• Journal of Distribution Science
• /
• v.14 no.2
• /
• pp.73-82
• /
• 2016

Purpose - Counterproductive work behavior(CWB) was typically categorized according to the behavior whether it targets other people(i.e., interpersonal CWB: I-CWB). Employing organizations(i.e., organizational CWB: O-CWB) has emerged as major concerns among researchers, managers, and the general public. An abundance of researches has informed us about the understanding for the antecedents of CWB, whereas little is known about the antecedents of CWB directed distribution service in employee's emotional labor. Therefore, the purpose of this research is to propose a research model in which surface acting enhances emotional exhaustion as an emotional labor strategy, which eventually increases counterproductive work behavior(including I-CWM and O-CWB). Research design, data, and methodology - This empirical research data were gathered from the samples of full time frontline hotel employees(including front office, call center, food/beverage, concierge, and room service) in South Korea. Six hotels were selected ranged from four to five stars, including privately owned and joint-venture properties. A convenience sampling method was used to select hotels. Full time frontline hotel employees from the six hotels were surveyed using a self-administered instrument for data collection. With the strong support of hotel managers, a total of 300 questionnaires were distributed, and 252 responses were collected indicating a response rate of 84.0%. In the process of working with the 252 samples, structural equation modeling is employed to test research hypotheses(H1: The relationship between surface acting and Interpersonal counterproductive work behavior(I-CWB) is mediated by emotional exhaustion, H2: The relationship between surface acting and organizational counterproductive work behavior(O-CWB) is mediated by emotional exhaustion). SPSS 18.0 and M-Plus 7.31 software were used for the data analysis. Descriptive statistics were used to assess the distribution of the employee profiles and correlations between factors. M-Plus 7.31 software was used to test the model fit, validity, and reliability of the factors, significance of the relationship between factors, and the effects of factors in the model. Results - To test our mediation hypotheses, we used an analytical strategy suggested by Preacher & Hayes (2008) and Shrout & Bolger (2002). This mediation approach directly tests the indirect effect between the predictor and the criterion variables through the mediator via a bootstrapping procedure. Thus, it addresses some weaknesses associated with the Sobel test. We found that surface acting was positively related to emotional exhaustion. Furthermore, emotional exhaustion was a significant predictor from the two kinds of counterproductive work behavior. In addition, surface acting was not significantly associated with the two kinds of counterproductive work behavior. These results indicated that the surface acting by frontline hotel employees was associated with higher emotional exhaustion, which is related with higher interpersonal counterproductive work behavior(I-CWB) and organizational counterproductive work behavior(O-CWB). In sum, we confirmed that the positive relationship between surface acting and the two kinds of counterproductive work behavior was fully mediated by emotional exhaustion. Conclusions - The current research broadens the conceptual work and empirical studies in counterproductive work behavior literature by representing a fundamental mechanism that how surface acting affects counterproductive work behavior.

• Journal of The Korean Association For Science Education
• /
• v.38 no.3
• /
• pp.393-405
• /
• 2018

In this study, we classified the group model construction types in the actual classroom situation implementing the instructional strategy mixed with individual model construction and group model construction types. The purpose of this study is to analyze the information flow and the individual construction types of each group model construction type to obtain implications for model co-construction in a real classroom environment. A two-session class on sound propagation was carried out for thirty-three 8th grade students in Seoul. A total of 65 individual model construction and 16 group model construction processes were collected and analyzed. The group model construction types were classified as unchanged, enumerated, and elaborated. The unchanged type was found in 8 groups, the enumerated type in 3 groups, and the elaborated type in 5 groups. The isolated individual and independent construction (i.I) were found mostly in the unchanged group construction type (50.0%) and enumerated group construction type (54.5%). In the unchanged type, the radial shape of flow in which one student's information is transmitted to all the members of the group appeared. In the enumerated type, the starting point of the information flow was observed from two individuals. In the elaborated type, linear information flow appeared and both the second dissemination and reflective construction (2d.R) contributed to the group model construction (58.3%). This study suggests a viewpoint that enables to understand the process of complex model construction in an actual classroom context rather than in an ideal situation. The result of this study suggests the necessity of a modeling strategy considering the characteristics of Korean small group culture. It is expected that the discussion will progress through further studies.

