• Journal of Distribution Science
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• v.12 no.10
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• pp.75-84
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• 2014

Purpose - This article aims to examine whether the stock issuance of firms in the retail industry follows Myers' (1984) pecking order theory, which is based on information asymmetry. According to the pecking order model, firms have a sequence of financing decisions, of which the first choice is to use retained earnings, the second one is to get into safe debt, the next involves risky debt, and the last involves finance with outside equity. Since the 2000s, the polarization of the LEs (Large enterprises) and SMEs (Small and Medium Enterprises) arose in the retail industry. The LEs exhibited an improvement in growth and profitability, whereas SMEs had a tendency to degenerate. This study contributes to corroborating the features of financing decisions in the retail industry distinguished from the other industries. Research design, data, and methodology - This study considers the stocks listed on the KOSPI and KOSDAQ markets from 1991 to 2013, and is more concentrated on the stocks in the retail industry. The data were collected from the financial information company, WISEfn. The empirical analysis is conducted by employing two measures of net equity issues (and), which were introduced in Fama and French (2005), and can be calculated from firms' accounting information. All variables are generated as the aggregate value of the numerator divided by aggregate assets, which, in effect, treats the entire sample as a single firm. Substantially, the financing decisions of the firms were analyzed by examining how often and under what circumstances firms issue and repurchase equity. Then, this study compares the features of the retail industry with those of the other industries. Results - The proportion of sample firms that show annual net stock issues reaching the level of the year's average was 54.33% for the 1990s, and fell to 39.93% per year for the 2000s. In detail, the fraction of the small firms actually increases from 45.08% to 51.04%, whereas that of large firms shows a dramatic decline from 58.94% to 24.76%. Considering the fact that the large firms' rapid increase in growth after the 2000s may lead to an increase in equity issues, this result is rather surprising. Meanwhile, net stock repurchases of assets are considerably disproportionate between the large (-50.11%) and the small firms (-15.66%) for the 2000s. Conclusions - Stock issuance of retail firms is not in line with the traditional seasoned equity offering based on information asymmetry. The net stock issuance of the small firms in the retail industry can be interpreted as part of an effort to reorganize business and solicit new investment to resolve degenerating business performance. For large firms, on the other hand, the net repurchase can be regarded as part of an effort to rearrange business for efficiency and amplifying synergy across business sections through spin-off. These results can help the government establish a support policy on retail industry according to size.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.192-203
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• 2016

The purpose of this study is to investigate the effects of task conflict on job attitudes (organizational commitment & job satisfaction), focusing on the mediating effects of supervisory communication & co-worker communication. Recently, the importance of communication as a research topic has been increasing. According to prior research, communication satisfaction has a positive effect on job performance. However, studies which take into account the different types of communication are lacking. Therefore, this study considered two types of communication (supervisory communication and coworker communication). A research model and hypotheses were developed in order to examine the theoretical research issues and questions. The sample consisted of 280 survey data drawn from employees in firms located in Korea. The data was analyzed by the statistical packages, SPSS 21.0 & AMOS 21.0 for Windows. The findings of the analysis are as follows. Firstly, it was found that task conflict had a negative (-) effect on organizational commitment & job satisfaction. Therefore, H1a & H1b are supported. Secondly, it was found that task conflict had a negative (-) effect on supervisory communication. Therefore, H2a is supported. However, it did not have a significant effect on co-worker communication. Hence, H2b is not supported. Thirdly, as regards the mediating effect of supervisory communication, it was found that supervisory communication mediated the effect of task conflict on job attitudes (organizational commitment & job satisfaction). Therefore, H3a & H3b are supported. Finally, the mediating effect of co-worker communication was not significant. Therefore, none of the sub-hypotheses of H4 are supported. Based on these findings, this study suggested directions for future research.

• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Journal of the Korean Society for Railway
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• v.15 no.1
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• pp.9-16
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• 2012

The dynamic stability of railway vehicle has been one of the important issues in railway safety. The dynamic simulator has been used in the study about the dynamic stability of railway vehicle and wheel/rail interface optimization. Especially, a small scale simulator has been widely used in the fundamental study in the laboratory instead of full scale roller rig which is not cost effective and inconvenient to achieve diverse design parameters. But the technique for the design of the small scale simulator about the dynamic characteristics of the wheel-rail system and the bogie system has not been well developed in Korea. Therefore, the research using the small-scaled derailment simulator and the 1/5 scaled bogie has been conducted. In this paper, we did running stability test of 1/5 scaled bogie using small-scaled derailment simulator. Also, for the operation of the small scaled simulator, it is required to investigate the performance and characteristics of the simulator system. This could be achieved by a comparative study between an analysis and an experiment. This paper presented the analytical model which could be used for verifying the test results and understanding of the physical behavior of the dynamic system comprising the small- scaled derailment simulator and the 1/5 scaled bogie.

