• Journal of the Korea Institute of Building Construction
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• v.10 no.6
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• pp.117-126
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• 2010

As one of the key IT applications, the project management information system (PMIS) has played a significant role in construction management processes. This is because PMIS is an information system that gathers, integrates, and disseminates the output of project management processes among project participants, and is used to support all aspects of a project, from initiation through closing. This paper aims to identify the CSFs(Critical Success Factor) of Project Management and quality associated with Project Management Information System (PMIS) in construction projects, to analyze the Effect of PMIS quality on Project Management Success. The CSFs of Project Management and the quality components for PMIS are identified through a review of the literature, and consolidated through interviews with professionals in the construction industry. A questionnaire instrument was sent out to experienced users (Construction Manager and Constructor), and 253 completed questionnaires were retrieved. To increase the applicability of the results, the respondents consisted of workers spread across various parts of the construction site. Using SPSS 12.0, the data was used to analyze the relationship between PMIS Quality and Project Management Success through multiple regression analysis. These findings help to clarify what the highly prioritized factors are, and could also be used as an assessment tool to evaluate the performance of PMIS and thus help to identify areas for improvement.

• Journal of Chest Surgery
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• v.47 no.3
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• pp.255-261
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• 2014

Background: To determine the predictors of clinical outcomes following surgical descending thoracic aortic (DTA) repair. Methods: We identified 103 patients (23 females; mean age, $64.1{\pm}12.3$ years) who underwent DTA replacement from 1999 to 2011 using either deep hypothermic circulatory arrest (44%) or partial cardiopulmonary bypass (CPB, 56%). Results: The early mortality rate was 4.9% (n=5). Early major complications occurred in 21 patients (20.3%), which included newly required hemodialysis (9.7%), low cardiac output syndrome (6.8%), pneumonia (7.8%), stroke (6.8%), and multi-organ failure (3.9%). None experienced paraplegia. During a median follow-up of 56.3 months (inter-quartile range, 23.1 to 85.1 months), there were 17 late deaths and one aortic reoperation. Overall survival at 5 and 10 years was $80.9%{\pm}4.3%$ and $71.7%{\pm}5.9%$, respectively. Reoperation-free survival at 5 and 10 years was $77.3%{\pm}4.8%$ and $70.2%{\pm}5.8%$. Multivariable analysis revealed that age (hazard ratio [HR], 1.10; 95% confidence interval [CI], 1.05 to 1.15; p<0.001) and left ventricle (LV) function (HR, 0.88; 95% CI, 0.82 to 0.96; p<0.003) were significant and independent predictors of long-term mortality. CPB strategy, however, was not significantly related to mortality (p=0.49). Conclusion: Surgical DTA repair was practicable in terms of acceptable perioperative mortality/morbidity as well as favorable long-term survival. Age and LV function were risk factors for long-term mortality, irrespective of the CPB strategy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.123-132
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• 2012

Gas sensors has been used very differently that depending on following purposes; Automotive (exhaust gas, fuel mixture gas, oxygen, particulates), agriculture / food industry (fresh, stored, CO2, humidity, NH3, nitrogen oxide gas, organic gas, toxic gas emitted from pesticides and insecticides), industrial / medical (chemical gas, hydrogen, oxygen and toxic gases), military (chemical weapon), environmental measurements (CO and other air pollution consisting of sulfur and nitrogen gas), residential (LNG, LPG, butane, indoor air, humidity). The types of industrial toxic substances are known about 700 species and many of these exist in gaseous form under normal conditions. he multi-gas detection sensors will be developed for casualties that detect the most important and find easy three kinds of gases in marine plant; carbon dioxide(CO2), carbon(CO), ammonia(NH3). Package block consists of gas sensing device minor ingredient, rf front end, zigbee chip. Develope interworking technology between the sensor and zigbee chip inside a package. Conduct a performance test through test jig about prototype zigbee sensor module with rf output power and unwanted emission test. This research task available early address when poisonous gas leaked from large industrial site and contribution for workers' safety at the enclosed space.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.176-176
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• 2019

