• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.55-76
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• 2015

The prior studies on the practical lawyer's information seeking behaviors, including Leckie et al. (1996) model showed that role of the work and nature of the work in attorney's practices had an significant influence on the attorney's information seeking behaviors. This study now asks if these prior analyses can be applicable to attorneys' practices nowadays. This study performed surveys and interviews with 21 practical attorneys in korea who were grouped by their experience period and the size of law firms. This study concludes that role of the work in Leckie et al. model still affects the attorneys' information seeking behaviors today and moreover, the attorney's experience and the size of law firms as variables also have made an impact on attorney's behaviors so far. By the way, this study further finds that the attorneys prefer the digital information in online database and formal information like statutes or case laws. These results are definitely different from them of the prior studies. In addition, this study suggests that the behavior such as meaningful using of the informal information in difficulties with improper information can be kinds of the attorney's information seeking behaviors.

• (The) Korean Journal of Advertising
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• v.29 no.7
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• pp.29-53
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• 2018

In our study, we investigated the effects of position of endorser and endorser's gaze direction(direct/averted_image/averted_text) on advertising attitude, purchase intent and brand recognition using eye-tracking method. Focusing on the printed cosmetic ads which the role of endorser is important and indirect persuade route is relatively is emphasized, we conducted experiment on 36 participants in 20s. As prior studies, our results shows that participants paid attention to more and faster on specific element which the endorser is gazing at. But it was not reflected to ad attitude and purchase intent directly. When the endorser is positioned in left the side, the highest purchase intent was shown in direct gaze condition, while when the endorser is on the right side, the highest ad attitude was shown in gazing image condition. Additionally, the brand recognition task following eye-tracking experiment shows that recognition accuracy was higher only in condition which the endorser is in the left side looking at the product image. These results demonstrated that the gaze direction of endorser plays a role as attentional guidance, which means it can lead customer's attention to particular region in the printed ad, but the effect can be varied depending on the position of endorser and which type of information the endorser is gazing at. Therefore, ultimately, to increase customer's ad attitude and purchase intent, complex consideration of not only the gazing direction of the endorser, but the position of endorser and other diverse elements is necessary.

• Journal of the Korea Concrete Institute
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• v.23 no.2
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• pp.185-193
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• 2011

In the present study, a unified shear design method was developed to evaluate the shear strength of concrete beams with and without FRP shear reinforcement. The contributions of FRP and concrete on shear strength were defined separately. By comparing the current design method calculated results with the existing test results, it was found that Triantafillou model shows a reliable prediction of FRP effective strain and FRP shear strength contributions. The concrete shear strength contribution was defined by the strain-based shear strength model developed in the previous study. The shear strength of concrete compression zone was evaluated based on the material failure criteria of the concrete subjected to the compressive normal and shear stresses. The proposed strength model was verified by comparing its prediction results to prior test results. The comparisons showed that the proposed method accurately predicts the strengths of the test specimens for both FRP shear reinforced and unreinforced concrete beams.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1201-1206
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• 2008

This study is focused on the investigation of the modal characteristics of the preliminary models of science technology satellite-3 (STSAT-3). Prior to the final decision of the composite structure model, several candidate structure models have been developed so as to find the most qualified structures with respect to the satellite structure systems' requirements and then utilize the information achieved to a real design. The main structure is composed of fiber reinforced composite faced honeycomb sandwich panel whose modal characteristics are found and compared to each other by means of finite element numerical analyses. Results from the current study demonstrate that a rectangular box shape having supporting inner panel shows relatively higher fundamental mode frequencies than octagonal box shape and etc., and regardless of the structure model shape tested herein, the fundamental mode turns out lateral bending mode.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.67-82
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• 2007

Due to the classes in object-orientation, which are too detailed and specific, their reusability can be decreased. Components, considered to be more coarse-grained compared to objects, help maintain software complexity effectively and facilitate software reuse. Furthermore, component technology becomes essential by the appearance of the new frameworks, such as MDA, SOA, etc. Consequently, it is necessary to reengineer an existing object-oriented system into a component-based system suitable to those new environments. In this paper, we propose a model-based quantitative reengineering methodology to identify components from object-oriented systems. We expand system model and process, which are defined in our prior work, more formally and precisely. A system model, constructed from object-oriented system, is used to extract and refine components in quantitative ways. We develop a supporting tool and show effectiveness of the methodology through applying it to an existing object-oriented system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.33-38
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• 2019

