• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3204-3220
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• 2021

We perform the task of video object segmentation by incorporating a conditional random field (CRF) and convolutional neural networks (CNNs). Most methods employ a CRF to refine a coarse output from fully convolutional networks. Others treat the inference process of the CRF as a recurrent neural network and then combine CNNs and the CRF into an end-to-end model for video object segmentation. In contrast to these methods, we propose a novel higher-order CRF model to solve the problem of video object segmentation. Specifically, we use CNNs to establish a higher-order dependence among pixels, and this dependence can provide critical global information for a segmentation model to enhance the global consistency of segmentation. In general, the optimization of the higher-order energy is extremely difficult. To make the problem tractable, we decompose the higher-order energy into two parts by utilizing auxiliary variables and then solve it by using an iterative process. We conduct quantitative and qualitative analyses on multiple datasets, and the proposed method achieves competitive results.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.22-27
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• 2020

In this paper, a generalized efficiency equation was proposed to estimate the internal loss of the SMPS (switched-mode power supply) with 3 variables. The first variable was an internal loss not related to the load current such as auxiliary power, the second was a loss proportional to the current such as diode loss, and the third was a loss proportional to square of the current such as conduction loss. Especially, theoretical internal losses of the totem pole bridgeless PFC which is widely used for high efficiency SMPS were expressed as output function to compare generalized efficiency equation. In addition, in order to reduce the conduction loss of the switch, when a multiple switch were paralleled, the correlation with the efficiency was analyzed and shown as a graph. In order to confirm the degree of the parallel switch structure on the efficiency improvement, a 2kW class totem pole bridgeless PFC was constructed and the effectiveness of the analysis was confirmed by comparing the generalized efficiency equation and theoretical loss analysis results with experimental data.

• The Journal of Industrial Distribution & Business
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• v.13 no.8
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• pp.29-50
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• 2022

Purpose - This study aims to investigate factors affecting Chatbot service acceptance attitude. For wide use of Chatbot service, firms need to find barriers or obstacles for customers, if any, not to use Chatbot service. Research design, data, and methodology - We apply value-based accept model to investigate the quality of Chatbot, to verify the meaning of service value of Chatbot and to find the relationship among variables. To test hypotheses, we conducted survey. We collected 300 questionnaires. SPSS version 2.0 is used. Regression analysis, moderating effect test is conducted. Results - 4 Qualities of Chatbot, Ease of use, Usefulness, Enjoyment, Interaction are affecting acceptance attitude, and 5 service values, only interaction does not affect emotion. Trust, Specialty, Necessity, Social, Emotion moderating Chatbot service to accepting attitude. Regarding moderating effects by personal characteristics and personal tendency, innovation resistance, innovativeness, and social effects are turned to have influence while regulatory focus, construal level does not have moderating force. Also, the auxiliary service like Chatbot service affects customers' evaluation on the main service quality. Conclusions - Service firms adopt Chatbot service for various purposes. The results imply that customers are generally recognize the merits of Chatbot, but there are some barriers such as innovation resistance characteristic especially uncomfortable.

• Korean Journal of Culture and Social Issue
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• v.29 no.1
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• pp.75-99
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• 2023

The current study aimed to explore the suicidal behaviors and risk factors of completed suicides using psychological autopsy and use them as index variables to classify suicidal types. In addition, this study looked into the influential factors that affect each suicidal type. related to suicidal behaviors and suicidal risk factors by psychological autopsy. In addiction, the distinctions among the classes were analyzed. For this, psychological autopsies were conducted on the families and the close ones of 128 completed suicides. Then, the index variables were finally chosen for classifying suicidal types. The selected index variables for suicidal risk factors were mental disorders, suicide/self-harm, significant changes in physical appearance, marital conflict, adjustment and relationship issues at work/school, unemployment/layoff, jobless status and serious financial problems. The selected index variables for suicidal behaviors were expressing their suicidal attempts, writing suicidal notes, asking for help, the time/place/method of suicidal behavior, past suicidal/self-harm experience and the first person who witnessed the suicide. The Latent Class Analysis(LCA) and the 3-step method were used for classifying suicidal types. Then external variables(financial changes, cohabitation, existence of stressors, changes in stress level or relationships and family members with mental disorder/alchohol problems/ physical disorders, and work/school stisfaction) were applied for distinguishing classes. As a result, 5 classes(financial problems, adjustment problems, complex problems, psychiatric problems, and response to event[s]) were revealed on suicidal behaviors and 3 classes(residence- suicidal attempt- found by family, nonresidence- nonsuicidal attempt- found by acquaintances, residence- nonsuicidal attempt- found by family) were presented on suicidal risk factors. External variables such as gender, marital status, cohabitation, changes in relationships significantly differentiated among the 3 classes. Especially, class 3(residence- nonsuicidal attempt- found by family) tended to cohabit with others, were married, and had a significantly high level of interpersonal conflicts. When comparing the 5 classes of suicidal risk factors, auxiliary variables such as economic changes, cohabitation, stress, relationship changes, and family-related problems, and school/work satisfaction significantly differentiated the 5 classes. Especially class 3 (complex problems) experienced comparatively less family-related problems, but showed an aggravating level of personal stress. Suicial prevention strategies should be provided considering the characteristics of each class and the influential factors.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.175-182
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• 2013

In this paper, the simulation model of house price is presented on the basis of pricing mechanism between the demand and the supply of apartments in seoul. The algorithm of house price simulation model for calculating the rate of price over time includes feedback control theory. The feedback control theory consists of stock variable, flow variable, auxiliary variable and constant variable. We suggest that the future price of apartment is simulated using mutual interaction variables which are demand, supply, price and parameters among them. In this paper we considers three items which include the behavior of apartment price index, the size of demand and supply, and the forecasting of the apartment price in the future economic scenarios. The proposed price simulation model could be used in public needs for developing a house price regulation policy using financial and non-financial aids. And the quantitative simulation model is to be applied in practice with more specific real data and Powersim Software modeling tool.

