• 한국전자거래학회지
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• 제7권1호
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• pp.87-106
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• 2002

The behavioral and dynamic implications of an ERP implementation/installation are, to say the least, not well understood. Getting the switches set to enable the ERP software to go live is becoming straightforward. The really difficult part is understanding all of the dynamic interactions that accrue as a consequence. Dynamic causal and connectionist models are employed to facilitate an understanding of the dynamics and to enable control of the information-enhanced processes to take place. The connectionist model ran be analyzing (behind the scenes) the information accesses and transfers and coming If some conclusions about strong linkages that are getting established and what the behavioral implications of those new linkages and information accesses we. Ultimately, the connectionist model will come to an understanding of the dynamic, behavioral implications of the larger ERP implementation/installation per se. The underlying connectionist model will determine information transfers and workflow. Once a map of these two infrastructures is determined by the model, it becomes a relatively easy job for an analyst to suggest improvements in both. Connectionist models start with analog object structures and then use learning to produce mechanisms for managerial problem diagnoses. These mechanisms are neural models with multiple-layer structures that support continuous input/output. Based on earlier work performed and published by the author[10][11], a Connectionist ReasOning and LEarning System(CROLES) is developed that mimics the real-world reasoning infrastructure. Coupled with an explanation subsystem, this system can provide explanations as to why a particular reasoning structure behaved the way it did. Such a system operates in the backgmund, observing what is happening as every information access, every information response coming from each and every intelligent node (whether natural or artificial) operating within the ERP infrastructure is recorded and encoded. The CROLES is also able to transfer all workflows and map these onto the decision-making nodes of the organization.

• 보건행정학회지
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• 제9권2호
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• pp.95-117
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• 1999

The purposes of the study was to analysis the factors on the physicians' indemnity experience and indemnity on malpractice. Data was collected from mail interview for the physicians from August, to October in 1996. Questions were asked to the physician who selected with random sample(n=8.338) about the opinion of malpractice insurance. experience that he(she) have requested the indemnity from patience. context of experienced indemnity and demographic characteristics of physician and patience. Response rate is 37.5%(n=3,124). This study was analyzed in two levels' the first. influential factors on whether physician has experience of indemnity and the second. influential factors of indemnity among physicians who had experienced the indemnity. The major findings were as follows : 1. Logistic regression on whether physicians had experience of indemnity request was conducted. And it indicated that statistically meaningful variables of model 1 (about all physicians) were department of surgery, physicians who have intention of insurance fee, physician age and income, physicians who owned the hospitals and statistically meaningful variables of model 11 (about physicians who owned the hospital) were department of surgery and internal treatment. 2. Multiple regression on the influential factors on indemnity was conducted. And it showed that statistically meaningful variables in model 1 were method of malpractice quarrel(physician association), whether physician had malpractice, whether suit succeeded, physician age, average practice time and income and whether physician owned the hospital and statistically meaningful variables of model 11 were whether physician had malpractice, number of outpatient, number of beds. As the conclusion, the thesis was examined about the variables related with experience of indemnity and cost of malpractice. But in order to prevent malpractice and promote medical quality, the reasonable system to solve a malpractice have to settle and cost estimation on malpractice is essential. Therefore an advanced research is progressed with methodology to decide the indemnity bases.

• Advances in concrete construction
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• 제13권5호
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

• 한국산업정보학회논문지
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• 제28권5호
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• pp.31-39
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• 2023

최근 자연어 처리(NLP) 기술, 특히 ChatGPT를 비롯한 거대 언어 모델(LLM)의 발전으로 특정 전문지식에 대한 질의응답(QA) 시스템의 연구개발이 활발하다. 본 논문에서는 거대언어모델과 문서검색 알고리즘을 활용하여 한국원자력연구원(KAERI)의 규정 등 다양한 문서를 이해하고 사용자의 질문에 답변하는 시스템의 동작 원리에 대해서 설명한다. 먼저, 다수의 문서를 검색과 분석이 용이하도록 전처리하고, 문서의 내용을 언어모델에서 처리할 수 있는 길이의 단락으로 나눈다. 각 단락의 내용을 임베딩 모델을 활용하여 벡터로 변환하여 데이터베이스에 저장하고, 사용자의 질문에서 추출한 벡터와 비교하여 질문의 내용과 가장 관련이 있는 내용들을 추출한다. 추출된 단락과 질문을 언어 생성 모델의 입력으로 사용하여 답변을 생성한다. 본 시스템을 내부 규정과 관련된 다양한 질문으로 테스트해본 결과 복잡한 규정에 대하여 질문의 의도를 이해하고, 사용자에게 빠르고 정확하게 답변을 제공할 수 있음을 확인하였다.

