• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.817-827
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• 2007

In the age of ubiquitous environment, huge number of devices and computing services are provided to users. Personalized service, which is modeled according to the character of each and every individual is of particular need. In order to provide various dynamic services according to user's movement, service unit and operating mode should be able to operate automatically with minimum user intervention. In this paper, we discuss the steps of offering approximate service based on user's request in ubiquitous environment. First, we present our simulator designed for modeling the physical resource and computing object in smart space - the infrastructure in ubiquitous. Second, intelligent agents, which we developed based on a FIPA specification compliant multi-agent framework will be discussed. These intelligent agents are developed for achieving the service goal through cooperation between distributed agents. Third, we propose an automated service discovery and composition method in heterogeneous environment using semantic message communication between agents, according to the movement by the user interacting with the service available in the smart space. Fourth, we provide personalized service through agent monitoring anytime, anywhere from user's profile information stored on handhold device. Therefore, our research provides high quality service more than general automated service operation.

• Tuberculosis and Respiratory Diseases
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• v.75 no.5
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• pp.181-187
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• 2013

The emergence of new therapeutic agents for non-small cell lung cancer (NSCLC) implies that histologic subtyping and molecular predictive testing are now essential for therapeutic decisions. Histologic subtype predicts the efficacy and toxicity of some treatment agents, as do genetic alterations, which can be important predictive factors in treatment selection. Molecular markers, such as epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement, are the best predictors of response to specific tyrosine kinase inhibitor treatment agents. As the majority of patients with NSCLC present with unresectable disease, it is therefore crucial to optimize the use of tissue samples for diagnostic and predictive examinations, particularly for small biopsy and cytology specimens. Therefore, each institution needs to develop a diagnostic approach requiring close communication between the pulmonologist, radiologist, pathologist, and oncologist in order to preserve sufficient biopsy materials for molecular analysis as well as to ensure rapid diagnosis. Currently, personalized medicine in NSCLC is based on the histologic subtype and molecular status. This review summarizes strategies for tissue acquisition, histologic subtyping and molecular analysis for predictive testing in NSCLC.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.134-139
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• 2008

In this paper, we propose a story generation system using multi emotional agents. The proposed multi emotional agents are equipped with multiple emotional model so that it can be used as individually personalized agents that can generates unique storylines. Basically these kinds of multi emotional agents are easily employed as Avatar or NPC in computer games. In the proposed system, emotional agents are used as actor or actress whose characters and preferences are different each other. The storylines generated using the proposed system are realistic since the characters are emotional as humans.

• International Journal of Contents
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• v.4 no.2
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• pp.19-23
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• 2008

This paper presents a novel method to construct a personalized e-Learning system based on dynamic estimations of item parameters and learners' abilities, where the learning content objects are of the same intrinsic quality or homogeneously distributed and the estimations are carried out using IRT(Item Response Theory). The system dynamically connects the test and the corresponding learning procedures. Test results are directly applied to estimate examinee's ability and are used to modify the item parameters and the difficulties of learning content objects during the learning procedure is being operated. We define the learning unit 'Node' as an amount of learning objects operated so that new parameters can be re-estimated. There are various content objects in a Node and the parameters estimated at the end of current Node are directly applied to the next Node. We offer the most appropriate learning Node for a person's ability throughout the estimation processes of IRT. As a result, this scheme improves learning efficiency in web-base e-Learning environments offering the most appropriate learning objects and items to the individual students according to their estimated abilities. This scheme can be applied to any e-Learning subject having homogeneous learning objects and unidimensional test items. In order to construct the system, we present an operation scenario using the proposed system architecture with the essential databases and agents.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.125-143
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• 2015

