• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.51-56
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• 2009

Purpose: Recently, most hospitals are introducing the PACS system and use of the system continues to expand. But small-scaled PACS called MicroPACS has already been in use through open source programs. The aim of this study is to prove utility of operating a MicroPACS, as a substitute back-up device for conventional storage media like CDs and DVDs, in addition to the full-PACS already in use. This study contains the way of setting up a MicroPACS with open source programs and assessment of its storage capability, stability, compatibility and performance of operations such as "retrieve", "query". Materials and Methods: 1. To start with, we searched open source software to correspond with the following standards to establish MicroPACS, (1) It must be available in Windows Operating System. (2) It must be free ware. (3) It must be compatible with PET/CT scanner. (4) It must be easy to use. (5) It must not be limited of storage capacity. (6) It must have DICOM supporting. 2. (1) To evaluate availability of data storage, we compared the time spent to back up data in the open source software with the optical discs (CDs and DVD-RAMs), and we also compared the time needed to retrieve data with the system and with optical discs respectively. (2) To estimate work efficiency, we measured the time spent to find data in CDs, DVD-RAMs and MicroPACS. 7 technologists participated in this study. 3. In order to evaluate stability of the software, we examined whether there is a data loss during the system is maintained for a year. Comparison object; How many errors occurred in randomly selected data of 500 CDs. Result: 1. We chose the Conquest DICOM Server among 11 open source software used MySQL as a database management system. 2. (1) Comparison of back up and retrieval time (min) showed the result of the following: DVD-RAM (5.13,2.26)/Conquest DICOM Server (1.49,1.19) by GE DSTE (p<0.001), CD (6.12,3.61)/Conquest (0.82,2.23) by GE DLS (p<0.001), CD (5.88,3.25)/Conquest (1.05,2.06) by SIEMENS. (2) The wasted time (sec) to find some data is as follows: CD ($156{\pm}46$), DVD-RAM ($115{\pm}21$) and Conquest DICOM Server ($13{\pm}6$). 3. There was no data loss (0%) for a year and it was stored 12741 PET/CT studies in 1.81 TB memory. In case of CDs, On the other hand, 14 errors among 500 CDs (2.8%) is generated. Conclusions: We found that MicroPACS could be set up with the open source software and its performance was excellent. The system built with open source proved more efficient and more robust than back-up process using CDs or DVD-RAMs. We believe that the operation of the MicroPACS would be effective data storage device as long as its operators develop and systematize it.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Life Science
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• v.20 no.4
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• pp.549-554
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• 2010

Increased external rotation and decreased internal rotation have been noted to occur progressively in the throwing shoulders of baseball pitchers. The purpose of this study was to provide descriptive data for terminal range eccentric antagonist/concentric agonist shoulder muscle strength in collegiate baseball pitchers with humeral head retroversion diagnosed through MRI. The dominant and non-dominant shoulders of 9 asymptomatic baseball pitchers were tested through a range of 20 degrees of external rotation to 90 degrees of internal rotation using the Biodex system 3 isokinetic dynamometer at speeds of $90^{\circ}/s$ and $180^{\circ}/s$. Differences between the dominant and non-dominant shoulders were assessed using the paired samples t-test. Total range of motion, measured at $90^{\circ}$ of glenohumeral abduction, was $180.1^{\circ}$ for dominant shoulders and $183.7^{\circ}$ for non-dominant shoulders. Humeral head retroversion measured $47.6{\pm}6.1^{\circ}$ in dominant and $37.8{\pm}5.3^{\circ}$ in non-dominant extremities. The mean internal rotator concentric contraction (IR-Con) showed a significant difference compared to $31.5{\pm}5.1$ (Nm) in dominant and $38.7{\pm}5.2$ (Nm) in non-dominant shoulders at $180^{\circ}/s$ (p<0.05). The mean external rotator eccentric contraction (ER-Ecc) showed a significant difference compared to $20.3{\pm}4.7$ (Nm) in dominant and $25.1{\pm}3.7$ (Nm) in non-dominant shoulders at $90^{\circ}/s$ (p<0.05). There is a pattern of increased external rotation and decreased internal rotation in the dominant extremity that significantly correlates with an increase in humeral retroversion.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.41-61
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• 2020

