• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.13-22
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• 2021

Recently network based attack technologies are rapidly advanced and intelligent, the limitations of existing signature-based intrusion detection systems are becoming clear. The reason is that signature-based detection methods lack generalization capabilities for new attacks such as APT attacks. To solve these problems, research on machine learning-based intrusion detection systems is being actively conducted. However, in the actual network environment, attack samples are collected very little compared to normal samples, resulting in class imbalance problems. When a supervised learning-based anomaly detection model is trained with such data, the result is biased to the normal sample. In this paper, we propose to overcome this imbalance problem through One-Class Anomaly Detection using an auto encoder. The experiment was conducted through the NSL-KDD data set and compares the performance with the supervised learning models for the performance evaluation of the proposed method.

• Journal of Korean Elementary Science Education
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• v.32 no.1
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• pp.104-112
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• 2013

We examined the strategies to stimulate the reflective thinking using science notebook for the improvement of problem solving ability which is one of the core skills for the future. The strategies we derived have four steps which are input, output, solving mission and reflection as my own mirror. We applied the strategies to the 6th grade class for autumn semester in order to examine the students learning process and the result. We could observe that students looked into their own learning and had a time to look back their activities in the class. We could also confirmed that science notebook would be effective to improve the problem solving as stimulating the reflective thinking. In addition, we could specify the strategy of using science notebook in the class. At a 'input' stage, students should be able to choose their own learning style as their preference and teacher need to give them proper feedback. Interaction with peers should be emphasized during the activities as 'question attack' and 'question defense' in 'output' stage and 'solving mission' stage. You should suggest the students various method to record their thought from looking back their classroom activities instead of mere writing. We also examine the students achievement from the students' notebook and Meta Cognitive Awareness test. As a result, students who had studied using science notebook showed statistically meaningful higher achievement than controlled students.

• Journal of The Korean Association For Science Education
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• v.25 no.1
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• pp.1-15
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• 2005

This study examined two students' problem solving approaches: the similarities and the differences in their problem solving approaches, and the general problem solving strategies (heuristics) the students employed were discussed. The two students represent differences not only in terms of grades earned, but also in terms of participation, motivation, attention to detail, and approaches to answering questions and problem solving. Three separate problems were selected for this study: A stoichiometry problem; a fruit salad problem; and a limiting reactant problem. Each student was asked individually on three separate occasions to contribute to this study. There are more similarities in the students' problem solving strategies than there are differences. Both students were able to correctly solve the stoichiometry and the fruit salad problems, and were unable to correctly solve the limiting reactant problem. They recognized that an algorithm could be used for both chemistry problems(a stoichiometry problem & a limiting reactant problem). Both students were unable to correctly solve the limiting reactant problem and to demonstrate a clear understanding of the Law of Conservation of Mass. Nor did they show an ability to apply it in solving the problem. However, there was a difference in each one's ability to extend what had been learned/practiced/quizzed in class, to a related but different problem situation.

• Korean Journal of Child Studies
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• v.27 no.4
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• pp.1-16
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• 2006

This study investigated the effectiveness of the Developmentally Appropriate Instruction Model for Science(DAIM-S) on increasing scientific curiosity and problem solving in young children. Subjects were 60 5-year-old middle class children, randomly assigned to one of two groups: either the DAIM-S group or the direct instruction group. For 2 months, the children in both groups took part in 21 science activity sessions. Both before and after treatment, subjects were tested on curiosity and scientific problem solving. The DAIM-S group showed higher achievement than the direct instruction group in the acquisition of curiosity and scientific problem solving. From these results, the researchers suggest application of the DIAM-S to the science teaching of young children.

