• Advances in nano research
• /
• v.12 no.3
• /
• pp.263-279
• /
• 2022

In this research, the physical education training quality was investigated using the entropy model to compute variance associated with a random value (a strong tool). The entropy and undefined estimation principles are used to extract the greatest entropy of information dependent on the index system. In the study of tennis motion tracking from a dynamic viewpoint, such stages are utilized to improve the perception of the players' achievement (Lv et al. 2020). Six female tennis players served on the right side (50 cm from the T point). The initial flat serve from T point was the movement under consideration, and the entropy was utilized to weigh all indications. As a result, a multi-index measurement vector is stabilized, followed by the confidence level to determine the structural plane establishment range. As a result, the use of the unascertained measuring technique of information entropy showed an excellent approach to assessing athlete performance more accurately than traditional ways, enabling coaches and athletes to enhance their movements successfully.

• International Journal of Advanced Culture Technology
• /
• v.1 no.2
• /
• pp.1-6
• /
• 2013

In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.

• Proceedings of the KSME Conference
• /
• 2000.04b
• /
• pp.144-147
• /
• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• Journal of the Korean Society for information Management
• /
• v.28 no.1
• /
• pp.309-326
• /
• 2011

Most metadata quality measurement employ simple techniques by counting error records. This study presents a new quantitative measurement of metadata quality using advanced weighting schemes in order to overcome the limitations of exiting measurement techniques. Entropy, user tasks, and usage statistics were used to calculate the weights. Integrated weights were presented by combining these weights and were applied to actual journal article metadata. Entropy weights were found to reflect the characteristics of the data itself. User tasks presented the required metadata elements to solve user's information need. Integrated weights showed balanced measures without being affected by the influence of error elements, This finding indicates the new method being suitable for quantitative measurement of metadata quality.

• Journal of Korea Port Economic Association
• /
• v.20 no.1
• /
• pp.1-20
• /
• 2004

The purpose of this paper is to analyze the degree of cargo concentration at Korean ports using Theil's Entropy and to compare the results with those of Gini coefficient, Hoyle(1983), and Hirshmann-Herfindahl models. The entropy indices were compared with other models after measuring the cargo concentration for the period of 1981-2000 among the 18 Korean ports. The core results of empirical analysis are as follows: first, the empirical results of entropy indices show the following trends: all the ports(concentration except 1996's slight deconcentration), ports in Western area(deconcentration in 1990s and slight concentration in 2000), ports in Southern area(deconcentration in 1980s and 1990s except concentration in 2000), and ports in Eastern area(continuous trends of concentration). However, competition power will be decreased if concentration is increased, because of the character of entropy index. The empirical results of 4 indices except Hoyle model show the comparatively same directions in terms of trends. This study found out the similar results among the following models: All the ports(entropy index & Gini coefficient & H-H model), ports in Western area(Entropy index &Hoyle model), ports in Southern area(Entropy index & Gini coefficient), and ports in Eastern area(Entropy index & H-H index).The policy planner of Korean ports should find out the determination factors of concentration and deconcentration of each ports and decide the investment priority, size and scope for balancing the development of regional ports.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.59-60
• /
• 2007

Entropy, one of leading metrics on anomalous traffic, attracts researcher's attention since a packet sampling and a traffic volume impact little on entropy value. In this paper, we apply the entropy metric to a domestic network traffic trace which has real anomalous traffics. We used source IP address/port and destination IP address/port that are important attributes of a packet as entropy variable We found that entropy value of multiple-port DoS attack shows something related to a staircase fashion. Also, we show a Possibility of detection of anomalous traffic on small time scale.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.19 no.39
• /
• pp.265-274
• /
• 1996

This paper presents the intersectional dependence relations for the better efficient evaluation of the three tactical missile system(T.M.S) by use of multi-criteria decision making methodology. T.M.S alternatives A, B and C will be evaluated by Analytic Hierarchy Process(AHP) based on entropy weight in this study. A numerical example is presented to illustrate the use of entropy weight measurement with intersectional dependence problems. This problems are evaluated five criteria : tacticals criteria, technology criteria, maintenance criteria, economy criteria, advancement criteria.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.30 no.7 s.250
• /
• pp.787-793
• /
• 2006

Recently kriging model has been widely used in the DACE (Design and Analysis of Computer Experiment) because of prominent predictability of nonlinear response. Since DACE has no random or measurement errors contrast to physical experiment, space filling experimental design that distributes uniformly design points over whole design space should be employed as a sampling method. In this paper, we examine the maximum entropy experimental design that reveals the space filling strategy in which defines the maximum entropy based on Gaussian or exponential. The influence of these two correlation functions on space filling design and their model parameters are investigated. Based on the exploration of numerous numerical tests, enhanced maximum entropy design based on exponential correlation function is suggested.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.9A
• /
• pp.896-905
• /
• 2010

In this paper, we present a new sensing method based on phase entropy. Entropy is a measurement which quantifies the information content contained in a signal. For the PSK modulation, the information is encoded in the phase of the transmitted signal. By focusing on phase, more information is collected during sensing, which suggests a superior performance. The sensing based on Phase entropy is not limited to PSK signal. We generalize it to PAM signal as well. It is more advantageous to detect the phase. The simulation results have confirmed the excellent performance of this novel sensing algorithm.

• Structural Monitoring and Maintenance
• /
• v.4 no.1
• /
• pp.33-52
• /
• 2017

A cantilever beam with a breathing crack is studied to improve the breathing crack identification sensitivity by the parametric optimization of sample entropy and wavelet transformation. Crack breathing is a special bi-linear phenomenon experienced by fatigue cracks which are under dynamic loadings. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a fatigue crack. To improve the sensitivity of entropy measurement for crack identification, wavelet transformation is merged with entropy. The crack identification is studied under different sinusoidal excitation frequencies of the cantilever beam. It is found that, for the excitation frequencies close to the first modal frequency of the beam structure, the method is capable of detecting only 22% of the crack depth percentage ratio with respect to the thickness of the beam. Using parametric optimization of sample entropy and wavelet transformation, this crack identification sensitivity is improved up to 8%. The experimental studies are carried out, and experimental results successfully validate the numerical parametric optimization process.