• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.4
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• pp.1-14
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• 2017

New business management methods different from the past are necessary because of the rapid changes of the corporates' environment. KOSDAQ(Korean Securities Dealers Automated Quotation) companies should be expected the more affirmative business performance of companies by listing, but it is a well-known that they have problems of low business performance mostly. This paper aims to investigate the influential factors on enhancing corporate innovation and nonfinantial business performance, and to clarify practical measures and present a solution of KOSDAQ companies' problems through analysis of previous researches and an empirical research. This research present corporate entrepreneurship and human resources innovation as impact factors on the business performance to apply finely the path of technological innovation for the solution of the relevance investigation limit between the complexity of corporates' innovation paths and the firms' performance. And also knowledge management activities and external networks management or the firms have been adopted as a corporate innovation activities for free from quantitative measures, such as conventional research and development(R&D) activities by considering recent corporates' knowledge business operations. The results of the empirical analysis shows that significant impact factors on corporate innovation activities are the firms' propensities of competitive advantage initiative, risk taking and chief executive officer's innovation. These can be interpreted that the CEOs' innovation propensity should be enhanced for stimulating corporate's innovaton activities, which include the CEOs' interest in the development of new technology, the exploiting new businesses and their support of the innovation discipline for employees. In addition, it can be said that it is necessary to intensify more initiatives within those enterprise for enhancing the competitive advantage in the identical industry. The significant impact factors of corporate entrepreneurship and human resource innovation on the non-financial performance are resulted as the propensities of firms' competitive advantage initiative, CEOs' innovation and employees' innovaton. This shows that the higher propensities of firms' competitive advantage initiative, CEOs' innovation and employees' innovaton, the higher the cognitive degrees of business performance within each corporate, which include the members' awareness about firms' sales growth, market share growth, profit ratio growth, customers' preference and corporates' awareness.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.39-50
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• 2014

This paper reviews the results of recent observations in the Yeonsuri valley of Mt. Youngmun during springtime (March to May) in 2012. Automated weather stations were installed at twelve sites in the valley to measure temperature and 2, 3 dimensional wind. We examined temporal and spatial characteristics of temperatures and wind data. The Yeonsuri valley springtime average temperature lapse rate between the top and bottom of the entire period is $-0.44^{\circ}C/100$ m. It can be changed by the synoptic weather conditions, the lapse rates is greatest in order of clear days ($-0.48^{\circ}C/100$ m), rainy ($-0.41^{\circ}C/100$ m) and cloudy days ($-0.40^{\circ}C/100$ m). In the night, the temperature inversion layer (thermal belt) and the cold pool are formed within the valley. In addition, we measured temperature and wind distribution from the bottom to 3.5 m, the cold layers existed up to 1.5 m, which were affected by ground mixed layer. The results will provide useful guidance on agricultural practices as well as model simulations.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.701-715
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• 2020

This study compared several reference evapotranspiration estimated using eight methods such as FAO-56 Penman-Monteith (FAO PM), Hamon, Hansen, Hargreaves-Samani, Jensen-Haise, Makkink, Priestley-Taylor, and Thornthwaite. In addition, by analyzing the monthly deviations of the results by the FAO PM and the remaining seven methods, monthly optimized correction coefficients were derived and the improvement effect was evaluated. These methods were applied to 73 automated synoptic observation system (ASOS) stations of the Korea Meteorological Administration, where the climatological data are available at least 20 years. As a result of evaluating the reference evapotranspiration by applying the default coefficients of each method, a large fluctuation happened depending on the method, and the Hansen method was relatively similar to FAO PM. However, the Hamon and Jensen-Haise methods showed more large values than other methods in summer, and the deviation from FAO PM method was also large significantly. When comparing based on the region, the comparison with FAO PM method provided that the reference evapotranspiration estimated by other methods was overestimated in most regions except for eastern coastal areas. Based on the deviation from the FAO PM method, the monthly correction coefficients were derived for each station. The monthly deviation average that ranged from -46 mm to +88 mm before correction was improved to -11 mm to +1 mm after correction, and the annual average deviation was also significantly reduced by correction from -393 mm to +354 mm (before correction) to -33 mm to +9 mm (after correction). In particular, Hamon, Hargreaves-Samani, and Thornthwaite methods using only temperature data also produced results that were not significantly different from FAO PM after correction. It can be also useful for forecasting long-term reference evapotranspiration using temperature data in climate change scenarios or predicting evapotranspiration using monthly or seasonal temperature forecasted values.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.55-72
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• 2010

