• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.21 no.1
• /
• pp.68-73
• /
• 2013

This study is to make a protype of forecast guidance for forecasters from analyzing the characteristics of Korea Fog. The trend of Korea fog showed the decline in the number of foggy days and the duration time, the gradient is -1.24days/year under 3 miles and -0.98days/year under 1 mile and -1.64hours/year under 3 miles and -3.18hours/year under 1 mile in duration time in 27 ROKAF base. To find the protype of inland and coastal forecast guidance, Daegu base as a representation of the inland base and Gangneung base as the representation of the coastal base were chosen. For Daegu base, the mixture of relative humidity, sky condition, and the position of high pressure were selected for the forecast guidance. For Gangneung base, pressure pattern, sea surface temperature, sea currents, and 850hPa temperature patterns were selected for the forecast guidance.

• Journal of the Korean Mathematical Society
• /
• v.45 no.2
• /
• pp.575-585
• /
• 2008

Suppose that D is a $C^*$-discrete quantum group and $D_0$ a discrete quantum group associated with D. If there exists a continuous action of D on an operator algebra L(H) so that L(H) becomes a D-module algebra, and if the inner product on the Hilbert space H is D-invariant, there is a unique $C^*$-representation $\theta$ of D associated with the action. The fixed-point subspace under the action of D is a Von Neumann algebra, and furthermore, it is the commutant of $\theta$(D) in L(H).

• Kyungpook Mathematical Journal
• /
• v.62 no.3
• /
• pp.407-423
• /
• 2022

In this paper, we determine the structure of rings that have secondary representation (called representable rings) and give some characterizations of these rings. Also, we characterize Artinian rings in terms of representable rings. Then we introduce completely representable modules, modules every non-zero submodule of which have secondary representation, and give some necessary and sufficient conditions for a module to be completely representable. Finally, we define strongly representable modules and give some conditions under which representable module is strongly representable.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.4
• /
• pp.43-52
• /
• 1996

This paper describes interactive computer procedures for design the forming sequences in cold forging. This system is implemented on the personal computer and its environment is a commercial AutoCAD system. The programming language. AutoLISP, was used for the configuration of the system. Since the process of metal forming can be considered as a transformation of geometry, treatment of the geometry of the part is a key in process planning. To recognize the part section geometry, the section entity representation, the section coordinate-redius representation and the section primitive geometru were adopted. This system includes six major modules such as input module, forging design module, forming sequence design module, die design module, FEM verification module and output module which are used independently or in all. The sequence drawing wigh all dimensions, which includes the dimensional tolerances and the proper sequence of operations, can generate under the environment of AutoCAD. The acceptable forming sequences can be verified further, using the FE simulation.

• Journal of Information Processing Systems
• /
• v.16 no.2
• /
• pp.261-276
• /
• 2020

Digital contents services are one of the topics that have been intensively studied in the media industry, where various semantic and ontology techniques are applied. However, query execution for ontology data is still inefficient, lack of sufficient extensible definitions for node relationships, and there is no specific semantic method fit for media data representation. In order to make the machine understand digital contents (DCs) data well, we analyze DCs data, including static data and dynamic data, and use ontology to specify and classify objects and the events of the particular objects. Then the formal representation method is proposed which not only redefines DCs data based on the technology of OWL/RDF, but is also combined with media segmentation methods. At the same time, to speed up the access mechanism of DCs data stored under the persistent database, an ontology-based DCs query solution is proposed, which uses the specified distance vector associated to a surveillance of semantic label (annotation) to detect and track a moving or static object.

