• 한국초등수학교육학회지
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• 제15권2호
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• pp.437-461
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• 2011

본 연구는 초등 수학영재들이 'n${\times}$n 격자점에서 정사각형 개수 구하기' 과제를 해결하는 과정에서 나타나는 메타인지 요소를 분석하여 이것이 문제해결과정에 어떻게 서로 상호작용을 하며, 또 메타인지 요소가 문제해결의 성패에 어떤 영향을 미치는 지를 살펴보고자 하였다 이를 위하여 현재 우리나라의 대표적인 3가지 영재교육기관(지역공동영재학급, 교육지원청부설 영재교육원, 대학부설 과학영재교육원)별로 각 1명씩 총 3명(기관의 순서대로 각각 학생 C, 학생 B, 학생 A라 함)을 대상으로 3시간 정도가 걸리는 수업을 연구자가 직접 참여한 관찰과 수업 녹화용 비디오 및 활동지 분석, 그리고 수업 후 면담 등을 통해 질적 사례 연구를 실시하였다.

• 한국지구과학회지
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• 제26권6호
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• pp.501-510
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• 2005

10학년 과학 교과서 지구 단원의 학습 내용에 포함되어 있는 탐구 과제가 제7차 교육 과정의 목표에 따라 제시되었는지를 판단하기 위해 11종 과학 교과서의 기본 과정에 제시되어 있는 탐구 과제의 유형과 기본 탐구 기능, 통합탐구 기능, 탐구 활동의 빈도를 조사하였고, 제시된 탐구 기능과 활동이 적절한지를 분석하였다. 분석한 결과 탐구 과제는 평균 24.0개가 제시되었으나 교과서마다 차이가 있었고 제시하는 유형이 달랐다. 탐구 활동의 빈도는 교과서마다 달랐고 제시된 것보다 더 많이 분석되었으며 통합적인 활동으로 제시되지 않고 하나의 탐구 기능처럼 제시되어 있었다. 또한 교과서에 제시된 통합 탐구 기능은 $77.2\%$로 기본 탐구 기능 $22.8\%$보다 많은 것으로 보였지만, 실제로 기본 탐구기능과 통합 탐구 기능의 분포 비율은 각각 $45.6\%$와 $56.4\%$로 조사되었다. 각 탐구 기능 중에서는 추리$(49.5\%)$와 자료해석$(68.7\%)$이 가장 많이 있었고, 문제 인식, 가설 설정, 일반화 등의 탐구 요소는 제시되고 있지 않았다. 또한 제7차 교육 과정에서 탐구 기능, 탐구 활동에 대한 의미를 제시하고 있지 않기 때문에 교과서마다 본질적 의미와 일치하지 않거나 협소한 의미로 사용되고 있었다. 이는 교육 과정이 탐구, 탐구 기능, 탐구 활동에 대한 의미를 조작적 수준으로 제시하고, 탐구 활동을 구성하기 위한 기준을 마련한 필요가 있음을 시사한다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.408-416
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• 2022

The new millennium is characterized by an unprecedented breakthrough in knowledge and information and communication technologies, and the challenges of the XXI century require modernized paradigms of interaction in all spheres of life. Education continues to play a key role in national and global growth. The key role of education and its leadership in developing creative potential, as the main paradigm of the countries' stability, have significantly influenced educational centers. The developers of educational programs use information technologies as an incentive to develop creative potential of educational process. Professional training of the educational candidate is enhanced by the use of information technologies, so the educational applicants should develop technological skills to be productive members of society. Using the latest achievements in the field of information technologies for the organization of the educational process helps to form the operational style of education applicants' thinking, which provides the ability to acquire skills of processing information, that is presented in the text, graphic, tabular form, and increase the level of general and informational culture necessary for better orientation in the modern information space. The purpose of the research is to determine the effectiveness of information technologies as an incentive to develop creative potential of educational process on the basis of the survey, to establish advantages and ability to provide high-quality education in the context of using information technologies. Methods of research: comparative analysis; systematization; generalization, survey. Results. Based on the survey conducted among students and teachers, it has been found out that the teachers use the following information technologies for the development of creative potential of the educational process: to provide video and audio communication process (100%), Moodle (95,6%), Duolingo (89,7%), LinguaLeo (89%), Google Forms (88%) and Adobe Captivate Prime (80,6%). It is determined that modular digital learning environments (97,9%), interactive exercises tools (96,3%), ICT for video and audio communication (96%) and interactive exercises tools (95,1%) are most conducive to the development of creative potential of the educational process. As a result of the research, it was revealed that implementation of information technologies for the development of creative potential of educational process in educational institutions is a complex process due to a large number of variables, which should be taken into account both on the educational course and on the individual level. It has been determined that the using the model of implementation information technologies for the development of creative potential in educational process, which is stimulated due to this model, benefits both students and teachers by establishing a reliable bilateral connection between teacher and education applicant.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1036-1057
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• 2013

Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

• 한국초등수학교육학회지
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• 제20권1호
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• pp.131-148
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• 2016

