• 전기의세계
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• v.41 no.12
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• pp.21-30
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• 1992

내연기관의 가솔린자동차보다 역사가 오래된 전기자동차는 상대적으로 주생성능과 가격 경쟁력의 열세로 그 자취를 감추었고 최근까지 주로 특수목적의 단거리 저속차량으로 사용되고 있다. 그러나 1890년대 후반부터 전세계가 자동차배기가스에 의한 대기오염과 지구온난화 현상등의 문제를 심각하게 공감하게 되었고 마침내 미국 캘리포니아주에서는 전가자동차의 강제판매를 규정화하게 이르렀다. 이 규정에 의하면 1998년도부터 차량 판매대수의 2%를 전기자동차 판매로 강제요구하고 있다. 이 비율은 2000녀도에 5% 2003년에는 10%로 늘어날 계획이다. 따라서 미국에 많은 자동차를 수출하고 있는 일본, 독일 및 여러 유럽국가에서는 이 사업에 막대한 자금을 투자하며 개발에 몰두하고 있다. 미국의 Big3도 에너지성의 도움으로 최근 USABC를 결성하여 전기자동차 개발에 박차를 가하고 있다. 지금까지 기존의 가솔린자동차 기술에 있어서 일본과 독일에 상대적 열세에 있었던 미국도 이번 캘리포니아주의 전기자동차 강제판매 규정에 따른 전기자동차 사업으로 미국자동차 시장의 새로운 판도를 조성하겠다는 의도인듯하다. 국내에서도 정부가 이 사업의 중요성을 심각히 인식하고 G7사업과제의 하나로 선정하여 산, 학, 연 각층의 전문가가 참여하여 성공적으로 개발을 마칠 수 있도록 적극 지원하고 있다. 지금까지의 평균주행성능을 보면 최고속도 100-120km/h, 일층전 최대주행거리 150-200km 정도이며, 아직 양산체제에 돌입하지 않았기 때문에 가격면에서 경쟁력이 없는 실정이다. 그러나 1990년도에 들면서 각종 요소부품들의 기술수준이 급성장을 이루어서 앞으로 10년정도 후면 성능과 가격면에서 가솔린자동차와 대등한 수준의 전기자동차 개발이 실현될 수 있으리라 예측된다.는 영향받지 않았다. Clonidine의 심박수 감소작용은 .뇌실내및 정맥내 diltiazem이나 nifedipine 처리후에 감약되었다. 5). 뇌실내 clonidine$(30{\mu}g)$ 처 리후 뇌실내 diltiazem$(400{\mu}g)$과 nifedipine$(350{\mu}g)$의 혈압하강및 심박수 감소효과는 영향 받지 않고 그대로 나타났다. 이상의 결과로 diltiazem과 nifedipine은 가토뇌내에서 methoxamine에 의한 혈압상승의 작용점인 alrfia-1 adrenoceptor의 흥분에는 영향을 미치지 못하나 clonidine의 작용점인 alpha-2 adrenoceptor의 흥분에 의한 혈압하강및 심박수 감소효과는 억제한다고 추론하였다.thin 함량은 110.6 mg/L로서 산업적인 생산성이 있는 것으로 나타났다. 이번 연구를 통하여 개발된 변이주 B76 및 이의 대량 발효를 위한 최종조건의 정립은 향후 astaxanthin의 산업적 생산공정에 필요한 기초자료로 이용될 것으로 기대된다.색총말내에 소형의 도형, 소형의 장형 연접소포 및 DENSE CORE VESICLE의 3가지 연접소포를 가지고 있었고 출현빈도수는 촉각엽에서 가장 큰 33%이었다. 제5형 신경연접은 축색종말내에 중등도크기의 원형, 대형의 원형연접소포 및 DENSE CORE VESICLE을 포함하였고 13%의 출현빈도수로 관찰되었다. 배추횐나비의 촉각에 있는 지각신경세포가 뇌의 촉각엽으로 뻗어 들어가 위의 5가지 신경연접중 어느 형을 형성하는지를 관찰하기 위하여 좌측 촉각의 기부를 제거하여 지각신경세포를 절단하였는데 그 결과, 좌측 촉각엽에서 제4형의 신경연접이 퇴행성 변화를 나타내었다.