As improving the life quality of citizen because of development of Urbanization and Information, civil application service of public institutions has been changed. The government provides a 24-hour civil service of e-government, public institutions operate U-complaints call center to pursue a personalized service to customers. As customer service are diversified, the inconvenience of service is increased. Therefore, public institutions instituted U-complaints call center to solve increased complaints. In early days, public institutions operated simple call center. However, it became intelligent U-complaints call center by SNS. The more increase the importance of agents' contact customer service, the more increase Job Performance considered by Organizational Commitment & Job Satisfaction of call center agents. This study analyzed that applied to Fairness Theory with Organizational Commitment, Job Satisfaction and analyze U-complaints call center agents' role and job performance of public institutions. Proposed a research model applied to job satisfaction with key variables, organizational commitments, job satisfaction. It's expected to impact on job performance of U-complaints call center agents in public institutions. For empirical study of research model, conducted a survey of the U-complaints call center agents of public institutions. 170 samples were collected from the survey and analyze relationship between the factors. Procedural justice, distribution fairness, fairness interaction are significant influence on organizational commitment of parameters by analysis U-complaints call center agents. Procedural justice and fairness of interaction was found not to effect on parameters of job satisfaction. Also, parameter, organizational commitment have significant influence on job satisfaction. However, have no influence on job performance. Therefore, the parameters of job satisfaction have significant influence on job performance. Public institutions should adopt to improve the quality of citizen services through U-complaints call center agents.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.268-271
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• 2003

In this paper, we propose a new framework based on negotiatory mobile multi agent system, and implement a mobile multi agent environment based on DECAF(Distributed Environment-Centered Agent Framework) which is one of the distributed agent development toolkit so as to implement a new PDS(Personal Digital Library System). The new framework has some optimality and higher performance in distributed environments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.29-33
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• 2004

I propose a personalized digital library system (PDLS) based on an advanced distributed agent platform. The new platform is developed by improving the DECAF (Distributed Environment-Centered Agent Framework) which is one of the conventional distributed agent development toolkits. Also, a mobile ORB (Object Request Broker), Voyager, and a new multi agent negotiation algorithm are adopted to develop the advanced platform. The new platform is for mobile multi agents as well as the distributed environment, whereas the DECAF is for the distributed and non-mobile environment. From the results of the simulation the searched time of PDLS is lower, as the numbers of servers and agents are increased. And the user satisfaction is four times greater than the conventional client-server model. Therefore, the new platform has some optimality and higher performance in the distributed mobile environment.

• Journal of Digestive Cancer Research
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• v.6 no.2
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• pp.45-49
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• 2018

Colorectal cancer (CRC) is the third most common cause of cancer-related death in the world. Although the long-term outcome of patients with metastatic CRC is still poor, target therapy including anti EGFR agents and anti VEGF agents and immunotherapy including anti PD-1 antibody and anti CTLA-4 antibody have shown clinical benefits in the treatment of patient with metastatic CRC. In the future, the personalized treatment strategy based on the clinical characteristics and biologic features of patients with metastatic CRC will be necessary. In this review, we summarized the mechanisms and clinical evidences of target therapy and immunotherapy, and the guideline of clinical practice in patients with metastatic CRC.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.473-480
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• 2006

Recently, remote education systems for web-based teaching-studying are rapidly increased. Also, a request for customized courseware suitable for individual learner's level and learning pattern is increasing. But, most remote education systems do not provide customized learning service fit for each learner's level and lots of learners easily lose their interest in studying. Therefore, a lot of researchers have tried to provide personalized customized learning service by analyzing leaner's level and learning pattern automatically with agents. In this paper, we designed and implemented a customized courseware for studying the computer application. There are four agents such as professor, assistant, student, and monitor agent in CCA and they cooperate with each other to provide learning contents suited to each learner's level.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.485-492
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• 2001

Recently, character agents are used as a user-friendly interface. In this paper, we have studied a generic framework for emotional character agents which are designed to infer emotions from diverse personalities, situations, user behaviors and to express them. The method of emotion inference is based on blackboard systems which are used to solve the problems in AI. Because it keeps independence between knowledge sources which are rules of emotions, a blackboard-based inference engine is easy to manage knowledge sources, Blackboard-based systems gave the system flexibility. So we can adapt the engine to various application systems. Each emotional agent monitors user behavior, learns user profile and infers user behavior. And it generates characters emotions according to the user profile. So, in case of same situations, the agent can generate different emotions according to users. We have studied to build an personalized emotional character agent which according to situations and user modeling.