2,287 research outputs found
Application of Grey Theory in the Construction of Impact Criteria and Prediction Model of Players’ Salary Structure
[[abstract]]Salaries of professional players are usually determined prior to the execution of the responsibilities assigned by the organizations
and are often based on the expected future performance of these players as derived from their past achievement. The study first
identifies criteria that would affect players’ salaries through literature reviews and then utilizes grey relational analysis (GRA) and
grey prediction model to calculate weights of salary impact criteria, players’ annual performance index, and salary prediction for
the coming year. The performance data of players from the Chinese Professional Baseball League (CPBL) are used in this study.
The results are as follows: (i) CPBL teams do refer to players’ past performance records and future performance prediction when
deciding on their salaries and (ii) future performance prediction must be made using at least a 3-year data set. The proposed
prediction model is able to effectively provide relevant and useful information to the CPBL teams’ management during players’
salary adjustment.[[notice]]補ćŁĺ®Ś
Leveling Maintenance Mechanism by Using the Fabry-Perot Interferometer with Machine Learning Technology
This study proposes a method for maintaining parallelism of the optical cavity of a laser interferometer using machine learning. The Fabry-Perot interferometer is utilized as an experimental optical structure in this research due to its advantage of having a brief optical structure. The supervised machine learning method is used to train algorithms to accurately classify and predict the tilt angle of the plane mirror using labeled interference images. Based on the predicted results, stepper motors are fixed on a plane mirror that can automatically adjust the pitch and yaw angles. According to the experimental results, the average correction error and standard deviation in 17-grid classification experiment are 32.38 and 11.21 arcseconds, respectively. In 25-grid classification experiment, the average correction error and standard deviation are 19.44 and 7.86 arcseconds, respectively. The results show that this parallelism maintenance technology has essential for the semiconductor industry and precision positioning technology
Computing Thresholds of Linguistic Saliency
PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200
Qubit Mapping Toward Quantum Advantage
Qubit Mapping is a pivotal stage in quantum compilation flow. Its goal is to
convert logical circuits into physical circuits so that a quantum algorithm can
be executed on real-world non-fully connected quantum devices. Qubit Mapping
techniques nowadays still lack the key to quantum advantage, scalability.
Several studies have proved that at least thousands of logical qubits are
required to achieve quantum computational advantage. However, to our best
knowledge, there is no previous research with the ability to solve the qubit
mapping problem with the necessary number of qubits for quantum advantage in a
reasonable time. In this work, we provide the first qubit mapping framework
with the scalability to achieve quantum advantage while accomplishing a fairly
good performance. The framework also boasts its flexibility for quantum
circuits of different characteristics. Experimental results show that the
proposed mapping method outperforms the state-of-the-art methods on quantum
circuit benchmarks by improving over 5% of the cost complexity in one-tenth of
the program running time. Moreover, we demonstrate the scalability of our
method by accomplishing mapping of an 11,969-qubit Quantum Fourier Transform
within five hours
A Neural Network Decision Method for Software Maintenance Life Cycle Identification
The software maintenance life cycle concept is a powerful model in helping software maintenance planning. The operationalization of the life cycle concept requires a heuristic decision method. Although the heuristic decision method works most of the time, the method requires integration of different tools and sometimes leads to errors. In this paper, we propose a neural network decision method, which combines data smoothing and maintenance stage identification into one unit
THE COMPARISON OF DIFFERENT ELASTIC TENSION OF KINESIO TAPING ON GASTROCNEMIUS MUSCLE ACTIVATION
The purpose of this study was to compare the effect of different elastic tension of Kinesio taping on gastrocnemius muscle activation. Thirty-seven healthy athletes was recruited and randomly divided into three groups: Elastic tension 0% (N = 13), 10% (N = 12), and 20% (N = 12). All athletes were applied Kinesio taping on gastrocnemius muscle in 3 different elastic tape tensions. The wireless electromyography was used to assess the gastrocnemius muscle activation before and after applied Kinesio taping while jogging on treadmill. The results showed that a significant interaction between different elastic tape tension and pre-post taping applied (
HLA typing in Taiwanese patients with oral squamous cell carcinoma
AbstractBackground/purposeThe human leukocyte antigen (HLA) system, which plays a vital role in immunity, is the most polymorphic gene complex found in the human genome. This study investigated HLA-related alleles and haplotypes in Taiwanese patients with oral squamous cell carcinoma (OSCC).Materials and methodsHLA class I (HLA-A and HLA-B) antigens and class II (HLA-DRB1) alleles were determined in 105 patients with OSCC and compared with those in 190 healthy controls. The antigens were measured serologically and the alleles by sequencing-based typing.ResultsCompared with the control group, patients with OSCC had higher frequencies of HLA-A24, HLA-B54, HLA-DRB1*0405, and HLA-DRB1*1201, while they had lower frequencies of HLA-B58 and HLA-DRB1*1302. Haplotype frequencies also varied significantly in individuals with OSCC, with certain haplotypes associated with lymph node metastases or a particular tumor stage.ConclusionThese results suggest that HLA genetic factors influence susceptibility to OSCC and perhaps to lymph node metastasis and tumor progression
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