• The Journal of Korean Association of Computer Education
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• v.9 no.3
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• pp.109-119
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• 2006

Algorithm is a fundamental concept for all related research areas in computer science. Though many researches have paid attention to computer algorithm in solving applied problems, few researches have been conducted on how to effectively instruct the computer algorithm concept. This paper proposed the instructional method for the computer algorithm concept by using mathematics problems of the fourth grade, elementary school. We have applied our the instructional methodology to classroom, and empirically tested the effectiveness of our methodology. The results show that the effectiveness of instructional method, compared to the traditional instructional methodology.

• Journal of The Korean Association of Information Education
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• v.11 no.1
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• pp.29-38
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• 2007

Computer programming in computer education draws much attention recently. Encouraged by the increased tendency of acquiring logical ability and creativity through learning, various attempts have been made to develop them through learning computer programming in the area of computer education as well. The fact that a computer program is the representation of a computer algorithm expressed in a computer language makes us realize that the devise of a logical method for a solution - i.e., the design of an algorithm - is the key to the solution of a problem. Recognizing the importance of computer algorithm would lead us to such a point that systematic investigations for directional establishment for algorithm education are necessary. We observe that researches on teaching computer algorithm have concentrated mostly on specific problems such as sorting and searching, which can be characterized as problem-dependent and individual. In this paper, the idea of conceptual algorithm is stated from the standpoint of conceptual types of problem-solving methods which are considered as problem-independent and collective. A novice approach to algorithm education based on the characteristics of types of conceptual algorithms is proposed for the purpose of developing systematic, problem-independent, algorithmic problem-solving capabilities of learners, which is widely different from the current methods of individual and problem-dependent algorithm education.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1046-1051
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• 1994

It is known that SOFM has the property of effectively creating topographically the organized map of various features on input signals, SOFM can effectively be applied to the recognition of Korean phonemes. However, is isn't guaranteed that the network is sufficiently learned in SOFM algorithm. In order to solve this problem, we propose the learning algorithm combined with the conventional K-means clustering algorithm in fine-tuning stage. To evaluate the proposed algorithm, we performed speaker dependent recognition experiment using six phoneme classes. Comparing the performances of the Kohonen's algorithm with a proposed algorithm, we prove that the proposed algorithm is better than the conventional SOFM algorithm.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.285-286
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• 2008

In this paper, we propose adaptive search channel estimate algorithm. The proposed algorithm is modified LMS algorithm which has a variable step size and parallel convolution. In simulation result, a error estimate accuracy of the proposed algorithm is about -20 dB and general LMS algorithm is about 10 dB. The proposed algorithm is better error estimate accuracy than general LMS algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.600-619
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• 2015

We propose a cost-efficient hybrid algorithm for online location updates that efficiently combines feature point detection with the online trajectory-based sampling algorithm. Our algorithm is designed to minimize the average trajectory error with the minimal number of sample points. The algorithm is composed of 3 steps. First, we choose corner points from the map as sample points because they will most likely cause fewer trajectory errors. By employing the online trajectory sampling algorithm as the second step, our algorithm detects several missing and important sample points to prevent unwanted trajectory errors. The final step improves cost efficiency by eliminating redundant sample points on straight paths. We evaluate the proposed algorithm with real GPS trajectory data for various bus routes and compare our algorithm with the existing one. Simulation results show that our algorithm decreases the average trajectory error 28% compared to the existing one. In terms of cost efficiency, simulation results show that our algorithm is 29% more cost efficient than the existing one with real GPS trajectory data.

• Korean Journal of Optics and Photonics
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• v.16 no.1
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• pp.43-49
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• 2005

In this paper, we propose a method for optimizing a computer-generated hologram(CGH) by combining the Tabu Search(TS) algorithm with the Simulated Annealing(SA) algorithm. By replacing an initial random pattern of the SA algorithm with an approximately ideal hologram pattern of the TS algorithm, we design a CGH which has high diffraction efficiency(DE). We compared the performance of the proposed algorithm with the SA algorithm using computer simulation and an optical experiment. As a result, we confirmed diffraction efficiency and uniformity to be enhanced in the proposed algorithm.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.129-134
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• 2023

The greatest challenge of this century is the protection of stored and transmitted data over the network. This paper provides a new hybrid algorithm designed based on combination algorithms, in the proposed algorithm combined with Hill and the Advanced Encryption Standard Algorithms, to increase the efficiency of color image encryption and increase the sensitivity of the key to protect the RGB image from Keyes attackers. The proposed algorithm has proven its efficiency in encryption of color images with high security and countering attacks. The strength and efficiency of combination the Hill Chipper and Advanced Encryption Standard Algorithms tested by statical analysis for RGB images histogram and correlation of RGB images before and after encryption using hill cipher and proposed algorithm and also analysis of the secret key and key space to protect the RGB image from Brute force attack. The result of combining Hill and Advanced Encryption Standard Algorithm achieved the ability to cope statistically

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.82-90
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• 2001

Genetic Algorithm(GA) has known as a method of solving NP problem in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementation of Genetic Algorithm is focused on in recent studies. This paper proposes a new type of embedded one chip computer fort Hardware Implementation of Genetic Algorithm. The proposed embedded one chip computer consists of 16 Bit CPU care and hardware of genetic algorithm. In contrast to conventional hardware oriented GA which is dependent on main computer in the process of GA, the proposed embedded one chip computer is independent on main computer. Conventional hardware GA uses the fixed length of chromosome but the proposed embedded one chip computer uses the variable length of chromosome by employing the efficient 16 bit Pipeline Unit. Experimental results show that the proposed one chip computer is applicable to the design of evolvable hardware for Random NRZ bit synchronization circuit.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.207-210
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• 2009

Edge detection is an important process in low level image processing. But many proposed methods for edge detection are not very robust to the image noise and are not flexible for different images. To solve the both problems, an algorithm is proposed which eliminate the noise by mean shift algorithm in advance, and then adaptively determine the double thresholds based on gradient histogram and minimum interclass variance, With this algorithm, it can fade out almost all the sensitive noise and calculate the both thresholds for different images without necessity to setup any parameter artificially, and choose edge pixels by fuzzy algorithm.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.211-214
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• 2009

Edge detection always influenced by noise belong to the original image, therefore need use some methods to sort this issue, mean shift algorithm has the smooth function which suit for the edge detection purpose, so adopted to fade out the unimportant information, and the sensitive noise portions. After this section, use the Canny algorithm to pick up the contour of the objects we focus on, meanwhile select the Soble operator that has the orientation attribute to support the method work well. In final, take experiment and get the perfect result we wanted, make sure this method make sense and better than the sole Edge detection algorithm,