Healthcare Expert System based on Group Cooperation Model

Romeo Mark A. Mateo,Jaewan Lee,Bobby D. Gerardo 보안공학연구지원센터 2008 International Journal of Software Engineering and Vol.2 No.1

Expert systems for healthcare are widely studied where accuracy of diagnosis and efficiency of the system for various healthcare services are examined. Also, recent researches include decision support services, expert medical services and autonomous management, which are based on multi-agent systems. The cooperation of agents is crucial in analyzing, and managing the data of patient in order to detect abnormal patterns so that it can provide an advance treatment. This research shows the implementation of healthcare expert system (HES) based on group cooperation model. Communications through the components of the group cooperation model are designed based on multi-agent approach. The proposed agent managers effectively coordinate the processing of client requests. Replica managers provide quality of service for clients by replicating objects. An adaptive scheme using round robin and fuzzy least load algorithms is managed by load balancing service. And in this paper, we presented the implementation by using CORBA for distributed objects and Jade Framework for agents..

Hierarchical Structured Multi-agent for Distributed Databases in Location Based Services

Mateo Romeo Mark A.,Lee Jaewan,Kwon Oh-Hyun Korea Association of Information Systems 2005 情報시스템硏究 Vol.14 No.3

Location management is very important in location-based services to provide services to the mobile users like banking, city guides and many more. Ubiquitous and mobile devices are the source of data in location management and its significant operations are update and search method. Some studies to improve these were presented by using optimal sequential paging, location area scheme and hierarchical database scheme. In addition, not all location services have the same access methods on data and it lead to difficulties of providing services. A proposed location management of multi-agent architecture is presented in this study. It shows the coordination of the agents on the distributed database of location-based services. The proposal focuses on the location management of the mobile object presented in a hierarchical search and update. Also, it uses a nearest neighbor technique for efficient search method of mobile objects.

Scalable Search based on Fuzzy Clustering for Interest-based P2P Networks

( Romeo Mark A. Mateo ),( Jaewan Lee ) 한국인터넷정보학회 2011 KSII Transactions on Internet and Information Syst Vol.5 No.1

An interest-based P2P constructs the peer connections based on similarities for efficient search of resources. A clustering technique using peer similarities as data is an effective approach to group the most relevant peers. However, the separation of groups produced from clustering lowers the scalability of a P2P network. Moreover, the interest-based approach is only concerned with user-level grouping where topology-awareness on the physical network is not considered. This paper proposes an efficient scalable search for the interest-based P2P system. A scalable multi-ring (SMR) based on fuzzy clustering handles the grouping of relevant peers and the proposed scalable search utilizes the SMR for scalability of peer queries. In forming the multi-ring, a minimized route function is used to determine the shortest route to connect peers on the physical network. Performance evaluation showed that the SMR acquired an accurate peer grouping and improved the connectivity rate of the P2P network. Also, the proposed scalable search was efficient in finding more replicated files throughout the peer network compared to other traditional P2P approaches.

Dynamic Service Assignment based on Proportional Ordering for the Adaptive Resource Management of Cloud Systems

( Romeo Mark A. Mateo ),( Jaewan Lee ) 한국인터넷정보학회 2011 KSII Transactions on Internet and Information Syst Vol.5 No.12

The key issue in providing fast and reliable access on cloud services is the effective management of resources in a cloud system. However, the high variation in cloud service access rates affects the system performance considerably when there are no default routines to handle this type of occurrence. Adaptive techniques are used in resource management to support robust systems and maintain well-balanced loads within the servers. This paper presents an adaptive resource management for cloud systems which supports the integration of intelligent methods to promote quality of service (QoS) in provisioning of cloud services. A technique of dynamically assigning cloud services to a group of cloud servers is proposed for the adaptive resource management. Initially, cloud services are collected based on the excess cloud services load and then these are deployed to the assigned cloud servers. The assignment function uses the proposed proportional ordering which efficiently assigns cloud services based on its resource consumption. The difference in resource consumption rate in all nodes is analyzed periodically which decides the execution of service assignment. Performance evaluation showed that the proposed dynamic service assignment (DSA) performed best in throughput performance compared to other resource allocation algorithms.