China's rapid development and commercialization of high-tech technologies in the fourth industrial revolution has led to effective technology exchanges between Korean and Chinese firms becoming more important to Korea's mid-term and long-term industrial development. However, there is still a lack of empirical research on how technology exchanges between Korean and Chinese firms proceed and their effectiveness. In response, this study conducted a social network analysis based on text mining data of Korea-China business technology exchange and cooperation articles introduced in the news from 2018 to March 2020 on the current status and effects of Korea-China technology exchanges related to the fourth industrial revolution, and conducted a regression analysis how network centrality effect on the firm performance. According to the results, most of the Korean major electronic firms are actively networking with Chinese firms and institutions, showing high centrality in the centrality index. Korean telecommunication firms showed high betweenness centrality and subgraph centrality, and Korean Internet service providers and broadcasting contents firms showed high eigenvector centrality. In addition, Chinese firms showed higher betweenness centrality than Korean firms, and Chinese service firms showed higher closeness centrality than manufacturing firms. As a result of regression analysis, this network centrality had a positive effect on firm performance. To the best of our knowledge, this is the first to analyze the impact of the technical cooperation between Korean and Chinese firms under the fourth industrial revolution context. This study has theoretical implications that suggested the direction of social network analysis-based empirical research in global firm cooperation. Also, this study has practical implications that the guidelines for network analysis in setting the direction of technical cooperation between Korea and China by firms or governments.

• Journal of the Korean earth science society
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• v.37 no.4
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• pp.218-229
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• 2016

The bedform stability diagram indicates the shape and size of bedforms that will occur to a given grain size and flow velocity. The diagram has been constructed from experimental data which have been mostly acquired by flume experiments. Generally, the flume experiments have been performed on well sorted sediments with unimodal grain size distribution, in order to understand relationship between grain size and flow velocity. According to the diagram, a ripple structure initiates to be formed from lower flow regime flat bed, as the flow velocity increases on the surface of fine-sand or medium-sand sediments. This study aims to verify that the experimental result of bedform stability diagram will be reproduced in our flume experimental systems, and also to confirm that the result is consistent not only on well-sorted sand sediments but also on poorly-sorted sand sediments with bimodal grain size distribution. The experimental results in this study show that initiation of 2D or 3D ripple structure on poorly-sorted sand sediments requires higher flow velocity and shear stress than those for initiation of the structure on well-sorted sand sediments. In general, carbonate sediments are characterized by poor sorting due to inactive hydraulic sorting and bimodal grain size distribution with allochems and matrices. The results suggest that the carbonate depositional system possibly need a higher flow velocity for initial formation of 2D or 3D bedform structures. The reason might be the fact that pulling off and lifting of a grain in poorly sorted sediments require more energy due to sorting, friction, stabilization, armour effects, and their complex interaction. This preliminary study warrants additional experiments under various conditions and more accurate analysis on the relationship between formation of bedforms and grain size distribution.

• Journal of Bio-Environment Control
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• v.18 no.4
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• pp.309-315
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• 2009

Maintenance of adequate soil water content during the period of crop growth is necessary to support optimum plant growth and yields. A better understanding of soil water movement for precision irrigation would allow efficient supply of water to crops, thereby resulting in minimization of water drainage and contamination of ground water. This research reports on the characterization of spatial and temporal variations in water contents through three different textured soils, such as loam, sandy loam, and loamy sand, when water is applied on the soil surface using an one-line drip irrigation system and the soils are dried after the irrigation stops, respectively. Water contents through each soil profile were continuously monitored using three Sentek probes, each consisting of three capacitance sensors at 10, 20, and 30cm depths. Spatial variability in water content for each soil type was strongly influenced by soil textural class. There were big differences in wetting pattern and the rate of downward movement between loam and sandy loam soils, showing that the loam soil had a wider wetting pattern and a slower rate of downward movement than did the sandy loam soil. The wetting pattern in loamy sand soil was not apparent due to a low variability in water content (< 10%) by a lower-water holding capacity as compared to those measured in the loam and sandy loam soils, implying that the rate of water drainage below a depth of 30cm was high. When soils were dried, there were highly exponential relationships between water content and time elapsed after irrigation stops ($r^2$${\geq}$0.98). It was estimated that equilibrium moisture contents for loam, sandy loam, and loamy sand soils would be 17.6%, 6.2%, and 4.2%, respectively.