Recently, the battlefield environment has changed from platform-centric warfare(PCW) which focuses on maneuvering forces into network-centric warfare(NCW) which is based on the connectivity of each asset through the warfare information system as information technology increases. In particular, C4I(Command, Control, Communication, Computer and Intelligence) system can be an important factor in achieving NCW. It is generally used to provide direction across distributed forces and status feedback from thoseforces. It can provide the important information, more quickly and in the correct format to the friendly units. And it can achieve the information superiority through SA(Situational Awareness). Most of the advanced countries have been developed and already applied these systems in military operations. Therefore, ROK forces also have been developing C4I systems such as KJCCS(Korea Joint Command Control System). And, ours are increasing the budgets in the establishment of warfare information systems. However, it is difficult to evaluate the C4I effectiveness properly by deficiency of methods. We need to develop a new combat effectiveness evaluation method that is suitable for NCW. Existing evaluation methods lay disproportionate emphasis on technical factors with leaving something to be desired in human factors. Therefore, it is necessary to consider technical and human factors to evaluate combat effectiveness. In this study, we proposed a new Combat Effectiveness evaluation algorithm called E-TechMan(A Combat Effectiveness Evaluation Algorithm Considering Technical and Human Factors in C4I System). This algorithm uses the rule of Newton's second law($F=(m{\Delta}{\upsilon})/{\Delta}t{\Rightarrow}\frac{V{\upsilon}I}{T}{\times}C$). Five factors considered in combat effectiveness evaluation are network power(M), movement velocity(v), information accuracy(I), command and control time(T) and collaboration level(C). Previous researches did not consider the value of the node and arc in evaluating the network power after the C4I system has been established. In addition, collaboration level which could be a major factor in combat effectiveness was not considered. E-TechMan algorithm is applied to JFOS-K(Joint Fire Operating System-Korea) system that can connect KJCCS of Korea armed forces with JADOCS(Joint Automated Deep Operations Coordination System) of U.S. armed forces and achieve sensor to shooter system in real time in JCS(Joint Chiefs of Staff) level. We compared the result of evaluation of Combat Effectiveness by E-TechMan with those by other algorithms(e.g., C2 Theory, Newton's second Law). We can evaluate combat effectiveness more effectively and substantially by E-TechMan algorithm. This study is meaningful because we improved the description level of reality in calculation of combat effectiveness in C4I system. Part 2 will describe the changes of war paradigm and the previous combat effectiveness evaluation methods such as C2 theory while Part 3 will explain E-TechMan algorithm specifically. Part 4 will present the application to JFOS-K and analyze the result with other algorithms. Part 5 is the conclusions provided in the final part.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.479-488
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• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

• Cartoon and Animation Studies
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• s.36
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• pp.147-165
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• 2014

Around the turn of 21st century, there has been a major technological shift in the animation industry. With development of reality-based computer graphics, major American animation studios replaced hand-drawn method with the new 3D computer graphics. Traditional animation was known for its simplified shapes such as circles and triangle that makes characters' movements distinctive from non-animated feature films. Computer-generated animation has largely replaced it, but is under continuous criticism that automated movements and reality-like graphics devaluate the aesthetics of animation. Although hand-drawn animation is still produced, 3D computer graphics have taken commercial lead and there has been many changes to acting of animated characters, which calls for detailed investigation. Firstly, the changes in acting of 3D characters can be traced from looking at human-like rigging method that mimics humanistic moving mechanism. Also, if hair and clothing was part of hand-drawn characters' acting, it has now been hidden inside mathematical simulation of 3D graphics, leaving only the body to be used in acting. Secondly, looking at "Stretch and Squash" method, which represents the distinctive movements of animation, through the lens of media, a paradox arises. Hand-drawn animation are produced frame-by-frame, and a subtle change would make animated frames shiver. This slight shivering acts as an aesthetic distinction of animated feature films, but can also require exaggerated movements to hide the shivering. On the contrary, acting of 3D animation make use of calculated movements that may seem exaggerated compared to human acting, but seem much more moderate and static compared to hand-drawn acting. Moreover, 3D computer graphics add the third dimension that allows more intuitive movements - maybe animators no longer need fine drawing skills; what they now need is directing skills to animate characters in 3D space intuitively. On the assumption that technological advancement and change of artistic expressionism are inseparable, this paper compares acting of 3D animation studio Pixar and classical drawing studio Disney to investigate character acting style and movements.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.162-173
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• 2009

Information on the expected geographical shift of suitable zones for growing crops under future climate is a starting point of adaptation planning in agriculture and is attracting much concern from policy makers as well as researchers. Few practical schemes have been developed, however, because of the difficulty in implementing the site-selection concept at an analytical level. In this study, we suggest site-selection criteria for quality Fuji apple production and integrate geospatial data and information available in public domains (e.g., digital elevation model, digital soil maps, digital climate maps, and predictive models for agroclimate and fruit quality) to implement this concept on a GIS platform. Primary criterion for selecting sites suitable for Fuji apple production includes land cover, topography, and soil texture. When the primary criterion is satisfied, climatic conditions such as the length of frost free season, freezing risk during the overwintering period, and the late frost risk in spring are tested as the secondary criterion. Finally, the third criterion checks for fruit quality such as color and shape. Land attributes related to these factors in each criterion were implemented in ArcGIS environment as relevant raster layers for spatial analysis, and retrieval procedures were automated by writing programs compatible with ArcGIS. This scheme was applied to the A1B projected climates for South Korea in the future normal years (2011-2040, 2041-2070, and 2071-2100) as well as the current climate condition observed in 1971-2000 for selecting the sites suitable for quality Fuji apple production in each period. Results showed that this scheme can figure out the geographical shift of suitable zones at landscape scales as well as the latitudinal shift of northern limit for cultivation at national or regional scales.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.