• Nonlinear Functional Analysis and Applications
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• v.29 no.1
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• pp.83-98
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• 2024

In this paper, we investigate the existence and uniqueness of solutions to a new class of integro-differential equation boundary value problems (BVPs) with ㄒ-Hilfer operator. Our problem is converted into an equivalent fixed-point problem by introducing an operator whose fixed points coincide with the solutions to the given problem. Using Banach's and Schauder's fixed point techniques, the uniqueness and existence result for the given problem are demonstrated. The stability results for solutions of the given problem are also discussed. In the end. One example is provided to demonstrate the obtained results

• Journal of the Korean School Mathematics Society
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• v.16 no.4
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• pp.745-770
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• 2013

In the knowledge-based society today, most knowledge is the integrated one which is difficult to be classified into subjects rather than the knowledge of a single subject. Thus, integrated thinking, which integrated knowledge is preferentially acquired first and then can be also associated with imagination and artistic sensitivity, is simultaneously required in order that we have a problem-solving capability in our daily life. STEAM education(science, technology, engineering, arts and mathematics) is one of the educational methods to improve this problem-solving capability as well as integrated thinking. This research developed materials for STEAM education which can be applied to the 6th grade curriculum of elementary school mathematics, then input it, and analyzed how it impacts with students' attitudes toward mathematics. Unit 3 'Prism' and Pyramid' were restructured and replaced by classes such as 'Spaghetti Project' or 'Paper Craft'. Unit 4 'Several Solid Figure' was taught as a class of 'EDUCUBE'. Unit 6 'Proportional Graph' was taught as a class of 'Creating my own bracelet'. After having this class, we found that mathematics class applied STEAM also has a positive effect on the mathematical attitude of students. Many students said that math is fun and gets more interesting after having math class applied STEAM and we come to know that they have positive awareness of mathematics.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.355-361
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• 1999

An application of case-based reasoning is proposed to build an influence diagram for identifying successful new ventures. The decision to invest in new ventures in characterized by incomplete information and uncertainty, where some measures of firm performance are quantitative, while some others are substituted by qualitative indicators. Influence diagrams are used as a model for representing investment decision problems based on incomplete and uncertain information from a variety of sources. The building of influence diagrams needs much time and efforts and the resulting model such as a decision model is applicable to only one specific problem. However, some prior knowledge from the experience to build decision model can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem solving experience to solve a new decision. In this paper, we suggest a case-based reasoning approach to build an influence diagram for the class of investment decision problems. This is composed of a retrieval procedure and an adaptation procedure. The retrieval procedure use two suggested measures, the fitting ratio and the garbage ratio. An adaptation procedure is based on a decision-analytic knowledge and decision participants knowledge. Each step of procedure is explained step by step, and it is applied to the investment decision problem in new ventures.

• Journal of IKEEE
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• v.23 no.4
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• pp.1134-1139
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• 2019

One of the most important applications of computer vision algorithms is the detection of threat objects in x-ray security images. However, in the practical setting, this task is complicated by two properties inherent to the dataset, namely, the problem of class imbalance and visual complexity. In our previous work, we resolved the class imbalance problem by using a GAN-based anomaly detection to balance out the bias induced by training a classification model on a non-practical dataset. In this paper, we propose a new method to alleviate the visual complexity problem by using a KNN-based automatic cropping algorithm to remove distracting and irrelevant information from the x-ray images. We use the cropped images as inputs to our current model. Empirical results show substantial improvement to our model, e.g. about 3% in the practical dataset, thus further outperforming previous approaches, which is very critical for security-based applications.

• Journal of Korean Clinical Health Science
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• v.7 no.2
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• pp.1289-1297
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• 2019

Purpose: The purpose of this study was to investigate occupational therapy at M college in Changwon and the impact of smart phone use on the school life of college students and to help them find ways to further develop in the future. Methods; Data collection was conducted using questionnaires, and the questionnaires consisted of 152 total questions with 15 interpersonal questions, 23 problem solving skills, 43 self-efficacy, 16 class participation scale, and 55 self-directed learning scale. It was conducted to first and second graders of M college and conducted a survey through the corresponding academic year from March 26, 2019 to March 29, 2019 to retrieve 120 questionnaires and use them for analysis. The collected data were analyzed using SPSS. Statistic 20.0. Results: Studies show that "school life satisfaction" is usually the highest at 53 percent. The "smartphone user motivation" was the highest with 50.8 percent, while the "most frequently used feature on smartphones" was the highest with 57.5 percent on SNS. Satisfaction after using a smartphone was the highest with 49.2 percent, while 41.7 percent said it would be easier to acquire and utilize information in the areas of satisfaction. Conclusion: Smartphone addiction, interpersonal relationships, problem-solving skills, self-efficacy, participation in classes, and self-control learning items are not only affected by one part, but also by the other.