• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.285-297
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• 2014

This research is involved in looking into the cognition pattern of social worker position of a fourth-year student majoring in Social Welfare. The purpose of this research is to offer a basic data needed for education of the students who are preparing to get a job of a social worker. For this, applying Q methodology, this research made an objective analysis of their subjective response to social worker position targeting the 30 students in the department of social welfare at the four-year-course college located in Gyeongsangbuk-do and Gyeongsangnam-do. The research results showed that the cognition pattern of the college students' occupational view on social welfare position could be categorized into the three; The first pattern is a "job-skeptic & reality-evasive" type, who tends to perceive the position of a social worker as the one having a lot of job exhaustion and much workload, showing a pessimistic view on the meaning or a sense of mission of a social worker position. The second pattern is a "practice-centered & specialized-job-seeking type" who tends to think much of practical aspects of a social worker job and to seek after the position of a social worker as a specialized job, and at the same time to rely on the policy or system for a social worker position. The third pattern is a "value-oriented & self-achievement type", who tends to think much of the necessity of value or ethics in putting social welfare into practice and also to make much of self-achievement through the channel of a social welfare worker position. Taken together, it might be possibile to turn out professional human resources, but this research thinks it is more necessary to place the education of values of a social welfare worker.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.150-160
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• 2018

Purpose: This study was conducted to understand what various factors influence school life adaption of nursing students by measuring life stress, anger and optimism. Methods: The subjects were 186 students in B city and the data were collected for the period of 17-28 April 2017. The collected data were analyzed with an independent t-test, ANOVA, Scheffe's method, Cronbach's alpha and Pearson's correlation coefficients. The results are as follows respectively: life stress 1.34/4, state anger 1.24/4, trait anger 1.57/4 at average, and among optimism was 3.45/5 at average. Multiple regression analysis showed perceived physical health status(${\beta}=.20$ t=2.72, p=.007), satisfaction on college(${\beta}=.19$, t=2.53 p=.012) and life stress (${\beta}=-.14$ t=-2.28, p=.027) were related to factors. They accounted 18.2% of the optimism of the subjects. However, there was no significant correlation between optimism and anger of nursing students. Conclusion: It is necessary to develop a program to improve the optimism of nursing college students and to develop a program that can enhance the coping ability of stress to cope with life stress experienced by nursing students.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Korean Journal of Environment and Ecology
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• v.28 no.5
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• pp.542-549
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• 2014

This study was conducted to investigate the body size, sexual size dimorphism (SSD), and related environmental factors between Red-tongued viper snakes (Gloydius ussuriensis) inhabiting two different places, i.e., Jeju Island and its islet Gapado, and to provide data required to maintain species diversity from May, 2006 until June, 2009. The snout-vent length of the Red-tongued viper snake population inhabiting Jeju Island was found to be 242-532 mm ($422.0{\pm}46.7mm$, n = 100) in females and 296-580 mm ($434.5{\pm}51.7mm$, n = 63) in males. In contrast, the snout-vent length was observed to be 205-395 mm ($335{\pm}43.6mm$, n = 55) in female and 215-430 mm ($328{\pm}39.4mm$, n = 73) in male Red-tongued viper snakes inhabiting Gapado. These data demonstrated the snout-vent length of both female and male Red-tongued viper snakes on Jeju Island to be larger than those on Gapado (Female t = 17.343, df = 115, P<0.001; Male = 19.128, df = 101, P<0.001). SSD was measured to be -0.03 in the Red-tongued viper snake population on Jeju Island, with more or less larger sizes in the males, while it was 0.02 in the Red-tongued viper snake population in the Gapado, with a little larger sizes in the females. The reason for this difference in the snake populations between Jeju Island and Gapado may be due to adaption to the different ecological environments. In addition, as SSD, the snout-vent length of the Red-tongued viper snake populations and in young vipers was somewhat higher in the males than in the females on Jeju Island (t = -2.011, df = 117, P<0.05). However, no significant differences were observed in the snout-vent length of the young and the general Red-tongued viper snake populations on Gapa Island. For the population on Jeju island, the head length (F = 6.318, $df_{1,2}$=1,117, P<0.05), head width (F=8.090, $df_{1,2}$=1,117, P<0.01), inter eye length (F=15.898, $df_{1,2}$=1,117, P<0.001), and tail length (F=238.488, $df_{1,2}$=1,111, P<0.001) were all larger in the males, while females showed higher body mass (F=64.111, $df_{1,2}$=1,114, P<0.001). In the case of the Gapa Island population, no significant differences in the head length, head width, and inter eye length between females and males were observed, while the males had a longer tail length (F=168.555, $df_{1,2}$=1,74, P<0.001) and the females were heavier (F=17.812, $df_{1,2}$=1,76, P<0.001). Though no significant differences were found in the head length, head width, and inter eye length, the tail length (F=67.793, $df_{1,2}$=1,72, P<0.001) and body mass (F=4.558, $df_{1,2}$=1,72, P<0.05) were higher in the young male Red-tongued viper snakes than in the females. The snout-vent length, head length, head width, and inter eye length, which did not display SSD in the young Red-tongued viper snake populations, were higher in the male Red-tongued viper snake populations than in the female population from Jeju Island, implying that SSD in the Red-tongued viper snake population on Jeju Island is expressed due to environmental effects during their growth.