A Notification Framework for Messaging Support in Parking Guidance System

Romeo Mark A. Mateo,Frank Elijorde,Jaewan Lee 한국정보통신학회 2012 2016 INTERNATIONAL CONFERENCE Vol.5 No.1

Intelligent Search Mechanism based on Neuro-fuzzy System for the Distributed Object Groups

Romeo Mark A. Mateo,Jaewan Lee 보안공학연구지원센터 2008 International Journal of Security and Its Applicat Vol.2 No.1

Current research in distributed systems focuses on object group models which are designed for scalable systems and provide accessible objects to the entire group. However, dynamic grouping using knowledge extraction from group of objects is not considered which provides accurate search for appropriate objects. In this paper, an integration of intelligent models in distributed object groups is presented in intelligent distributed framework. This paper proposes a locator service for the framework which implements the intelligent search mechanism based on neuro-fuzzy system. To have an accurate search of objects, the fuzzy system of the locator service is trained using the neuron-fuzzy algorithm. The proposed method is compared to other methods in accuracy of classification and result shows that it outperformed other algorithm based on processing time and accuracy.

클라우드 시스템에서 소셜 시멘틱 웹 기반 협력 프레임 워크

마테오로미오 ( Romeo Mark A. Mateo ),양현호 ( Hyunho Yang ),이재완 ( Jaewan Lee ) 한국인터넷정보학회 2012 인터넷정보학회논문지 Vol.13 No.1

클라우드 서비스는 비즈니스 향상을 위해 사용되며, 특히, 고객 관리에서는 고객 서비스 향상을 위한 툴로서 소셜 네트워크를 사용한다. 그러나 대부분의 클라우드 시스템은 시멘틱 구조를 지원하지 않기 때문에 소셜 네트워크 사이트의 중요한 정보는 비즈니스정책을 위해 처리 및 사용이 어렵다. 본 연구에서는 클라우드 시스템에서 소셜 시멘틱 웹에 기반을 둔 협력 프레임 워크를 제안한다. 제안한 프레임 워크는 클라우드 소비자와 서비스 제공자를 위한 효율적인 협력시스템을 제공하기 위해, 소셜 시멘틱 웹 지원을 위한 요소들로 구성된다. 지식획득모듈은 소셜 에이전트가 수집한 데이터로부터 규칙을 추출하며, 이 규칙들은 협력 및 경영정책에 사용된다. 본 논문은 제안한 시멘틱 모델에서 소셜 네트워크 사이트 데이터의 처리 및 효율적인 협력을 위한 클라우드 서비스 제공자의 가상 그룹핑을 위해 사용될 패턴 추출에 대한 구현 결과를 보여준다. Cloud services are used for improving business. Moreover, customer relationship management(CRM) approaches use social networking as tools to enhance services to customers. However, most cloud systems do not support the semantic structures, and because of this, vital information from social network sites is still hard to process and use for business strategy. This paper proposes a collaboration framework based on social semantic web for cloud system. The proposed framework consists of components to support social semantic web to provide an efficient collaboration system for cloud consumers and service providers. The knowledge acquisition module extracts rules from data gathered by social agents and these rules are used for collaboration and business strategy. This paper showed the implementations of processing of social network site data in the proposed semantic model and pattern extraction which was used for the virtual grouping of cloud service providers for efficient collaboration.

유비쿼터스 주차관리를 위한 차량충돌 검증시스템

마테오로미오 ( Romeo Mark A. Mateo ),양현호 ( Hyunho Yang ),이재완 ( Jaewan Lee ) 한국인터넷정보학회 2011 인터넷정보학회논문지 Vol.12 No.5

WSN기반 주차관리 시스템에서 대부분의 연구는 주차장에서 사건을 통제하기 위해 무선 센서를 이용하지만, 주차장에서의 차량충돌에 대한 연구는 거의 수행되지 않았다. 시간에 따른 자세한 차량의 위치는 충돌 사건을 분석하는데 매우 중요하다. 본 연구는 주차장에서 차량 충돌사건을 감지하여 분석하고, 이를 차주에게 통보하는 충돌감지 방법을 제시한다. 차량의 위치 및 이동 방향을 감지하기 위해, 움직임 센서로부터의 정보를 활용하며, 빠른 OBB 교차 테스트를 사용하여 검증을 위한 객체를 추적한다. 성능평가 결과 위치추적 기법은 센서를 추가함에 따라 좀 더 정확함을 보였고, 제안한 OBB 충돌 테스트가 일반적인 OBB 교차테스트에 비해 속도가 향상됨을 나타내었다. Most researches in WSN-based parking management system used wireless sensors to monitor the events in a car parking area. However, the problem of car collisions in car parks was not discussed by previous researches. The car position details over time are vital in analyzing a collision event. This paper proposes a collision verification method to detect and to analyze the collision event in the parking area, and then notifies car owners. The detection uses the information from motion sensors for comprehensive details of position and direction of a moving car, and the verification processes an object tracking technique with a fast OBB intersection test. The performance tests show that the location technique is more accurate with additional sensors and the OBB collision test is faster compared to a normal OBB intersection test.