본 연구는 초등학교 5학년 영재학급 학생들(8명)이 패턴의 일반화 과제를 해결함에 있어 귀납 추론으로 일반식은 추측하였으나 그에 대한 형식적 정당화로 이행하는 과정에서 겪는 어려움을 분석하고 그 해결을 돕기 위한 교사 발문의 역할 모색과 발문 기법 제안을 목적으로 하였다. 학생들의 형식적 정당화를 돕기 위한 교사 발문 목록들을 3차에 걸친 현장 적용을 통해 확인한 결과, 초등학교 영재학급 학생들은 형식적 정당화로 이행을 할 때 정당화를 시도해야하는 이유, 연역적 탐구에 대한 인식 부족, 유연한 탐구 방법에 대한 심리적 저항감으로 인해 어려움을 겪었다. 면담 분석 결과 학생들이 정당화의 필요성과 귀납적 탐구 결과의 한계를 체감할 수 있도록 교사가 태도면에서 출발하여 방법면과 내용면으로 구체화해갈 수 있도록 체계적인 발문을 준비하는 것이 중요함을 확인할 수 있었다. 이에 따라 내용면에서의 4가지와 절차면에서의 3가지 발문 기법을 제안하면서 논의를 바탕으로 발문 일람표와 그 흐름도를 제시하고 교사 발문의 역할이 주는 교육적 시사점을 논의하였다.

• 감성과학
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• 제16권3호
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• pp.319-332
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• 2013

그동안 학습과 기억이 과거의 경험에 의해 구성된다는 측면이 강조되어왔으나, 최근의 연구들은 이들 인지과정이 미래의 보상물을 최대화하는 목표를 달성하기 위해 이루어짐을 조명하였다. 본 개관 논문은 이와 관련된 연구를 소개하고 목표지향적 학습과 기억에 대하여 논의하고자 한다. 먼저 강화 학습에서 내적 모형 기반 학습, 즉 상위 차원의 목표를 달성하기 위해 즉각적인 보상을 가져오지 않음에도 불구하고 특정한 행동을 취하는 과정이 이루어지고, 또한 직접적 강화를 받지 않은 대상으로의 일반화 및 유추가 일어나 미래의 적응적 행동을 가져옴을 보여준 연구들을 소개한다. 또한 위와 같은 목표지향적 학습 과정의 신경학적 기제를 탐색한 연구들을 개관하고, 선조체의 도파민 신호를 기반으로 한 과정이 기억 과정에 역시 영향을 미칠 수 있음을 논의한다. 특히, 기억이 과거의 경험을 모두 동일한 수준으로 부호화하고 인출하는 과정이 아니라, 상위 수준의 목표에 맞춘 의사결정과정의 결과임을 보여주는 연구들을 소개한다. 이러한 연구들은 미래에 얻게 될 보상 정보가 역향적으로 현재의 인지처리에 영향을 줄 수 있음을 시사한다.

• Design & Manufacturing
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• 제11권1호
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• pp.1-6
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• 2017

In these days, due to generalization of using smart mobile phone and wearable device such as smart watch, demand of Cover-glass and touch screen panel for protecting display increases. With increasing the demand of Cover-glass, slimming technique is promising for weight lightening, zero bezel. Cover-glass produced by this technique is required to decreasing thickness with increase strength. In the Cover-glass manufacturing process, mechanical processing and chemical processing has improve in the strength. Generally, Diamond electrodeposition wheel is used in mechanical process. Reinforced glass with the characteristics of the brittle and high hardness was manufactured by using a diamond electrodeposition wheel. At this time, Because of surface of the tool present non-uniform distribution of diamond particle, it has generate Loading of wheel and it has been decrease life of grinding tool, efficiency of grinding, quality and shape accuracy of workpiece. Thus Research is needed to controling particle distribution of diamond electrodeposition wheel uniformly. And it is necessary to study micro hole machining such as proximity senser hole, speaker hole positioned Cover-glass. Reinforced glass with the characteristics of the brittle and high hardness is difficult to machining. Processing of reinforced glass have generated wear of tool, micro cracks. Also, it is decreasing shape accuracy. In this paper, We conducted a study on how to control particle distribution uniformly about the diamond tool manufactured using elecetodeposition processing. It analyzed the factors that affect the arrangement of the particles in the electrodeposition process by design of experiment. And There is produced the grinding tool, which derives an optimum deposition conditions, for processing Cover-glass edge and the machinability was evaluated.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.132-137
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• 2007

Experimental software data capturing the essence of software projects (expressed e.g., in terms of their complexity and development time) have been a subject of intensive modeling. In this study, we introduce a new category of Hybrid Fuzzy Neural Networks (gHFNN) and discuss their comprehensive design methodology. The gHFNN architecture results from highly synergistic linkages between Fuzzy Neural Networks (FNN) and Polynomial Neural Networks (PNN). We develop a rule-based model consisting of a number of "if-then" statements whose antecedents are formed in the input space and linked with the consequents (conclusion pats) formed in the output space. In this framework, FNNs contribute to the formation of the premise part of the overall network structure of the gHFNN. The consequences of the rules are designed with the aid of genetically endowed PNNs. The experiments reported in this study deal with well-known software data such as the NASA dataset. In comparison with the previously discussed approaches, the proposed self-organizing networks are more accurate and yield significant generalization abilities.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.365-373
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• 1999

Recently, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as a model construction process. Irrespective of the efficiency of a learning procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network models. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.