• Journal of the Korean Home Economics Association
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• v.37 no.11
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• pp.59-73
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• 1999

The purpose of the present study was to identify the effect of perceivers’value and religions on the impresson of Korean catholic priest’s ritual dress. The subject consisted of 415 undergraduated students. The experimental materials developed for this study were 3type color photographs stimuli of catholic priest model and 7-point sementic differential scale composed of 49 bipolar adjectives representing personal traits. Perceivers were differenciated by AVL test. The data were analyzed by factor analysis and analysis of variance. The major findings drawl from this study were as follows : 1) Four factors( openness, religious nature, potency, characteristics of apperance) emerged to account for the dimentional structure of the impression of priest’s ritual dress. 2) The ritual dress and perceivers religion had partially significant effect on the impression of the priest. The ritual dress had an effect on openness and potency while the religious of perceivers affected religious symbolism and potency. Black suit with Roman collar and soutan were seen more authoritative, strong and independent than liturgical vestments. Catholic group saw priest with ritual dress more pure and potent than the other religious groups. 3) The ritual dress and perceiver’s value had partially significant effect on the impression of the priest. The ritual dress had an effect on openness, potency and the value had an significant interaction effect on potency. The group with political value perceived the priest with soutan more potent than black suit with Roman collar and liturgical vestments. Therefore the ritual dress and perceivers’value/religion had significant erect on Korean priest impression of openness, religious nature, potency. Research had also shown the similarity-attraction hypothesis which the individuals who hold similar characterisics are more Likely to be attracted.

• Cross-Cultural Studies
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• v.26
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• pp.321-351
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• 2012

This paper attempts to clarify the similarity found in Seo Jungjoo's two books of poems, Seo Jungjoo Shiseon and Shillacho, and thereby to establish the continuity between Seo's early poetry and his mid-period poetry. This attempt arises from the realization that unfamiliar poetic material, background, and narration are merely surface features, and that in fact his early concerns nevertheless persist in terms of his poetic imagination and his Weltanschauung. Furthermore, this continuity seems to originate from shamanistic spiritual chaos that is consubstantially interrelated with the spirit of his deceased lover. After chaos and confusion subsided, the poet's endeavor to discover the lineal origin of his personal shamanism shows itself in Seo Jungjoo Shiseon, and we witness the embodiment of such endeavor in Shillacho. His interest in the skies as it is expressed in my poem, and Shilla as it is intimated by Gwanghwamun are sublimated in saso yeonjag and the words of Queen Seondeog into shamanic wisdom that served as the norm for both spiritual life and physical life in ancient times, and the wisdom is carried on further into the present in Seo's own times. Moreover, the star and the bell sound that were presented as signs of desirable Weltanschauung in Sangrigwawon are transformed into the symbols of shamanic wisdom, and into the inner magic formula that contributes to achieving the wisdom. This analysis offers as its result the evidence embedded in his poems that shows, first, that the two books correspond to merely two separate stages of his poetic concern, and second, that his early poetic concern persists, though transformed through a peculiar manner, into his mid-period poems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.172-178
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• 2020

In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.167-176
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• 2020

Recommendation Systems is the top requirements for many people and researchers for the need required by them with the proper suggestion with their personal indeed, sorting and suggesting doctor to the patient. Most of the rating prediction in recommendation systems are based on patient's feedback with their information regarding their treatment. Patient's preferences will be based on the historical behaviour of similar patients. The similarity between the patients is generally measured by the patient's feedback with the information about the doctor with the treatment methods with their success rate. This paper presents a new method of predicting Top Ranked Doctor's in recommendation systems. The proposed Recommendation system starts by identifying the similar doctor based on the patients' health requirements and cluster them using K-Means Efficient Clustering. Our proposed K-Means Clustering with Content Based Doctor Recommendation for Cancer (KMC-CBD) helps users to find an optimal solution. The core component of KMC-CBD Recommended system suggests patients with top recommended doctors similar to the other patients who already treated with that doctor and supports the choice of the doctor and the hospital for the patient requirements and their health condition. The recommendation System first computes K-Means Clustering is an unsupervised learning among Doctors according to their profile and list the Doctors according to their Medical profile. Then the Content based doctor recommendation System generates a Top rated list of doctors for the given patient profile by exploiting health data shared by the crowd internet community. Patients can find the most similar patients, so that they can analyze how they are treated for the similar diseases, and they can send and receive suggestions to solve their health issues. In order to the improve Recommendation system efficiency, the patient can express their health information by a natural-language sentence. The Recommendation system analyze and identifies the most relevant medical area for that specific case and uses this information for the recommendation task. Provided by users as well as the recommended system to suggest the right doctors for a specific health problem. Our proposed system is implemented in Python with necessary functions and dataset.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.797-808
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• 2012

In smart work environment, a company provides employees a flexible work environment for tele-working using mobile phone or portable devices. On the other hand, such environment are exposed to the risks which the attacker can intrude into computer systems or leak personal information of smart-workers' and gain a company's sensitive information. To reduce these risks, the security administrator needs to analyze the usage patterns of employees and detect abnormal behaviors by monitoring VPN(Virtual Private Network) access log. This paper proposes a decision support system that can notify the status by using visualization and similarity measure through clustering analysis. On average, 88.7% of abnormal event can be detected by this proposed method. With this proposed system, the security administrator can detect abnormal behaviors of the employees and prevent account theft.

