• Journal of Animal Science and Technology
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• v.44 no.5
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• pp.607-616
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• 2002

This study analyzed the effects of pH, sex, backfat thickness, ribeye area, cold carcass weight, shipping month, muscle internal temperature, average daily temperature, and average relative humidity for slaughtered Hanwoo to meat color by season. The analyses focused on interaction and each effect to meat color of the factors. For the result for analysis of multiple linear regressions, meat color values were decreased as pH increased in all meat color, and the meat color values increased as the backfat thickness was increased. As the results of the decision tree analysis by each factor, cow and steer slaughtered in spring and autumn were the highest in the lightness(L*). The redness(a*) was the cases that pH was less than 5.63 and average relative humidity was over than 71.5% for Hanwoo slaughtered in autumn. The chroma(C*) value was the highest for Hanwoo that was slaughtered in summer and autumn, the pH was less than 5.60, and the back fat thickness was over than 8 mm. The hue angle($h^0$) was shown that the muscle internal temperature was less than 4.7$^{\circ}C$ among Hanwoo which was slaughtered in spring, summer, and autumn, the pH was less than 5.66, and the back fat thickness was over than 8 mm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.313-324
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• 2015

In this paper, in order to support the construction of a smart home environment of low power consumption, we propose a heterogeneous interface determination engine and architecture. Technology of "smart home" is in the spotlight according to the development of IT technology nowadays. Smart homes are configured with multiple sub-networks, and each sub-network is formed by the smart devices using various communication interfaces. Thus, in the smart home environment, interlocking technology between heterogeneous interfaces is essentially required for supporting communication between different networks. Further, each communication interface is a difference in power consumption, and home smart devices are often operated in 24 hours, especially smart phones and other wireless devices are sensitive to power consumption. Therefore, in order to build a energy efficient home network, It is important to select the appropriate interface to handle traffic depending on the situation. In this paper, we propose "The Heterogeneous Interface Decision Engine and Architecture for constructing of Low Power Home Network," and analyze the performance of the proposed method and verify the validity through experiments on the test bed.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.383-389
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• 2004

This paper proposes a method to provide intelligence for characters in fighting action games by using a neural network. Each action takes several time units in general fighting action games. Thus the results of a character's action are not exposed immediately but some time units later. To design a suitable neural network for such characters, it is very important to decide when the neural network is taught and which values are used to teach the neural network. The fitness of a character's action is determined according to the scores. For learning, the decision causing the score is identified, and then the neural network is taught by using the score change, the previous input and output values which were applied when the decision was fixed. To evaluate the performance of the proposed algorithm, many experiments are executed on a simple action game (but very similar to the actual fighting action games) environment. The results show that the intelligent character trained by the proposed algorithm outperforms random characters by 3.6 times at most. Thus we can conclude that the intelligent character properly reacts against the action of the opponent. The proposed method can be applied to various games in which characters confront each other, e.g. massively multiple online games.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.216-223
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• 2008

The purpose of this study was to examine the effects of the satisfaction and absorption of spectating on desire of re-spectating at the professional sporting events. This study set a model of consumer behavior decision based on the results of the precedent studies about the determinative factors of consumer behavior and the hypothetical model done by Wakefield ＆ Sloan(1995), Hansen ＆ Gauthier(1989), Jeffrey(1997), Green(1995), and Kim(1999) and clarified it through the regression. To attain the goal of the study described above paragraphs, some viewers of 2007 season pro-soccer and pro-baseball games were set as a collected group. Then, using the stratified cluster random sampling method, finally drew out and analyzed 605 spectators in total. Data collected through a questionnaire designed for this study consist of fixed alternative choice response to items constructed to represent the operational definition for each variable. Statistics employed for data analysis was correlation and multiple regression. Based upon the results of the study, the following conclusions appear warranted: 1. Satisfaction of spectating influence on desire of re-spectating at the professional sporting events. 2. Satisfaction of absorption influence on desire of re-spectating at the professional sporting events.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.447-458
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• 2012

We present a method to recognize hand gestures using skeletal joint data obtained from Microsoft's Kinect sensor. We propose a combination feature of multi-angle histograms robust to orientation variations to represent the observation sequence of skeletons. The proposed feature efficiently represents the orientation variations of gestures that can be occurred according to person or environment by combining the multiple angle histograms with various angular-quantization levels. The gesture represented as combination of multi-angle histograms and random decision forest classifier improve the recognition performance. We conduct the experiments in hand gesture dataset obtained from a kinect sensor and show that our method outperforms the other methods by comparing the recognition performance.

