• Title/Summary/Keyword: Order Matching Rule

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Component Commonality and Order Matching Rules in Make-to-Forecast Production

  • Morikawa, Katsumi;Deguchi, Yusuke;Takahashi, Katsuhiko;Hirotani, Daisuke
    • Industrial Engineering and Management Systems
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    • v.9 no.3
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    • pp.196-203
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    • 2010
  • Make-to-forecast production is a way to realize high customization and fast responsiveness. This study firstly investigates the effect of introducing a common component in a make-to-forecast production environment. The common component can eliminate a modification step, which is a major cost component in make-to-forecast production. It is illustrated, however, that introducing a versatile component that merely covers several variants is unattractive, and thus adding values to the common component is inevitable in this environment. Secondly, an order-matching rule under the condition that two partially overlapped delivery lead time intervals exist is proposed. The rule considers the effect of matching orders to units that can cover both intervals. An alternative re-matching rule is also developed and examined. Numerical experiments clarify that the proposed rule generally realizes higher contribution ratio and lower percentages of orphans and rejected orders. The proposed re-matching rule increases the average contribution ratio at the expense of increased orphans and order rejections.

A Rule-Based System for VLSI Gate-Level Logic Optimization (VLSI 게이트 레벨 논리설계 최적화를 위한 Rule-Based 시스템)

  • Lee, Seong-Bong;Chong, Jong-Wha
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.1
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    • pp.98-103
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    • 1989
  • A new system for logic optimization at gate-level is proposed in this paper. Ths system is rule-based, i which the rules represent the local trnsformation replacing a portion of circuits with the simplified equivalent circuits. In this system, 'rule generalization' and 'local optimization' are proposed for effective pattern matching. Rule generalization is used to reduce the circuit-search for pattern matching, and local optimization, to exclude unnecessary circuit-search. In additionk, in order to reduce unnecessary trial of pattern matching, the matching order of circuit patern is included in the rule descriptions. The effectiveness of this system is shown by its application ot the circuits which are generated by a hardware compiler.

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Association Rule Mining by Environmental Data Fusion

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.279-287
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    • 2007
  • Data fusion is the process of combining multiple data in order to produce information of tactical value to the user. Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. In this paper, we develop was macro program for statistical matching which is one of five branch types for data fusion. And then we apply data fusion and association rule techniques to environmental data.

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Development of a Knowledge-Based Job Shop Scheduler Applying the Attribute-Oriented Induction Method and Simulation (속성지향추론법과 시뮬레이션을 이용한 지식기반형 Job Shop 스케쥴러의 개발)

  • 한성식;신현표
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.48
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    • pp.213-222
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    • 1998
  • The objective of this study is to develop a knowledge-based scheduler applying simulation and knowledge base. This study utilizes a machine induction to build knowledge base which enables knowledge acquisition without domain expert. In this study, the best job dispatching rule for each order is selected according to the specifications of the order information. And these results are built to the fact base and knowledge base using the attribute-oriented induction method and simulation. When a new order enters in the developed system, the scheduler retrieves the knowledge base in order to find a matching record. If there is a matching record, the scheduling will be carried out by using the job dispatching rule saved in the knowledge base. Otherwise the best rule will be added to the knowledge base as a new record after scheduling to all the rules. When all these above steps finished the system will furnish a learning function.

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A Multibit Tree Bitmap based Packet Classification (멀티 비트 트리 비트맵 기반 패킷 분류)

  • 최병철;이정태
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.3B
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    • pp.339-348
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    • 2004
  • Packet classification is an important factor to support various services such as QoS guarantee and VPN for users in Internet. Packet classification is a searching process for best matching rule on rule tables by employing multi-field such as source address, protocol, and port number as well as destination address in If header. In this paper, we propose hardware based packet classification algorithm by employing tree bitmap of multi-bit trio. We divided prefixes of searching fields and rule into multi-bit stride, and perform a rule searching with multi-bit of fixed size. The proposed scheme can reduce the access times taking for rule search by employing indexing key in a fixed size of upper bits of rule prefixes. We also employ a marker prefixes in order to remove backtracking during searching a rule. In this paper, we generate two dimensional random rule set of source address and destination address using routing tables provided by IPMA Project, and compare its memory usages and performance.

Robust position estimation using POMDP

  • Kang, Daehee
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.328-333
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    • 1996
  • In this paper, we propose a new method to estimate robot position without landmark. At first, it is studied to estimate robot state using Markov decision rule. And, a matching method is discussed for estimating current position more accurately under the estimated current state. At second, we combine or fuse the matching method with the POMDP method in order to estimate the position under a dynamically changing environment. Finally we will show that our method can estimate the position precisely and robustly of which error are not cumulated through simulation results.

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The Study on matrix based high performance pattern matching by independence partial match (독립 부분 매칭에 의한 행렬 기반 고성능 패턴 매칭 방법에 관한 연구)

  • Jung, Woo-Sug;Kwon, Taeck-Geun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.9B
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    • pp.914-922
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    • 2009
  • In this paper, we propose a matrix based real-time pattern matching method, called MDPI, for real-time intrusion detection on several Gbps network traffic. Particularly, in order to minimize a kind of overhead caused by buffering, reordering, and reassembling under the circumstance where the incoming packet sequence is disrupted, MDPI adopts independent partial matching in the case dealing with pattern matching matrix. Consequently, we achieved the performance improvement of the amount of 61% and 50% with respect to TCAM method efficiency through several experiments where the average length of the Snort rule set was maintained as 9 bytes, and w=4 bytes and w=8bytes were assigned, respectively, Moreover, we observed the pattern scan speed of MDPI was 10.941Gbps and the consumption of hardware resource was 5.79LC/Char in the pattern classification of MDPI. This means that MDPI provides the optimal performance compared to hardware complexity. Therefore, by decreasing the hardware cost came from the increased TCAM memory efficiency, MDPI is proven the cost effective high performance intrusion detection technique.

A Study of Association Rule Mining by Clustering through Data Fusion

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.927-935
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    • 2007
  • Currently, Gyeongnam province is executing the social index survey every year to the provincials. But, this survey has the limit of the analysis as execution of the different survey per 3 year cycles. The solution of this problem is data fusion. Data fusion is the process of combining multiple data in order to provide information of tactical value to the user. But, data fusion doesn#t mean the ultimate result. Therefore, efficient analysis for the data fusion is also important. In this study, we present data fusion method of statistical survey data. Also, we suggest application methodology of association rule mining by clustering through data fusion of statistical survey data.

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An Online Personal Rapid Transit Dispatching Algorithm Based on Nearest Neighbor Dispatching Rule (최근린 배차 규칙 기반 온라인 Personal Rapid Transit 배차 알고리즘)

  • Han, Chung-Kyun;Kwon, Bo Bea;Kim, Baek-Hyun;Jeong, Rag-Gyo;Lee, Hoon;Ha, Byung-Hyun
    • Journal of the Korea Society for Simulation
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    • v.23 no.4
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    • pp.97-109
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    • 2014
  • Personal rapid transit (PRT) is a new transportation system, which is energy efficient and brings high quality of customer service. Customers arrive dynamically at stations and request transportation service. In this paper, we propose a new online PRT dispatching algorithm for pickup and delivery of customers. We adopt the nearest neighbor dispatching rule, which is known as performing well in general. We extend the rule with bipartite matching in order to deal with multiple vehicles and customers at the same time. We suggest a systematic way for selecting vehicles that will be considered to be dispatched, since the scope with which vehicles are selected may affect the system performance. We regard the empty travel distance of vehicles and the customer waiting time as the performance measures. By using simulation experiments, it has been examined that the scope of dispatching affects the system performance. The proposed algorithm has been validated by comparing with other dispatching rules for transportation services. We have shown that our algorithm is more suitable for PRT operating environment than other dispatching rules.

Pattern Partitioning and Decision Method in the Semiconductor Chip Marking Inspection (반도체 부품 마크 미세 결함 검사를 위한 패턴 영역 분할 및 인식 방법)

  • Zhang, Yuting;Lee, Jung-Seob;Joo, Hyo-Nam;Kim, Joon-Seek
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.9
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    • pp.913-917
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    • 2010
  • To inspect the defects of printed markings on the surface of IC package, the OCV (Optical Character Verification) method based on NCC (Normalized Correlation Coefficient) pattern matching is widely used. In order to detect the micro pattern defects appearing on the small portion of the markings, a Partitioned NCC pattern matching method was proposed to overcome the limitation of the NCC pattern matching. In this method, the reference pattern is first partitioned into several blocks and the NCC values are computed and are combined in these small partitioned blocks, rather than just using the NCC value for the whole reference pattern. In this paper, we proposed a method to decide the proper number of partition blocks and a method to inspect and combine the NCC values of each partitioned block to identify the defective markings.