• International Commerce and Information Review
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• v.16 no.5
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• pp.151-178
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• 2014

The objective of the present case study is to analysis how effectively Hilti, which is a former family firm owned and managed by a family in Liechtenstein as a tiny european country, a land sandwiched between Switzerland and Austria, has made a global market success. Liechtenstein has $160km^2$ land and about 36,000 residents. Despite its small size of country, however, Hilti Corporation doesn't view its location as a liability in its business strategy. Hilti is a global leading provider of professional power tools in building, mining, civil engineering etc. Also, Hilti is a firm with a clear vision to become the leading industry partner for construction professionals and building installations through customer focus, high quality equipment, and tools and systems specially designed for specific jobs. This study considered Hilti as a good case, which verifies that born-conditions, endogenous factors according to Michael Porters diamond model does not decisive role more for international competitiveness of firms. Lessons from Hilti are that in order to obtain and sustain the global competitiveness of small and medium-sized firms in Korean manufacturing sector under high production cost, they have to do actively innovative. Also they can give to customers newer and higher customer-values than competitors in abroad give. The case summarizes that the strategy of Hilti for the global market success is comprised of several factors: Technological and organizational innovation, and a clear customer-value oriented business strategy and its implementation. Innovation and its integration into marketing for the customers value creation is central to Hilti's Success. The present case study is expected to provide insights and implication for many firms in Korea that are seeking to secure global presence and market success.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.12
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• pp.723-732
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• 2017

As the development of ICT technology, in order to solve the problem of scattered water information's availability, WINS(Water management Information Networking System) by the Ministry of Land, Infrastructure and Transport was established and has been operated since 2004. However, there has been a disadvantage of providing specialized and limited information to the water resources sector mainly and a lack of active sharing of information because of no compulsory provision of information sharing between participants. In order to solve these problems, this paper carried out system development study, to do this, the status of domestic water information was surveyed and domestic and overseas related systems were compared and analyzed. The latest ICT technology was used to realize the contents as screen, and the user interface definition was created to present a role model of integrated water management through maximizing visualization by combining GIS and realtime data and providing space-time integrated information. These prior studies reached to actual construction of the ICT-based integrated management system for water information by K-water. This system is in service to the public installed in the water information portal, "MyWater".

• Journal of the Society of Disaster Information
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• v.15 no.2
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• pp.223-238
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• 2019

Purpose: This study aims at exploring implications of discourse and social practice produced by various stakeholders in politics, economy and society to provide useful material for effective disaster response in South Korea. Method: Applying the Critical Discourse Analysis model of Fairclough, this study analyzes the newspaper articles of three domestic press companies mainly about the November 2017 Pohang earthquake. Results: As a result, first, the three media companies point out the low effectiveness of disaster response manuals and evacuation training. Second, strengthening shelter services and expanding support for the victims are important for recovery from the earthquake. Third, to prevent the future damages, they suggest the implementation efforts to improve the seismic design and short message service based disaster alert system. Conclusion: Based on the findings, this study suggests to improve the practicality and effectiveness of disaster prevention measures, establish an organic and integrated disaster response system, emphasize the roles and participation of citizens, check the responsibility of experts, and make the media to form sound discourse on disaster response.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.5 s.45
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• pp.41-52
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• 2005

Using the variable control gain scheme on the basis of fuzzy-based decision-making process, Fuzzy supervisory control (FSC) technique exhibits better control performance than linear control technique with one static control gain. This paper demonstrates the effectiveness of the FSC technique by evaluating the robust performance of the FSC technique under the presence of uncertainties in the models and the excitations. Robust performance of the FSC system is compared with that of optimally designed LQG control system for the benchmark cable-stayed bridge presented by Dyke et al. Parameter studies on the robust performance evaluation are carried out by varying the stiffness of the bridge model as well as the magnitudes of several earthquakes with different frequency contents. From the comparative study of two control systems, FSC system shows the enhanced control performance against various magnitudes of several earthquakes while maintaining lower level of power required for controlling the bridge response. Especially, FSC system clearly guarantees the improved robust performance of the control system with stable reduction effects on the seismic responses and slight increases in total power and stroke for the control system, while LQG control system exhibits poor robust performance.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2292-2314
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• 2006