• Korean Security Journal
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• no.59
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• pp.9-35
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• 2019

Until now, a lot of research on cyber security have been tried, but there have been few studies on overall relationships, including internal factors and external factors. Therefore, this study examined cyber security management considering not only internal elements of SMEs but also corporate management environment. The first qualitative analysis and the second quantitative analysis were conducted through mixed method research. Qualitative analysis was conducted through a semi-structured interview method, and three themes were found: insufficient cyber security management system, internal noncooperation for cyber security, and problems derived from decision-making system. In the quantitative analysis, multiple regression analysis was conducted on the data obtained through the questionnaire. The perception of cyber threats and internal support among independent variables positively influenced the cyber security management system or the dependent variable. Through this study, internal variables had a causal impact on the cyber security management system rather than external environment variables. This implies that the variables related to the organizational culture such as employees' perception are important. These results are expected to provide practical significance for enhancing the cyber security management system in SMEs.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.822-832
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• 2001

We have implemented an inductive learning system that learns PROSPECTOR-rule-style classification rules from sets of examples. In our a approach, a genetic algorithm is used in which a population consists of rule-sets and rule-sets generate offspring through the exchange of rules relying on genetic operators such as crossover, mutation, and inversion operators. In this paper, we describe our learning environment centering on the syntactic structure and meaning of classification rules, the structure of a population, and the implementation of genetic operators. We also present a method to evaluate the performance of rules and a heuristic approach to generate rules, which are developed to implement mutation operators more efficiently. Moreover, a method to construct a classification system using multiple learned rule-sets to enhance the performance of a classification system is also explained. The performance of our learning system is compared with other learning algorithms, such as neural networks and decision tree algorithms, using various data sets.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.348-358
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• 2017

The process of evaluating and selecting the best available techniques presents various characteristics for each country. In the case of EU, BAT is selected through TWG meeting after first screening, mass and energy balance, impact assessment and decision support process. Korea has proposed four principles to select BAT that can be carbon neutral for each environmental infrastructure in order to reduce greenhouse gas emissions. In order to evaluate and select the best available technique, it is necessary to differentiate the method according to whether it is a technique generally applied at the current workplace, whether it is a single technique or a combination technique, and whether it is a technology technique or management technique. In the case of a single technique, it should be evaluated whether it is a technique applied in the workplace, excessive cost, superior environmental technique over BAT, and secondary environmental pollution. In the case of multiple techniques, it is necessary to examine whether the emission standards are met and whether the pollutants can be treated at the same level as BAT. In the case of BAT candidates for management techniques, whether or not they contribute directly or indirectly to lowering the emission level of pollutants can be an important evaluation item. In the case of environmental techniques that are not generally applied in the workplace, it is recommended that the following 8 steps be carried out, including those prescribed by law. In the first stage, the list of performance evaluation factors is listed. In the second stage, the level of disposal of pollutants and the level of satisfaction with standards are listed. In the third stage, the environmental evaluation elements are listed. In the fourth stage, Is to list the economic evaluation elements, step 6 is to list the pollution and accident prevention evaluation factors, step 7 is the quantitative evaluation of the technical working group, and step 8 is BAT confirmation through deliberation of the central environmental policy committee.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.61-73
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• 2007

We examined technological forecasting of extended TFDEA(Technological Forecasting with Data Envelopment Analysis) and thereby apply the extended method to the technological forecasting problem of main battle tank. The TFDEA has the possibility of using comparatively inefficient DMUs(Decision Making Units) because it is based on DEA(Data Envelopment Analysis), which usually leads to multiple efficient DMUs. Therefore, TFDEA may result in incorrect technological forecasting. Instead of using the simple DEA, we incorporated the concept of Super-efficiency, Cross-efficiency, and CCCA(Constrained Canonical Correlation Analysis) into the TFDEA respectively, and applied each method to the case study of main battle tank using verifiable practical data sets. The comparative analysis shows that the use of CCCA with TFDEA results in very comparable prediction accuracies with respect to MAE(Mean Absolute Error), MSE(Mean Squared Error), and RMSE(Root Mean Squared Error) than using the concept of Super-efficiency and Cross-efficiency.