• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.53-64
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• 2007

Purpose: This study was aimed to develop and evaluate of a Problem-based Learning (PBL) in the course of Nursing Management and Ethics. Method: The design of the study was both methodological and one group only pre-post design. The sample included 61 senior students who are currently enrolled in Nursing management and Ethics course in college of nursing. Data regarding PBL evaluation were collected on the critical thinking and clinical reasoning using structured questionnaires during March to June, 2005. Data were analyzed using descriptives and paired t-test. Results: A total of three PBL packages was developed by the two faculty members and two teaching assistants who are majoring in nursing management. PBL packages that had been developed was applied to 61 senior students for three months. Critical thinking and clinical reasoning were measured twice pre and post the application of PBL packages. There were statistically significant differences in the critical thinking and clinical reasoning between the pre and post PBL application. Conclusion: PBL was considered to be effective in understanding the learning concepts in the Nursing Management and Ethics. Further research on the facilitative strategies and development model considering the characteristics of Nursing Management and Ethics course is needed.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.287-295
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• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• PNF and Movement
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• v.14 no.3
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• pp.157-176
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• 2016

Purpose: The purpose of this study was to share an experience about processes and lessons learned to execute evidence-based practice (EBP) in neurological physical therapy. Methods: The most important thing in applying EBP to practice is to search, find, and appraise the existing evidence. Many evidence databases are available, such as CENTRAL, PEDro, PUBMED, and EMBASE. However, the knowledge represented in these databases is not always perfect. The practice model is a set of processes to resolve client problems. Therapists should make hypothesis-focused decisions through EBP. Integrating clinical reasoning and evidence is most important when it comes to the execution of EBP. Results: The process of EBP consisted of following: coming up with clinical questions, followed by searching for, appraising, evaluating, and integrating evidence. To integrate EBP into practice, it is necessary to consider clinical expertise, patient value and preferences, as well as research wth the best evidence. We provided an example of a clinical case with a stroke patient to show how this process and framework concerning clinical reasoning through evidences can be integrateds. During this process, we also utilized information technology to improve EBP ability. Conclusion: We should recognize what manner of information is needed to resolve eash patient's problem, and we should search for this information efficiently. Then, we should judge the value of the information obtained as it applies, to the clinical setting.

• Journal of Korean Physical Therapy Science
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• v.18 no.1
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• pp.33-49
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• 2011

The process of physical therapy uses a problem-solving approach to enhance a patients's functioning status. The International Classification of Functioning, Disability and Health(ICF) is the common concept for the functioning in the world. Physical therapists require the ability to identify problems, formulate hypothesis, and plan intervention strategies through clinical reasoning. In the clinical process, physical therapists need to use standard and common languages in speech and in documentation. The purpose of this study was to suggest the process of making strategy for efficient intervention, examining and evaluating the functional problem of the person with stroke using ICF tools. For the first step in this process model, therapists could list the information relating to functional problems used by the ICF Core set and then could identify the interaction among the problems using the ICF assessment sheet. For the next step, therapist is needed to make the hypothesis and hypothesis testing, and then set a primary functional goals and therapeutic goals in detail after prioritizing the problems to be managed based on the problem list. Finally, after setting the identified problems as the purpose of intervention through the hypothesis testing, therapist could do some intervention after making a plan to solve these problems, and find out the outcomes using the ICF evaluation display. This report illustrates how to apply the process based on ICF concept into physical therapy practice. Making a decision for the most efficient intervention requires that therapists use the clinical reasoning process based on ICF concept.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.175-195
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• 2005

사례기반추론(case-based reasoning)은 사례간 유사도를 평가하여 유사한 이웃사례를 찾아내고, 이웃사례의 결과를 이용하여 새로운 사례에 대한 예측결과를 생성하는 전통적인 인공지능기법 중 하나다. 이러한 사례기반추론이 최근 적용이 쉽고 간단하다는 장점과 모형의 갱신이 실시간으로 이루어진다는 점 등으로 인해, 온라인 환경에서의 고객관계관리를 위한 도구로 학계와 실무에서 주목을 받고 있다 하지만, 전통적인 사례기반추론의 경우, 타 인공지능기법에 비해 정확도가 상대적으로 크게 떨어진다는 점이 종종 문제점으로 제기되어 왔다. 이에, 본 연구에서는 사례기반추론의 성과를 획기적으로 개선하기 위한 방법으로 유전자 알고리즘을 활용한 사례기반추론의 동시 최적화 모형을 제안하고자 한다. 본 연구가 제안하는 모형에서는 기존 연구에서 사례기반추론의 성과에 중대한 영향을 미치는 요소들로 제시된 바 있는 사례 특징변수의 상대적 가중치 선정(feature weighting)과 참조사례 선정(instance selection)을 유전자 알고리즘을 이용해 최적화함으로서, 사례간 유사도를 보다 정밀하게 도출하는 동시에 추론의 결과를 왜곡할 수 있는 오류사례의 영향을 최소화하고자 하였다. 제안모형의 유용성을 검증하기 위해, 본 연구에서는 국내 한 전문 인터넷 쇼핑몰의 구매예측모형 구축사례에 제안모형을 적용하여 그 성과를 살펴보았다. 그 결과, 제안모형이 지금까지 기존 연구에서 제안된 다른 사례기반추론 개선모형들은 물론, 로지스틱 회귀분석(LOGIT), 다중판별분석(MDA), 인공신경망(ANN), SVM 등 다른 인공지능 기법들에 비해서도 상대적으로 우수한 성과를 도출할 수 있음을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.512-517
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• 2008

It is show that increasing of aged and handicapped people requires development of Ubiquitous computing technique to offer the specialized service for handicapped-people. For this, we need a development of Context Awareness and Service Reasoning Technique that the technique is supplied interaction between user and U-environment instead of the old unilateral relation. The old research of context awareness needed probabilistic presentation model like a Bayesian Network based on expert Systems for recognize given circumstance by a domain of uncertain real world. In this article, we define a domain of disorder activity assistant service application and context model based on ontology in diversified environment and minimized intervention of user and developer. By use this context model, we apply the structure learning of Bayesian Network and decide the service and activity to development of application service for handicapped people. Finally, we define the proper Conditional Probability Table of the structured Bayesian Network and if random situation is given to user, then present state variable of Activity and Service by given Causal relation of Bayesian Network based on Conditional Probability Table and it can be result of context awareness.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.16 no.4
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• pp.459-471
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• 2009

Introduction: Critical thinking involves identifying problem(s), assessing resources, and generating possible solutions and allows clinical nurses to decide which solution is the most reasonable under the given circumstances, taking into consideration the "hat ifs" and how they will affect the end result. This research was conducted to further understanding and identification of subjective factors in critical thinking in clinical nurses. Methods: The research design was a Q-Methodological Approach. Q-population was formulated from a non-structured questionnaire and interviews from 17 experienced clinical nurses. Thirty selected Q-statements were sorted by 30 experienced clinical nurses. Results: Four factors for critical thinking were identified: (1) Deductive reasoning based on causal relation, (2) Construction of an effective model based on patients' responses, (3) Formulating categories based on priorities for effective interventions, and (4) Judging validity of the situational significance on clinical performances. Conclusion: Critical thinking is an attitude and reasoning process. From this study, the frame of reference for clinical nurses in formulating critical thinking within the context of clinical settings is identified and indicates the way nurses utilize thinking skills when they care for patients and areas that need further exploration as nurses and faculty develop education systems to advance clinical performance competency.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• The Journal of Information Systems
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• v.8 no.1
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• pp.27-44
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• 1999

Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information. Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.