• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.933-940
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• 2022

In this paper, the algorithm was developed to recognize hand 3D position through 2D image sensor and implemented a system to remotely control the 6 d.o.f. robot arm by using it. The system consists of a camera that acquires hand position in 2D, a computer that controls robot arm that performs movement by hand position recognition. The image sensor recognizes the specific color of the glove putting on operator's hand and outputs the recognized range and position by including the color area of the glove as a shape of rectangle. We recognize the velocity vector of end effector and control the robot arm by the output data of the position and size of the detected rectangle. Through the several experiments using developed 6 axis robot, it was confirmed that the 6 d.o.f. robot arm remote control was successfully performed.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.163-196
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• 2023

The academic library development plan has external importance as it explicitly declares the library's role and development direction. Internally, it is also a library service guideline. To develop the development plan, libraries must understand the trends and needs of international, national, and affiliating universities and their constituents. Accordingly, this research includes case, content, and network analyses of foreign academic libraries' development plans to identify the trends. The analysis results show most foreign academic libraries employed various strategies and plans, which can be characterized as 'collaboration,' 'collection development,' and 'research support.' Consequently, we propose the following factors to consider when developing an academic library development plan: specification of mission, vision, and core values; recognition of core values such as diversity, equity, and inclusion; awareness of the significance of collaboration and partnership with other units within the universities and external organizations; and utilization of university library development plans as tools for achieving management objectives.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.61-71
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• 2009

Vehicle license plate is the only way to check the registrated information of a vehicle. Many works have been devoted to the vision system of recognizing the license plate, which has been widely used to control an illegal parking. However, it is difficult to correctly segment characters on the license plate since an illumination is affected by a weather change and a neighboring obstacles. This paper proposes a robust method of segmenting the character of the license plate on irregular illumination condition. The proposed method enhance the contrast of license plate images using the Chi-Square probability density function. For segmenting characters on the license plate, binary images with the high quality are gained by applying the adaptive threshold. Preprocessing and labeling algorithm are used to eliminate noises existing during the whole segmentation process. Finally, profiling method is applied to segment characters on license plate from binary images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.19-30
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• 2009

In this paper, We propose a method with which we can detect facial components and face in input image. We use eye map and mouth map to detect facial components using eyes and mouth. First, We find out eye zone, and second, We find out color value distribution of skin region using the color around the eye zone. Skin region have characteristic distribution in YCbCr color space. By using it, we separate the skin region and background area. We find out the color value distribution of the extracted skin region and extract around the region. Then, detect mouth using mouthmap from extracted skin region. Proposed method is better than traditional method the reason for it comes good result with accurate mouth region.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.509-516
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• 2022

Accurate pose prediction of objects in 3D space is an important visual recognition technique widely used in many applications such as scene understanding in both indoor and outdoor environments, robotic object manipulation, autonomous driving, and augmented reality. Most previous works for object pose estimation have the limitation that they require an exact 3D CAD model for each object. Unlike such previous works, this paper proposes a novel neural network model that can predict the poses of unknown objects based on only their RGB color images without the corresponding 3D CAD models. The proposed model can obtain depth maps required for unknown object pose prediction by using an adaptive depth estimator, AdaBins,. In this paper, we evaluate the usefulness and the performance of the proposed model through experiments using benchmark datasets.

• Smart Structures and Systems
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• v.31 no.5
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• pp.469-483
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• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.603-605
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• 2021

With the expansion of the indoor service-providing robot market and the electrification of automobiles, research on autonomous driving is being actively conducted. In general, in the case of outside, the location is mainly recognized through GPS, and location positioning is performed indoors using technologies such as WiFi, UWB (Ultra-Wide Band), VLP, LiDAR, and Vision. In this paper, we introduce a system for location-positioning using LED lights with different color temperatures in an indoor environment. After installing LED lights in a simulated environment such as a tunnel, it was shown that information about the current location can be obtained through the analysis of chromaticity values according to location. Through this, it is expected to be able to obtain information about the location of the vehicle in the tunnel and the movement of the device in a room such as a warehouse or a factory.

