• The Journal of Korean Association of Computer Education
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• v.16 no.2
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• pp.9-18
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• 2013

In secondary education, learning a computer science subject has the purpose to improve creative problem solving ability of students by learning computational thinking and principles. In particular, learning algorithm has been emphasized for this purpose. There are studies that learning algorithm has the effect of creative problem solving based on the leading studies that learning algorithm has the effect of problem solving. However, relatively the importance of the learning algorithm can weaken, because these studies depend on creative problem solving model or special contents for creativity. So this study proves that learning algorithm has the effect of creative problem solving in the view that common problem solving and creative problem solving have the same process. For this, analogical reasoning was selected among common thinking skills and divide-and-conquer algorithm was selected among abstractive principles for analogical reasoning in sorting algorithm. The frequency which solves the search problem by using the binary search algorithm was higher than the control group learning only sequence of sorting algorithm about the experimental group learning divide-and-conquer algorithm. This result means that learning algorithm including abstractive principle like divide-and-conquer has the effect of creative problem solving by analogical reasoning.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.292-298
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• 2022

Coding education and algorithm education are essential in the era of the fourth industrial revolution. Text-oriented algorithm textbooks are perceived as difficult by students who are new to coding and algorithms. There is a need to develop educational content so that students can easily understand the principles of complex algorithms. This paper has implemented basic sorting algorithms as augmented reality contents for students who are new to algorithm education. To make it easier to understand the concept and principles of sorting algorithms, sorting data was expressed as a 3D box and the comparison of values according to the algorithms and the movement of values were produced as augmented reality contents in the form of 3D animations. In order to help with the understanding of sorting algorithms in C language, the change of variable values and the exchange of data were shown as animations according to the execution order of the code and the flow of the loop. Students can conveniently use contents through a smart phone without special equipment by being produced in a marker-based manner. Interest and immersion, as well as understanding of classes of sorting algorithms can be increased through educational augmented reality-based educational contents.

• Journal of The Korean Association of Information Education
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• v.12 no.3
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• pp.303-312
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• 2008

In correspondence to the educational demand on study of computer principles that is recently being focused, this study promotes basic understanding on data structure and algorithm at the elementary student level through the process of simple numerical expressions and proposes effective education contents and methods. For this, an unplugged type computer education material was produced to understand the method of the computers for receiving data through activities. Also, we proposed students to create animation data to learn numerical expressions and algorithm through arrangements and linked lists. To examine educational effectiveness of this study, an experiment study was conducted through the education content and method to the subject of one class in the fifth-grade of elementary school located in OO metropolitan city. As a result, the student learned that there is a difference in calculation method between computers and people; and this enabled basic understanding on algorithm and data structure and presented positive responses to algorithm and data structure. In conclusion, it is confirmed that it is possible to provide effective education for students if the principle study of algorithm is proposed to proper levels.

• Current Optics and Photonics
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• v.6 no.3
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• pp.260-269
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• 2022

Segmented planar imaging detector for electro-optical reconnaissance (SPIDER) is an emerging technology for optical imaging. However, this novel detection approach is faced with degraded imaging quality. In this study, a 6 × 6 planar waveguide is used after each lenslet to expand the field of view. The imaging principles of field-plane waveguide structures are described in detail. The local multiple-sampling simulation mode is adopted to process the simulation of the improved imaging system. A novel image-reconstruction algorithm based on deep learning is proposed, which can effectively address the defects in imaging quality that arise during image reconstruction. The proposed algorithm is compared to a conventional algorithm to verify its better reconstruction results. The comparison of different scenarios confirms the suitability of the algorithm to the system in this paper.

• Journal of The Korean Association of Information Education
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• v.20 no.2
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• pp.151-160
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• 2016

Algorithm education is emphasized as an instrument for teaching the basic principles of Computer Science. But these materials is very short-fall. We'll present the CS Unplugged-based algorithm contents, which is easy to learn for elementary student. These contents for self-directed learning consisted of the activity-based learning. For problem-solving algorithm learning in everyday life we were developed the hashing techniques on the basis of the basic searching and sorting algorithms. For checking the adequacy of these materials were tested by surveys of teacher professional groups, and we obtain the appropriate conclusions for sorting algorithm contents for improving the problem-solving ability for in elementary student.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.271-280
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• 2010

Education focus on cultivating creative talent in the rapidly changing knowledge and Information society. Algorithms of computer science students to logical thinking and problem solving to find the best solution is an effective learning content. But the algorithm often educate at the University of reality when considering the level of elementary school students' cognitive structure and it is very important for teaching. In this study, based on the principle of the algorithm with an educational content for students to understand the principles of their own problems as the best way to resolve the situation with the ability to want to kidney. Content that contains elements of the game interesting for students to participate actively interested in effective teaching methods to the understanding of the principles of the algorithm will be a big help.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.145-162
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• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.27-36
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• 2010

Introducing algorithm and programming education to the middle school 'Information' curriculum is appropriate to develop higher thinking skills like problem solving ability and creativity that is the most important ability to the people living in the knowledge and information society. But to providing reduced algorithm and programming contents of higher education increase the cognitive burden on the students in the concrete operational period who is not yet reached to the formal operational period, and moreover transfering principles and strategies learned in the algorithm to the programming for the problem solving is difficult. For this study, student's developmental characteristics in the concrete operational period among cognitive developmental periods was considered, and FAAP(First-Algorithm After-Programming) learning model which can transfer algorithm to programming was developed, and finally the effectiveness of learning motivation and achievement to the concrete operational period's students was verified. Results of the tests showed that learning motivation and achievement of the concrete operational period's students that learned FAAP model were different significantly.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.46-55
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• 1997

This paper presents the development of intelligent performance management of computer communication networks for larger-scale integrated systems and the demonstration of its efficacy using computer simula- tion. The innermost core of the performance management is based on fuzzy set theory. This fuzzy perfor- mance manager has learning ability by using principles of neuro-fuzzy model, neuralnetwork, genetic algo- rithm(GA). Two types of performance managers are described in this paper. One is the Neuro-Fuzzy Per- formance Manager(NFPM) of which learning ability is based on the conventional gradient method, and the other is GA-based Neuro-Fuzzy Performance Manager(GNFPM)with its learning ability based on a genetic algorithm. These performance managers have been evaluated via discrete event simulation of a computer network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1916-1934
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• 2023

The phishing attack is a malicious emerging threat on the internet where the hackers try to access the user credentials such as login information or Internet banking details through pirated websites. Using that information, they get into the original website and try to modify or steal the information. The problem with traditional defense systems like firewalls is that they can only stop certain types of attacks because they rely on a fixed set of principles to do so. As a result, the model needs a client-side defense mechanism that can learn potential attack vectors to detect and prevent not only the known but also unknown types of assault. Feature selection plays a key role in machine learning by selecting only the required features by eliminating the irrelevant ones from the real-time dataset. The proposed model uses Hyperparameter Optimized Artificial Neural Networks (H-ANN) combined with a Hybrid Firefly and Grey Wolf Optimization algorithm (H-FFGWO) to detect and block phishing websites in Internet of Things(IoT) Applications. In this paper, the H-FFGWO is used for the feature selection from phishing datasets ISCX-URL, Open Phish, UCI machine-learning repository, Mendeley website dataset and Phish tank. The results showed that the proposed model had an accuracy of 98.07%, a recall of 98.04%, a precision of 98.43%, and an F1-Score of 98.24%.