• Journal of fish pathology
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• v.34 no.1
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• pp.17-22
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• 2021

Eukaryotic translation is initiated by either cap-dependent or cap-independent way, and the cap-independent translation can be initiated by the internal ribosomal entry site (IRES). In this study, to know whether the 5'UTR leader sequence of marine birnavirus (MABV) segment A and segment B can act as IRES, bicistronic vectors harboring a CMV promoter-driven red fluorescent gene (mCherry) and poliovirus IRES- or MABV's leader sequence-driven green fluorescent gene (eGFP) were constructed, then, transfected into a mammalian cell line (BHK-21 cells) and a fish cell line (CHSE-214 cells). The results showed that the poliovirus IRES worked well in BHK-21 cells, but did not work in CHSE-214 cells. In the evaluation of MABV's leader sequences, the reporter eGFP gene under the 5'UTR leader sequence of MABV's segment A was well-translated in CHSE-214 cells, indicating 5'UTR of MABV's segment A initiates translation in the cap-independent way and can be used as a fish-specific IRES system. However, the 5'UTR leader sequence of MABV's segment B did not initiate translation in CHSE-214 cells. As the precise mechanism of birnavirid IRES-mediated translation is not known, more elaborate investigations are needed to uncover why the leader sequence of segment B could not initiate translation in the present study. In addition, further studies on the host species range of MABV's segment A IRES and on the screening of other fish-specific IRESs are needed.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.629-640
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• 2000

this paper present an efficient line-drawing algorithm that reduces the amount of space required, Because of its efficiency , this line-drawing algorithm is faster than the Bresenham algorithm or the recursive bisection method. this efficiency was achieved through a new data structure; namely , the modified segment tree (MST). Using the modified segment tree and the distribution rule suggested in this paper, we dra lines without generating the recursive calls used in [3] and without creating the binary operation used in [4]. we also show that line accuracy improves in proportion to the display resolution . In practice, we can significantly improve the algorithm's performance with respect to time and space, This improvement offer an increase in speed, specially with lines at or near horizontal, diagonal. or vertical ; that is, this algorithm requires the time complexity of (n) and the space complexity O(2k+1), where n is the number of pixels and k is a level of the modified segment tree.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1496-1499
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• 2004

The paper persents an efficient method of extracting line segment in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities based on the simplified Bayesian updating model. The probabilities and orientations of cells in the grid map are continuously updated while the robot explorers to their values. The line segments are, then, extracted from the clusters using Hough transform methods. The eng points of a line segment are evaluated from the cells in each cluster, which is simple and efficient comparing to existing methods. The proposed methods are illustrated by sets of experiments in an indoor environment.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.59-64
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• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.1022-1030
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• 2003

In this paper we propose a efficient offset curve construction algorithm for $C^0$-continuous Open and Closed 2D sequence curve with line segment in the plane. One of the most difficult problems of offset construction is the loop problem caused by the interference of offset curve segments. Prior work[1-10] eliminates the formation of local self-intersection loop before constructing a intermediate(or raw) offset curve, whereas the global self-intersection loop are detected and removed explicitly(such as a sweep algorithm[13]) after constructing a intermediate offset curve. we propose an algorithm which removes global as well as local intersection loop without making a intermediate offset curve by forward tracing of tangential circle. Offset of both open and closed poly-line segment sequence curve in the plane constructs using the proposed approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1095-1109
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• 2022

Along with the popularity of GPS system and smart cell phone, trajectories of pedestrians or vehicles are recorded at any time. The great amount of works had been carried out in order to discover traffic paradigms or other regular patterns buried in the huge trajectory dataset. The core of the mining algorithm is how to evaluate the similarity, that is, the "distance", between trajectories appropriately, then the mining results will be accordance to the reality. Euclidean distance is commonly used in the lots of existed algorithms to measure the similarity, however, the trend of trajectories is usually ignored during the measurement. In this paper, a novel segment transform distance (STD) algorithm is proposed, in which a rule system of line segment transformation is established. The similarity of two-line segments is quantified by the cost of line segment transformation. Further, an improvement of STD, named ST-DTW, is advanced with the use of the traditional method dynamic time warping algorithm (DTW), accelerating the speed of calculating STD. The experimental results show that the error rate of ST-DTW algorithm is 53.97%, which is lower than that of the LCSS algorithm. Besides, all the weights of factors could be adjusted dynamically, making the algorithm suitable for various kinds of applications.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.125-132
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• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.133-140
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• 2002

This paper presents a method for line segment grouping used for detection of various building roofs. First, by using edge preserving filtering. noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line linking is performed according to direction and length of line segments and finally the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. The algorithm has been applied to aerial imagery and the results show accurate building roof detection.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.645-652
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• 2004

In this paper, we aggregate multi-links information between boundary nodes using the line segment scheme that aggregates topology in-formation within PG referring bandwidth and delay parameter. The proposed scheme can search multi-links efficiently using the depth priority method based on hop count instead of searching all links. To do this, we propose a modified line segment algorithm using two line segment method that represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multi pie-links aggregation. And we apply it to current star topology aggregation. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme with respect to call success rate, access time and crankback rate. Through the simulation result analysis, the proposed star topology aggregation scheme presents the better performance than existing scheme.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.1-10
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• 2013

This paper proposes a method to detect vanishing points of an indoor scene using line segment classification. Two-stage vanishing points detection is carried out to detect vanishing point in indoor scene efficiently. In the first stage, the method examines whether the image composition is a one-point perspective projection or a two-point one. If it is a two-point perspective projection, a horizontal line through the detected vanishing point is found for line segment classification. In the second stage, the method detects two vanishing points exactly using line segment classification. The method is evaluated by synthetic images and an image DB. In the synthetic image which some noise is added in, vanishing point detection error is under 16 pixels until the percent of the noise to the image becomes 60%. Vanishing points detection ratio by A.Quattoni and A.Torralba's image DB is over 87%.