• Journal of Korean Academy of Nursing Administration
• /
• v.1 no.1
• /
• pp.97-111
• /
• 1995

In our society today, a variety of medical caring system, along with a scientific development in the area of oriental medical science plus national demand, has increased the augmentation and the opening of oriental wards and hospitals (Han Bang), which has come to create an additional requirement of nursing activity at oriental medicine wards should be different from that of the general wards or the same as the other. In view of this, various studies need to be made in this connection. The purpose of this study is to comprehend the number of nurses who want to work at oriental medicine wards and measure job satisfaction in nursing as compared with those working at general wards so as to provide basic materials for future assignment and supplementary training for the nurses. An attempt was made to contribute toward nursing administration on the one hand improving nursing training course on the other hand. A total of 72 nurses currently working at two oriental medicine hospitals available in Seoul and 82 general nurses were selected for this study using the questionaire from December 1993 to January 1994. An instrument for the study was based on the measurement of work satisfaction developed by Paula L. Stamps including 37 questions complemented by Kim for revision (1993) and 14 questions regarding general characteristics and oriental medicine wards. The instrument to test dependability showed Cronbach's=0.7711. The collected data have been processed by computer package SPSS. General characteristics of the two groups and the matters involved in oriental medicine wards were calculated into real figure and percentage an similarities between the two groups were analyzed by t-test and F-test according to the characteristics of variables. The comparative test on work satisfaction among the two groups including general characteristics and work factors were conducted by t-test and F-test. The major findings as a result of the study are as follows : 1. As general characteristics, age group of $26{\sim}30$ years are more than any segment of age. As to marital status, the number of those in single status is slightly higher than the married. Approximately 80% of them are graduates of nursing schools and nursing colleges. They are mostly in service for one to three years. There is no significant difference between the two groups. 2. The number of those who want to work at oriental medicine wards represents 40.3% against 58.4%, being in favor of general wards. 3. The reason for service at oriental medicine wards is that "there is room for potential research" which happened to rank first, followed by "easy job," "good working atmosphere" and "growing interest in oriental medicine." 4. Work satisfactions among nurses who work at oriental medicine wards prove greater than that of nurses who work at general wards. 5. Work satisfaction between the two groups by work factors is reflected with significant difference statistically on task requirement, interaction and doctor-nurse relationships. 6. The general charcateristics and the work satisfaction by work factors prove that there are significant difference in age, marital status, education and the period of work. They tend to be more satisfied with the work as they grow in age. Significant differneces are found in the work factors such as autonomy, adiministration and professional job in the relationship with doctor-nurse. As to marital status, the married are more satisfied than the unmarried. There are significant differneces in the factors respecting administration and doctor-nurse college graduates are highly satisfied with task requirement. However, satisfaction with the professional level has proven the highest degree for those having master degree. The period of work and satisfaction : There are significant differneces in task requirement, administration, interactions, professional level and doctor-nurse relationships. As a general rule, the degree of satisfactions is in proportion to the lengrh of service. The following conclusions are drawn based on the fndings mentioned above. Even though the work satisfaction of the nurse who work at oriental medicine ward is relatively high, it is desired that personal consultation be given as to disposition of nurses when they are assigned to oriental medicine wards. It is also recommended that lectures on oriental medicine be conducted through supplementary training and/or basic nursing course in order that they may be motivated for ingenious activities with an increasing sense of self-esteem which will eventually enhance positive changes for the patients who are in need of oriental medicine nursing and for the medical teams. In addition, joint reseaches involvingclinical care and education should be in constant process for unique and scientific development for those who are subject to oriental medicine nursing care.

