• Journal of Multimedia Information System
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• 제5권4호
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• pp.235-244
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• 2018

Potential maximum soil moisture retention (S) is a dominant parameter in the Soil Conservation Service (SCS; now called the USDA Natural Resources Conservation Service (NRCS)) runoff Curve Number (CN) method commonly used in hydrologic modeling for event-based flood forecasting (SCS, 1985). Physically, S represents the depth [L] soil could store water through infiltration. The depth of soil moisture retention will vary depending on infiltration from previous rainfall events; an adjustment is usually made using a factor for Antecedent Moisture Conditions (AMCs). Application of the method for continuous simulation of multiple storms has typically involved updating the AMC and S. However, these studies have focused on a time step where S is allowed to vary at daily or longer time scales. While useful for hydrologic events that span multiple days, this temporal resolution is too coarse for short-term applications such as flash flood events. In this study, an approach for deriving a time-variable potential maximum soil moisture retention curve (S-curve) at hourly time-scales is presented. The methodology is applied to the Napa River basin, California. Rainfall events from 2011 to 2012 are used for estimating the event-based S. As a result, we derive an S-curve which is classified into three sections depending on the recovery rate of S for soil moisture conditions ranging from 1) dry, 2) transitional from dry to wet, and 3) wet. The first section is described as gradually increasing recovering S (0.97 mm/hr or 23.28 mm/day), the second section is described as steeply recovering S (2.11 mm/hr or 50.64 mm/day) and the third section is described as gradually decreasing recovery (0.34 mm/hr or 8.16 mm/day). Using the S-curve, we can estimate the hourly change of soil moisture content according to the time duration after rainfall cessation, which is then used to estimate direct runoff for a continuous simulation for flood forecasting.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.23-28
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• 2024

The multi-tenancy and high scalability of the cloud have inspired businesses and organizations across various sectors to adopt and deploy cloud computing. Cloud computing provides cost-effective, reliable, and convenient access to pooled resources, including storage, servers, and networking. Cloud service models, SaaS, PaaS, and IaaS, enable organizations, developers, and end users to access resources, develop and deploy applications, and provide access to pooled computing infrastructure. Despite the benefits, cloud service models are vulnerable to multiple security and privacy attacks and threats. The SaaS layer is on top of the PaaS, and the IaaS is the bottom layer of the model. The software is hosted by a platform offered as a service through an infrastructure provided by a cloud computing provider. The Hypertext Transfer Protocol (HTTP) delivers cloud-based apps through a web browser. The stateless nature of HTTP facilitates session hijacking and related attacks. The Open Web Applications Security Project identifies web apps' most critical security risks as SQL injections, cross-site scripting, sensitive data leakage, lack of functional access control, and broken authentication. The systematic literature review reveals that data security, application-level security, and authentication are the primary security threats in the SaaS model. The recommended solutions to enhance security in SaaS include Elliptic-curve cryptography and Identity-based encryption. Integration and security challenges in PaaS and IaaS can be effectively addressed using well-defined APIs, implementing Service Level Agreements (SLAs), and standard syntax for cloud provisioning.

• 한국안전학회지
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• 제24권5호
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• pp.48-56
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• 2009

This paper presents the procedure for the optimal design of a PSC-I girder bridge considering life cycle cost (LCC). The load carrying capacity curves for the concrete deck, PSC-I girder and $\pi$-type pier were derived and used for the estimate of service lives. Total life cycle cost for the service life was calculated as sum of initial cost, damage cost, maintenance cost, repair and rehabilitation cost, user cost, and disposal cost. The advanced First Order Second Moment method was used to estimate the damage cost. The optimization method was applied to the design of PSC-I girder bridge. The objective function was set to the annual cost, which is defined by dividing the total life cycle cost by the service life, and constraints were formulated on the basis of Korean Standards. The optimal design was performed for various service lives and the effects of design factors were investigated.

• 보건의료산업학회지
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• 제11권2호
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• pp.105-115
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• 2017

Objectives : The aim of this study was to suggest the optimal cut off for best, very good, good, slightly bad, and bad grades. Methods : The subjects were recruited from 4 areas of South Korea and 487 questionnaires were analyzed. The nominal and continuous self-rated health questions were used to reveal the optimal cut off and the Short Form-12 Health Survey questionnaire (SF-12) was additionally used. Frequency, Pearson's correlation coefficient, and ROC-curve analysis were used; the significance level was <.05. Results : Subjects assigned 15(3.1%), 90(18.5%), 237(48.7%), 130(26.7%), and 15(3.1%) to best, very good, good, slightly bad and bad groups respectively. The self-rated health score was associated with total Component (r=.563, p<.001), Physical Component (r=.520, p<.001) and Mental Component of SF-12 (r=.303, p<.001). The optimal cut off was 80.5, 70.5, 53.5, and 40.5 for best, very good or more, good or more, and under slightly bad respectively and area under curve was 0.898, 0.908, 0.945, and 0.908 accordingly. Conclusions : This study suggests that the self-rated health score and grade could be integrated with the optimal cut off.

• 한국통신학회논문지
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• 제24권12A호
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• pp.2025-2033
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• 1999

본 연구에서는 IMT-2000 서비스의 상용화 실시 시기를 전문가 의견을 바탕으로 하여 예측한 결과 2001년 2월경에 첫 서비스를 실시할 것으로 나타나 전문가들은 대체로 빠른 진척을 예상하고 있음을 알 수 있었다. 또한 본 연구의 가장 중요한 부분인 IMT-2000 서비스 가입 수요예측에서는 가격 경쟁력에 대한 두 가지 경우에 따라 다른 모형을 제시하였다. 본 연구에서는 신제품에 대한 수요예측에 정성적 방법인 전문가 의견법과 정량적 방법인 성장곡선 모형을 결합하여 과거자료가 없는 신제품의 수요예측의 오차를 줄이고자 하였다. 각 성장곡선 모형에 필요한 계수를 전문가들의 주관적인 의견을 근거로 하여 추정하였다.