동적 그룹 바인딩 기반의 모바일 에이전트를 이용한 인텔리전트 분산 플랫폼

마테오로미오 ( Romeo Mark A. Mateo ),이재완 ( Jae-wan Lee ) 한국인터넷정보학회 2007 인터넷정보학회논문지 Vol.8 No.3

오늘날 정보 기술 및 지능형 시스템에서는 분산 데이터베이스로부터 패턴들을 찾고 규칙들을 추출하기 위해 데이터 마이닝 기술을 사용한다. 분산환경에서 데이터 마이닝 기술을 이용해 추출된 규칙들은 동적인 중복, 적응형 부하 균형 및 기타 기술들에서 활용될 수 있다. 그러나 대량의 데이터 전송은 에러를 야기하며 신뢰할 수 없는 결과를 초래할 수 있다. 이 논문은 이동 에이전트를 사용하여 동적 그룹 바인딩을 기반으로 한 인텔리전트 분산 플랫폼을 제안한다. 그룹서비스를 통해효율적인 객체 검색을 위한 분류 알고리즘을 구현한다. 지능형 모델은 동적 중복을 위해 추출된 규칙을 사용한다. 데이터 마이닝 에이전트와 데이터 압축 에이전트는 각각 서비스 노드 데이터베이스로부터 규칙을 추출하여 데이터를 압축한다. 제안한 알고리즘은 데이터를 전송하기 전에 neuro-fuzzy 분류기를 사용하여 빈도가 적은 데이터 셀을 합하는 전처리 과정을 수행한다. 객체그룹 분류, 서비스 노드 데이터베이스 마이닝, 데이터 압축 및 규칙 추출에 대한 시뮬레이션을 수행했다. 효율적인 데이터 압축 및 신뢰성 있는 규칙 추출에 대한 실험 결과 제안한 알고리즘이 다른 방법들과 비교해 이러한 관점에서 성능이 우수함을 나타내었다. The current trends in information technology and intelligent systems use data mining techniques to discover patterns and extract rules from distributed databases. In distributed environment, the extracted rules from data mining techniques can be used in dynamic replications, adaptive load balancing and other schemes. However, transmission of large data through the system can cause errors and unreliable results. This paper proposes the intelligent distributed platform based on dynamic group binding using mobile agents which addresses the use of intelligence in distributed environment. The proposed grouping service implements classification method for efficient search of objects. In this paper, the intelligent model uses the extracted rules for dynamic replication scheme of objects. Data compressor agent and data miner agent extracts rules and compresses data, respectively, from the service node databases. The proposed algorithm performs preprocessing where it merges the less frequent dataset using neuro-fuzzy classifier before sending the data. Object group classification, data mining the service node database, data compression method, and rule extraction were simulated. Result of experiments in efficient data compression and reliable rule extraction shows that the proposed algorithm has better performance compared to other methods.

그리드 시스템에서 그룹유사함수를 이용한 확장성 있는 자원공유

마테오로미오 ( Romeo Mark A. Mateo ),이재완 ( Jaewan Lee ),이말례 ( Malrey Lee ) 한국인터넷정보학회 2010 인터넷정보학회논문지 Vol.11 No.4

그리드 시스템에서의 확장성은 점증하고 있는 그리드 이용자를 수용하기 위해 효율적으로 설계되어야 한다. 본 논문은 그리드환경에서 확장성 가상조직(SVO: Scalable Virtual Organization)을 사용하여 VO들 간의 확장형 자원 공유 기법을 제시한다. 제안하는 그리드 구조는 SVO를 관리하기 위한 그리드 시스템의 표준 서비스들로 구성되며, 통합할 VO들을 선택하기 위해, VO들 간의 유사도를 결정하는 데 사용하는 그룹 유사함수를 제시한다. 다른 유사 함수들을 제시한 기법(GSF)과 비교하고, 시뮬레이션을 통해 SVO의 성능을 평가하였다. The scalability of a grid system should be efficiently designed to handle the increasing number of grid users. This paper presents a scalable resource sharing mechanism among virtual organizations (VO) in grid environment by the scalable virtual organizations (SVO). The proposed grid architecture is composed of standard services of a grid system to manage the SVO. We propose a group similarity function which is used to determine similarities among VOs to select the VOs to merge. We compared other similarity functions to the GSF and determined the throughput performance of the SVO using simulation for grid system.