• Journal of Distribution Science
• /
• v.9 no.4
• /
• pp.29-42
• /
• 2011

With the many advantages of the internet, online shopping has become one of the fastest growing types of retail businesses. However, internet-based firms are much more firmly required to retain existing customers rather than secure new ones, and to make them revisit the site by strengthening trust and loyalty, thereby improving profits and outrivaling competitors. Commitment is an essential part of successful long-term relationships between buyers and sellers. Although commitments by both parties in an exchange can provide the foundation for the development of relational social norms, disproportionate commitments can lead to opportunism by the less committed partner. Moreover, flow, which is characterized by intense concentration and enjoyment, was found to be significantly linked with exploratory use behavior, which in turn was linked to the extent of computer use. The level of flow was, itself, determined by the individual's sense of being in control, and the level of challenge perceived in maneuvering a website. Website attractiveness goes hand in hand with the attractiveness of an internet shopping mall, and it can be conceptualized as the persuasive effectiveness of a message by the use of familiarity, favor, similarity, etc. It occurs when information receivers try to achieve self-satisfaction when they actually or emotionally identify themselves with an information source. This study investigates the relationship between the perceived system characteristics of an internet shopping mall and the loyalty of online consumers, and it examines how perceived website attractiveness and flow play mediating roles between the perceived system characteristics of an internet shopping mall and the affective commitment in the context of a clothes internet shopping mall. For these purposes, a structural model comprising several variables was developed. That model was tested with an analysis of moment structure (AMOS) using data from respondents who had purchased clothing through the internet during the past three months. In this model, the perceived system characteristics of an internet shopping mall, such as familiarity, reputation, uniqueness, positive emotions, self-efficacy, and interactivity, were proposed to affect the website's attractiveness and flow, and lead to a higher affective commitment over time. Thus, the perceived website attractiveness and flow were proposed as core mediating variables between perceived system characteristics and affective commitment. The results of a reliability test using Cronbach's Alpha, and a confirmatory factor analysis warranted using unidimensionality for the measures for each construct. In addition, the nomological validity of the measures was warranted from the results of a correlation analysis. The results of empirical analyses indicated that systematic attributes resulting in website attractiveness and user's characteristics, thereby triggering customers' flow, play a crucial role in inducing customers' affective commitment, and a user's characteristics are twice as important as systematic attributes in this study. Moreover, familiarity, reputation, and uniqueness all have a significant effect on website attractiveness, and the research showed that uniqueness took the first place, and that familiarity and reputation followed in order of magnitude. The fact that reputation was not the most important factor that affects the attractiveness of an internet shopping mall, with uniqueness or familiarity having a greater impact, suggests much deeper implications. Finally, positive emotion, self-efficacy, and interactivity all have a significant effect on customers' flow. In particular, the fact that positive emotion, compared to self-efficacy or interactivity, has much more impact on flow is very suggestive.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.129-143
• /
• 2012

Recently, the rapid progress of a number of standardized web technologies and the proliferation of web users in the world bring an explosive increase of producing and consuming information documents on the web. In addition, most companies have produced, shared, and managed a huge number of information documents that are needed to perform their businesses. They also have discretionally raked, stored and managed a number of web documents published on the web for their business. Along with this increase of information documents that should be managed in the companies, the need of a solution to locate information documents more accurately among a huge number of information sources have increased. In order to satisfy the need of accurate search, the market size of search engine solution market is becoming increasingly expended. The most important functionality among much functionality provided by search engine is to locate accurate information documents from a huge information sources. The major metric to evaluate the accuracy of search engine is relevance that consists of two measures, precision and recall. Precision is thought of as a measure of exactness, that is, what percentage of information considered as true answer are actually such, whereas recall is a measure of completeness, that is, what percentage of true answer are retrieved as such. These two measures can be used differently according to the applied domain. If we need to exhaustively search information such as patent documents and research papers, it is better to increase the recall. On the other hand, when the amount of information is small scale, it is better to increase precision. Most of existing web search engines typically uses a keyword search method that returns web documents including keywords which correspond to search words entered by a user. This method has a virtue of locating all web documents quickly, even though many search words are inputted. However, this method has a fundamental imitation of not considering search intention of a user, thereby retrieving irrelevant results as well as relevant ones. Thus, it takes additional time and effort to set relevant ones out from all results returned by a search engine. That is, keyword search method can increase recall, while it is difficult to locate web documents which a user actually want to find because it does not provide a means of understanding the intention of a user and reflecting it to a progress of searching information. Thus, this research suggests a new method of combining ontology-based search solution with core search functionalities provided by existing search engine solutions. The method enables a search engine to provide optimal search results by inferenceing the search intention of a user. To that end, we build an ontology which contains concepts and relationships among them in a specific domain. The ontology is used to inference synonyms of a set of search keywords inputted by a user, thereby making the search intention of the user reflected into the progress of searching information more actively compared to existing search engines. Based on the proposed method we implement a prototype search system and test the system in the patent domain where we experiment on searching relevant documents associated with a patent. The experiment shows that our system increases the both recall and precision in accuracy and augments the search productivity by using improved user interface that enables a user to interact with our search system effectively. In the future research, we will study a means of validating the better performance of our prototype system by comparing other search engine solution and will extend the applied domain into other domains for searching information such as portal.

