• 제목/요약/키워드: Rule-chain

검색결과 96건 처리시간 0.026초

미국 관세청의 선적전 추가 보안관련 정보 제출법안(10+2 Rule)에 관한 연구 (A Study on the Importer Security Filing and Additional Carrier Requirements(10+2 rule) in U.S.)

  • 송선욱
    • 통상정보연구
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    • 제10권4호
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    • pp.395-416
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    • 2008
  • The advance information for oceangoing cargoes destined to th United States enable CBP to evaluate the potential risk of smuggling WMD and to facilitate the prompt release of legitimate cargo following its arrival in the Unites States. On January 1, 2008, CBP promulgate regulations, also known as 10+2 rule, to require the electronic transmission of additional data elements for improved high-risk targeting, including appropriate security elements of entry data for cargo destined to the United States by vessel prior to loading of such cargo on vessels at foreign seaports. The potential impact to an importer's international supply chain will be as follows ; Firstly, importers will take incremental supply chain costs and filing costs. Secondly, anticipate delay in shipment of containerized cargo. Thirdly, importers could be charged fines if they fail to file and file inaccurate or missing data. Companies exporting to the United States should be interested in 10+2 rule, analyze their current processes and procedures to ensure that they are prepared to handle the additional filing requirements of 10+2 rule. And they should focus on how 10+2 impacts their supply chain in terms of costs and sourcing. They will be necessary to revise service legal agreements with their forwarders, customs brokers or carriers in order to meet filing requirements of 10+2 rule.

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Generalized $\alpha$ chain rule에 기반한 Group Item Recommendation (Group Item Recommendation based on Generalized a Chain Rule)

  • 염선희;조동섭
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (2)
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    • pp.241-243
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    • 2001
  • 데이터 마이닝을 통해 우리는 숨겨진 지식, 예상되지 않았던 경향 그리고 새로운 법칙들을 방대한 데이터에서 이끌어내고자 한다. 본 논문에서 우리는 사용자들의 구매 트랜잭션을 시간에 따라 분석하여 동시에 구매되는 상품을 미리 예측하는 알고리즘을 제안하고자 한다. 기존의 방법들에서는 구매된 상품간의 시간차를 고려하지 않은 방법만을 제안해 왔다. 따라서 서로 연관되지 않은 상품군이 예측될 확률이 높았다. 본 논문에서 제안하고 있는 $\alpha$ chain rube에서는 일정 시간동안의 사용자들이 상품을 구매한 후 다음 상품을 구매할 때까지의 시간을 고려한다. 따라서 좀더 정확히 동시에 구매될 상품군을 예측할 수 있다. 본 논문은 제안하고 있는 $\alpha$ chain rule을 계산해 내는 알고리즘에 대해 주로 논의하겠다.

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SCM환경에서 CRM을 이용한 ATP 모델 연구 (ATP Model Related CRM in SCM Environment)

  • 박주식;김원식;남호기;박상민
    • 대한안전경영과학회지
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    • 제3권1호
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    • pp.45-56
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    • 2001
  • In the supply chain, The ATP function doesn't only give customers to confirmation of delivery. It can be used by the core function with ATP rule that can reconcile supplies and demands on the supply chain. Therefore We can acquire the conformation about accuracy on the due date of supplier by using the ATP function of management about real and concurrent access on the supply chain, also can decide the affect about product availability due to forecasting or customer's orders through the ATP. This study analyze the data concerned with ATP and define the necessity on a SCM solution. Under the these environments, after defining the ATP rule that can improve the customer value and data flow related the CRM, we propose the advanced ATP model that proposes the method and classification system that can flexibly aggregate the ATP data with ATP rule on the supply chain.

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사용자 경험을 고려한 규칙기반 악성 URL 탐지 라이브러리 개발 (Development of Rule-Based Malicious URL Detection Library Considering User Experiences)

  • 김보민;한예원;김가영;김예분;김형종
    • 정보보호학회논문지
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    • 제30권3호
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    • pp.481-491
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    • 2020
  • 악성 URL의 전송을 통한 악성코드 전파 및 불법적 정보 수집은 정보보안 분야의 가장 큰 위협 중의 하나이다. 특히, 최근 스마트폰의 보급으로 인하여 사용자들이 악성 URL에 노출될 확률이 더욱 높아지고 있다. 또한, 악성 URL을 노출 시키는 방법 역시 다양해 지고 있어서 이를 탐지하는 것이 점점 어려워지고 있다. 본 논문은 악성 URL에 대한 사용자의 경험에 대한 설문을 진행한 후, 이를 고려하여 악성 URL을 규칙기반으로 탐지하기 위한 라이브러리 개발 연구를 다루고 있다. 특히, 본 연구에서는 독자적인 규칙을 기반으로 악성 URL을 탐지 하기 위해 Rule-set을 정의하고, Rule-chain을 생성하여 악성 URL 탐지의 확장성을 제시하고 있다. 또한 어떤 애플리케이션에서도 활용이 가능한 라이브러리 형태로의 개발을 통해 다양한 응용프로그램에서 활용할 수 있도록 하였다.

CONSTRUCTING GENE REGULATORY NETWORK USING FREQUENT GENE EXPRESSION PATTERN MINING AND CHAIN RULES

  • Park, Hong-Kyu;Lee, Heon-Gyu;Cho, Kyung-Hwan;Ryu, Keun-Ho
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.623-626
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    • 2006
  • Group of genes controls the functioning of a cell by complex interactions. These interacting gene groups are called Gene Regulatory Networks (GRNs). Two previous data mining approaches, clustering and classification have been used to analyze gene expression data. While these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rule. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and detect gene expression patterns applying FP-growth algorithm. And then, we construct gene regulatory network from frequent gene patterns using chain rule. Finally, we validated our proposed method by showing that our experimental results are consistent with published results.