• 디지털융복합연구
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• 제11권7호
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• pp.261-269
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• 2013

u-Health는 최근 기술이며 의료 진단과 건강관리를 위한 새로운 방법론이다. 그러나 이를 실현하려면 몇 가지 기술적 장벽들(이동성, 소형화, 배터리 수명 문제 등)을 넘어서야 한다. 본 논문에서는 u-Health 서비스에 적합한 스마트폰용 스펙트럼 측정 시스템을 개발하였다. 실험 결과 기존 솔루션에 비해 무선이면서 크기가 매우 작지만 성능 면(재현성 비교실험에서 Spectrum, Calibration Curve, Prediction)에서 거의 일치한다는 것을 확인하였다. 따라서 개발된 솔루션은 u-Health 분야에서 널리 활용되어질 것으로 기대된다.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.179-184
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• 2021

In our study we performed a sentiments analysis from the images. For this purpose, we used 153 images that contain: people, animals, buildings, landscapes, cakes and objects that we divided into two categories: images that suggesting a positive or a negative emotion. In order to classify the images using the two categories, we created two models. The SAI-G model was created with Google's AutoML Vision service. The SAI-C model was created on the Clarifai platform. The data were labeled in a preprocessing stage, and for the SAI-C model we created the concepts POSITIVE (POZITIV) AND NEGATIVE (NEGATIV). In order to evaluate the performances of the two models, we used a series of evaluation metrics such as: Precision, Recall, ROC (Receiver Operating Characteristic) curve, Precision-Recall curve, Confusion Matrix, Accuracy Score and Average precision. Precision and Recall for the SAI-G model is 0.875, at a confidence threshold of 0.5, while for the SAI-C model we obtained much lower scores, respectively Precision = 0.727 and Recall = 0.571 for the same confidence threshold. The results indicate a lower classification performance of the SAI-C model compared to the SAI-G model. The exception is the value of Precision for the POSITIVE concept, which is 1,000.

• 벤처창업연구
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• 제10권3호
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• pp.123-131
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• 2015

빠르게 발전하는 IoT 시대에 발맞추어, IoT 적용과 관련하여 다양한 시나리오에 이용할 수 있는 경영 전략을 이끌어내기 위한 체계적인 접근이 요구된다. 본 논문에서는, IOT를 적용할 때 시장 잠재력을 평가하고 초기 경영 전략을 세울 때 사용할 수 있는 개념적 틀을 제시한다. 개념적 틀은 널리 알려진 가치곡선분석, 생태계 분석 그리고 품질의 집을 이용하여 구성하였다. 가치곡선 분석은 소비자에게 가치를 주는 항목을 파악하는 부분과 이와 관계된 공급자의 강점을 분석하는데 이용된다. 생태계 분석은 공급사슬 상의 참가자들과 그들의 관계를 파악하는데 이용된다. 품질의 집은 공급자에게 소비자의 요구사항을 파악하고 그것을 공급자의 기술적인 요구 조건과 비교하여 초기 사업 전략을 구축하는데 적합한 분석도구이다. 본 논문에서는 우리가 제시한 개념적 틀을 IoT를 적용하였을 때 큰 발전 가능성이 있는 Car-sharing 서비스와 telehealth 서비스 이렇게 두 가지 서비스에 적용하여 분석하였다.

• 한국농공학회논문집
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• 제47권3호
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• pp.59-68
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• 2005

The rainfall-runoff potential of Jangseong reservoir watershed was studied based on SCS (Soil Conservation Service, which is now the NRCS, Natural Resources Conservation Service, USDA) runoff curve number (CN) technique. Precipitation and reservoir operation data had been collected. The rainfall-runoff pairs from the watershed for ten years was estimated using reservoir water balance analysis using reservoir operation records. The maximum retention, S, for each storm event from rainfall-runoff pair was estimated for selected storm events. The estimated S values were arranged in descending order, then its probability distribution was determined as log-normal distribution, and associated CNs were found about probability levels of Pr=0.1, 0.5, and 0.9, respectively. A subwatershed that has the similar portions of land use categories to the whole watershed of Jangseong reservoir was selected and hydrologic monitoring was conducted. CNs for subwatershed were determined using observed data. CNs determined from observed rainfall-runoff data and reservoir water balance analysis were compared to the suggested CNs by the method of SCS-NEH4. The $CN_{II}$ measured and estimated from water balance analysis in this study were 78.0 and 78.1, respectively. However, the $CN_{II}$, which was determined based on hydrologic soil group, land use, was 67.2 indicating that actual runoff potential of Jangseong reservoir watershed is higher than that evaluated by SCS-NEH4 method. The results showed that watershed runoff potential for large scale agricultural reservoirs needs to be examined for efficient management of water resources and flood prevention.

• 산업경영시스템학회지
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• 제37권4호
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• pp.106-115
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• 2014

Until now, because a new product (or facility) launched in market has been retired from one year of age, we can have had ASL by stub-curve method by Iowa curve. Recently, many innovative products with important role in market like display and solar-cell etc. are more durable and, what are better, they have the constant variance in ASL because of their good quality. Of course, there are some ones like smart mobile phone with relatively big dispersion in ASL. Estimating ASL of products like display and solar-cell etc., the new approach is needed. In this paper a new method applied traditional Iowa curve with accelerated reliability test (indoor/outdoor) etc. is proposed.