Thailand had issued a national strategic development master plan with issues related to water resources and water security in the entire water management. Water resources are an important factor of living and development of the country's socio-economy to be stable, prosperous and sustainable. Therefore, water management in both multidimensional and multi-sectoral systems is important and will supports socio-economic and environmental development. The direction of national development in accordance with the national strategic framework for 20 years that requires the country to level up security level in terms of water, energy and food. To response to the proposed goals, there is a subplan to increase water productivity of the entire water system for economical development use by evaluating use value and to create more value added from water use to meet international standard level. This study aims to evaluate the water productivity of Thailand in each basin and all sectors such as agricultural sector, service and industrial sectors by using the water use data from water account analysis and GDP data from NESDB during the past 10 years (1996-2015). The comparison of water productivity with other countries will also be conducted and in addition, the measures to improve water productivity in next 20 years will be explored to response to the National Strategic Master Plan goals. Water productivity is defined as output per unit of water depleted. The simplest way to compare water productivity across different enterprises is in monetary terms. World Bank presents water productivity as an indication of the efficiency by which each country uses its water resources. There are two data sets used for water productivity analyses, i.e., the first is water use data at end users and the second is Gross Domestic Product. The water use at end users are estimated by water account method based on the System of Environmental-Economic Accounting for Water (SEEA-Water) concept of United Nations. The water account shows the analyses of the water balance between the use and supply of each water resource in physical terms. The water supply and use linkage in the water account analyses separated into each phases, i.e., water sources, water managers, water service providers, water user at end user under water regulators of all kinds of water use activities such as household, industrial, agricultural, tourism, hydropower, and ecological conservation uses. The Gross Domestic Product (GDP), a well- known measuring method of the national economic growth is not actually a comprehensive approach to describe all aspects of national economic status, since GDP does not take into account the costs of the negative impacts to natural resources that result from the overexploitation of development projects, however, at present, integrating the environment with the economy of a country to measure its economic growth with GDP is acceptable worldwide. The study results will show the water use at each basin, use types at end users, water productivity in each sector from 1996-2015 compared with other countries, Besides the productivity improvement measures will be explored and proposed for the National Strategic Master Plan.

• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.669-673
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• 2003

We fabricated a buried-ridge waveguide laser diode (B-RWG LD) which has more advantages for obtaining lateral single mode operation on the same ridge width and for the planarization of the device surface, compared to the conventional RWG LD. In this LD, the difference of the lateral effective refractive index can be controlled by the thickness of the InGaAsP layer which is grown on the active and the p-InP layers. The InGaAsP multiple quantum well was grown on a n-InP substrate by the CBE. The buried ridge structure was formed by selective wet etchings, followed by liquid phase epitaxy methods. The fabricated LD with the ridge width of 7 ${\mu}{\textrm}{m}$ showed a linear increase of the optical power up to 20 ㎽ without any kinks and a saturated output power of more than 80 ㎽. By measuring the far field pattern, we demonstrate that LDs with the ridge widths of 5 ${\mu}{\textrm}{m}$ and 7 ${\mu}{\textrm}{m}$ were operated in a lateral single mode up to 2.7I$_{th}$ and 2.4I$_{th}$, respectively.ely.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1217-1227
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• 2018

This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.

• International Area Studies Review
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• v.15 no.2
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• pp.125-150
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• 2011

As the economy grows, there is a concern that the economic development causes a productivity reduction because of the service intensive growth. However, the economy of developed countries encounter with the productivity growth as their economy grows, which phenomenon called Baumol's paradox. Oulton (1999, 2001) find out the reason of Baumol's paradox in a forward and backward chain effects. So, this paper is aimed at verifying the theory of Oulton (1999, 2001). Moreover, we test the difference effect between a consumer service and producer service input using a dummy variable. We use the Input-Output Table (1990, 1995, 2000, 2005) that is offered by the Bank of Korea to accomplish the purpose of our research that is represented above. We find out that the Korea's intermediate producer service inputs cause a multifactor productivity growth. That result is matched with the Oulton (1999, 2001)'s theory. But, the intermediate consumer service inputs don't have a significant effect on a multifactor productivity. The result of verifying the effect of intermediate producer service inputs among industries shows that the effects on manufacture industries are less than other industries.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Database Research
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• v.34 no.3
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• pp.148-158
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• 2018

The optical character recognition (OCR) is a technique to extract and recognize texts from images. It is an important preprocessing step in data analysis since most actual text information is embedded in images. Many OCR engines have high recognition accuracy for images where texts are clearly separable from background, such as white background and black lettering. However, they have low recognition accuracy for images where texts are not easily separable from complex background. To improve this low accuracy problem with complex images, it is necessary to transform the input image to make texts more noticeable. In this paper, we propose a method to segment an input image into text lines to enable OCR engines to recognize each line more efficiently, and to determine the final output by comparing the recognition rates of CLAHE module and Two-step module which distinguish texts from background regions based on image processing techniques. Through thorough experiments comparing with well-known OCR engines, Tesseract and Abbyy, we show that our proposed method have the best recognition accuracy with complex background images.