• Information Systems Review
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• v.21 no.4
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• pp.69-97
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• 2019

Knowledge service firms are able to have higher 'Organizational Performance (OP)' by improving efficiency in management processes on customer problem solving. This study explores the role of inefficiency that has been overlooked up to now compared to the management process efficiency. We also suggest in this study 'Hierarchical Culture (HC)' and 'IT Relatedness (IR)' as the factors influencing the inefficiency of management processes, and propose the moderating effect of 'Task Difficulty (TD)' on the relationship between independent factors and 'Inefficiency of Business Process(IP)'. The results of analysis show that 'HC' has a positive effect on 'IP', and 'IR' has a negative effect on 'IP'. 'TD' was significant moderator of between independent variables and 'IP'. 'IP' was shown to play a full mediating role between independent factors and 'OP'. In conclusion, knowledge service firms are desired to reduce 'HC' and enhance 'IR' by minimizing unnecessary formal procedures, securing flexibility in decision making through appropriate empowerment, creating a smooth flow of knowledge, and enhancing the level of IT resource management and utilization. In addition, in order to effectively reduce 'IP', it is required that a company with a high degree of 'TD' to more reduce a 'HC' and a company with a low degree of 'TD' to more enhance a 'IR'.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.131-146
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• 2011

It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.

• The Korean Journal of Health Service Management
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• v.2 no.1
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• pp.105-124
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• 2008

The purpose of this research is to provide the data base for the activation of Quality Improvement operation through investigating the status of Quality Improvement operation, and finding out factors influencing on the goal-orientation of QI performers in the medical centers of more than one hundred beds where are practicing Quality Improvement operation. In order to reach the purpose, document study was carried out grounded on the proceeding researches and formulated statistical data in relation with the status of Quality Improvement performers, and proof study was carried out through questionnaire survey. The subjects of the survey were the Quality Improvement performers working in seventy three medical centers in Pusan-Gyeongnam, Daegu-Gyeongbuk, and Ulsan. Among eighty three Quality Improvement performers, fifty, five were questionnaire surveyed, on the result of which Reliability Analysis, Factor Analysis, and Multiple Regression Analysis were made, using statistical program. The the results of the proof analysis on this research are as follows. First, in the factors influencing the devoting to goal pursuit of QI performers, organization-goal contribution(0.44) had significant positive effects, while organization conflict(-0.25) had significant negative effects. In other words, the higher the organization-goal contribution was, the higher the devoting to goal pursuit was, while the less the organization conflict was, the higher the devoting to goal pursuit was, which was statistically significant.(p<0.05). Second, in the aspect of goal performance types of QI performers, the process-centered type showed high level of the devoting to goal pursuit, which was statistically significant.(p<0.05). Third, in the aspect of QI performance degree, the higher the devoting to goal pursuit was, the higher the QI performance degree was, which was statistically significant.(p<0.05). In addition, the performers who perceived their workplaces organic structure showed much higher QI performance degree, which statistically significant.(p<0.05). Generalizing the results of this research, it is possible to offer a few suggestions as follows. First, as the competition among the medical centers is more severe recently owing to medical center evaluation system, medical centers are practicing various Quality Improvement operation in all of medical services such as clinical performance and management performance, to reach the purpose of both cost-cutting and medical quality improvement. Thus in order to practice Quality Improvement operation more efficiently in medical centers, it is essential to nuke use of problem-solving methods and statistical members. This as the willingness of chief executives and positive attitude and recognition of organization members. This requires the installation of divisions in charge and disposition of persons in charge, not to speak of persistent training of Quality Improvement. Second, the divisions in charge of QI carry out Quality Improvement operation at the medical center level, and take the role of generalizing and adjusting QI performances of various departments. Owing to this role, the division in charge of QI is considered indispensable organization in the QI operation of medical centers along with medical QI committee, while it contributes to the government's goal of reducing quality level gaps among medical centers. Therefore it is necessary for government and QI organizations to give institutional support and resources for the sake of QI operation of medical centers, besides to supply systematic trainning and informations to the divisions and persons in charge of QI. Third, it is certain that disposition of persons in charge should be determined in view of the scale and the scope of QI operation in medical centers.

• 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.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of Korean Home Economics Education Association
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• v.23 no.3
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• pp.139-160
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• 2011

The purpose of this study is twofold: (i) to develop a teaching and learning plan and practical performance assessment tools for the improvement of teenager-parent communication and relationships as well as explore their effects on the communication in the everyday family life; and (ii) to find the underlying problems of teenager- parent communication through conversation analysis and to provide a improved dialogue model. We provided the experimental group with a performance task of communication training between teenagers and their parents in the real family situation while the control group practiced communication skills in a learning situation. However for both classes, before and after performance tasks were equally provided. The experimental group exhibited a longer conversation time with their parents, better communication skills, and higher degrees of relational satisfaction than the control group. Conversation analysis revealed that the experimental group reduced the use of blocking techniques in the teenager-parent conversations more than the control group, and all so raised the frequency of functional communications more than the control group. In both areas of communication in the experimental group was significantly improved, Most notably, a problem-solving case through no-lose conflict resolution methods was effective, succeeding by 70% in the e experimental group and 43.3% in the control group. Parents use blocking techniques like admonition, lecturing, blaming. sarcastic remarking, ordering and so forth, while teenagers use dispute, avoidance, blaming, and teasing in this order. The communication problems during the conversation process, teenagers' evasive and rebellious way of speaking instigates adverse communication responses from parents, so their conversation tends to unfold as ambiguous evasion opposed to: inquiring or evasion by short answers vs. ordering-preaching, or disputing vs. criticizing-making sarcastic, disputing vs. disputing-teaching, and criticizing vs. criticizing.

• Journal of the Korean Recycled Construction Resources Institute
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• v.1 no.1
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• pp.8-16
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• 2013

Currently, global warming has advanced by the usage of fossil fuels such as coal and petroleum. and the atmosphere temperature in the world of 100 years(1906~2005) has been risen $0.74^{\circ}C{\pm}0.18^{\circ}C$, IPCC announced that the global warming effect of last decade was nearly doubled compared to the changes($0.07^{\circ}C{\pm}0.02^{\circ}C$/10year) in the past 100 years. Moreover, due to the global warming, heat wave, heavy snow, heavy rain, super typhoon, were caused and are increasing to happen in the world continuously causing damages and destruction of social infrastructures, where concrete structures are suffering deterioration by long-term extreme climate changes. to solve these problems, the new construction technology and codes are necessary. In this study, to solve these problems, experiments on a variety of cases considering the temperature and humidity, the main factors of climate factors, were performed, and the cases are decided by temperature and humidity. The specimens were tested in compressive strength test and split tensile test by the curing age(3,7,28 days) morever, performance based design(PBD) method was applied by using the satisfaction curve developed from the experiment date. PBD is the design method that gathers the current experimental analysis and past experimental analysis and develops the material properties required for the structure, and carries out the design of concrete mix, and it is recently studied actively worldwide. Also, it is the ultimate goal of PBD to design and perform on structures have sufficient performance during usage and to provide the problem solving for various situations, Also, it can achieve maximum effect in terms of functionality and economy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.646-680
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• 2000

In this paper, we discuss the design and implementation of a concurrency control manager for a main memory DBMS(MMDBMS). Since an MMDBMS, unlike a disk-based DBMS, performs all of data update or retrieval operations by accessing main memory only, the portion of the cost for concurrency control in the total cost for a data update or retrieval is fairly high. Thus, the development of an efficient concurrency control manager highly accelerates the performance of the entire system. Our concurrency control manager employs the 2-phase locking protocol, and has the following characteristics. First, it adapts the partition, an allocation unit of main memory, as a locking granule, and thus, effectively adjusts the trade-off between the system concurrency and locking cost through the analysis of applications. Second, it enjoys low locking costs by maintaining the lock information directly in the partition itself. Third, it provides the latch as a mechanism for physical consistency of system data. Our latch supports both of the shared and exclusive modes, and maximizes the CPU utilization by combining the Bakery algorithm and Unix semaphore facility. Fourth, for solving the deadlock problem, it periodically examines whether a system is in a deadlock state using lock waiting information. In addition, we discuss various issues arising in development such as mutual exclusion of a transaction table, mutual exclusion of indexes and system catalogs, and realtime application supports.

• Journal of the Korean GEO-environmental Society
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• v.13 no.11
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• pp.61-68
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• 2012

Most widely methods for reinforcement of soil utilized in Korea are anchor method, soil nail method and micro pile method. These methods are classified by the intended use of the structure to be constructed, but the reinforcement of the ground is accomplished contains in common the process of grouting work after inserting the reinforcements. Domestically, gravity grouting has been used mostly so far, but there has always been the risk of insufficient restoration of the loose ground area from the drill holes because the grouting is conducted only by gravity. On the other hand, pressure reinjection grouting may enhance the grouting quality by solving the problem of the existing grouting method considerably since it additionally reinjects grouting through pre-installed tube a certain time after the first grouting. Accordingly, this study evaluated the pullout characteristics by the grouting methods by performing model test on decomposed granite soil, and investigated the support increasing characteristics of reinforcements depending on the curing time, reinjection pressure, and uplift force variation of the pressure reinjection grouting. The result of this research shows that the pressure reinjection grouting demonstrated 1.1~1.3 times of performance of the gravity grouting, and suggests some analysis on optimal water content, reinjection pressure and curing time of the pressure reinjection grouting.

• Journal of Korean Academy of Nursing
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• v.29 no.2
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• pp.314-327
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• 1999

In this study, domains, contents, and effects of pre-existed intervention programs for individuals with arthritis were meta-analyzed to develop arthritis health promotion program based on Holistic Model. The developed program includes strategies of cognition, environment, and behavior. and also generates positive changes in the physical, psychological, and social demensions. Then needs assessment on conveniently selected 153 women who visited a university hospital in Seoul or in Inchon are conducted to identify the objective domains of arthritis health promotion program According to the study results. target health problems of the arthritis health promotion program were shown as pain, disability, depression, and role impediment in social domain. These objectives could be achieved by including the strategies of changing cognition, the strategies of changing behavior through learning the skill related to the health promoting behavior. and the strategies of changing environment in the health promotion program. That is, it is analyzed that the contents of program are not exclusive one another in physical. psychological. and social demensions, and also are not exclusive one another in aspect of cognition, behavior, and environment. The necessary methods to achieve the desired objectives for the developed arthritis health promotion program and evaluation subjects are as follows : (1) In the arthritis health promotion program, knowledge on management of arthritis, efficacy related to arthritis management, skill for pain management, skill for exercise, establishment of positive self-concept, enhancement of positive thinking, stress management. skill for problem solving, skill for setting goals. skill for requesting help, and skill for communication are all included. Through the improvement of all those strategies, intermediate objectives, such as “joint protection, and maintenance of pain management behavior”, “maintenance of regular exercise”, and “promotion of coping skill in psychosocial dimension” are achieved. (2) These intermediate objectives are also the methods for achieving objectives in next stage. It implies that through the intermediate objectives. the final objectives such as “minimization of physical symptoms and signs”, “maximization of psychological function”, and “maximazation of role performance in social domain” could be achieved. Each of these final objectives reflects the different dimension of quality of life, respectively. When these objectives are achieved, the quality of life that client perceives is improved. Therefore, through evaluation of these final objectives, the level of achieving final outcome of arthritis health promotion such as quality of life is determined.