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Analysis and Compare for Control Charts Under the Changed Alarm Rule

  • Haiyu Wang;Jichao Xu;Park, Young H.
    • International Journal of Quality Innovation
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    • 제4권2호
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    • pp.65-72
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    • 2003
  • This paper mainly studies to build control charts under different alarm rule. For different alarm rule, the control limit parameters of a control chart should be changed, then some kinds of control schemes under different alarm rule were compared and the methods of calculating ARL for different control schemes were given.

An Inventory Rationing Method in a M-Store Regional Supply Chain Operating under the Order-up-to Level System

  • Monthatipkul, Chumpol
    • Industrial Engineering and Management Systems
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    • 제8권2호
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    • pp.80-92
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    • 2009
  • This paper addresses the inventory rationing issue embedded in the regional supply chain inventory replenishment problem (RSIRP). The concerned supply chain, which was fed by the national supply chain, consisted of a single warehouse distributing a single product to multiple stores (M-stores) with independent and normally distributed customer demand. It was assumed that the supply chain operated under the order-up-to level inventory replenishment system and had only one truck at the regional warehouse. The truck could make one replenishment trip to one store per period (a round trip per period). Based on current inventories and the vehicle constraint, the warehouse must make two decisions in each period: which store in the region to replenish and what was the replenishment quantity? The objective was to position inventories so as to minimize lost sales in the region. The warehouse inventory was replenished in every fixed-interval from a source outside the region, but the store inventory could be replenished daily. The truck destination (store) in each period was selected based on its maximum expected shortage. The replenishment quantity was then determined based on the predetermined order-up-to level system. In case of insufficient warehouse inventories to fulfill all projected store demands, an inventory rationing rule must be applied. In this paper, a new inventory rationing rule named Expected Cost Minimization (ECM) was proposed based on the practical purpose. The numerical results based on real data from a selective industry show that its performance was better and more robust than the current practice and other sharing rules in the existing literature.

A Performance Comparison between Operation Strategies for Idle Vehicles in Automated Guided Vehicle System

  • Kim, Kap-Hwan;Kim, Jae-Yeon
    • 한국경영과학회지
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    • 제23권2호
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    • pp.67-81
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    • 1998
  • An Automated Guided Vehicle System (AGVS) with a unidirectional loop guide path is modeled as a discrete-time stationary Markov chain. It is discussed how to estimate the mean response time, the utilization, and the cycle time of AGV for a delivery order. Three common operation strategies for idle vehicles - central zone positioning rule, circulatory loop positioning rule and point of release positioning rule - are analyzed. These different operation strategies are compared with each other based on the performance measures.

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고객생애가치를 이용한 납기확약 모델 구현에 관한 연구 (Design of Capable to Promise Using Lifetime Value)

  • 박재현;양광모;강경식
    • 대한안전경영과학회지
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    • 제4권2호
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    • pp.71-81
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    • 2002
  • Today's environment of enterprise is changing. They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In the Supply chain, The ATP function doesn't only give customers to conformation of delivery. It can be used by the core function with ATP rule that can reconcile supplies and demands on the supply chain. Therefore We can be acquire the conformation about on the due date of supplier by using the ATP function of management about real and concurrent access on the supply chain, also decide the affect about product availability due to forecasting or customer's orders through the ATP. In this paper, It consolidates the necessity on a CTP and analyzes data which is concerned of ATP. Under the these environments, defines the ATP rule that can improve the customer value and data flow related the LTV(Life Time Value) and builds on a algorithm.

관세 정형 빅데이터를 활용한 우범공급망 거래패턴 선별 (Transaction Pattern Discrimination of Malicious Supply Chain using Tariff-Structured Big Data)

  • 김성찬;송사광;조민희;신수현
    • 한국콘텐츠학회논문지
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    • 제21권2호
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    • pp.121-129
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    • 2021
  • 본 연구에서는 데이터마이닝(Data Mining) 기법 중 하나인 연관관계분석(Association Rule Mining)을 적용하여 위험화물 선별모델을 구축함으로써 관세위험을 최소화하고자 한다. 이를 위해 관세청 수입신고서 빅데이터를 활용하여 연관관계분석 알고리즘인 어프라이어리 알고리즘(Apriori Algorithm)을 적용하고 공급망 간의 위험정도를 계산한다. 대규모의 수입신고 데이터로부터 해외공급자와 수입업체 간의 세율관련(과세가격, 품목, 중수량 등), 원산지표시 위반 등에 관련한 적발결과 관한 규칙셋(Rule Set)과 이 규칙들의 신뢰도(Confidence)을 확보하여 우범공급망 간의 거래패턴을 예측할 수 있는 선별모델을 구축한다. 총 2년 6개월 치의 수입신고 데이터를 활용하여 5-겹 교차검증(5-fold cross validation)을 수행한 결과 16.6%의 Precision과 33.8%의 Recall을 보였다. 이는 빈도기반 방법보다 Precision 기준 약 3.4배 Recall 기준 약 1.5배 높은 결과이다. 이로써 논문에서 제안하고 있는 방법이 관세위험을 줄일 수 있는 효과적인 방법임을 확인하였다.