• 한국물환경학회지
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• 제40권3호
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• pp.121-129
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• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

• 한국기록관리학회지
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• 제20권1호
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• pp.115-137
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• 2020

본 연구는 영구기록물기술규칙 기반의 기술현황이 갖는 한계점을 살펴보고, 이에 대한 해결방안으로 RiC-CM(Record in Context - Conceptual model)을 적용한 영구기록물 기술방안을 제안하는데 그 목적을 두었다. 이를 위해 문헌연구와 사례연구를 진행하였다. 국가기록원 영구기록원 기술현황의 한계에 대한 RiC-CM 기반의 해결방안과 그에 대한 효과는 다음과 같다. 첫째, RiC-CM는 특정 영구기록물이 복수 출처맥락을 반영하는 것이 가능하다. 이는 기록물과 각각의 출처를 개체로 정의하고 이들의 연관성을 관계로 표현하는 방식으로 해결할 수 있다. 기록물 개체들의 관계를 맺어주는 것만으로도 특정 영구기록물과 관련된 출처정보를 보다 정확히 표현 가능하고, 전체적인 생산맥락을 파악하기 용이하다. 둘째, RiC-CM는 연관이 있는 기록물 철·건 정보를 연계하는 것이 가능하다. 특정 기록물 군(퐁)에 속하는 하위 기록물 철·건들은 각각 개체로 지정하고, 생산맥락에 따른 관계를 부여하는 방식으로 해결할 수 있다. 이를 통해 실제 서비스를 제공할 때 연관된 영구기록물들의 정보를 한데모아 서비스하는 것이 가능하다. 그리고 이용자 입장에서는 영구기록물 검색의 폭을 넓힐 수 있다. 셋째, RiC-CM은 특정 생산기관과 연관된 모든 생산기관 정보를 연계하는 것이 가능하다. 만약 복수의 생산기관들이 서로 연관되어 있다면, 생산기관들을 각각의 개체로 정의하고 이들 간의 관계를 '연관이 있다(associated with)'로 표현할 수 있다. 이를 통해 생산기관의 맥락정보, 즉 기록의 출처맥락을 종합적으로 살펴보는데 도움이 된다. 본 연구를 통해 전자기록 관리환경의 패러다임 변화에 대응하여, 차세대 영구기록물 기술규칙인 RiC-CM에 대한 연구에 활용될 수 있기를 기대한다.

• 한국전자통신학회논문지
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• 제19권1호
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• pp.317-326
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• 2024

생체 인식은 사람의 생체적, 행동적 특징 정보를 특정 장치로 추출하여 본인 여부를 판별하는 기술이다. 생체 인식 분야에서 생체 특성 위조, 복제, 해킹 등 사이버 위협이 증가하고 있다. 이에 대응하여 보안 시스템이 강화되고 복잡해지며, 개인이 사용하기 어려워지고 있다. 이를 위해 다중 생체 인식 모델이 연구되고 있다. 기존 연구들은 특징 융합 방법을 제시하고 있으나, 특징 융합 방법 간의 비교는 부족하다. 이에 본 논문에서는 지문, 얼굴, 홍채 영상을 이용한 다중 생체 인식 모델의 융합 방법을 비교 평가했다. 특징 추출을 위해VGG-16, ResNet-50, EfficientNet-B1, EfficientNet-B4, EfficientNet-B7, Inception-v3를 사용했으며, 특성융합을 위해 'Sensor-Level', 'Feature-Level', 'Score-Level', 'Rank-Level' 융합 방법을 비교 평가했다. 비교평가결과 'Feature-Level' 융합 방법에서 EfficientNet-B7 모델이 98.51%의 정확도를 보이며 높은 안정성을 보였다. 그러나 EfficietnNet-B7모델의 크기가 크기 때문에 생체 특성 융합을 위한 모델 경량화 연구가 필요하다.

• Laboraroty Animal Research
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• 제34권4호
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• pp.248-256
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• 2018

O-2-$^{18}F$-fluoroethyl-l-tyrosine ($[^{18}F]FET$) has been widely used for glioblastomas (GBM) in clinical practice, although evaluation of its applicability in non-clinical research is still lacking. The objective of this study was to examine the value of $[^{18}F]FET$ for treatment evaluation and prognosis prediction of anti-angiogenic drug in an orthotopic mouse model of GBM. Human U87MG cells were implanted into nude mice and then bevacizumab, a representative anti-angiogenic drug, was administered. We monitored the effect of anti-angiogenic agents using multiple imaging modalities, including bioluminescence imaging (BLI), magnetic resonance imaging (MRI), and positron emission tomography-computed tomography (PET/CT). Among these imaging methods analyzed, only $[^{18}F]FET$ uptake showed a statistically significant decrease in the treatment group compared to the control group (P=0.02 and P=0.03 at 5 and 20 mg/kg, respectively). This indicates that $[^{18}F]FET$ PET is a sensitive method to monitor the response of GBM bearing mice to anti-angiogenic drug. Moreover, $[^{18}F]FET$ uptake was confirmed to be a significant parameter for predicting the prognosis of anti-angiogenic drug (P=0.041 and P=0.007, on Days 7 and 12, respectively, on Pearson's correlation; P=0.048 and P=0.030, on Days 7 and 12, respectively, on Cox regression analysis). However, results of BLI or MRI were not significantly associated with survival time. In conclusion, this study suggests that $[^{18}F]FET$ PET imaging is a pertinent imaging modality for sensitive monitoring and accurate prediction of treatment response to anti-angiogenic agents in an orthotopic model of GBM.