• Journal of the Korean Society for Railway
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• v.18 no.6
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• pp.630-638
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• 2015

The total number of passengers on the KTX since its construction in 2004 surpassed 500 million in October, 2015. The operation of KTX made it possible to reach anywhere in a country in half a day, which subsequently altered people's lifestyle. As the KTX has become an important mode of transportation, there is a growing interest in the optimal size and location of its stations. Currently, the stations are constructed through public-private partnerships since a sufficient amount of budget is hard to secure only from the public sector; however, because railway stations are traditionally aimed at promoting public interests, an emphasis on the profitability of the private sector could compromise public interests. At this juncture, this study separately computes the number of users based on each of the two primary functions of the stations-as a railway station and as a sales facility-and estimates the numbers of people according to various transportation modes that are taken to access the stations. This estimation is applied to the case of Dongdaegu Station, which will open in 2016. Such an application helps to predict and respond to possible congestion as brought about by the expansion of the sales facility.

• The Journal of Bigdata
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• v.7 no.1
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• pp.213-224
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• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.

• Food Science of Animal Resources
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• v.28 no.5
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• pp.604-609
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• 2008

Analyses were conducted to estimate carcass component of yield grade factors by sex and live weight class and to develop the prediction equation of retail product weight by sex in Korean native cattle (Hanwoo). Data from 42,113 Hanwoo carcasses were used to estimate the traits of yield grade factor and an additional 1,066 carcasses were used to develop the prediction equation of retail meat weight. The average of fasting weight of cow, bull and steer were 529 kg, 596 kg, and 634 kg respectively. Carcass weight (CW), backfat thickness (BFT), loineye area (REA), Index score of wholesale meat and yield grade were significantly (p<0.01) affected by sex and live weight. The lean meat percentage, fat percentage and bone percentage based on the weight of cold carcasses were significantly different (p<0.05) between sex groups. The equation of predicting the retail meat product from this study could be expressed as a multiple regression $Y=-4.18+0.63{\times}CW\;(kg)-0.17{\times}BFT\;(cm)+0.16{\times}REA\;(cm^2)$, $R^2=0.93$. Among the independent factors, the BFT was the highest contributor to the prediction equation. Using the equation from this study should allow for rapid, precise and cost-effective assessment of the retail product in Hanwoo beef carcasses.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.247-256
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• 2000

오늘날의 기업은 상품을 판매하는 것 뿐만 아니라 기업의 신용과 이미지를 위해 그 상품에 대한 사후처리(After Service) 업무에 많은 투자를 하고 있다. 이러한 양질의 사후서비스를 고객에게 공급하기 위해서는 많은 인력을 합리적으로 관리해야 하고 요청되는 고장수리 서비스 업무를 빠르게 해결하기 위해서는 업무를 인력들에게 합리적으로 배정을 하고 회사의 비용을 최소화하면서 정해진 시간에 요청된 작업을 처리하기 위해서는 인력들에게 작업을 배정하고 스케줄링하는 문제가 발생된다. 본 논문에서는 이러한 문제를 해결하기 위해 화학계기의 A/S 작업을 인력에게 합리적으로 배정하는 스케줄링 시스템에 관한 연구이다. 먼저 스케줄링 모델을 HP 사의 화학분석 및 시스템을 판매, 유지보수 해 주는 "영진과학(주)"회사의 작업 스케줄을 분석하여 필요한 도메인과 고객서비스전략과 인력관리전략에서 제약조건을 추출하였고 여기에 스케줄링 문제를 해결하기 위한 방법으로 제약만족문제(CSP) 해결기법인 도메인 여과기법을 적용하였다. 도메인 여과기법은 제약조건에 의해 변수가 갖는 도메인의 불필요한 부분을 여과하는 것으로 제약조건과 관련되어 있는 변수의 도메인이 축소되는 것이다. 또한, 스케줄링을 하는데에 있어서 비용적인 측면에서의 스케줄링방법과 고객 만족도에서의 스케줄링 방법을 비교하여 가장 이상적인 해를 찾는데 트래이드오프(Trade-off)를 이용하여 최적의 해를 구했으며 실험을 통해 인력에게 더욱 효율적으로 작업들을 배정 할 수 있었고 또한, 정해진 시간에 많은 작업을 처리 할 수 있었으며 작업을 처리하는데 있어 소요되는 비용을 감소하는 결과를 얻을 수 있었다. 검증하였다.를, 지지도(support), 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등의 관계를 통해 다양한 방법으로 모색해본다. 이 연구에서 제안하는 이러한 개념계층상의 흥미로운 부분의 탐색은, 전자 상거래에서의 CRM(Customer Relationship Management)나 틈새시장(niche market) 마케팅 등에 적용가능하리라 여겨진다.선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity

• Information Systems Review
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• v.10 no.2
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• pp.137-158
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• 2008

Rapid development of various information technologies creates new opportunities in online and offline markets. In this changing market environment, customers have various demands on new products and services. Therefore, their power and influence on the markets grow stronger each year. Companies have paid great attention to customer relationship management. Especially, personalized product recommendation systems, which recommend products and services based on customer's private information or purchasing behaviors in stores, is an important asset to most companies. CRM is one of the important business processes where reliable information is mined from customer database. Data mining techniques such as artificial intelligence are popular tools used to extract useful information and knowledge from these customer databases. In this research, we propose a recommendation system that predicts customer's purchase intention. Then, customer's purchasing intention of specific product is predicted by using data mining techniques using receipt data set. The performance of this suggested method is compared with that of other data mining technologies.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.11-20
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• 2007

Even though much research has been performed to recommend favorite items to the buyers in the internet shopping mall, to the best of our knowledge. it is hard to find previous research on the recommendation of buy points. In this paper, we propose a method which can be used to recommend buy points of an item to the buyers. To do this, a database containing normalized price patterns is constructed from the archive of past prices. Then, the future price pattern is retrieved from the database based on the similarity. Here, regression analysis is used to find and analyze the elements that affect the price. We also present performance results showing that the proposed method can be useful for shopping malls.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.293-300
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• 2006

The Recommender systems help users to find and evaluate items of interest. Such systems have become powerful tools in the domains from electronic commerce to digital libraries and knowledge management. Sellers can recommend products to customers with the prediction of future buying behavior on the basis of the consumer's population statistics and past selling behavior. In this paper, we are describing the design and the development of personalization recommender system which increases satisfaction level of customers by searching products to reflect the pattern and propensity of customers properly. The suggested system supplies the real-time analysis service to predict the customers purchase situation by applying the association rule of the data mining.

• Management & Information Systems Review
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• v.34 no.1
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• pp.179-190
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• 2015

Local governments are commercializing natural environment, one of tourist commodities, to ensure that the proceeds from sale of tourist commodities are returned to local residents(Han Yeong-joo, Lee Moo-yong, 2001). In Songdo beach, Busan, cable car dismantled in 1980s due to the run-down state of the facility is poised for restoration in 26 years and can be said to be of great value as tourist commodity of the region and necessitates the demand forecast. To overcome limitations of demand forecast in existing studies, the analysis was made based on feasibility rate(Gruber index, self-confidence index), the realizable predictive value, for the willingness-to-visit rate when forecasting the demand of visitors. The results of demand forecast suggested that number of visitors would range from approximately 550,684 persons to 1,514,416 persons when the target region for demand forecast was confined to Busan Metropolitan City, and was in the range between 1,013,740 persons and 2,854,340 persons when the target region was expanded to cover Busan, Ulsan, and Gyeongnam. Based on the results of this study, estimation of visitors and demand forecast for Songdo offshore cable car restoration which reflect characteristics of Songdo beach of Busan would provide important basis for proceeding with tourism industry development project.

• The Journal of Bigdata
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• v.8 no.2
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• pp.189-200
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• 2023

At the beginning of the COVID-19 pandemic, Korea's wine market had shrunk as other countries. However, right after the pandemic, Korea's imported wine consumption had been increased 69.6%. Because of the ban on overseas travel, wine was consumed in the domestic market. And consumption of high-end wines were increased significantly due to revenge spending and home drinking. However, from 2022 Korea's wine market has begun to shrink sharply again. Therefore this study forecasts the size of imported wine market by 2032 to provide useful information to wine related business entities. KITA(Korea International Trade Association)'s 95 time-series data per quarter from Q1 of 2001 to Q3 of 2023 was utilized in this research. The accuracy of model was tested based on value of MAPE. And ARIMA model was chosen to forecast the size of market value and Winter's multiplicative model was used for the size of market volume. The result of ARIMA model for the value (MAPE=10.56%) shows that the size of market value in 2032 will be increased up to USD $1,023,619, CAGR=6.22% which is 101% bigger than its size of 2023. On the other hand, the volume of imported wine market (MAPE=10.56%) will be increased up to 64,691,329 tons, CAGR=-0.61% which is only 15.12% bigger than its size of 2023. The result implies that the value of Korea's wine market will continue to grow despite the recent decline. And the high-end wine market will account for most of the increase.