• Archives of design research
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• v.20 no.3 s.71
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• pp.61-72
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• 2007

Having started with "Space War", the first game produced by MIT in the 1960's, the gaming industry expanded rapidly and grew to a large size over a short period of time: the brand new games being launched on the market are found to contain many different elements making up a single content in that it is often called the 'the most comprehensive ultimate fruits' of the design technologies. This also translates into a large increase in the number of things which need to be considered in developing games, complicating the plans on the financial budget, the work force, and the time to be committed. Therefore, an approach for analyzing the elements which make up a game, computing the importance of each of them, and assessing those games to be developed in the future, is the key to a successful development of games. Many decision-making activities are often required under such a planning process. The decision-making task involves many difficulties which are outlined as follows: the multi-factor problem; the uncertainty problem impeding the elements from being "quantified" the complex multi-purpose problem for which the outcome aims confusion among decision-makers and the problem with determining the priority order of multi-stages leading to the decision-making process. In this study we plan to suggest AHP (Analytic Hierarchy Process) so that these problems can be worked out comprehensively, and logical and rational alternative plan can be proposed through the quantification of the "uncertain" data. The analysis was conducted by taking FPS (First Person Shooting) which is currently dominating the gaming industry, as subjects for this study. The most important consideration in conducting AHP analysis is to accurately group the elements of the subjects to be analyzed objectively, and arrange them hierarchically, and to analyze the importance through pair-wise comparison between the elements. The study is composed of 2 parts of analyzing these elements and computing the importance between them, and choosing an alternative plan. Among these this paper is particularly focused on the Delphi technique-based objective element analyzing and hierarchy of the FPS games.

• Journal of Life Science
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• v.14 no.3
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• pp.484-489
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• 2004

Artificial joint replacement is one of the major surgical advances of the 21th century. The primary purpose of a TKA (Total Knee Arthroplasty) is to restore normal knee Auction. Therefore, ideally, a TKA should: (a) maintain the natural leverage of the knee joint muscles to ensure generating adequate knee muscle moments to accomplish daily tasks such as rising from a chair or climbing stairs;(b) allow the same range of motion as an complete knee; and (c) provide adequate knee joint stability. Four individuals (2 peoples after surgery one year and 2 peoples after surgery three years) participated in this study. All they were prescreened for health and functional status by the same surgeon who performed the operations. Two days of accommodation practice occurred prior to the actual strength testing. The isometric strength (KIN-COM III) of the quadriceps and hamstring were measured at 60$^\circ$ and 30$^\circ$ of knee flexion, respectively. During isokinetic concentric testing, the range of motion was between 10$^\circ$ to 80$^\circ$ of knee flexion (stand-to-sit) and extension (sit-to-stand). for a given test, the trial exhibiting maximum torque was analyzed. A 16-channel MYOPACTM EMG system (Run Technologies, Inc.) was used to collect the differential input surface electromyographic (EMG) signals of the vastus medialis (VM), vastus lateralis(VL), rectus femoris (RF) during sit-to-stand and stand-to-sit tests. Disposable electrodes (Blue SensorTM, Medicotest, Inc.) were used to collect the EMG signals. The results were as follows; 1. Less maximum concentric (16% and 21% less for 1 yew man and 3 years mm, respectively) and isometric (12% and 29%, respectively) quadriceps torque for both participants. 2.14% less maximum hamstrings concentric torque for 1 year man but 16% greater torque for 3 years mm. However, 1 year man had similar hamstring isometric peak torque for both knees. 3. Less quadriceps co-contraction by 1 year man except for the VM at 10$^\circ$-20$^\circ$ and 30$^\circ$-50$^\circ$ range of knee flexion.

• Journal of Venture Innovation
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• v.1 no.1
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• pp.1-14
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• 2018

The 4th Industrial Revolution is making a big change for our company like the tsunami. The CPS system, which is represented by the digital age, is based on the data accumulated in the physical domain and is making business that was not imagined in the past through digital technology. As a result, the business model of the 4th Industrial Revolution era is different from the previous one. In this study, we analyze the trends and the issues of business innovation theory research. Then, the business innovation model of the digital age was compared with the previous period. Based on this, we have searched for a business model suitable for the 4th Industrial Revolution era. The existing business models have many difficulties to explain the model of the digital era. Even though more empirical research should be supported, Michael Porter's diamond model is most suitable for four cases of business models by applying them. Type A sharing outcome with customer is a model that pay differently according to the basis of customer performance. Type B Value Chain Digitalization model provides products and services to customers with faster and lower cost by digitalizing products, services and SCM. Type C Digital Platform is the model that brings the biggest ripple effect. It is a model that can secure profitability by creating new market by creating the sharing economy based on digital platform. Finally, Type D Sharing Resources is a model for building a competitive advantage model by collaborating with partners in related industries. This is the most effective way to complement each other's core competencies and their core competencies. Even though numerous Unicorn companies have differentiated digital competitiveness with many digital technologies in their respective industries in the 4th Industrial Revolution era, there is a limit to the number of pieces to be listed. In future research, it is necessary to identify the business model of the digital age through more specific empirical analysis. In addition, since digital business models may be different in each industry, it is also necessary to conduct comparative analysis between industries