This paper proposes an effective recognition method of VPI patient's speech employing DNN-HMM-based speech recognition system, and evaluates the recognition performance compared to GMM-HMM-based system. The proposed method employs speaker adaptation technique to improve VPI speech recognition. This paper proposes to use simulated VPI speech for generating a prior model for speaker adaptation and selective learning of weight matrices of DNN, in order to effectively utilize the small size of VPI speech for model adaptation. We also apply Linear Input Network (LIN) based model adaptation technique for the DNN model. The proposed speaker adaptation method brings 2.35% improvement in average accuracy compared to GMM-HMM based ASR system. The experimental results demonstrate that the proposed DNN-HMM-based speech recognition system is effective for VPI speech with small-sized speech data, compared to conventional GMM-HMM system.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.161-168
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• 2021

Cracks affect the robustness of infrastructures such as buildings, bridge, pavement, and pipelines. This paper presents an automated crack detection system which detect cracks in diverse surfaces. We first constructed the combined crack dataset, consists of multiple crack datasets in diverse domains presented in prior studies. Then, state-of-the-art deep learning models in computer vision tasks including VGG, ResNet, WideResNet, ResNeXt, DenseNet, and EfficientNet, were used to validate the performance of crack detection. We divided the combined dataset into train (80%) and test set (20%) to evaluate the employed models. DenseNet121 showed the highest accuracy at 96.20% with relatively low number of parameters compared to other models. Based on the validation procedures of the advanced deep learning models in crack detection task, we shed light on the cost-effective automated crack detection system which can be applied to different surfaces and structures with low computing resources.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.367-377
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• 2024

The purpose of this study is to develop a competency model that enhances the management capabilities of vocational training institutions and to identify the priorities of educational needs. After reviewing prior studies to tentatively establish a competency model, a training needs assessment was conducted in the field using this model. Data for the analysis were collected through a survey conducted among vocational training institutions. Following the needs assessment, a new management competency model for vocational training institutions was formulated, comprising six competencies and 26 competency dimensions, by eliminating the dimensions considered relatively less important. The competency model developed through this study is anticipated to be utilized in creating management education programs for directors of domestic vocational training institutions.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.27-43
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• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.461-480
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• 2008

There are innumerable studies on technology adoption and usage continuance; most examine cognitive factors while affective factors or the feelings of users are left relatively unexplored. Although attitude and user satisfaction are factors commonly considered in Information Systems(IS) research, they represent only some aspects of feelings. In contrast, researchers in diverse fields have begun to note the importance of feelings in understanding and predicting human behavior. Feelings are anticipated to be essential particularly in the context of modern applications, such as mobile internet(M-internet) services, where users are not simply technology users but also service consumers. Drawing on the support of consumer research, social psychology and computer science, this study proposes a balanced cognition-affect model of IS continuance. Prior works in relation to IS research have already considered the emotional factors. The common factors are enjoyment, anxiety, affect and satisfaction. The main difference in our study is that the factors that we used are the primary dimensions of affect according to Circumplex Model of Affect. The horizontal axis of the model represents the pleasure dimension and the vertical represents the arousal dimension. Other emotional factors such as enjoyment and anxiety can be viewed as a combination of these two dimensions, and they can be placed in the vector space formed by these two primary dimensions. Affect has been defined as the enjoyment a person derives from using computers. Satisfaction has different conceptualizations. It has been conceptualized as judgment based on the expectation disconfirmation theory. Thus, while prior works considered the direct and indirect effects of "feeling-related constructs"(enjoyment and anxiety) on usage behavior, our study proposes effects of "feeling-based constructs"(pleasure and arousal). The balanced cognition-affect model is tested in a survey of, M-internet service users. The results establish the validity of the model.