• The Journal of Korean Academy of Prosthodontics
• /
• v.47 no.2
• /
• pp.148-155
• /
• 2009

Statement of problem: The interest in all-ceramic restorations has increased as more techniques have become available. With the introduction of machinable dental ceramics and CAD/CAM systems there is a need to evaluate the quality levels of these new fabrication techniques. Purpose: This study is to evaluate the crown fidelity(absolute marginal discrepancy and internal gap) of various zirconia-based all-ceramic crowns fabricated with different CAD/CAM(computer-assisted design/computer-assisted manufacturing) systems and conventional cast metal-ceramic crowns. Material and methods: A resin tooth of lower right second premolar was prepared. After an impression was taken, one metal master die was made. Then 40 impressions of metal master dies were taken for working dies. 10 crowns per each system were fabricated using 40 working dies. Metal-ceramic crowns were cast by using the conventional method, and Procera, Lava, and Cerec inLab crowns were fabricated with their own CAD/CAM manufactruing procedures. The vertical marginal discrepancies and internal gaps of each crown groups were measured on a metal master die without a luting agent. The results were statistically analyzed using the one-way ANOVA and Tukey's HSD test. Results: 1. Vertical marginal discrepancies were $50.6{\pm}13.9{\mu}m$ for metal-ceramic crowns, $62.3{\pm}15.7{\mu}m$ for Procera crowns, $45.3{\pm}7.9{\mu}m$ for Lava crowns, and $71.2{\pm}2.0{\mu}m$ for Cerec inLab crowns. 2. The Internal gaps were $52.6{\pm}10.1{\mu}m$ for metal-ceramic crowns, $161.7{\pm}18.5{\mu}m$ for Procera crowns, $63.0{\pm}10.2{\mu}m$ for Lava crowns, and $73.7{\pm}10.7{\mu}m$ for Cerec inLab crowns. Conclusion: 1. The vertical marginal discrepancies of, 4 crown groups were all within the clinically acceptable range($120{\mu}m$). 2. The internal gaps of LAVA, Cerec inlab, and metal-ceramic crowns were within clinically acceptable range except Procera crown($140{\mu}m$).

