• Korean Journal of Psychosomatic Medicine
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• v.7 no.1
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• pp.116-123
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• 1999

Objectives : The authors attempted to assess how much the mechanism of dissociation affects somatization disorder patients psychopathologically, and explore the relationship between sexual or physical abuse and somatic symptoms in somatization disorder patients. Methods : The authors administered the Dissociative Experiences Scales-Korean version(DESK) and Dissociative Disorders Interview Schedule to 25 patients with somatization disorder and 51 normal subjects. Results : There were no significant demographic differences between patient and control groups. The mean score of DES-K for patient group was 18.2, and 10.0 for the control group. The percentage of the individuals with high scores(20 and over) was 36.0 in the patient group and 7.8 in the control group, respectively. The percentage of the individuals with sexual and/or physical abuse was 16.0 in the patient group and zero in the control group. Our results showed that DES-K scores were not influenced by the factor of age or religion in either group, but the scores of the patients with somatization disorder were significantly higher than those in the normal subjects. Conclusion : There was an implication that the mechanism of dissociation affects issues of psychopathogenesis and psychopathology in Korean patients with somatization disorder, even though they have different sociocultural backgrounds in comparison to Western patients. The authors suggest it is useful to focus attention on childhood abuse and dissociation in the evaluation and dynamic psychotherapy of patients with somatization disorder.

• Korean Journal of Psychosomatic Medicine
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• v.23 no.1
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• pp.26-35
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• 2015

Objectives:The purpose of this study was to evaluate reliability and validity of the Korean version of the Postconcussional Syndrome Questionnaire(KPCSQ) which was originally developed in 1992 by Lees-Haley. Methods:Patients with traumatic brain injury were recruited from April 2009 to December 2011 from the Korean University Ansan Hospital. We selected patients that met the ICD-10 diagnostic criteria of postconcussional syndrome and organic mental disorder including organic mood disorder, organic emotionally labile disorder, organic anxiety disorder and organic personality disorder. The KPCSQ, Trait and State Anxiety Inventory(STAI-I, II), and Center for Epidemiologic Studies Depression Scale(CESD) were administered to all subjects. Factor analysis of the items were performed and test-retest correlation were evaluated. Internal consistency of the KPCSQ and its subscales was assessed with Cronbach's alpha. External validity of the KPCSQ were examined by correlation coefficient with the STAI-I, II, and CESD. Results:The Cronbach's alpha coefficient of the total PCSQ was 0.956. The test-retest reliability coefficient was 0.845. The PCSQ showed significant correlation with STAI-I, II and CESD. The factor analysis of the PCSQ yielded 4 factors model. Factor 1 represented 'affective and cognitive symptoms', factor 2 represented 'somatic symptoms', factor 3 represented 'infrequent symptoms' and factor 4 represented 'exaggeration or inattentive response'. There was no significant difference between the PCS group and the organic mental disorder group in the score on each measure. The scores on KPCSQ and its subscales in the subjects that had scored 5 or more in 'exaggeration or inattentive response' are significantly higher than those in the subjects had scored 4 in 'exaggeration or inattentive response'. Conclusions:This study suggests that the Korean version of PCSQ is a valid and reliable tool for assessing psychiatric symptomatology of patients with traumatic brain injury. Further investigations with greater numbers of subjects are necessary to assess the clinical usefulness of the KPCSQ.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.10-24
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• 2021

Purpose: The purpose of this study is to determine the dangers of biodiesel and general diesel mixtures currently used as alternative fuels by equipment (tag method and penski Marten method) and to determine the difference between flash point and combustion point (closed, open) according to test methods. It is intended to be used as a reference material for identification and evaluation of firecausing substances by confirming the risk of mixtures by comparative analysis and measurement, and establishing a risk assessment method for chemical substances. Method: Flash point test method and result treatment were tested based on ASTM and KS M mode, which are tag sealing and pen schematense test methods used as flash point and combustion point test methods for crude oil and petroleum products. The manufacturer of the equipment used in this experiment was a test equipment that satisfies the test standards of KS M 2010 with equipment produced by TANAKA of Japan. The flash point and combustion point were measured, and the flash point according to the test method of biodiesel and general diesel mixture ( Closed, open), and the ignition point of a mixture of biodiesel and general diesel was compared and analyzed for ignition risk compared with conventional diesel. Results: Looking at the experimental results, first, as an analysis of the risk of flammability of the mixture, the flash point of a substance containing 70% biodiesel was found to be about 92℃ based on general diesel with a flash point of 64.5℃, and gasoline and biodiesel or When the biodiesel mixture was synthesized, it was confirmed that the flash point tends to decrease. In addition, the difference between the flash point and the combustion point was analyzed as about 20 ~ 30℃, and when a small amount of gasoline or methanol was mixed, the flash point was lowered, but it was confirmed that the combustion point was similar to that of the existing mixture. Conclusion: In this study, in order to secure the effectiveness of the details of the criteria for judging dangerous materials in the existing Dangerous Materials Safety Management Act, and to secure the reliability and reproducibility of the judgment of dangerous materials, we confirm the criteria for judging the risk of the mixture through an experimental study on flammable mixtures. It will be able to provide reference data for experimental criteria for flammable liquids that are regulated in the field. In addition, if this study accumulates know-how on experiment by test method, it is expected that it can be used as a basis for research on risk assessment and research on dangerous goods.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.39-51
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• 2003

