• Title/Summary/Keyword: context model

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Driver Preference Based Traffic Information Recommender Using Context-Aware Technology (상황인식 기술을 이용한 운전자 선호도 기반 교통상세정보 추천 시스템)

  • Sim, Jae Mun;Kwon, Ohbyung;Kang, Ji Uk
    • Knowledge Management Research
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    • v.11 no.2
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    • pp.75-93
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    • 2010
  • Even though there have been many efforts on driver's route recommendation, driver still should get involved to choose the driving path in a manual manner. Uncertain traffic information provided to the driver delays his arrival time and hence may cause diminished economic values. One of the solutions of reducing the uncertainty is to provide various kinds of traffic information, rather than send real-time information. Therefore, as the wireless communication technology improves and at the same time volume of utilizable traffic contents increases in geometrical progression, selecting traffic information based on driver's context in a timely and individual manner will be needed. Hence, the purpose of this paper is to propose a methodology that efficiently sends the rich traffic contents to the personal in-vehicle navigation. To do so, driver preference is modeled and then the recommendation algorithm of traffic information contents was developed using the preference model. Secondly, ontology based traffic situation analyzation method is suggested to automatically inference the noticeable information from the traffic context on driver's route. To show the feasibility of the idea proposed in this paper, an open API service is implemented in consideration of ease of use.

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A Study of Integration Modelling for Context-aware Service Based on Ontology (온톨로지 기반의 상황인지 서비스를 위한 통합 모델에 관한 연구)

  • Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.253-255
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    • 2015
  • In a variety of network environments, the provision of context-aware services, it is difficult to integrate and share because of the heterogeneity problem between distributed data. This paper proposes the integration model using the ontology as a method for solving the above. This uses an ontology to integrate the context-aware informations that are collected. The ontology is generated by the acquisition, semantic analysis and inference of the metadata of the context-aware information. This is the basis of the analysis and analysis of the additional system. Accordingly, this paper studies ways to create an ontology and apply them. The advantage of the proposed scheme can be used without modifying the existing tools, it is possible to easily perform the expansion and consolidation of the system.

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Adaptive Security Management Model based on Fuzzy Algorithm and MAUT in the Heterogeneous Networks (이 기종 네트워크에서 퍼지 알고리즘과 MAUT에 기반을 둔 적응적 보안 관리 모델)

  • Yang, Seok-Hwan;Chung, Mok-Dong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.1
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    • pp.104-115
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    • 2010
  • Development of the system which provides services using diverse sensors is expanding due to the widespread use of ubiquitous technology, and the research on the security technologies gaining attention to solve the vulnerability of ubiquitous environment's security. However, there are many instances in which flexible security services should be considered instead of strong only security function depending on the context. This paper used Fuzzy algorithm and MAUT to be aware of the diverse contexts and to propose context-aware security service which provides flexible security function according to the context.

Decision Tree Based Context Clustering with Cross Likelihood Ratio for HMM-based TTS (HMM 기반의 TTS를 위한 상호유사도 비율을 이용한 결정트리 기반의 문맥 군집화)

  • Jung, Chi-Sang;Kang, Hong-Goo
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.2
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    • pp.174-180
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    • 2013
  • This paper proposes a decision tree based context clustering algorithm for HMM-based speech synthesis systems using the cross likelihood ratio with a hierarchical prior (CLRHP). Conventional algorithms tie the context-dependent HMM states that have similar statistical characteristics, but they do not consider the statistical similarity of split child nodes, which does not guarantee the statistical difference between the final leaf nodes. The proposed CLRHP algorithm improves the reliability of model parameters by taking a criterion of minimizing the statistical similarity of split child nodes. Experimental results verify the superiority of the proposed approach to conventional ones.

Driver's Behavioral Pattern in Driver Assistance System (운전자 사용자경험기반의 인지향상 시스템 연구)

  • Jo, Doori;Shin, Donghee
    • Journal of Digital Contents Society
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    • v.15 no.5
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    • pp.579-586
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    • 2014
  • This paper analyzes the recognition of driver's behavior in lane change using context-free grammar. In contrast to conventional pattern recognition techniques, context-free grammars are capable of describing features effectively that are not easily represented by finite symbols. Instead of coordinate data processing that should handle features in multiple concurrent events respectively, effective syntactic analysis was applied for patterning of symbolic sequence. The findings proposed the effective and intuitive method for drivers and researchers in driving safety field. Probabilistic parsing for the improving this research will be the future work to achieve a robust recognition.

User Centered Context-aware Smart Home Applications (사용자 중심의 환경맥락 기반 스마트 홈 응용)

  • 오유수;장세이;우운택
    • Journal of KIISE:Software and Applications
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    • v.31 no.2
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    • pp.111-125
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    • 2004
  • In this paper, we applied user-centered context to Smart Home Applications. Current research activities on smart home have just focused on the infrastructure without considering user's contexts and implementation cost. We first realized the user-centered personalized services using ubi-UCAM (a Unified Context-aware Application Model), which exploited contexts from various kinds of smart sensors. We, then, verified its usefulness in the ubiquitous computing-enabled home environment. It can be extended to various application areas since it guarantees independence between sensors and services. Accordingly, it will play a key role in future smart home environment.

Reasoning Non-Functional Requirements Trade-off in Self-Adaptive Systems Using Multi-Entity Bayesian Network Modeling

  • Saeed, Ahmed Abdo Ali;Lee, Seok-Won
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.3
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    • pp.65-75
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    • 2019
  • Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.

A Comparative Analysis of Healthcare-Associated Infection Policy in South Korea and Its Implications in Coronavirus Disease 2019

  • Jeong, Yoolwon;Kim, Kinam
    • Health Policy and Management
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    • v.31 no.3
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    • pp.312-327
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    • 2021
  • Background: Infection prevention and control (IPC) to manage healthcare-associated infection (HCAI) has emerged as one of the most significant public health issues in Korea. The purpose of this study is to draw implications in IPC policies by analyzing the context, process, and major actors in policy development and comparatively analyzing IPC policy contents of Korea with three other countries. Additionally, IPC policies were analyzed in the context of coronavirus disease 2019 (COVID-19) to provide implications for future pandemics and HCAI events. Methods: This study incorporates a qualitative approach based on document and content analysis, applying codes and thematic categorization. IPC policy contents are comparatively analyzed by adopting the concept model, developed by the World Health Organization, which consists of core components of IPC structure at the national and facility level. Results: National IPC policies were developed within a complex social and political context, through the involvement of various stakeholders. IPC policies in Korea place a high emphasis on establishing IPC programs and built environments in healthcare facilities, whereas there were potentials for improvement in policies involving patients and promoting a safety culture. IPC policies, which currently focus on general hospitals and certain functions of hospitals, should further be expanded to target all healthcare facilities and functions, to ensure more efficient and sustainable IPC responses in the current and future disease outbreaks. Conclusion: IPC is a complex policy arena and lessons learned from the analysis of existing policies in the context of COVID-19 should provide valuable strategic implications for future policies.

Context-awareness Clustering with Adaptive Learning Algorithm (상황인식 기반 클러스터링의 적응적 자율 학습 분할 알고리즘)

  • Jeon, Il-Kyu;Lee, Kang-whan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.612-614
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    • 2022
  • This paper propose a clustering algorithm for mobile nodes that possible more efficient clustering using context-aware attribute information in adaptive learning. In typically, the data will be provided to classify interrelationships within cluster properties. If a new properties are treated as contaminated information in comparative clustering, it can be treated as contaminated properties in comparison clustering. In this paper, To solve this problems in this paper, we have new present a context-awareness learning based model that can analyzes the clustering attributed parameters from the node properties using accumulated information properties.

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Development of Analytic Dicho-Hierarchy Process for Setting Priority of Technological Alternatives (기술대체안의 운선순위 설정을 위한 2분화 계층분석방법의 개발)

  • 조근태;권철신
    • Proceedings of the Technology Innovation Conference
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    • 2000.06a
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    • pp.35-46
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    • 2000
  • The Analytic Hierarchy Process(AHP) model developed by Saaty is a very useful decision-making model designed for selecting and evaluating project alternatives through $\ulcorner$pairwise comparison$\lrcorner$ in the context of hierarchical structure. In this paper, we construct a modified AHP model named Analytic Dicho-Hierarchy Process (ADHP) model necessary for evaluating technology alternatives.

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