• Title/Summary/Keyword: Rule Set

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Knowledge-Based System for Rule Scantling Based on Object-Oriented Knowledge Representation and Open Architecture Concepts (객체지향적 지식표현과 개방형설계에 의한 구조부재 치수 결정 지원 시스템 개발)

  • Kyung-Ho Lee;Dong-Kon Lee;Soon-Hung Han;Kyu-Yeul Lee;Kyu-Chul Lee
    • Journal of the Society of Naval Architects of Korea
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    • v.30 no.2
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    • pp.30-36
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    • 1993
  • An expert system to help a novice engineer in designing midship section is developed. The system is developed based on a general-purpose expert system shell, NEXPERT. Firstly, the design knowledge is extracted from an existing rule scantling program. The knowledge has been grouped and structured into a hierarchy by applying object-oriented concepts. Secondly, the knowledge base is integrated with a database of existing ships and engineering analysis modules through the Application Programming Interface(API)technique. Graphical User Interface which is developed using Motif wiget set is adopted. These altogether enable construction of an user friendly expert system.

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A Study on the Language Independent Dictionary Creation Using International Phoneticizing Engine Technology (국제 음소 기술에 의한 언어에 독립적인 발음사전 생성에 관한 연구)

  • Shin, Chwa-Cheul;Woo, In-Sung;Kang, Heung-Soon;Hwang, In-Soo;Kim, Suk-Dong
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.1E
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    • pp.1-7
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    • 2007
  • One result of the trend towards globalization is an increased number of projects that focus on natural language processing. Automatic speech recognition (ASR) technologies, for example, hold great promise in facilitating global communications and collaborations. Unfortunately, to date, most research projects focus on single widely spoken languages. Therefore, the cost to adapt a particular ASR tool for use with other languages is often prohibitive. This work takes a more general approach. We propose an International Phoneticizing Engine (IPE) that interprets input files supplied in our Phonetic Language Identity (PLI) format to build a dictionary. IPE is language independent and rule based. It operates by decomposing the dictionary creation process into a set of well-defined steps. These steps reduce rule conflicts, allow for rule creation by people without linguistics training, and optimize run-time efficiency. Dictionaries created by the IPE can be used with the Sphinx speech recognition system. IPE defines an easy-to-use systematic approach that can lead to internationalization of automatic speech recognition systems.

A Model for Production Planning in a Multi-item Production System -Multi-item Parametric Decision Rule- (다품목(多品目) 생산체제(生産體制)의 생산계획(生産計劃)을 위한 모델)

  • Choe, Byeong-Gyu
    • Journal of Korean Institute of Industrial Engineers
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    • v.1 no.2
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    • pp.27-38
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    • 1975
  • This paper explores a quantitative decision-making system for planning production, inventories and work-force in a multi-item production system. The Multi-item Parametric Decision Rule (MPDR) model, which assumes the existence of two types of linear feed-back rules, one for work-force level and one for production rates, is basically an extension of the existing method of Parametric Production Planning (PPP) proposed by C.H. Jones. The MPDR model, however, explicitly considers the effect of manufacturing progress and other factors such as employee turn-over, difference in work-days between month etc., and it also provides decision rules for production rates of individual items. First, the cost relations of the production system are estimated in terms of mathematical functions, and then decision rules for work-force level and production rates of individual items are establised based upon the estimated objective cost function. Finally, a direct search technique is used to find a set of parameters which minimizes the total cost of the objective function over a specified planning horizon, given estimates of future demands and initial values of inventories and work-force level. As a case problem, a hypothetical decision rule is developed for a particular firm (truck assembly factory).

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Knowledge Based Recommender System for Disease Diagnostic and Treatment Using Adaptive Fuzzy-Blocks

  • Navin K.;Mukesh Krishnan M. B.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.2
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    • pp.284-310
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    • 2024
  • Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

Improving Automobile Insurance Repair Claims Prediction Using Gradient Decent and Location-based Association Rules

  • Seongsu Jeong;Jong Woo Kim
    • Asia pacific journal of information systems
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    • v.34 no.2
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    • pp.565-584
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    • 2024
  • More than 1 million automobile insurance repairs occur per year globally, and the related repair costs add up to astronomical amounts. Insurance companies and repair shops are spending a great deal of money on manpower every year to claim reasonable insurance repair costs. For this reason, promptly predicting insurance claims for vehicles in accidents can help reduce social costs related to auto insurance. Several recent studies have been conducted in auto insurance repair prediction using variables such as photos of vehicle damage. We propose a new model that reflects auto insurance repair characteristics to predict auto insurance repair claims through an association rule method that combines gradient descent and location information. This method searches for the appropriate number of rules by applying the gradient descent method to results generated by association rules and eventually extracting main rules with a distance filter that reflects automobile part location information to find items suitable for insurance repair claims. According to our results, predictive performance could be improved by applying the rule set extracted by the proposed method. Therefore, a model combining the gradient descent method and a location-based association rule method is suitable for predicting auto insurance repair claims.