• Journal of Internet Computing and Services
• /
• v.17 no.1
• /
• pp.101-107
• /
• 2016

Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.

• Journal of the Korean Society of Radiology
• /
• v.12 no.3
• /
• pp.409-415
• /
• 2018

The development of smart devices has brought about significant changes in daily life and one of the most significant changes is the virtual reality zone. Virtual reality is a technology that creates the illusion that a 3D high-resolution image has already been created using a display device just like it does in itself. Unrealized subjects are forced to rely on audiovisual materials, resulting in a decline in the concentration of practices and the quality of classes. It used virtual reality to develop effective teaching materials for radiology students. In order to produce a video clip bridge using virtual reality, a radiology clinic was selected to conduct two exposures from July to September 2017. The video was produced taking into account the radiology and work flow chart and filming was carried out in two separate locations : in the computerized tomography unit and in the LINAC room. Prior to filming the scenario and the filming route were checked in advance to facilitate editing of the video. Modeling and mapping was performed in a PC environment using the Window XP operating system. Using two leading virtual reality camera Gopro Hero, CC pixels were produced using a 4K UHD, Adobe, followed by an 8 megapixel resolution of $3,840{\times}2,160/4,096{\times}2,160$. Total regeneration time was performed in about 5 minutes during the production of using virtual reality to prevent vomiting and dizziness. Currently developed virtual reality radiation and educational contents are being used to secure the market and extend the promotion process to be used by various institutions. The researchers will investigate the satisfaction level of radiation and educational contents using virtual reality and carry out supplementary tasks depending on the results.

• Science of Emotion and Sensibility
• /
• v.21 no.2
• /
• pp.101-112
• /
• 2018

This study was carried out to enhance the competitiveness of blackbox design for domestic and international companies, based on the explosive growth of the blackbox market due to development of blackbox design for vehicle accident prevention and post-treatment. In the past, the blackbox market has produced products indiscriminately to meet the ever-increasing demand of consumers. Therefore, we thought a new design method was necessary to effectively investigate the needs of rapidly changing consumers. In this study, we aimed to identify the best-selling blackbox to understand the design flow, and the optimum area for a blackbox, considering the uniqueness of associated vehicle. Based on discussion with blackbox design experts, we studied the direction of design and the problems with blackbox use, which were reflected in blackbox development. Through this research, two types of design - leading blackbox (A type) and mass production blackbox (B type) - were proposed for compatibility of the blackbox with the car. The leading type of blackbox was positioned so that it was wrapped with the room mirror hinge before the screw was fastened, in order to achieve an integrated design. Therefore, we designed an integrated form and resolved the placement problem of an adhesive blackbox. To blend, the mass production blackbox implemented material and surface processing in the same way with the car, and adopted the slide structure to automatically turn off the main body power when removing the SDcard, reflecting consumer needs. This study considers evolving consumer needs through a case study and collective intelligence and deals with implementation of the whole design process during mass production. In this study, we aimed to strengthen the competitiveness of the blackbox design based on design method and its realization.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.157-173
• /
• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.23-45
• /
• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Global Scholars of Marketing Science
• /
• v.17 no.4
• /
• pp.113-139
• /
• 2007

