• 대한공업교육학회지
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• v.40 no.1
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• pp.142-162
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• 2015

The purpose of this study are to provide the basic data materials and implementations for successful performance of electric-work field representatives of South Korean firms by identifying their roles and competency and examining their educational need. For this research purposes, three phased analysis was followed on: (1) the roles of electric-work field representatives, (2) competency of electric-work field representatives and (3) educational need for their competency. This research method was to conduct a focus group interview for 10 expert field representatives along with survey. The collected data materials were processed by MS Excel and SPSS 21.0 for statistical analysis including average, standard deviation and other basic statistics; the gap in awareness of field representatives; and need values. For the needs analysis, the difference between significance of field representatives' competency and current status was examined by t test. And the awareness gap between competency importance and current status was identified based on the Borich equation. The Locus for Focus model was employed herein to identify the kinds of competency with high importance and high inconsistency to prioritize. As a result, this research has found as follows: first, the roles of field representatives were found to be in 13 different kinds of roles. Second, electric-work field representatives were found to need to have 16 different skills. Third, regarding the 16 abilities, the gap between current status and significance was analyzed herein. The results showed statistically significant differences in all cases. The Borich needs analysis found the first required ability was communication ability followed by power of execution, conflict management ability, analytical thinking and time management ability. Also, the results of Locus for Focus model analysis displayed that the first quadrant(HH) included 7 highly-demanded abilities of communication ability, analytical thinking, decision making ability, specialty, time management ability, power of execution and drive for work implementation. The top-priority group was found to have 5 items of communication ability, analytical thinking, time management ability, power of execution and drive for work implementation which were commonly seen in the Locus for Focus model outcomes. Based on these findings, this research could identify the roles and competency of electric-work field representatives and provide the basic data materials applicable to future personal management of electricity companies including recruitment, division of work, job description, evaluation, etc. Also this research offered guidelines on demanded abilities in the field and where to place priority. The kinds of abilities with high educational demand as found in this research must be considered in designing educational programs for the competency building of field representatives. This research is expected to provide useful information in developing such educational programs for field representatives.

• Journal of Nutrition and Health
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• v.53 no.2
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• pp.121-128
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• 2020

Purpose: The Rubus coreanus fruit (RF) is an important traditional medicinal herb having antioxidant, anti-inflammatory, and immunoregulatory properties. These activities are known to change dramatically, depending on maturity of the RF. It is presumed that change of functional components, such as flavonoids, tannins, phenolic acids, triterpenoids and organic acids in RF, affect the various bioactivities. This study aimed to confirm changes in the anti-melanogenic effects of RF based on maturity, and to identify the bioactive compounds responsible. Methods: The cell viability of mature RF (MRF) and immature RF (IRF) extracts was investigated using B16F10 cells. To compare the anti-melanogenic effect of MRF and IRF extracts, we first assessed the melanin content. High-performance liquid chromatography analysis was performed to evaluate changes in the level of ellagic acid according to maturity of the RF. In addition, tyrosinase inhibitory activity of both extracts was examined. Results: MRF and IRF extracts (50-200 ㎍/mL) do not affect the cell viability of B16F10 melanoma cells. IRF extract more effectively inhibited melanin synthesis than MRF extract. The content of ellagic acid in IRF extract was higher than that obtained in MRF extract. Furthermore, greater inhibition of tyrosinase activity was observed after exposure to IRF extract than MRF extract. A positive correlation was determined between ellagic acid content and tyrosinase inhibitory activity, and a negative correlation was obtained between ellagic acid content and melanin content. Taken together, our results indicate that ellagic acid is one of the major bioactive compounds of RF that imparts a whitening effect. Conclusion: Our results indicate that ellagic acid in MRF and IRF extracts affect the anti-melanogenesis effect through inhibition of tyrosinase activity. Therefore, the ellagic acid rich IRF has greater potential for application as a natural and functional cosmetic material.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.315-328
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• 2017

Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little domestic research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests, which are most widely used type of assessment in current Korean educational setting. Multiple-choice tests, in which options are presented with the questions, are efficient in that grading can be automated; however, they allow for students who don't know the answer, to find the correct answer from the options. Park(2005) has developed a modified multiple-choice testing system (CMMT) using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. The present study was conducted to find out if penalizing wrong answers could lower the possibility of students choosing an answer among the options when they don't know the correct answer. 116 students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: 2 conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. The results were analyzed using a two-way ANOVA for the number of no response, the test score and self-report score. Analysis showed that the number of no response was significantly higher for the CMMT format and that test scores were significantly lower when the penalizing percentage was high. The possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed. In addition, the need for further research in the cognitive sciences to develop computerized assessment tools, was discussed.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.3
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• pp.14-26
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• 2018

The Biotope Area Ratio (BAR) is a quantitative pre-planning index for sustainable development and an integrated indicator for the balanced development of buildings and outdoor spaces. However, it has been pointed out that there are problems in operations management: errors in area calculation, insufficiency in the underground soil condition and depth, reduction in biotope area after construction, and functional failure as a pre-planning index. To address these problems, this study proposes implementing LIM. Since the weights of the BAR are mainly decided by the underground soil condition and depth with land cover types, the study focused on the terrain and pavements. The model should conform to BIM guidelines and standards provided by government agencies and professional organizations. Thus, the scope and Level Of Detail (LOD) of the model were defined, and the method to build a model with BIM software was developed. An apartment complex on sloping ground was selected as a case study, a 3D terrain modeled, paving libraries created with property information on the BAR, and a LIM model completed for the site. Then the BAR was calculated and construction documents were created with the BAR table and pavement details. As results of the study, it was found that the application of the criteria on the BAR and calculation became accurate, and the efficiency of design tasks was improved by LIM. It also enabled the performance of evidence-based design on the terrain and underground structures. To adopt LIM, it is necessary to create and distribute LIM library manuals or templates, and build library content that comply with KBIMS standards. The government policy must also have practitioners submit BIM models in the certification system. Since it is expected that the criteria on planting types in the BAR will be expanded, further research is needed to build and utilize the information model for planting materials.

• Strategy21
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• s.32
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• pp.123-159
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• 2013

The purpose of this research paper is to re-valuate the factors that affected the Royal Navy's rearmament and preparation for war by conducting analysis on the discussion held in the Britain on the strategic priorities and Navy's coping measures adopted during the interwar period. After the end of the WWI, each of the military arms of the Britain faced significant difficulty in securing budget and increasing their military power all throughout the interwar period, and the Navy was not an exception. The WWII that got started on September 1939 was the turning point in which this difficulty led to full-fledged crisis. Immensely many criticisms followed after the war and problems were identified when it comes to the Royal Navy's performance during the war. This type of effort to identify problem led to the attempt to analyze whether Royal Navy's preparation for war and rearmament policy during interwar period were adequate, and to identify the root causes of failure. Existing studies sought to find the root cause of failed rearmament from external factors such as the deterioration of the Britain itself or pressure from the Treasury Department to cut the budget for national defense, or sought to detect problems from the development of wrong strategies by the Navy. However, Royal Navy's failed preparation for the war during interwar period is not the result of one or two separate factors. Instead, it resulted due to the diverse factors and situations that the Britain was facing at the time, and due to intricate and complex interaction of these factors. Meanwhile, this research paper focused on the context characterized by 'strategic selection and setting up of priorities' among the various factors to conduct analysis on the Navy's rearmament by linking it with the discussion held at the time on setting up strategic priorities, and sought to demonstrate that the Navy Department's inadequate counter-measures developed during this process waned Royal Navy's position. After the end of WWI, each of the military arms continued to compete for the limited resources and budget all throughout the interwar period, and this type of competition amidst the situation in which the economic situation of Britain was still unstable, made prioritization when it comes to the allocation of resources and setting up of the priorities when it comes to the military power build-up, inevitable. Amidst this situation, the RAF was able to secure resources first and foremost, encouraged by the conviction of some politicians who were affected by the 'theory of aerial threat' and who believed that curtailing potential attack with the Air Force would be means to secure national security at comparatively lower cost. In response, Navy successfully defended the need for the existence of Navy despite the advancement of the aerial power, by emphasizing that the Britain's livelihood depends on trade and on the maintenance of maritime traffic. Despite this counter-measuring logic, however, Navy's role was still limited to the defense of overseas territory and to the fleet run-off instead of sea traffic route production when it comes to the specific power build-up plan, and did not understand the situation in which financial and economic factors gained greater importance when it comes to the setting up of strategic priorities. As a result, Navy's plan to build its powers was met with continual resistance of the Treasury Department, and lost the opportunity to re-gain the status of 'senior service' that it had enjoyed in the past during the competition for strategic prioritization. Given that the strategic and economic situation that Korea faces today is not very different from that of the Britain during the interwar period, our Navy too should leverage the lessons learned from the Royal Navy to make the effort to secure viable position when it comes to the setting of priorities in case of national defense strategy by presenting the basis on why maritime coping should be prioritized among the numerous other threats, and by developing the measures for securing the powers needed effectively amidst the limited resources.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Resources Recycling
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• v.15 no.3 s.71
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• pp.38-45
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• 2006

The thermal filter press dewatering(TFPD) technology to improve the dewaterability through increasing the inner vapor pressure, lowering the filtration viscosity and forming the porosity easily within cake as applying the heat at the sludge layer was developed in this study. The hot water with temperature of $95^{\circ}C$ and pressure of $1.2kg_f/cm^2$ was supplied to the heating plate equipped between filter plates with plate size of $470{\times}470mm$ and material of polypropylene. Sludge was dewaterd by supplying pressure of $5kg_f/cm^2$ and then by squeezing pressure of $15kg_f/cm^2$. As a results of estimating the characteristics of thermal dewatering to consider the initial water content and organic content to be influenced by a period of water shortage and rainwater, the dewatered cake water content was about 35 wt% and dewatering velocity was $4DSkg/m^2{\cdot}hr$ under the rainwater period, and the dewatered cake water content was about 50 wt% and dewatering velocity was $1.5DSkg/m^2{\cdot}hr$ in the case of sludge of water shortage season. These results was superior to the mechanical dewatering performance with water content of 70wt% and dewatering velocity of $0.9DSkg/m^2{\cdot}hr$. On the base of the results of TFPD, energy consumpted to deal with DS(Dry Solid) of 1kg was estimated by 300 kJ. It was analyzed that the energy consumption of TFPD was decreased about one third with comparison to the dryer system. Dewatering velocity of this technology was faster than the one of mechanical dewatering equipment and it was easier to product low water content cake. Therefore, this technology was recognized that dewaterability was predominant because of the fast of dewatering velocity and production of low water content cake, and also this known as economical efficiency was excellent because of low energy consumption in comparison with dryer.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.166-177
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• 2006

The cache size tends to grow in the embedded processor as technology scales to smaller transistors and lower supply voltages. However, larger cache size demands more energy. Accordingly, the ratio of the cache energy consumption to the total processor energy is growing. Many cache energy schemes have been proposed for reducing the cache energy consumption. However, these previous schemes are concerned with one side for reducing the cache energy consumption, dynamic cache energy only, or static cache energy only. In this paper, we propose a hybrid scheme for reducing dynamic and static cache energy, simultaneously. for this hybrid scheme, we adopt two existing techniques to reduce static cache energy consumption, drowsy cache technique, and to reduce dynamic cache energy consumption, way-prediction technique. Additionally, we propose a early wake-up technique based on program counter to reduce penalty caused by applying drowsy cache technique. We focus on level 1 data cache. The hybrid scheme can reduce static and dynamic cache energy consumption simultaneously, furthermore our early wake-up scheme can reduce extra program execution cycles caused by applying the hybrid scheme.