• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2193-2198
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• 2016

In this study, we propose an algorithm to simulate the function of the coupling structure and having two neurons to find out exactly recover the temporary or permanent position errors that can occur during operation in a digital circuit was separated by function, a $3{\times}3$ array. If any particular part in the combined cells are differentiated cells have a problem that function to other cells caused an error and perform the same function are subjected to a step of apoptosis by the surrounding cells. Designed as a function block in the function and the internal structure having a cell structure of this digital circuit proposes an algorithm. In case of error of module 4 of block 1 considered in this study, sum of all module numbers for horizontal direction, total module number sum for vertical direction, and sum of all module numbers for diagonal direction, We were able to find the location.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.339-345
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• 2016

In general, mosaic blocks are used to hide some specified areas, such as human faces and disgusting objects, in an input image when images are uploaded on a web-site or blog. This paper proposes a new algorithm for robustly detecting grid mosaic areas in an image based on the edge projection. The proposed algorithm first extracts the Canny edges from an input image. The algorithm then detects the candidate mosaic blocks based on horizontal and vertical edge projection. Subsequently, the algorithm obtains real mosaic areas from the candidate areas by eliminating the non-mosaic candidate regions through geometric features, such as size and compactness. The experimental results showed that the suggested algorithm detects mosaic areas in images more accurately than other existing methods. The suggested mosaic detection approach is expected to be utilized usefully in a variety of multimedia-related real application areas.

• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1117-1124
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• 2007

In this paper, an algorithm that can define the threshold value automatically proposed in order to detect a brain ventricle in MRI brain images. After the wavelet transform, edge sharpness, which means the average magnitude of detail signals on the contour of the object, was computed by using the magnitude of horizontal and vertical detail signals. The contours of a brain ventricle were detected by increasing the threshold value repeatedly and computing edge sharpness. When the edge sharpness became maximal, the optimal threshold was determined, and the detection of a brain ventricle was accomplished finally. In this paper, we compared the proposed algorithm with the geodesic active contour model numerically and verified the efficiency of the proposed algorithm by applying real MRI brain images.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.1-13
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• 2024

In this study, we applied an on-site diagnostic method for estimating the structural safety of a plastic greenhouse. A three-dimensional light detection and ranging (3D LiDAR) sensor was used to scan the greenhouse to extract point cloud data (PCD). Differential thresholds of the color index were applied to the partitions of raw PCD to separate steel frames from plastic films. Additionally, the K-means algorithm was used to convert the steel frame PCD into the nodes of unit members. These nodes were subsequently transformed into structural shape data. To verify greenhouse shape reproducibility, the member lengths of the scan and blueprint models were compared with the measurements along the X-, Y-, and Z-axes. The error of the scan model was accurate at 2%-3%, whereas the error of the blueprint model was 5.4%. At a maximum snow depth of 0.5 m, the scan model revealed asymmetric horizontal deflection and extreme bending stress, which indicated that even minor shape irregularities could result in critical failures in extreme weather. The safety factor for bending stress in the scan model was 18.7% lower than that in the blueprint model. This phenomenon indicated that precise shape estimation is crucial for safety diagnostic. Future studies should focus on the development of an automated process based on supervised learning to ensure the widespread adoption of greenhouse safety diagnostics.

• International Journal of CAD/CAM
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• v.4 no.1
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• pp.33-45
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• 2004

In this work, a rational procedure has been formulated for the selection of points approximating slice contours cut in LOM (Laminated Object manufacturing) with first order approximation. It is suggested that the number of points representing a slice contour can be 'minimised' or 'optmised' by equating the horizontal chordal deviation (HCD) to the user-defined surface form tolerance. It has been shown that such optimization leads to substantial reduction in slice height calculations and NC codes file size for cutting out the slices. Due to optimization, the number of contour points varies from layer to layer, so that points on successive layer contours have to be matched by four sided ruled surface patches and triangular patches. The technological problems associated with the cutting out of triangular patches have been addressed. A robust algorithm has been developed for the determination of slice height for optimum and arbitrary numbers of contour points with different strategies for error calculations. It has been shown that optimisation may even lead to detection and appropriate representation of elusive surface features. An index of optimisation has been defined and calculations of the same have been tabulated.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.170-176
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• 2010

Prediction is an important step in high-performance lossless data compression. In this paper, we propose a novel lossless image coding algorithm to increase prediction accuracy which can display low-resolution images quickly with a multi-resolution image technique. At each resolution, we use pixels of the previous resolution image to estimate current pixel values. For each pixel, we determine its estimated value by considering horizontal, vertical, diagonal edge information and average, weighted-average information obtained from its neighborhood pixels. In the experiment, we show that our method obtains better prediction than JPEG-LS or HINT.

• Structural Engineering and Mechanics
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• v.60 no.3
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• pp.405-412
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• 2016

Bone is a living material with a complex hierarchical structure that gives it remarkable mechanical properties. Bone constantly undergoes mechanical. Its quality and resistance to fracture is constantly changing over time through the process of bone remodeling. Numerical modeling allows the study of the bone mechanical behavior and the prediction of different trauma caused by accidents without expose humans to real tests. The aim of this work is the modeling of the femur fracture under static solicitation to create a numerical model to simulate this element fracture. This modeling will contribute to improve the design of the indoor environment to be better safe for the passengers' transportation means. Results show that vertical loading leads to the femur neck fracture and horizontal loading leads to the fracture of the femur diaphysis. The isotropic consideration of the bone leads to bone fracture by crack propagation but the orthotropic consideration leads to the fragmentation of the bone.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.66-72
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• 2017

The three dimensional ultrasonic anemometer was constructed to reduce the disadvantages of the two-dimensional anemometer and to be free from the use environment. Three pairs of transmitting and receiving ultrasonic sensors were designed to face each other at an angle of $45^{\circ}$ to the upper and lower surfaces at intervals of $120^{\circ}$. 200 kHz ultrasonic sensor Oscillation, transmission and reception, level detection, power supply circuit were designed and U, V, W wind speed vector components were obtained by measuring the time of first received ultrasonic pulse by transmitting pulse ultrasound. It is implemented as firmware in ARM Coretex-M3 processor so that horizontal and vertical wind direction and wind speed can be converted into digital signal by vector calculation. In this study, The three-dimensional ultrasonic anemometer can complement the disadvantages of the two-dimensional anemometer (mechanical and ultrasonic), and it is expected to gradually replace the two-dimensional anemometer due to its high utilization rate by collecting additional information such as vertical wind.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.122-128
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• 1998

This paper presents compression of image sequences based on the classification of interframe difference image blocks. classification process consists of image activity classification and energy distribution classification. In the activity classification, interframe difference image blocks are classified into activity blocks and non-activity blocks using the edge detection. In the distribution classification, activity blocks are further classified into vertical blocks, horizontal blocks, and small activity blocks using the AC energy distribution features. The RBFN, trained with numerical classification results, successfully classifies difference image blocks according to image details. Image sequence compressing based on the classification of interframe difference image blocks using the RBFN shows better compression results and less training time than the classical sorting method and the MLP network.