• Research in Mathematical Education
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• v.12 no.4
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• pp.259-270
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• 2008

The change of the developed countries to highly technological societies continuously requires that they nurture and use the full potential of mathematically and scientifically talented people. As this is a process that should start early in order to be efficient, the main responsibility of identifying and addressing the specific needs of these people is assigned to public school systems and, in particular, to elementary teachers. In this regard, three significant areas of concern arise and are discussed in this paper: (a) The complexity in identifying mathematically promising and mathematically talented elementary students; (b) The highly responsible and difficult task for elementary teachers to differentiate and serve the mathematically promising students within an inclusive classroom; and (c) The need of teachers with specialized training and mathematics knowledge in pre-high school grades. The last one should be considered predominantly as a logical consequence of the first two. The main goal and, hence, the purpose of the paper is to promote understanding of this crucial necessity of mathematics specialists and to advocate for a change in this direction.

• Knowledge Management Research
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• v.13 no.3
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• pp.55-77
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• 2012

Selecting promising technology is becoming more and more difficult due to the increased number and complexity. In this study, we propose hybrid AHP/DEA-AR method and hybrid AHP/DEA-AR-G method to evaluate efficiency of technology alternatives based on ordinal rating data collected through survey to technology experts in a certain field and select efficient technology alternative as promising technology. The proposed method normalizes rating data and uses AHP to derive weights to improve the credibility of analysis, then in order to avoid basic DEA models' problems, use DEA-AR and DEA-AR-G to evaluate efficiency of technology alternatives. In this study, we applied the proposed methods to clean technology and compared with the basic DEA models. According to the result of the comparison, we can find that the both proposed methods are excellent in confirming most efficient technology, and hybrid AHP/DEA-AR method is much easier to use in the process of technology selection.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• The Journal of the Acoustical Society of Korea
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• v.33 no.1
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• pp.81-86
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• 2014

This paper presents a study on the effectiveness of using the spectral and the temporal octave-band order statistics for musical genre classification. In order to represent the relative disposition of the harmonic and non-harmonic components, we utilize the octave-band order statistics of power spectral distribution. Experiments on the widely used two music datasets were performed; the results show that the octave-band order statistics improve genre classification accuracy by 2.61 % for one dataset and 8.9 % for another dataset compared with the mel-frequency cepstral coefficients and the octave-band spectral contrast. Experimental results show that the octave-band order statistics are promising for musical genre classification.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1412-1415
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• 1996

In this paper, a new identification method of the cascade control system is proposed which can overcome the weak points of Krishnaswamy and Rangaiah(1987)'s method. This new method consists of two steps. One is on-line process identification using the numerical integration to approximate the two process dynamics with a high order linear transfer function. The other is a model reduction technique to derive out low order transfer function(FOPTD or SOPTD) from the obtained high order linear transfer function to tune the controller using usual tuning rules. While the proposed method preserves the advantages of the Krishnaswamy and Rangaiah(1987)'s method, it has such a simplicity that it requires only measured input and output data and simple least-squares technique. Simulation results show that the proposed method can be a promising alternative in the identification of cascade control systems.

• Korean Journal of Crystallography
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• v.16 no.2
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• pp.61-65
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• 2005

Despite a short history, the research on porous coordination polymers is gaining importance in inorganic chemistry thanks to facile synthesis, unambiguous characterization by X-ray diffraction and potentials as high-surface-area materials. Recently, gas sorption properties of various porous materials are under active investigations in order to know whether it is possible to store industrially important gases through physisorption, and porous coordination polymers are one of the most promising candidates for such a purpose. This article reviews two recent papers reporting a series of isomorphous frameworks based on Zn(II), dicarboxylate and diamine ligands and their gas sorption properties.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.215-221
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• 1997

A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1323-1326
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• 2003

CORBA has been a popular middleware, but recently Web Services has been emerging as a promising web middleware since it uses Internet established standards such as URL, HTTP, XML, and etc. CORBA uses IDL for describing CORBA object interface and Web Services uses WSDL for its description. Thus, in order to port or integrate CORBA objects into Web Services, one needs to understand the relationship between CORBA IDL and WSDL. In this paper, we analyze IDL and WSDL, and compare between two. It turns out that there exists a direct mapping between two, and that understanding operational environments and logic of two technologies is much more important in converting or integrating CORBA objects into Web services successfully.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.193-195
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• 1992

Snow accretion on transmission lines may cause critical accidents such as sleet jump, tower collpases, etc,. In order to assist power system operators to prevent thses accidents, aprototype expert system had been developed. The system has basic functions of forecasting snow accretion on transmission lines and making a list of all feasible and effective deicing countermeasures. The knowledge of the effect of weather conditions on the snow accretion process continue main rule base. Simulation results show that the proposed system is very promising.

• Journal of Korea Technology Innovation Society
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• v.5 no.3
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• pp.382-395
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• 2002

Metal Injection Molding(MIM) is a technology without any mechanical processing, which is a promising area backed up by nano powder technology developed in late 1990's. The market was about 24 billion U$ in 1999. Many applications are made in process development, uses, powder making, hindering and sintering, of which order is in terms of the number of patents. This technologies are mainly developed by US firms, and applied by Japanese firms. Europe and Korea are still catch-up stage. More efforts should be made in this field because new opportunities are opening, thanks to nano technology.