• International Journal of Contents
• /
• v.11 no.3
• /
• pp.47-53
• /
• 2015

Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

• Convergence Security Journal
• /
• v.7 no.1
• /
• pp.83-89
• /
• 2007

This paper is to suggest the method of embedding a signature to pictures secretly under the orthogonal wavelet transform which represents pictures as multi-resolution representations. As it is focused upon the differential output under the multi-resolution representation of pictures, this method can embed bit series to pictures. In doing so, it can compound approximately 6K byte of information with gray-level image $256{\times}256$. The method can include not only the database which designates copyright of pictures but also the author and usage of pictures, and the information of the picture itself. Therefore, this method can easily discriminate the inspection of picture database.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.11
• /
• pp.3761-3779
• /
• 2022

The performance of existing recognition algorithms for binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals degrade under conditions of low signal-to-noise ratios (SNR). Hence, a novel recognition algorithm based on features in the graph domain is proposed in this study. First, the power spectrum of the squared candidate signal is truncated by a rectangular window. Thereafter, the graph representation of the truncated spectrum is obtained via normalization, quantization, and edge construction. Based on the analysis of the connectivity difference of the graphs under different hypotheses, the sum of degree (SD) of the graphs is utilized as a discriminate feature to classify BPSK and QPSK signals. Moreover, we prove that the SD is a Schur-concave function with respect to the probability vector of the vertices (PVV). Extensive simulations confirm the effectiveness of the proposed algorithm, and its superiority to the listed model-driven-based (MDB) algorithms in terms of recognition performance under low SNRs and computational complexity. As it is confirmed that the proposed method reduces the computational complexity of existing graph-based algorithms, it can be applied in modulation recognition of radar or communication signals in real-time processing, and does not require any prior knowledge about the training sets, channel coefficients, or noise power.

• Cross-Cultural Studies
• /
• v.29
• /
• pp.25-53
• /
• 2012

The attitude of observer in the painting of history is to exclude a prejudice and a subjective view of an artist and to introduce a photograph, which is a record of objectivity, in the process of painting. Its ultimate intent is to redescribe the fact of an event's image intactly without any prejudice and to represent the event as a proven evidence that it was. The representation of history based on fact had already been conceived in imagination of renowned artists such as Francisco Goya or $Th{\acute{e}}odore$ $G{\acute{e}}ricault$ even before cameras were invented. What they portrayed was their own truth of reality which is gained through their observation, not a history that have corresponded to political ideologies, for all reliance on a limited tool of representation, painting. Furthermore, history was necessary for 19th century impressionism artists to be represented under proven fact in a neutral perspective excluding all subjective prejudice, not based on the representation with imagination. Edouard Manet in particular reconstited an instant moment on the basis of real proof of photograph without personal prejudice or opinion as if today's photojournalism. The catastrophic series by Andy Warhol and the photographic painting by Gerhard Richter show another role of painting in the realm of art, each of them implying information distortion and abuse by current media and intentional deformation toward history as Manet's painting of history. Today, the representation of an historical event that we experience in the era of the Internet and social networks having a great deal of information already came to be the exclusive property of the cutting edge mass media. Nevertheless, the attitude of observer which is realistic and contemplative in the realm of art is the crucial point in terms of artists' act as ever.

• Current Optics and Photonics
• /
• v.5 no.3
• /
• pp.270-277
• /
• 2021

The adaptive sparse representation (ASR) can effectively combine the structure information of a sample dictionary and the sparsity of coding coefficients. This algorithm can effectively consider the correlation between training samples and convert between sparse representation-based classifier (SRC) and collaborative representation classification (CRC) under different training samples. Unlike SRC and CRC which use fixed norm constraints, ASR can adaptively adjust the constraints based on the correlation between different training samples, seeking a balance between l₁ and l₂ norm, greatly strengthening the robustness and adaptability of the classification algorithm. The correlation coefficients (CC) can better identify the pixels with strong correlation. Therefore, this article proposes a hyperspectral image classification method called correlation coefficients and adaptive sparse representation (CCASR), based on ASR and CC. This method is divided into three steps. In the first step, we determine the pixel to be measured and calculate the CC value between the pixel to be tested and various training samples. Then we represent the pixel using ASR and calculate the reconstruction error corresponding to each category. Finally, the target pixels are classified according to the reconstruction error and the CC value. In this article, a new hyperspectral image classification method is proposed by fusing CC and ASR. The method in this paper is verified through two sets of experimental data. In the hyperspectral image (Indian Pines), the overall accuracy of CCASR has reached 0.9596. In the hyperspectral images taken by HIS-300, the classification results show that the classification accuracy of the proposed method achieves 0.9354, which is better than other commonly used methods.