• Journal of the Korean Chemical Society
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• v.43 no.2
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• pp.182-192
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• 1999

The new GD/ICP-AES quick change over system has been developed and characterized. Within less than 15 minutes, ICP-AES could be switched to GD-AES and vise a versa. As a result, both solid and liquid samples could be analyzed in a very short period of time by the ICP/GD-AES quick change over system developed in our laboratory. The influences of the experimental variables, such as flow rate of coolant gas, flow rate of auxiliary gas, flow rate of sample carrier gas, sampling depth, orifice size of sampling cone, and rf (radio frequency) power on emission intensity have been presented. The detection limits of Cd(I) 228.8 nm, Mn (II) 257.61 nm, and Fe(II) 259.95 nm were found to be 3.86, 1.49, and 5.79 ppb, respectively. And linealities of the calibration curves were measured to be unity.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.57-67
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• 2006

In sampling survey, nonresponse tend to occur inevitably. If we use information from respondents only, the estimates will be baised. To overcome this, various non-response imputation methods have been studied. If there are few auxiliary variables for replacing missing imputation or spatial autocorrelation exists between respondents and nonrespondents, spatial autocorrelation can be used for missing imputation. In this paper, we apply several nonresponse imputation methods including spatial imputation for the analysis of farm household economy data of the Gangwon-Do in 2002 as an example. We show that spatial imputation is more efficient than other methods through the numerical simulations.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.51-76
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• 2014

As the smart phone devices gain popularity, companies no longer consider mobile application marketing as an auxiliary marketing tactic. The branded mobile application (branded app) becomes an important part of marketing strategies. This study is an attempt to investigate antecedents of the use intention of the branded app from the perspective of TAM (Technology Acceptance Model). This study takes a macro perspective in explaining the adoption process by incorporating a set of new, yet promising additional variables into the TAM model such as flow experience, benefits, innovation inclination, and customization features. Data were collected by using a survey research. A total of 270 responses were collected. Questionnaires from 25 individuals were removed from the data set due to the insincere responses, leaving the final sample size of 245. Findings support all but one hypotheses of the study. Both perceived utilitarian benefits and customization features of the branded app were found to have positive influences on the perceived usefulness of the branded app. Also, the innovation inclination and perceived entertainment of branded app users showed positive influences on the perceived ease of use of branded app. In addition, it was shown that the perceived usefulness about the use of the branded app influenced positively the flow experience and the users' attitudes toward branded app. Also, the ease of use perceived by branded app users had positive influences on the perceived usefulness and the user's attitude toward branded app. However, the ease of use of branded app did not have a significant influence on the flow experience among users. Moreover, the flow experience from the use of branded app users influenced positively the user's attitude toward branded app. Finally, the users' attitudes toward branded app had positive influences on their intention to use the branded app. Implications for practitioners and academicians are provided.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.1
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• pp.47-57
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• 2010

Subgrid scale stabilization method is applied to Woo and Liu(2004)'s extended Boussinesq FEM numerical model to eliminate the 2dx wiggles. In order to optimize the computational efficiency, Hessian operator is introduced and the matrix of velocity vector is combined to one matrix for solving matrix equations. The mass lumping technique is also applied to the matrix equations of auxiliary variables. The newly developed code is applied to simulate Vincent and Briggs(1989)' wave transformation experiments and the results show that the numerical solution is almost wiggle-free and it matches very well with experimental data. Due to improvement of computational efficiency and wiggle reduction, it is plausible to apply this model to a realistic problem such as harbor oscillation problems.

• The Journal of Information Systems
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• v.31 no.3
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• pp.47-65
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• 2022

Purpose With the recent development of Big Data and Artificial Intelligence technology, self-driving technology has developed into three stages (partial self-driving) or four stages (conditional self-driving), it is expected to bring a new paradigm to transportation in the city. Although many researchers are researching related technologies, there is no research on self-driving for disabled persons. In this study, the basic research was conducted based on the assumption that the shared self-driving car used by the disabled person is similar to the special transportation currently driving. Design In this study, data analysis and machine learning techniques were utilized to analyze the mobility patterns of disabled persons by type and to search for leading factors affecting the traffic volume of special transportation. Findings The study found that external physical disorders and developmental disorders often visit general welfare centers, internal organ disorders often visit general hospitals, and the elderly and mental disorders have various destinations. In addition, machine learning analysis showed that the main transportation routes for the disabled person use arterial roads and auxiliary arterial roads and that the ratio of building usage-related variables affecting the use of special transportation for a disabled person is high. In addition, the distance to the subway and bus stops was also mentioned as a meaningful variable. Based on these analysis results, it is expected that the necessary infrastructure for shared self-driving cars for disability person traffic will be used as meaningful research data in the future.