This study aims to, looking from a standpoint of network, has investigated the shipping industry's B2B e-marketplace, the characteristics that can earn electronic trust from the users, and characteristics of the web-site. It has examined the mechanism whereby electronic trust be earned and how it affects web-site involvement and service transaction intention. Ultimately, The study attempts to make proposals whereby such trust can lead for a cooperative trading community in the shipping industry's B2B e-marketplace The Covalence structural equation modeling was designed and empirically tested for the shipping industry's B2B e-marketplace. The shipping industry employees were given questionnaires and data were analyzed. Except for perceived security of the three characteristic factors on the web-site, the perceived site quality and characteristics factors in operation only affected co-variables. Transaction Fairness was determined to be the most important factor among exogenous factors increasing electronic trust. With regards to transaction rules, if a transaction is beneficial only to one side, then no long term transaction will not take place. If the concerned parties properly recognize that transaction fairness is crucial to electronic transaction, then it will enormously contribute to successful operations of shipping e-marketplace. Also, Perceived efficiency in transaction also affects electronic trust. This reduces transaction costs and speeds up and simplifies the transaction process. It has reduced greater time and costs than existing off-line transaction, and would positively affect electronic trust. By making an open forum for participants to obtain information for transaction, they can gather useful information, and at the same time, the web-site operator can provide information, which, in turn, will increase electronic trust in electronic transaction. Furthermore, such formation of trust in electronic transaction influences shipping companies in such a way that they will want to continuously participate in the transaction, raising web-site involvement. The result of increased trust is that shipping companies in the future will do business with each other and form a foundation for continuous transactions amongst themselves. Consequently, the formation of trust in electronic transaction greatly influences web-site involvement and service transaction intention. The results of the study have again proved that in order to maintain continuous business relationship with the current clients, electronic trust in virtual space, which operates the shipping industry's B2B e-marketplace, is important for the interested parties.

• KDI Journal of Economic Policy
• /
• v.12 no.4
• /
• pp.47-69
• /
• 1990

Using an aggregator model, we look into the possibilities for substitution between Korea's exports, imports, domestic sales and domestic inputs (particularly labor), and substitution between disaggregated export and import components. Our approach heavily draws on an economy-wide GNP function that is similar to Samuelson's, modeling trade functions as derived from an integrated production system. Under the condition of homotheticity and weak separability, the GNP function would facilitate consistent aggregation that retains certain properties of the production structure. It would also be useful for a two-stage optimization process that enables us to obtain not only the net output price elasticities of the first-level aggregator functions, but also those of the second-level individual components of exports and imports. For the implementation of the model, we apply the Symmetric Generalized McFadden (SGM) function developed by Diewert and Wales to both stages of estimation. The first stage of the estimation procedure is to estimate the unit quantity equations of the second-level exports and imports that comprise four components each. The parameter estimates obtained in the first stage are utilized in the derivation of instrumental variables for the aggregate export and import prices being employed in the upper model. In the second stage, the net output supply equations derived from the GNP function are used in the estimation of the price elasticities of the first-level variables: exports, imports, domestic sales and labor. With these estimates in hand, we can come up with various elasticities of both the net output supply functions and the individual components of exports and imports. At the aggregate level (first-level), exports appear to be substitutable with domestic sales, while labor is complementary with imports. An increase in the price of exports would reduce the amount of the domestic sales supply, and a decrease in the wage rate would boost the demand for imports. On the other hand, labor and imports are complementary with exports and domestic sales in the input-output structure. At the disaggregate level (second-level), the price elasticities of the export and import components obtained indicate that both substitution and complement possibilities exist between them. Although these elasticities are interesting in their own right, they would be more usefully applied as inputs to the computational general equilibrium model.

• The Journal of Korean Academy of Prosthodontics
• /
• v.53 no.2
• /
• pp.120-127
• /
• 2015

Purpose: The aim was to investigate the effect of implant thread designs on the stress dissipation of the implant. Materials and methods: The threads evaluated in this study included the V-shaped, buttress, reverse buttress, and square-shaped threads, which were of the same size (depth). Building four different implant/bone complexes each consisting of an implant with one of the 4 different threads on its cylindrical body ($4.1mm{\times}10mm$), a force of 100 N was applied onto the top of implant abutment at $30^{\circ}$ with the implant axis. In order to simulate different osseointegration stages at the implant/bone interfaces, a nonlinear contact condition was used to simulate immature osseointegration and a bonding condition for mature osseointegration states. Results: Stress distribution pattern around the implant differed depending on the osseointegration states. Stress levels as well as the differences in the stress between the analysis models (with different threads) were higher in the case of the immature osseointegration state. Both the stress levels and the differences between analysis models became lower at the completely osseointegrated state. Stress dissipation characteristics of the V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration. These results indicated that implant thread design may have biomechanical impact on the implant bed bone until the osseointegration process has been finished. Conclusion: The stress dissipation characteristics of V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration.