• 제목/요약/키워드: Cognitive Complexity

검색결과 193건 처리시간 0.024초

장기요양환자에서 환자 특징 및 기능상태와 환자돌봄 시간과의 관련성 (A Relationship of Care Time with Functional Status and Patients Characteristics among Patients in Long-term Care Hospitals)

  • 이지전;김정인;유승흠;유형식;이상욱
    • Journal of Preventive Medicine and Public Health
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    • 제37권3호
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    • pp.282-291
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    • 2004
  • Objectives : The aim of this study was to investigate the functional status variables related to the care time of health professionals for patients in long-term care facilities. Methods : The functional stati of 1001 patients in 8 long-term care hospitals were examined by the Resident Assessment Instrument for Long-term Care Facility Version 2.0. The care time of health professionals for patients was calculated using data from a self-reported task survey by nurses, auxiliary nurses, private aides, doctors, physiotherapists and social workers. Results : The average care time per diem was 240.6 minutes. The care time by doctors, nurses and private aides were 11.0, 71.0 and 139.5 minutes, respectively. The lower the function of activities of daily living (ADL) and the greater the symptoms of extensive services, special care and clinical complexity, the more care time was served. On the contrary, the greater the symptoms of nursing rehabilitation, depression, cognitive disorder, behavior problem and psychiatry/mood disorder, the less care time was served. Age and gender were not significantly related to the care time. Conclusions : Developing a case mix classification system for elderly long term care patients may be helpful for both of patients and health care providers. The ADL, extensive services, special care and clinical complexity of variables should be considered in the development of a case mix system for the long term care of patients in Korea.

비즈니스 시뮬레이션으로 살펴본 스마트워크의 확산 기간과 생산성 연구 (The Diffusion Period and Productivity of Smartwork by Business Simulation)

  • 정병호
    • 디지털산업정보학회논문지
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    • 제17권1호
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    • pp.57-73
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    • 2021
  • The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.

Distributed Matching Algorithms for Spectrum Access: A Comparative Study and Further Enhancements

  • Ali, Bakhtiar;Zamir, Nida;Ng, Soon Xin;Butt, Muhammad Fasih Uddin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권4호
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    • pp.1594-1617
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    • 2018
  • In this paper, we consider a spectrum access scenario which consists of two groups of users, namely Primary Users (PUs) and Secondary Users (SUs) in Cooperative Cognitive Radio Networks (CCRNs). SUs cooperatively relay PUs messages based on Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperative techniques, in exchange for accessing some of the spectrum for their secondary communications. From the literatures, we found that the Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA) aim to maximize the PU sum-rate resulting in a lower sum-rate for the SU. In this contribution, we have investigated a suit of distributed matching algorithms. More specifically, we investigated SU-based CDA (CDA-SU) and SU-based PDA (PDA-SU) that maximize the SU sum-rate. We have also proposed the All User-based PDA (PDA-ALL), for maximizing the sum-rates of both PU and SU groups. A comparative study of CDA, PDA, CDA-SU, PDA-SU and PDA-ALL is conducted, and the strength of each scheme is highlighted. Different schemes may be suitable for different applications. All schemes are investigated under the idealistic scenario involving perfect coding and perfect modulation, as well as under practical scenario involving actual coding and actual modulation. Explicitly, our practical scenario considers the adaptive coded modulation based DF schemes for transmission flexibility and efficiency. More specifically, we have considered the Self-Concatenated Convolutional Code (SECCC), which exhibits low complexity, since it invokes only a single encoder and a single decoder. Furthermore, puncturing has been employed for enhancing the bandwidth efficiency of SECCC. As another enhancement, physical layer security has been applied to our system by introducing a unique Advanced Encryption Standard (AES) based puncturing to our SECCC scheme.

한글 입력 방식의 구현을 위한 범용적인 복합 낱자 분석 시스템 (Logic Analyzer of Composite Hangul Units for Implementation of Input Methods)

  • 김용묵;김국
    • 인지과학
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    • 제28권4호
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    • pp.223-243
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    • 2017
  • 한글 입력 방식은 어떤 형태이건 기본 낱자들에 대한 글쇠배열과 결합 규칙이라는 두 요소를 반드시 가진다. 그런데 그 규칙을 토대로 입력 방식을 실제로 구현해 보면, 기본 낱자가 여럿 모인 복합 낱자를 입력할 때 모호성이 존재하거나 다음 글자의 연속 입력이 되지 않는 식의 문제가 발생할 수 있다. 한글은 모아쓰기라는 특성으로 인해 낱자 경계와 글자 경계라는 보이지 않는 정보가 입력 과정에서 추가로 고려되어야하기 때문이다. 초성과 종성을 문맥에 따라 구분해야 하는 두벌식, 글쇠가 매우 적은 모바일 환경, 수십 종류의 낱자들을 조합해야 하는 옛한글이라는 조건이 더해지면 입력 방식을 기술하고 분석하는 난이도가 더욱 높아진다. 본 논문에서는 한글 입력 방식에서 쓰이는 낱자의 결합 규칙을 대결합과 소결합으로 구분해서 기술하는 체계를 제안하며, 이를 토대로 어떤 입력 방식이 주어졌을 때 복합 낱자를 입력하는 세부 규칙을 생성하고 예상되는 문제점을 자동으로 분석해 주는 도구 프로그램을 소개하였다. 그리고 모바일용 삼성 천지인과 KT나랏글 한글 입력 방식을 실제로 분석한 결과를 제시하였다.

영한 번역의 언어학적 평가 모델 연구 - 기계번역을 중심으로 - (A Linguistic Evaluation of English-to-Korean Translation - Centered on Machine Translation -)

  • 김덕봉;조병은;김명철;권용현
    • 인지과학
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    • 제12권4호
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    • pp.11-27
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    • 2001
  • 기계번역 품질 평가는 중대한 문제이다. 기계번역의 품질이 사용자 요구와 거리가 상당히 있는 현재의 상황에서 기계번역 시스템의 객관적 평가는 기계번역 소프트웨어 사용자와 판매자 간의 신뢰를 구축하고 개발자들 간에 생산적인 경쟁관계를 조성하게 하여 결과적으로 기계번역 품질의 고급화를 지속적으로 유도하는 역할을 할 것이다. 이를 위해서는 특히 언어학적 측면과 자료처리 측면에서 개선이 계속되고 있는지를 확인할 수 있도록 기계번역 시스템의 품질을 평가할 수 있는 연구가 있어야 한다. 본 논문에서는 이런 정들을 고려해 넣은 영한 기계번역의 언어학적 평가 방법을 제시하고 이를 몇 개의 상용 기계번역 시스템을 대상으로 실험하여 실험결과를 보고한다. 이 방법은 기본적으로 언어현상과 학습수준으로 분류된 3.373 영어 문장으로 구성된 평가자료에 기반하고 있다.

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A Novel Grasshopper Optimization-based Particle Swarm Algorithm for Effective Spectrum Sensing in Cognitive Radio Networks

  • Ashok, J;Sowmia, KR;Jayashree, K;Priya, Vijay
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권2호
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    • pp.520-541
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    • 2023
  • In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

수학 교과서 과제의 수학적 모델링 과제로의 변형 과정에서 겪는 초등학교 교사의 어려움과 수학적 모델링 과제 개발을 위한 지식의 변화: 한 경력 교사의 사례를 중심으로 (Analyzing an elementary school teacher's difficulties and mathematical modeling knowledge improvement in the process of modifying a mathematics textbook task to a mathematical modeling task: Focused on an experienced teacher)

  • 정혜윤
    • 한국수학교육학회지시리즈A:수학교육
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    • 제62권3호
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    • pp.363-380
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    • 2023
  • 본 연구의 목적은 초등학교 교사가 수학 교과서 과제를 수학적 모델링 과제로 변형하는 과정에서 경험하는 어려움과 수학적 모델링 과제 개발을 위한 지식 변화의 사례를 분석하는 것이다. 이를 위해 10년 경력의 초등교사가 교사연구공동체의 반복적인 논의에 참여하면서 초등학교 5학년 수학의 자료와 규칙성 영역 중 평균 지도를 위한 과제를 수학적 모델링 과제로 변형하였다. 연구결과, 첫째, 교사는 과제 변형 과정에서 현실성의 반영, 수학적 모델링 과제의 적절한 인지적 수준 설정, 수학적 모델링 과정에 따른 세부 과제의 제시에 어려움을 겪었다. 둘째, 반복된 과제 변형을 통해, 교사는 학습 내용과 학생의 인지적 수준을 고려한 현실성 있는 과제의 개발, 과제의 복잡성 및 개방성 조정을 통한 과제의 인지적 수준 조정, 학생의 과제 해결 과정에 대한 사고실험을 통한 수학적 모델링 과정에 따른 세부 과제의 제시를 수행할 수 있었으며, 이는 수학적 모델링의 개념과 과제의 특징 등 수학적 모델링 과제 개발을 위해 요구되는 교사 지식이 향상되었음 보여준다. 본 연구결과는 향후 수학적 모델링 교사교육과 관련하여, 교과서 과제 변형을 통한 수학적 모델링 과제 개발 역량 향상의 기회를 제공하는 교사교육, 수학적 모델링의 이론 및 실제를 결합한 교사교육, 교사연구공동체에의 참여를 통한 교사교육이 필요함을 보여준다.

차량 내 통합 컨트롤 유형에 따른 운전자 수행도 비교 (Comparisons of Driver Performance with Control Types of the Driver Information System)

  • 임형욱;박성준;정성욱;정의승
    • 대한인간공학회지
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    • 제26권1호
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    • pp.1-10
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    • 2007
  • As drivers spend more time in their cars, perception of driving a vehicle turns from utilizing a transportation means into residing in a personal space or even in moving office. Such a perception renders automobile manufacturers incorporate more vehicle functions, especially in-vehicle information systems As the number of system functions increases, the complexity of control and 2 types of display menus were designed after a literature review and a market analysis. With these controls and display menus, the experiment was performed to look into the difference of driver performance and preference on the integrated vehicle control type. Finally, the study suggests the integrated vehicle control type to minimize driver's cognitive load, and to use various functions efficiently. The study also discusses the practical use of the final integrated vehicle control type.

Governance Structures to Facilitate Collaboration of Higher Education Institutions (HEIs) and Science &Technology Parks

  • Kang, Byung-Joo
    • World Technopolis Review
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    • 제5권2호
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    • pp.108-118
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    • 2016
  • There are very few studies on governance structure for the collaboration between HEIs and science and technology parks until today. Major activities between science parks and HEIs are R&D activities, collaborative researches, technology transfer, space provision for BIs and Technology BIs in the science parks, provision of technical, legal and financial services for start-ups and venture firms. Governance structure for the collaboration of high education institutes with science and technology parks is the handling of complexity and management of dynamic flows of collaboration between two groups. Three models on the governance structure for the collaboration are suggested in this study. The first model is a governance structure that links R&D system such as universities, public research institutes and private research institutes with industrial production cluster such as a group of companies and industrial parks. The second model is a governance structure that has four layers of hierarchy. This hierarchical governance model is composed of four levels of organizations such as central government, three actors, one center for collaboration and many individual research performers. The third model is a governance structure that networks all the stakeholders horizontally. Under this structure, governance is conducted by the network members with no separate and unique governance entity.

개선된 데이터마이닝을 위한 혼합 학습구조의 제시 (Hybrid Learning Architectures for Advanced Data Mining:An Application to Binary Classification for Fraud Management)

  • Kim, Steven H.;Shin, Sung-Woo
    • 정보기술응용연구
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    • 제1권
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    • pp.173-211
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    • 1999
  • The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

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