• 복식
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• 제64권2호
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• pp.35-49
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• 2014

In cases of fashion businesses operating by consignment, base estimate on quantity of sales is the most essential part of merchandising. This study classified factors influential to sales into factors with systematic influence and factors with unsystematic influence. In order to find out influence of each factor on sales, non-linear regression was used with SPSS package on the basis of actual data on sales for 5 years for sport shoes brand. Major findings of this study are as follows. First, price level had significant negative(-) influence on sales. Second, price expectation effects had significant negative(-) influence on sales. Third, competitor's price effect showed significant negative(-) value. Fourth, day-of-the-week effect showed significant positive(+) effect. The theoretical marketing implications of this study are as follows. First, study on price leads to expansion of the researches from apparels to sport shoes. Field of study on price was enlarged through expansion of variable of study from price level and price expectation effect to promotion, day-of-the-week effect and rainfall effect. Second, quantitative scale of day-of-the-week effect was found and it could be confirmed that there was seasonal differences with day-of-the-week effect. Implications of above findings on marketing managers are as follows. First, it was found that an increase in competitiveness of brand power and a decline in absolute value of competitor's price effect can be realized when new product groups are developed to meet the unsatisfied needs in the market. Second, it was possible to find out the parameters scales of the price response function, making it possible to estimate sales for the next season, and in turn realize increase in rate of sales and profit rate. This research is based on the dynamic price response function, which is rare to find in the apparel business and it academic significance due to its expanding response model which was focused on price in conventional researches to non-systematic variables.

• 농업과학연구
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• 제7권2호
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• pp.131-144
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• 1980

수자원개발(水資源開發)의 계획(計劃) 및 설계(設計)를 위한 하천(河川)의 월유출량(月流出量) 추정방법(推定方法)인 전월단위(全月單位)의 사변수(四變數) 선형회귀모형(線型回歸模型)을 일반화(一般化)하여 유출량(流出量) 기록(記錄)의 Extension, 무계기(無計器) 하천(河川)의 유출량(流出量) 추정(推定) 등(等)에 이용(利用)할 수 있도록 하였으며 금강(錦江) 수계(水系)에 적용(適用)한 결과(結果)는 다음과 같다. 1. 선형회귀모형(線型回歸模型)은 물수지방정식(收支方程式)을 중첩(重疊)의 원리(原理)가 적용(適用)되는 선형(線型)(linear)으로 취급(取扱)하여 통계적(統計的)으로 모형(模型)을 설정(設定)하고 유역(流域) Response의 물리적(物理的) System 및 그 변화(變化)를 연역적(演譯的)으로 정성적(定性的)(qualitatively), 개략적(槪略的)(lumped)인 해석(解析)을 하려는 것이다. 각(各) 회귀계수(回歸係數)들이 각(各) parameter들의 phisical properties의 의미(意味)를 내포(內包)하는 일종(一種)의 grey box로 해석(解析)하려는 statistically deterministic model이다. 2. 금강(錦江) 수계(水系)의 4개(個) 수문지점(水文地點)의 선형회귀모형(線型回歸模型)의 방정식(方程式)은 다음과 같다. 통계적(統計的) 기준(基準)에 따라 판정(判定)한 결과(結果) 고도(高度)의 유의성(有意性)이 있는 모형(模型)으로 판정(判定)되었으며 특(特)히 유출량(流出量) 기록(記錄)이 짧은 경우에도 이용(利用)할 수 있다. 각(各) parameter들의 회귀계수(回歸係數)는 유역면적(流域面積)에 따라 질서(秩序)있게 변화(變化)하는 것을 알 수 있다. 즉(卽) 강우량(降雨量)(Pn)의 경우 유역(流域)이 커질수록 interception, detention storage에 의(依)한 손실(損失)도 커지며, 토양수분변화량(土壤水分變化量) (Qn-1)의 경우 유역(流域)이 커질수록 유역(流域)의 저류능(貯溜能)이 커지므로 기저유출(基底流出)도 커지며, 증발산량(蒸發散量)(En)의 경우 유역이 커질수록 Coverage의 나지화(裸地化) 면적(面積)이 커지므로 증발산량(蒸發散量) 손실(損失)도 커진다. 3. 선형회귀모형(線型回歸模型)의 정성적(定性的)인 phisical properties가 유역면적(流域面積)에 따라 변화(變化)하는데 착안(着眼)하여 모형(模型)을 일반화(一般化)하여 수계별(水系別) 유역면적별(流域面積別)로 회귀계수(回歸係數)를 구(求)하여 무계기(無計器) 하천(河川)에서도 월유출량(月流出量) 추정(推定) 모형(模型)을 설정(設定)할 수 있게 하였다. 금강수계(錦江水系)의 선형회귀모형(線型回歸模型)의 일반화도표(一般化圖表)는 다음 Fig.10과 같다.