Efficient numerical method is developed for the prediction of aerodynamic noise generation and propagation in low Mach number flows such as aeolian tone noise. The proposed numerical method is based on acoustic/viscous splitting techniques of which acoustic solvers use simplified linearised Euler equations, full linearised Euler equations and nonlinear perturbation equations as acoustic governing equations. All of acoustic equations are forced with immersed surface dipole model which is developed for the efficient computation of aerodynamic noise generation and propagation in low Mach number flows in which dipole source, originating from unsteady pressure fluctuation on a solid surface, is known to be more efficient than quadrupole sources. Multi-scale overset grid technique is also utilized to resolve the complex geometries. Initially, aeolian tone from single cylinder is considered to examine the effects that the immersed surface dipole models combined with the different acoustic governing equations have on the overall accuracy of the method. Then, the current numerical method is applied to the simulation of the aeolian tones from twin cylinders aligned perpendicularly to the mean flow and separated 3 diameters between their centers. In this configuration, symmetric vortices are shed from twin cylinders, which leads to the anti-phase of the lift dipoles and the in-phase of the drag dipoles. Due to these phase differences, the directivity of the fluctuating pressure from the lift dipoles shows the comparable magnitude with that from the drag dipoles at 10 diameters apart from the origin. However, the directivity at 100 diameters shows that the lift-dipole originated noise has larger magnitude than, but still comparable to, that of the drag-dipole one. Comparison of the numerical results with and without mean flow effects on the acoustic wave emphasizes the effects of the sheared background flows around the cylinders on the propagating acoustic waves, which is not generally considered by the classic acoustic analogy methods. Through the comparison of the results using the immersed surface dipole models with those using point sources, it is demonstrated that the current methods can allow for the complex interactions between the acoustic wave and the solid wall and the effects of the mean flow on the acoustic waves.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.95-102
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• 2007

This paper presents the core technology of Construction Business Process Automation to model and automate construction business processes. Business Process Reengineering (BPR) and Automation (BPA) have been recognized as one of the important aspects in construction business management. However, BPR requires a lot of efforts to identify, document, implement, execute, maintain, and keep track thousands of business processes to deliver a project. Moreover, existing BPA technologies used in existing Enterprise Resource Planning (ERP) systems do not lend themselves to effective scalability for construction business process management. Application of Workflow and Object Technologies would be quite effective in implementing a scalable enterprise application for construction business processes by addressing how: 1) Automated construction management tasks are developed as software components, 2) The process modeling is facilitated by dragging-and dropping task components in a network, 3) Raising business requests and instantiating corresponding process instances are delivered, and 4) Business process instances are executed by using workflow technology based on real-time simulation engine. This paper presents how the construction business process automation is achieved by using equipment reservation and cancellation processes simplified intentionally.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.28-35
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• 2006

An accurate prediction of budburst in grapevines is indispensable for vineyard frost warning system operations in spring because cold tolerance depends heavily on phonology. However, existing frost warning systems utilize only daily minimum temperature forecasts since there is no way to estimate the site-specific phonology of grapevines. A budburst estimation model based on thermal time was used to project budburst dates of two grapevine cultivars (Kyoho and Campbell Early), and advisories were issued depending on phonology as well as temperature. A 'warning' is issued if two conditions are met: the forecasted daily minimum temperature falls below $-1.5^{\circ}C$ and the estimated phonology is within the budburst period. A 'watch' is issued for a temperature range of -1.5 to $+1.5^{\circ}C$ with the same phonology condition. Validation experiments were done at 8 vineyards in Anseong in spring 2005, and the results showed a good agreement with the observations. This method was applied to the climatological normal year (1971-2000) to determine sites with high frost risk at a 30 m grid cell resolution. Among 608,585 grid cells constituting Anseong, 1,059 cells were identified as high risk for growing Kyoho and 2,788 cells for Campbell Early.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.29-42
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• 2012

Recently, traffic congestion has become serious due to increase of private car usages. Carsharing or other innovative public transportation systems were developed to alleviate traffic congestion and carbon emissions. These measures can make the traffic environment more comfortable, and efficient. Cloud Transportation System (CTS) is a recent carsharing model. User can rent an electronic vehicles with various traffic information through the CTS. In this study, a concept, vision and scenarios of CTS are introduced. And, authors analyzed the location of CTS rental stations and estimated CTS demands. Firstly, we analyze the number of the population, employees, students and traffic volume in study areas. Secondly, the frequency and utilization time are examined. Demand for CTS in each traffic zone was estimated. Lastly, the CTS rental station location is determined based on the analyzed data of the study areas. Evaluation standard of the determined location includes accessibility and density of population. And, the number of vehicles and that of parking zone at the rental station are estimated. The result suggests that Haewoondae Square parking lot would be assigned 11 vehicles and 14.23 parking spaces and that Dongbac parking lot be assigned 7.9 vehicles and 10.29 parking spaces. Further study requires additional real-time data for CTS to increase accuracy of the demand estimation. And network design would be developed for redistribution of vehicles.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.