• Journal of IKEEE
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• v.17 no.1
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• pp.29-35
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• 2013

In this paper, we suggest an improved Convex Hull algorithm considering sort in plane point set. This algorithm has low computational complexity since processing data are reduced by characteristic of extreme points. Also it obtains a complete convex set with just one processing using an convex vertex discrimination criterion. Initially it requires sorting of point set. However we can't quickly sort because of its heavy operations. This problem was solved by replacing value and index. We measure the execution time of algorithms by generating a random set of points. The results of the experiment show that it is about 2 times faster than the existing algorithm.

• 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.

• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.39-53
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• 2009

This paper suggests a new process structuring method, which we call process modularization, for decomposing and grouping activities in a process. Above all, we propose the concept of a module that is a group of activities positioned on the same flow before and after control constructs. Since activities in a module are relatively strongly interrelated with one another, it is important to take into consideration of these together. A design structure matrix (DSM) is used to structure the process because it has a lot of advantages in process modeling and analysis. We developed two algorithms: the restricted topological sorting (RTS) algorithm for ordering activities and the module finding (MF) algorithm for detecting modules in a process, which utilize the DSM. The suggested approach enables a firm's manager to design and analyze the process effectively. We also developed a supporting tool to accelerate the progress of process modularization. The supporting tool aids the process manager in finding the module and understanding the process structure easily. An illustrative example is addressed to show operations of the suggested approach.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1230-1242
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• 1993

In a case of mushroom (Lentinus Edodes L.) , visual features are crucial for grading and the quantitative evaluation of the growth state. The extracted quantitative visual features can be used as a performance index for the drying process control or used for the automatic sorting and grading task. First, primary external features of the front and back sides of mushroom were analyzed. And computer vision based algorithm were developed for the extraction and measurement of those features. An automatic thresholding algorithm , which is the combined type of the window extension and maximum depth finding was developed. Freeman's chain coding was modified by gradually expanding the mask size from 3X3 to 9X9 to preserve the boundary connectivity. According to the side of mushroom determined from the automatic recognition algorithm size thickness, overall shape, and skin texture such as pattern, color (lightness) ,membrane state, and crack were quantified and measured. A portion of t e stalk was also identified and automatically removed , while reconstructing a new boundary using the Overhauser curve formulation . Algorithms applied and developed were coded using MS_C language Ver, 6.0, PC VISION Plus library functions, and VGA graphic function as a menu driven way.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.227-245
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• 2013

The term "constructability" in regard to cast-in-place concrete construction refers mainly to the ease of reinforcing steel placement. Bar congestion complicates steel placement, hinders concrete placement and as a result leads to improper consolidation of concrete around bars affecting the integrity of the structure. In this paper, a multi-objective approach, based on the non-dominated sorting genetic algorithm (NSGA-II) is developed for optimal design of reinforced concrete cantilever retaining walls, considering minimization of the economic cost and reinforcing bar congestion as the objective functions. The structural model to be optimized involves 35 design variables, which define the geometry, the type of concrete grades, and the reinforcement used. The seismic response of the retaining walls is investigated using the well-known Mononobe-Okabe analysis method to define the dynamic lateral earth pressure. The results obtained from numerical application of the proposed framework demonstrate its capabilities in solving the present multi-objective optimization problem.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1571-1580
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• 1999

When a hierarchical structure is derived from data set for data mining and machine learning, using a conceptual clustering algorithm, one of the unsupervised learning paradigms, it is not unusual to have a different set of outcomes with respect to the order of processing data objects. To overcome this problem, the first classification process is proceeded to construct an initial partition. The partition is expected to imply the possible range in the number of final classes. We apply center sorting to the data objects in the classes of the partition for new data ordering and build a new partition using ITERATE clustering procedure. We developed an algorithm, REIT that leads to the final partition with stable and best partition score. A number of experiments were performed to show the minimization of order bias effects using the algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.107-111
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• 2005

With the increasing use of multimedia technologies, image compression requires higher performance as well as new functionality in the informationized society. Specially, in the specific area of still image encoding in embedded system, a new standard, JPEG2000 that improve various problem of JPEG was developed. This paper proposed a method that reduce quantity of data delivered in EBCOT(Embedded Block Coding with Optimized Truncation) process using SPIHT(Set Partitioning in Hierarchical Trees) Algorithm to optimize selection of threshold from feature of wavelet transform coefficients and to remove sign bit in LL area for the increment of compression efficiency on JPEG2000. The experimental results showed the proposed algorithm achieves more improved bit rate in embedded system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.894-901
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• 2017

In the existence of motion, azimuth phase error due to accuracy limitation of GPS/IMU and system delay is unavoidable and it is essential to apply autofocus to estimate and compensate the azimuth phase error. In this paper, autofocus algorithm using MWLS(Modified WLS) is proposed. It shows the robust performance compared with original WLS using new target selection/sorting metric and iterative azimuth phase estimation technique. SAR raw data obtained in a captive flight test is used to validate the performance of the proposed algorithm.