• Journal of English Language & Literature
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• v.57 no.5
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• pp.787-812
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• 2011

This essay aims to explore Herman Melville's recognition and resolution of the vicious link between law and violence in his posthumous Billy Budd, Sailor (1924). In order to investigate the issues, this essay refers to Freud, Benjamin, Derrida, Lacan, and Žižek, all perceptive to the uncanny affinity of law and violence. Especially, Žižek's arguments of "superego" as an embodiment of cruel and destructive violence supplementing the official law and of "love" as an ethical possibility beyond the limit of the problematic law are introduced in this study to make Melville's reflection of the inseparableness between law and violence much clearer. John Claggart and Captain Vere embody the legal (superegoic) violence. Claggart even procurs secret enjoyment, in the name of maintaining positive law. Billy Budd discloses another violence defending his justness according to natural law. However, Melville suggests the possibility of suspending the problematic tie of law/violence through "love," as portrayed at the last part of the story. The two final words from Billy and Vere, as a sort of delayed dialogue between them after the event of their secret interview before Billy's hanging, suggest that they finally distance from the obscene nightly law of superego-respectively from outward punitiveness toward Vere and from inward punishment for Vere's excessive enforcement of Billy's hanging-and identify each other's lack as their own. Their love implicated in the last words is for the real other-in Lacan's sense-who discloses the constitutive lack or incompleteness of beings and aporia of the law. This essay's examination of Melville's representations about the superegoic violence as the (im-)possible condition of law and the possibility of withdrawing from it would help us recognize Billy Budd, Sailor as the author's own last word for the possible vision of love cutting the vicious knot of law/violence.

• Journal of English Language & Literature
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• v.55 no.1
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• pp.25-59
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• 2009

This study explores the characteristics of Elizabeth Bishop's poetry in comparison with the two of her closest friends and poets, Marianne Moore and Robert Lowell. Bishop's reputation has dramatically changed since her death. In the 1970s she was "a writer's writer's writer," and admired by a small group of poets or critics. Since 1990s, however, there has been a great shift in the evaluation of her poetry, which is so called "The Elizabeth Bishop Phenomenon." It does not seem to be an easy task to examine what has driven the phenomenon, and why she used to be a minor poet or "the most honored yet most elusive of poets" but now she has a widespread recognition by the academy and beyond it. The "intrinsic qualities" of Bishop's poetry, however, can be one of the main reasons why it took several decades for Bishop to become a central figure in the literary canon. Looking into her "intrinsic qualities," this paper discusses Bishop's "The Fish," "Roosters" through the Moore-Bishop relationship, and reads Bishop's "Armadillo" and "The Monument" through the Lowell-Bishop relationship. It also deals with letters, interviews, Moore's "The Fish," and Lowell's "Skunk Hour" and "For the Union Dead" to show the Bishop's deep and complex relationships with the two poets, and more importantly their differences. Bishop's poetry is difficult, "elusive," and sometimes "enigmatic," not because her texts are full of difficult words to understand but because there are the subtle interchange between perception and meaning, "the dynamics of keen feeling," the unresolved patterns, and the transient vision under the seemingly transparent surface of the texts.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.119-124
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• 2023

Deep learning has recently demonstrated conspicuous efficacy across diverse domains than traditional machine learning techniques, as the most popular approach for pattern recognition. The classification problems for tabular data, however, are remain for the area of traditional machine learning. This paper introduces a novel network module designed to tabular data into high-dimensional tensors. The module is integrated into conventional deep learning networks and subsequently applied to the classification of structured data. The proposed method undergoes training and validation on four datasets, culminating in an average accuracy of 90.22%. Notably, this performance surpasses that of the contemporary deep learning model, TabNet, by 2.55%p. The proposed approach acquires significance by virtue of its capacity to harness diverse network architectures, renowned for their superior performance in the domain of computer vision, for the analysis of tabular data.