• 한국초등수학교육학회지
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• 제14권3호
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• pp.769-788
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• 2010

본 연구는 우리나라 초등학교 수학 교과서와 미국 MIC 교과서의 비와 비율 관련 단원을 전반적인 비교와 구체적인 비교로 특징을 분석하였다. 이를 바탕으로 교육과정과 비와 비율 관련단원 내용의 문제점과 시사점을 찾아 수학과 교육과정 및 교과서 개발, 수학 학습지도 방법 개선의 기초 자료를 제공하는 데 그 목적을 둔다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.1976-1997
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• 2016

This paper investigates the problem of co-tier interference mitigation for dynamic small- cell networks, in which the load of each small-cell varies with the number of active associated small-cell users (SUs). Due to the fact that most small-cell base stations (SBSs) are deployed in an ad-hoc manner, the problem of reducing co-tier interference caused by dynamic loads in a distributed fashion is quite challenging. First, we propose a new distributed channel allocation method for small-cells with dynamic loads and define a dynamic interference graph. Based on this approach, we formulate the problem as a dynamic interference graph game and prove that the game is a potential game and has at least one pure strategy Nash equilibrium (NE) point. Moreover, we show that the best pure strategy NE point minimizes the expectation of the aggregate dynamic co-tier interference in the small-cell network. A distributed dynamic learning algorithm is then designed to achieve NE of the game, in which each SBS is unaware of the probability distributions of its own and other SBSs' dynamic loads. Simulation results show that the proposed approach can mitigate dynamic co-tier interference effectively and significantly outperform random channel selection.

• Structural Engineering and Mechanics
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• 제78권2호
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• pp.209-218
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• 2021

For engineering, there are two major challenges in reliability analysis. First, to ensure the accuracy of simulation results, mechanical products are usually defined implicitly by complex numerical models that require time-consuming. Second, the mechanical products are fortunately designed with a large safety margin, which leads to a low failure probability. This paper proposes an efficient and high-precision adaptive active learning algorithm based on the Kriging surrogate model to deal with the problems with low failure probability and time-consuming numerical models. In order to solve the problem with multiple failure regions, the adaptive kernel-density estimation is introduced and improved. Meanwhile, a new criterion for selecting points based on the current Kriging model is proposed to improve the computational efficiency. The criterion for choosing the best sampling points considers not only the probability of misjudging the sign of the response value at a point by the Kriging model but also the distribution information at that point. In order to prevent the distance between the selected training points from too close, the correlation between training points is limited to avoid information redundancy and improve the computation efficiency of the algorithm. Finally, the efficiency and accuracy of the proposed method are verified compared with other algorithms through two academic examples and one engineering application.

• Geomechanics and Engineering
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• 제18권6호
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.131-142
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• 2021

Recently, there has been an active service that provides customized news to news subscribers. In this study, we intend to design a customized news service system through Deep Learning-based Social Network Service (SNS) activity analysis, applying real news and avoiding fake news. In other words, the core of this study is the study of delivery methods and delivery devices to provide customized news services based on analysis of users, SNS activities. First of all, this research method consists of a total of five steps. In the first stage, social network service site access records are received from user terminals, and in the second stage, SNS sites are searched based on SNS site access records received to obtain user profile information and user SNS activity information. In step 3, the user's propensity is analyzed based on user profile information and SNS activity information, and in step 4, user-tailored news is selected through news search based on user propensity analysis results. Finally, in step 5, custom news is sent to the user terminal. This study will be of great help to news service providers to increase the number of news subscribers.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.1-10
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• 2022

Nowadays software defect prediction (SDP) is most active research going on in software engineering. Early detection of defects lowers the cost of the software and also improves reliability. Machine learning techniques are widely used to create SDP models based on programming measures. The majority of defect prediction models in the literature have problems with class imbalance and high dimensionality. In this paper, we proposed Centroid and Nearest Neighbor based Class Imbalance Reduction (CNNCIR) technique that considers dataset distribution characteristics to generate symmetry between defective and non-defective records in imbalanced datasets. The proposed approach is compared with SMOTE (Synthetic Minority Oversampling Technique). The high-dimensionality problem is addressed using Ant Colony Optimization (ACO) technique by choosing relevant features. We used nine different classifiers to analyze six open-source software defect datasets from the PROMISE repository and seven performance measures are used to evaluate them. The results of the proposed CNNCIR method with ACO based feature selection reveals that it outperforms SMOTE in the majority of cases.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.453-459
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• 2022