Using rough set to develop the optimization strategy of evolving time-division trading in the futures market (러프집합을 활용한 캔들스틱 트레이딩 최적화 전략)

  • Kim, Hyun-Ho;Oh, Kyong-Joo
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.5
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    • pp.881-893
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    • 2012
  • This paper proposes to develop system trading strategy using rough set, decision tree in futures market. While there is a great deal of literature about the analysis of data mining, there is relatively little work on developing trading strategies in futures markets. There are three objectives in this paper. The first objective is to analysis performance of decision tree in rule-based system trading. The second objective is to find proper profitable trading interval. The last objective is to find optimized training period of trading rule training. The results of this study show that proposed model is useful trading strategy in foreign exchange market and can be desirable solution which gives lots of investors an important investment information.

Distributed Algorithm for Maximal Weighted Independent Set Problem in Wireless Network (무선통신망의 최대 가중치 독립집합 문제에 관한 분산형 알고리즘)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.5
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    • pp.73-78
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    • 2019
  • This paper proposes polynomial-time rule for maximum weighted independent set(MWIS) problem that is well known NP-hard. The well known distributed algorithm selects the maximum weighted node as a element of independent set in a local. But the merged independent nodes with less weighted nodes have more weights than maximum weighted node are frequently occur. In this case, existing algorithm fails to get the optimal solution. To deal with these problems, this paper constructs maximum weighted independent set in local area. Application result of proposed algorithm to various networks, this algorithm can be get the optimal solution that fail to existing algorithm.

Parallel Multiple Hashing for Packet Classification

  • Jung, Yeo-Jin;Kim, Hye-Ran;Lim, Hye-Sook
    • Proceedings of the IEEK Conference
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    • 2004.06a
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    • pp.171-174
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    • 2004
  • Packet classification is an essential architectural component in implementing the quality-of-service (QoS) in today's Internet which provides a best-effort service to ail of its applications. Multiple header fields of incoming packets are compared against a set of rules in packet classification, the highest priority rule among matched rules is selected, and the packet is treated according to the action of the rule. In this Paper, we proposed a new packet classification scheme based on parallel multiple hashing on tuple spaces. Simulation results using real classifiers show that the proposed scheme provides very good performance on the required number of memory accesses and the memory size compared with previous works.

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A Study on the Planning Characteristics of Infill System for Long Life Housing Applied with MC Design (MC설계를 적용한 장수명주택 인필의 계획특성에 관한 연구)

  • Wang, Woo-Chul;Lim, Seok-Ho
    • Journal of the Korean housing association
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    • v.27 no.1
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    • pp.63-70
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    • 2016
  • Domestic apartment housing has been designed in accordance with the new housing supply-driven policies for a long time. As a result, its design, material production, construction, maintenance and remodeling process, rather than being systematically performed, were individually approached to cause insufficient linkage between technologies. For these problems and the supply of long life housing, active research on long life housing has been conducted in Korea since 2005. However, the existing research on long life housing has been focused on a single item with no connection made between infill systems, and no overall interface rule, resulting in no activation of the business. In this study, for the supply and activation of long life housing, we aim to analyze the problems of existing long life housing to set up its matching standards for infill systems.

A Maintenance Policy Determination of Dependent k-out-of-n:G System with Setup Cost (초기설치비를 고려한 의존적 k-out-of-n:G 시스템의 보전정책 결정)

  • 조성훈;안동규;성혁제;신현재
    • Journal of the Korean Society of Safety
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    • v.14 no.2
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    • pp.155-162
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    • 1999
  • reliability from components reliability. In this case, it assumes that components failure is mutually independent, but it may not true in real systems. In this study, the mean cost per unit time is computed as the ratio of mean life to the mean cost. The mean life is obtained by the reliability function under power rule model. The mean cost is obtained by the mathematical model based on the inspection interval. A heuristic method is proposed to determine the optimal number of redundant units and the optimal inspection interval to minimize the mean cost per unit time. The assumptions of this study are as following : First, in the load-sharing k-out-of-n:G system, total loads are applied to the system and shared by the operating components. Secondly, the number of failed components affects the failure rate of surviving components as a function of the total load applied. Finally, the relation between the load and the failure rate of surviving components is set by the power rule model. For the practical application of the above methods, numerical examples are presented.

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