is proposed to make simulations conform to the realistic radio occultation (RO) signal propagation. The two aiming algorithms used in this study ensure the initial and end point ray trajectories are located in the prescribed region. In past studies, the ray tracing techniques applied to the RO signal simulation usually assumed a spherically symmetrical atmosphere for simplicity. The exact GPS and low earth orbit (LEO) satellite locations are not considered in the simulation. These two assumptions make the simulation unrealistic for GPS signal propagation in the RO technique. In the proposed model, the shape of the earth is assumed as an ellipse. The information from European Centre for Medium-Range Weather Forecasts (ECMWF) analysis is used to setup the atmosphere in the simulation. Two aiming algorithms are developed to determine the initial signal propagating direction to make the simulated signal start from the prescribed GPS satellite position and end in the close vicinity of the LEO satellite position. An ideal spherical symmetric atmospheric structure is used to verify the ray tracing model. The fractional difference between real and simulated refractivity results is less than 0.1%. Otherwise, the GPS and LEO satellite position in the Formosat-3/COSMIC observation and the ECMWF analysis, considering the earth¡¦s flattening, is also used to verify the aiming algorithms. All of the simulated signals end in close vicinity to the LEO satellite position in the simulation results