This study attempted to explore the realization and research direction of a successful metaverse environment in the future by analyzing international research trends of the metaverse using topic modeling. A total of 208 papers among WoS and ScienceDirect papers using metaverse as keywords were selected, and quantitative frequency analysis and topic modeling were performed. As a result, it was confirmed that research has rapidly increased after 2022. The main keywords of the research topics were 'second', 'life', 'learning', 'reality', 'metaverse', 'virtual', 'blockchain', 'nft', 'medical', 'avatar', etc. The topic keywords 'Second life & Education' and 'Virtual Reality & Medical' accounted for a large proportion of 57%, followed by 'Blockchain & Cryptocurrency', 'Avatar & Interaction', and 'Sensing and Device'. As a result of semantic analysis, current metaverse research is focused on application and utilization, and research on underlying technologies and devices is also active. Therefore, it is necessary to identify the commonalities and differences between domestic and foreign studies, and to study the application method considering the domestic environment. In addition, new jurisprudence research is more necessary along with predicting new problems. It is expected that the results of study will provide the right research direction for domestic researchers in the era of digital transformation and contribute to the realization of a digital society.

• Smart Structures and Systems
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• 제29권4호
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• pp.523-533
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• 2022

A novel metaheuristic search method, namely black widow optimization (BWO) is employed to increase the accuracy of slope stability analysis. The BWO is a recently-developed optimizer that supervises the training of an artificial neural network (ANN) for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The designed slope bears a loaded foundation in different distances from the crest. A sensitivity analysis is conducted based on the number of active individuals in the BWO algorithm, and it was shown that the best performance is acquired for the population size of 40. Evaluation of the results revealed that the capability of the ANN was significantly enhanced by applying the BWO. In this sense, the learning root mean square error fell down by 23.34%. Also, the correlation between the testing data rose from 0.9573 to 0.9737. Therefore, the postposed BWO-ANN can be promisingly used for the early prediction of FOS in real-world projects.

• 대한임베디드공학회논문지
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• 제17권4호
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• pp.191-197
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• 2022

This study proposes an image-based Pose Intention Network (PIN) algorithm for rehabilitation via patients' intentions. The purpose of the PIN algorithm is for enabling an active rehabilitation exercise, which is implemented by estimating the patient's motion and classifying the intention. Existing rehabilitation involves the inconvenience of attaching a sensor directly to the patient's skin. In addition, the rehabilitation device moves the patient, which is a passive rehabilitation method. Our algorithm consists of two steps. First, we estimate the user's joint position through the OpenPose algorithm, which is efficient in estimating 2D human pose in an image. Second, an intention classifier is constructed for classifying the motions into three categories, and a sequence of images including joint information is used as input. The intention network also learns correlations between joints and changes in joints over a short period of time, which can be easily used to determine the intention of the motion. To implement the proposed algorithm and conduct real-world experiments, we collected our own dataset, which is composed of videos of three classes. The network is trained using short segment clips of the video. Experimental results demonstrate that the proposed algorithm is effective for classifying intentions based on a short video clip.

• 산경연구논집
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• 제13권1호
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• pp.1-9
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• 2022

Purpose: This study aims to find empirical evidence and clarity on the phenomenon of the direct and indirect effect of perceived behavioral control on fraud prevention through whistleblowing intention. This study also aims to understand the influence of organizational ethical culture moderating between whistleblowing intention and fraud prevention. Research design, data, methodology: The samples of this research are 236 respondents consisting of the Head of the Finance Subdivision and Head of the Reporting Planning Subdivision and the finance staff who were determined using the purposive sampling method. The data obtained were analyzed using the Structural Equation Modeling technique. Results: The study results show that perceived behavioral control positively and significantly affects whistleblowing intention. In addition, perceived behavioral control does not affect fraud prevention mediated by whistleblowing intention. Furthermore, organizational ethical culture moderates whistleblowing intention and has a positive and significant effect on fraud prevention. Conclusions: This study concludes that the phenomenon of scandal that often occurs on a television is not a habit that must be followed. It requires an active role from the community as a form of concern for whistleblowing. Futher researchers can add other construct variables, such as good corporate governance to assess the performance improvement of the organizational layers, both internally and externally