• The Journal of Information Systems
• /
• v.27 no.1
• /
• pp.153-169
• /
• 2018

Purpose Since human brains catch images faster than texts or numbers, infographics has been widely used in business in the form of "information dashboard" to enhance the efficiency of decision-making. Groupware, however, has neglected the adoption and use of infographics, in particular, in the idea generation process. Given that an overall performance of groupware-based idea generation is no better than that of the (paper-and-pencil-based) Nominal Group Technique, Jung et al. (2010) adopted the notion of infographics in the form of performance feedback to solve the productivity paradox. With the consistent results, which demonstrate beneficial effects of infographics on performance enhancement, an interesting observation that groups with the bar chart treatment performed better than groups with the dot chart treatment was made. The main purpose of this study was to find if there were a performance consistency between the outcomes from the previous study and the outcomes from the current study. Design/methodology/approach In experiment 1, we employed the same system used in the previous study (i.e., Jung et al., 2010). As individuals' contributions accumulated, the mechanism visually displayed individuals' performances two-dimensionally in the form of a bar chart or a dot chart. Then, we compared the performance outcomes from this study to the outcomes from previous study (i.e., Jung et al., 2010). In experiment 2, we modified the performance graph to test the effect of "playfulness" on performance by converting dots to car images. Then, we compared the performance outcome from experiment 2 to the outcomes from experiment 1. Findings Just like our interesting (and unexpected) finding in Jung et al.'s study (2010), the outcome confirmed a consistent superior performance of a bar chart. This implies that a bar chart is a better choice when stimulating performance with a visual aid in the context of groupware-based idea generation. Although a bar chart was criticized in a way that errors of length-area judgments are 40 ~ 250% greater than those of positional judgments along a common scale, such illusion turned out to be facilitating upward performance comparison better. Regarding Experiment 2, the outcome showed that the revised-dot graph is as good as the bar graph in terms of quantity and quality score of ideas. We attribute the performance enhancement of the resized-dot to the interaction between the motivational characteristic and the situational characteristic of playfulness because individuals in the revised-dot graph treatment performed better than individuals in the dot graph treatment. Given the order of performance (Bar >= Revised Dot > Dot) that the revised-dot treatment performed the same as (or lower than) the bar treatment, an additional research is warranted to reach to a consistent outcome.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.7
• /
• pp.297-306
• /
• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.6
• /
• pp.672-680
• /
• 2019

This paper proposes "A Smart Farm Environment Optimization and Yield Prediction Platform based on IoT and Deep Learning" which gathers bio-sensor data from farms, diagnoses the diseases of growing crops, and predicts the year's harvest. The platform collects all the information currently available such as weather and soil microbes, optimizes the farm environment so that the crops can grow well, diagnoses the crop's diseases by using the leaves of the crops being grown on the farm, and predicts this year's harvest by using all the information on the farm. The result shows that the average accuracy of the AEOM is about 15% higher than that of the RF and about 8% higher than the GBD. Although data increases, the accuracy is reduced less than that of the RF or GBD. The linear regression shows that the slope of accuracy is -3.641E-4 for the ReLU, -4.0710E-4 for the Sigmoid, and -7.4534E-4 for the step function. Therefore, as the amount of test data increases, the ReLU is more accurate than the other two activation functions. This paper is a platform for managing the entire farm and, if introduced to actual farms, will greatly contribute to the development of smart farms in Korea.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.9
• /
• pp.37-44
• /
• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Journal of KIISE:Software and Applications
• /
• v.35 no.12
• /
• pp.780-788
• /
• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

• Journal of the Korea Computer Graphics Society
• /
• v.26 no.1
• /
• pp.17-25
• /
• 2020

We present a novel multi-core CPU based parallel algorithm for the cell-connectivity information extraction algorithm, which is one of the preprocessing steps for volume rendering of unstructured grid data. We first check the synchronization issues when parallelizing the prior serial algorithm naively. Then, we propose a 3-step parallel algorithm that achieves high parallelization efficiency by removing synchronization in each step. Also, our 3-step algorithm improves the cache utilization efficiency by increasing the spatial locality for the duplicated triangle test process, which is the core operation of building cell-connectivity information. We further improve the efficiency of our parallel algorithm by employing a memory pool for each thread. To check the benefit of our approach, we implemented our method on a system consisting of two octa-core CPUs and measured the performance. As a result, our method shows continuous performance improvement as we add threads. Also, it achieves up to 82.9 times higher performance compared with the prior serial algorithm when we use thirty-two threads (sixteen physical cores). These results demonstrate the high parallelization efficiency and high cache utilization efficiency of our method. Also, it validates the suitability of our algorithm for large-scale unstructured data.