• Convergence Security Journal
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• v.23 no.1
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• pp.19-25
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• 2023

The current network environment provides a real-time interactive service from an initial one-way information prov ision service. Depending on the form of web-based information sharing, it is possible to provide various knowledge a nd services between users. However, in this web-based real-time information sharing environment, cases of damage by illegal attackers who exploit network vulnerabilities are increasing rapidly. In particular, for attackers who attempt a phishing attack, a link to the corresponding web page is induced after actively generating a forged web page to a user who needs a specific web page service. In this paper, we analyze whether users directly and actively forge a sp ecific site rather than a passive server-based detection method. For this purpose, it is possible to prevent leakage of important personal information of general users by detecting a disguised webpage of an attacker who induces illegal webpage access using traceback information

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• Journal of Korean Academy of Nursing
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• v.25 no.4
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• pp.709-728
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• 1995

The job related activities of sixty nine nurses, working in the emergency rooms of three university hospitals, were analyzed for six days according to preestablished checklist of nursing activities ; the frequency of these activities and the amount of time spent in each specific nursing activity. The established checklist was monitored every five minutes for the duration of the duty autu, thus producing 414 items of data. The data were not gathered on consecutive days but over the period of one month from May 6, 1994 to June 5, 1994. The following conclusions are derived from analysis of the data : 1. Twelve categories of nursing activities were obtained : The primary activity was communication related to the patient and all information pertaining to the patient. Other activities included maintaining the patient's record, observation and assessment of the patient, cooperation with other medical personnel, management of equipment and drugs, procedure and treatment, specimen collection, consultation and education for the patient, including drug management and personal hygiene and any other relevant education to the patient's condition. 2. The average frequency of categorized nursing activity can be classified as follows : communication related to patient was the highest at 17.6 times. The next was maintaining the patient's record at 17.3 times. The observation and assessment occurred 16.9 times. Consultation and education for patients and family, 8 times, medication, 5.7 times, and procedures and treatments, 6 times. 3. The average time required for each activity was as follows : 230.1 minutes (or maintaining the patient's record, 204.9 minutes for communication related to the patient, 199.2 minutes for observation and assessment, 71.2 minutes for medication, 66 minutes for consultation and education of the patient and family, and 51.8 minutes for procedures and treatment. 4. The most demanding nursing activity in the emergency room for the nurse was answering questions from the patient's family, maintaining communication between the medical staff, maintaining and reviewing the patient's charts, writing prescriptions and monitoring 1. V. infusion rates. 5. The most time consuming nursing activities for the emergency room nurse include maintaining and following the patient's charts, communication between the medical staff, answering questions from the patient's family, observation of the patient and relaying all of the appropriate patient information to the incoming nurses during a shift change. 6. The F-test was administered to measure the required time for the categorized nursing activities according to day, evening, and night-shift nurses. There were significant differences (p<.05) in specimen collection, observation and assessment, cooperation between medical staffs, personal hygiene, communication related to patient, education and re-search. Posterior multiple comparison test showed that specimen collection, cooperation between medical staffs and personal hygiene were mostly done by the evening-shift nurses. Also most observations and assessments were done by the night-shift nurses. Education and communication to patients were done by day-shift nurses. Thus there were significant difference between shifts for the main nursing activities. So there should considev a reallocation of the duty of nurses on each shift. 7. The F-test also indicated that there wes a similarity in time duration for procedures and treatments and for cooperation between medical staff and nurses in all three hospitals. However, the remaining categories of nursing activities also showed a significant difference between the three hospitals. This indicated that there were differences in each emergency room that influence time for each categorized nursing activities and this should be given more consideration. Recommendations : 1. A seasonal difference should be considered in the activities of nurses in the emergency room and a comparative analysis should be carried out to deter-mine seasonal differentiation. 2. A study on more objectively measurable nursing activities should be administered as well as one determining the subjective responds towards nursing activities in the emergency room.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.101-110
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• 2012

Recently, social network sites are very popular with the enhancement of mobile device function and distribution. This gives rise to the registrations of the people on the social network sites and the usage of services on the social sites is also getting active. However, social network sites' venders do not provide services enough compared to the demand of users' to share contents from diverse roots by users effectively. In addition, the personal information can be revealed improperly in processes sharing policies and it is obvious that it raises a privacy invasion problem when users access the contents created from diverse devices according to the relationship by policies. However, the existing methods for the integration management of social network are weak to solve this problem. Thus, we propose a model to preserve user privacy, categorize contents efficiently, and give the access control permissions at the same time. In this paper, we encrypt policies and the trusted third party classifies the encrypted policies when the social network sites share the generated contents by users. In addition, the proposed model uses the RCBAC model to manage the contents generated by various devices and measures the similarity between relationships after encrypting when the user policies are shared. So, this paper can contribute to preserve user policies and contents from malicious attackers.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.981-986
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• 2020

The Internet of Things refers to a space-of-things connection network configured to allow things with built-in sensors and communication functions to interact with people and other things, regardless of the restriction of place or time.IoT is a network developed for the purpose of services for human convenience, but the scope of its use is expanding across industries such as power transmission, energy management, and factory automation. However, the communication protocol of IoT, MQTT, is a lightweight message transmission protocol based on the push technology and has a security vulnerability, and this suggests that there are risks such as personal information infringement or industrial information leakage. To solve this problem, we designed a synchronous MQTT security channel that creates a secure channel by using the characteristic that different chaotic dynamical systems are synchronized with arbitrary values in the lightweight message transmission MQTT protocol. The communication channel we designed is a method of transmitting information to the noise channel by using characteristics such as random number similarity of chaotic signals, sensitivity to initial value, and reproducibility of signals. The encryption method synchronized with the proposed key value is a method optimized for the lightweight message transmission protocol, and if applied to the MQTT of IoT, it is believed to be effective in creating a secure channel.