Objectives: The Profile of Mood States (POMS) has been used broadly and frequently in various medical studies with various subjects. For the development and application of the Korean edition of POMS, called K-POMS, we translated POMS into Korean and then evaluated the reliability and validity of K-POMS. Methods: The subjects were 161 male students with a mean age of 18.1 years (15-30) and 244 female students with a mean age of 16.6 years (14-23). They were requested to perform K-POMS and SCL-90-R (Korean version) at the same time. Means, reliability coefficients, and test-retest correlations of K-POMS were calculated. Content validities, correlations with SCL-90-R, and discrimination validities in comparison with 76 depressive patients were obtained, and factor analyses were carried out. Results: Mean scores of Total Mood Disturbance (TMD) and some subscales (T, F, C, V factor) showed a significant difference between male and female students. The internal consistency coefficient ($\alpha$) of the total 65 items was 0.93, and ranged from 0.67 to 0.90 for subscales. Test-retest correlations of 43 subjects ranged from 0.27 to 0.63. Seven psychiatrists rated the properness of the content of each item as more than moderate degree (mean scale points=2.66, in the range of 0 to 4). Every subscale of KPOMS exhibited significant correlation with the matching subscale of SCL-90-R. Mean scores of K-POMS of the total 405 subjects were significantly different from those of the 76 depressive subjects after age correction. Six factors were extracted, accounting for 51.2% of total variance. Factor 6 consisted of 6 items which came from various subscales of POMS and represented "uncertainty and helplessness," which may be somewhat different to depression or sadness proper. Conclusion: The validity and reliability of K-POMS could be confirmed. The significant difference in K-POMS scores between depressive subjects and normal subjects suggests that K-POMS can be used clinically for the evaluation and screening of depression. The main structure of K-POMS is very similar to that of POMS, except the Confusion-Bewilderment factor which shows weak factor consistency in K-POMS. This may reflect some emotional characteristic of Koreans such as an undifferentiated aspect of cognitive efficiency. The sixth factor newly extracted from K-POMS also may be indicative of an unique emotional aspect of young Koreans.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Asia Marketing Journal
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• v.14 no.1
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• pp.99-130
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• 2012

Service failure and a poor service recovery may lead loyal customers to try to aggressively punish the service firm. We use perceived betrayal and desire for vengeance as the key constructs to understand customer retaliation. Perceived betrayal is defined as a customer's belief that a firm has intentionally violated what is normative in the context of their relationship. And the desire for vengeance is defined as the retaliatory feelings that consumers feel toward a firm, such as the desire to exert harm on the firm. The perceived betrayal and the desire for vengeance are key antecedents of retaliatory behaviors such as vindictive complaining, negative WOM and third-party complaining for publicity. The empirical results suggest that betrayal is a key motivational factor that lead customers to restore fairness by making use of all means, including retaliation. We also find that relationship quality has effect on a customer's response to a failure in service recovery. As the levels of relationship increases, a violation of the proper fairness has a stronger effect on the sense of betrayal experienced by customers. Considerable research has investigated consumer responses to dissatisfaction. But our study examine the response of outraged and highly frustrated consumers. We focus on emotional and behavioral processes that have not been covered by previous dissatisfaction researches and which are unique to outraged consumers caused by extremely dissatisfied purchase experience. It has recently been pointed out by various mass media that the customers not only have positive effects on the company performance but also put the company in crisis. It has often been reported that one customer's dissatisfaction, for example, never ends as it is, and it tends to grow for retaliating upon the company, depending on the level of seriousness of the dissatisfaction. This sometimes leads to a lawsuit against the company. Our study focuses on the customers' emotional and behavioral responses induced by their extreme dissatisfactions. We divided the customer groups into the customers with high relationship quality and the customers with low relationship quality, and the difference between two groups is examined. The objective of this study is to comprehend the causal relationship between the feeling of betrayal caused by the service failure and the retaliatory behavior triggered by the desire of revenge. Our study is divided into three parts. First, a causal relationship between perceived unfairness and the perceived betrayal and desire for revenge. Second, the effect of the perceived betrayal and desire for revenge on the retaliatory behavior is investigated. Finally, the moderating role of relationship quality in the causal relationship between the unfairness in service recovery and the perceived betrayal is analyzed. This study finds the following empirical results. The distributive unfairness, procedural unfairness and interactional unfairness had significant effects on the perceived betrayal. Especially, the perceived distributive unfairness results in the highest perceived betrayal. When the service company does not provide customers proper and sufficient compensation for the failure, they feel the strong sense of betrayal. And in the causal relationship between the perceived betrayal, desire for revenge and retaliatory behavior, the perceived betrayal has significant effects on e desire for revenge. In addition desire for revenge has significant effects on negative word of mouth, retaliatory complaining behavior and publicity of complaints through third group. Therefore the perceived unfairness has effects on retaliatory behavior through the mediation of the perceived betrayal and desire for revenge. Finally the moderating role of relationship quality was examined in the relationship between the unfairness and perceived betrayal. If the customers experienced the perceived unfairness in the process of service recovery, the customers with high relationship quality feel the stronger perceived betrayal than the customers with low relationship quality do. When they experience the double service failure, the customer group with high relationship quality accumulating the sense of trust feel the more perceived betrayal than the customer with low relationship quality who do not have strong trust. The contribution of this study is to find the effect of the service failure on the retaliatory behavior with the moderating roles of relationship quality. The dimensions of unfairness in service recovery is found to have differential effects on the perceived betrayal, desire for revenge. And these differential effect is moderated by the level of relationship quality.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.