• Journal of Service Research and Studies
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• v.3 no.2
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• pp.53-60
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• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.9-26
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• 2005

In the pursuit of ever higher levels of performance, recent computer systems have made use of deep pipeline, dynamic scheduling and multi-issue superscalar processor technologies. In this situations, branch prediction schemes are an essential part of modem microarchitectures because the penalty for a branch misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. In this paper, we propose a novel branch prediction scheme, direction-gshare(d-gshare), to improve the prediction accuracy. At first, we model a neural network with the components that possibly affect the branch prediction accuracy, and analyze the variation of their weights based on the neural network information. Then, we newly add the component that has a high weight value to an original gshare scheme. We simulate our branch prediction scheme using Simple Scalar, a powerful event-driven simulator, and analyze the simulation results. Our results show that, compared to bimodal, two-level adaptive and gshare predictor, direction-gshare predictor(d-gshare. 3) outperforms, without additional hardware costs, by up to 4.1% and 1.5% in average for the default mont of embedded direction, and 11.8% in maximum and 3.7% in average for the optimal one.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.3
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• pp.63-74
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• 1999

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.3
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• pp.32-39
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• 2009

In this paper, system optimization design technique of an impulse ground penetrating image radar (GPIR) in time domain is proposed to improve depth resolution of the system. For the purpose, time domain analysis method of key components such as impulse generator and UWB antenna is explained and by simulation, parameters of each component are determined. In particular, by standardizing the impulse signal, spectrum efficiency of a radiated impulse signal is improved and a U-shaped planar dipole antenna for a UWB antenna is developed. By equipping a parabolic metal reflector with the proposed antenna, external noise is prevented and the ability of radiating an input impulse into ground is improved. In addition, to remove ringing effect of the propose antenna which causes serious degradation of the system performance, resistors are loaded at the edge of the antenna and then Tx and Rx UWB antennas are optimized by simulation in time domain. For images of targets buried under the ground migration technique is applied and influence of tough ground surface on distortion of received impulse signals is reduced using technique of noise and signal distortion reduction in time domain and its time resolution is enhanced. To verify the design optimization procedure, a prototype of an GPIR and an artificial test field are made. Measurement results show that the resolution of the system designed is as good as that of a theoretical model.

• Korean Journal of Occupational Health Nursing
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• v.9 no.1
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• pp.39-48
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• 2000

Hyperlipemia is the most leading risk factor of cardiovascular disease which is the main cause of death in Korea. However, there is a tendency to neglect the prevention and treatment since it has no specific symptoms. It has been reported that the level of serum-lipid can be lowered by the improvement of eating habits. Therefore, it is highly likely that the development of programs on the improvement of eating habits through behavioral theory is required to the community nursing practice. The theory of planned behavior, which assumes that human behaviors are determined by one's intention to carry out the behavior, can be characterized by the point that behaviors are not only individual factors but also social behaviors relating to subjective norms. It is widely recognized that this theory has a high predictability on health behavior due to it's simplicity clearness, and measurability as well as high quality of being general. Thus, the theory of planned behavior could be useful in developing a model of a health promotion program to the change of behaviors of the risk group of cardiovascular disease. Consequently, based on the theory of planned behavior, the purpose of this study is to develop an intention promotion program of the diet, and then to testify the effects. The sample of this study consisted of 26 industrial workers who had proved hyperlipemia from a medical examination in 1996 (experimental group 13, control group 13). The intention promotion program, which includes education, monitoring, pressure, counselling on the level of individuals, families and organizations, was conducted for 10 weeks The purpose of this program was to promoting intention of the diet through changes of the prerequisite factors of intention such as behavioral belief, outcome evaluation, normative belief and control belief. When it came to data analysis, the ${\chi}^2$-test and Fisher's Exact test were used to compare the general characteristics between the experimental and the control group, an independent t-test for the other variables. ANOVA was used to the test hypothesis, and the Pearson correlation test for variable's correlation. The results of this study can be summarized as follows ; 1) There was a significant increase in the intention(F=18.51, p=.00) of diet in the experimental group. 2) Diets(F=32.51, p=.001) in the experimental group were better carried out than in the control group. 5) There was a moderate correlation between the intention of diet and performance (r=.587. p=.003). From the results, it can be concluded that the intention promotion program is very effective, leading to the change of health promotion behavior. Above all, it is really valuable that the intention promotion program in this study regards health promotion behavior as a social behavior and that intervention was done on the level of family and organization. Consequently, when performing a health promotion program, social approach elevating the intention should go hand in hand in order to make the program effective.