• Asia Marketing Journal
• /
• 제25권3호
• /
• pp.148-159
• /
• 2023

As Major League Baseball (MLB)'s continuous decline in popularity has caused its game attendance to drop gradually, the league makes a desperate attempt such as game rule changes to remain relevant. Along with the introduction of new rules to make games more dynamic such as the pitch clock, bigger bases, and defensive shift limitations, it is important for MLB franchises to understand drivers for game attendance. We focus on the effect of accumulated winning performance of the two teams on game attendance, one of the key drivers of game attendance, and investigate how it is influenced by consumer and industry factors such as online search and game rule changes. We find that game attendance increases as the prior winning performance of the home (away) team increases (decreases). We also find that online search and rule changes for more dynamic games moderate the effect of winning performance on game attendance.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 춘계정기학술대회
• /
• pp.253-260
• /
• 2001

Understanding and adapting to changes of customer behavior is an important aspect for a company to survive in continuously changing environment. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different time snapshots. For this purpose, we first define three types of changes as emerging pattern, unexpected change and the added / perished rule. Then we develop similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is evaluated to detect significantly changed rules. Our proposed methodology can evaluate degree of changes as well as detect all kinds of change automatically from different time snapshot data. A case study for evaluation and practical business implications for this methodology are also provided.

• 한국컴퓨터정보학회논문지
• /
• 제21권10호
• /
• pp.99-105
• /
• 2016

The active rule system is a key element of the rule-based mobile agent middleware system for activeness and autonomy of the sensor network. The rule manager, which is the main components of active rule based mobile agent framework and active rule system, performs the control and management of the rule-related processes. In this paper, we design and implement the roles and functions of the rule manager in detail. The proposed rule manager plays an important role in the sensor network environment. The sensor data server loads the active rule on the mobile agent by the rule manager according to the situations, and the mobile agent migrates to the destination node and performs the designated action. This active rule-based mobile agent middleware system presents the usefulness for the various sensor network applications. Through the rule execution experiment using the rule-based mobile agent, we show the adaptability and applicability of rule-based mobile agent middleware system to the dynamic environmental changes in sensor networks.

• 대한기관윤리심의기구협의회지
• /
• 제2권1호
• /
• pp.1-5
• /
• 2020

The U.S. Department of Health and Human Services and fifteen other Federal Departments and Agencies have issued final revisions to the Federal Policy for the Protection of Human Subjects (the Common Rule, 45 CFR 46, Subpart A). The Common Rule was initially promulgated in 1991 and amended in 2005. The Final Rule to update the current regulations was published in the Federal Register on 19 January 2017. The final compliance date of the revised Common Rule including the cooperative research requirement is effective on 20 January 2020 after twice to delay. The revised Common Rule aims to make more effective conduct of minimal risk research reflecting modern research activities and recognize evolving technologies, including mobile technologies, internet, and the growth in computing power. The revisions to the Common Rule were based on a variety of sources of public, stakeholder, and expert comments. The author summarized the key changes and the implications to Korean human research regulations.

• Journal of information and communication convergence engineering
• /
• 제8권1호
• /
• pp.89-94
• /
• 2010

The most important of rule-base system is the knowledge base that determines the power of rule-base system. The important form of this knowledge is how to descript kinds of rules. The Rule-Base System (RBS) has been using in many field that need reflect quickly change of business rules in management system. As far, when develop the Rule-Based System, we must make a rule engine with a general language. There are three disadvantage of in this developed method. First, while there are many data that must be processed in the system, the speed of processing data will become very slow so that we cannot accept it. Second, we cannot change the current system to make it adaptive to changes of business rules as quickly as possible. Third, large data make the rule engine become very complex. Therefore, in this paper, we propose the two important methods of raising efficiency of Rule-Base System. The first method refers to using the Relational database technology to process the rules of the Rule-Base System, the second method refers to a algorithm of according to Quine McCluskey formula compress the rows of rule table. Because the expressive languages of rule are still remaining many problems, we will introduce a new expressive language, which is Rule-Base Data Model short as RBDM in this paper.

• 한국수자원학회논문집
• /
• 제37권7호
• /
• pp.569-579
• /
• 2004

최근 들어 지구온난화와 기상조건의 변화로 기후의 변동폭이 증가하면서 극심한 가물이 자주 발생하고 있다. 또한 기 개발된 용수원의 수질 오염, 물 분배에 관한 상류지역의 반대 및 지방자치단체간의 수리권 문제 등도 상류지역으로부터의 맑은 수자원 확보를 필요하게 만드는 요인이다. 따라서 이에 대한 용수공급 관리 방안의 필요성에 대한 인식이 부각되고 있으며, 수도권의 용수수요 변화에 대한 북한강 유역 댐의 용수공급 능력에 대한 적절한 검토가 필요한 실정이다. 본 연구에서는 북한강 유역 댐의 용수공급 가능성을 파악하고 적절한 용수 공급방안을 제시하기 위하여 shared vision 모형인 스텔라 소프트웨어를 이용한 모의 운영시스템을 개발하였다. 또한 이 모형에서는 수위에 따른 평균의 최소, 중간, 최대의 조건으로 3가지 Rule을 정하여 저수지의 운영곡선의 변화와 발전방류에 따른 안전 공급율 변화를 분석하였다.

• 반도체디스플레이기술학회지
• /
• 제17권1호
• /
• pp.6-11
• /
• 2018

With the development of the Internet of Things technology, a system that ensures the self-adaptability of an environment that includes various IoT devices is attracting public attention. The rules for determining behavior rules in existing self-adaptation systems are based on the assumption of changes in system members and environment. However, in the IoT environment, flexibility is required to determine the behavior rules of various types of IoT devices that change in real time. In this paper, we propose a rule configuration in a self-adaptive system using SWRL based on OWL ontology. The self-adaptive system using the OWL - SWRL rule configuration has two advantages. The first is based on OWL ontology, so we can define the characteristics and behavior of various types of IoT devices as an integrated concept. The second is to define the concept of a rule as a specific language type, and to add, modify and delete a rule at any time as needed. Through the rule configuration in the adaptive system, we have shown that the rule defined in SWRL can provide flexibility and deeper concept expression function to adaptability to IoT environment.

• 대한전자공학회논문지
• /
• 제27권1호
• /
• pp.37-45
• /
• 1990

In this paper, a knowledge base editor is presented as a supporting environment for an expert system building tool, OPS5. The knowledge base editor is especially useful for the fast and easy development of a knowledge base when the OPS5 production language is used. This knowledge base editor has some special facilities such as syntax and type checking, rule browsing and automatic bokkeeping. The syntax and type checking provides the facilities to find syntax and type errors in an edited knowledge base, respectively. The rule browsing facility offers various pattern matching schemes to see the causes and effects of a concerned rule. Automatic bookkeeping keeps the updated date and user name of a rule for the later reference whenever a user adds or changes a rule.

• 대한원격탐사학회지
• /
• 제27권6호
• /
• pp.637-651
• /
• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• 한국경영과학회지
• /
• 제25권4호
• /
• pp.81-95
• /
• 2000

A knowledge-based system with fuzzy production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of real system when we make inferences with a knowledge-based system. This paper proposes a strategy of dynamic inferencing for a knowledge-based system with fuzzy production rules. The strategy suggested in this paper applies weights of attributes of conditions of a rule in the knowledge-base. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by AHP(Analytic Hierarcy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with MIN operator, into a single DM for the rule. In this way, overall DM for a rule changes depending on the importance of attributes of the rule. As a result, the dynamic nature of a real system can be incorporated in an inference with fuzzy production rules.