• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.183-196
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• 2018

Studies that approach from the point of view that human thoughts or minds are dominated by behavior as well as that human behavior is dominated by thoughts or minds, have begun to attract attention from the late 2000s. The physical experience is reminiscent of a metaphorically connected abstract concept, which ultimately affects the judgment or evaluation of a particular object. However, studies that have been carried out so far have been limited to studies on the difference in perception and judgment depending on the objects to be viewed, the objects to be touched, and the objects to which they are carried. In this study, we tried to find out that the physical movement of the body in the upward or downward direction affects the psychological judgment differently. In the first experiment, a pair of words that were considered to be connected metaphorically was tested. In the second experiment, the subjects tried to solve the complicated calculation problem in a short time, and then they watched the video related to the upward movement or downward movement, and then proceeded to measure the psychological judgment. As a result, it was found that 'downward movement' of the body has a metaphorical connection with 'closure', while 'upward movement' is related to 'progress'. In the case of downward-experienced group compared to upward-experienced group, the reverse intentions of their own decision were low, and the confidences in their own decision and the expectations for performance were high.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.361-369
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• 2002

In order to extract motion features from an input image acquired by a static CCD-camera in a restricted area, we need a robust algorithm to cope with noise sensitivity and condition change. In this paper, we proposed an efficient algorithm to extract and track motion features in a noisy environment or with sudden condition changes. We extract motion features by considering a change of neighborhood pixels when moving objects exist in a current frame with an initial background. To remove noise in moving regions, we used a morphological filter and extracted a motion of each object using 8-connected component labeling. Finally, we provide experimental results and statistical analysis with various conditions and models.

• Journal of Sensor Science and Technology
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• v.14 no.3
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• pp.198-205
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• 2005

Recently, the systems using multiple sensors such as magnetic, acoustic and pressure sensor are used for detection of underwater objects or vehicles. Those systems have difficulty of maintenance and repair because they operate underwater. Thus, this paper describes a hybrid detection system with long term operating reliability. This has a multi-signal transmission structure to have a high reliability. First, a signal transmission & receiving part, which transfers data from underwater sensors to land and receive control message from land through optical cable, has 4 multi-path. Second, the nodes for signal transmission are connected dually each other with single-hop construction and sensors are connected to a couple of neighboring nodes. This enables the output signal to transmit from a node to the next node and the next but one node together. Also, the signal from a sensor can be transmitted to two nodes at the same time. Therefore, the system with this construction has high reliability in long term operation because it makes possible to transmit sensor data to another node which works normally although a transmission node or cable in system have some faults.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.38.3-39
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• 2016

We present the results of a search for Very Low-Luminosity Objects (VeLLOs) in the Gould Belt (GB) clouds using infrared and sub-millimeter (sub-mm) data from 1.25 to $850{\mu}m$ and our N2H+ (J = 1-0) observations. We modified the criteria by Dunham et al. to select the VeLLOs in the GB clouds, finding 95 VeLLO candidates, 79 of which are newly identified in this study. Out of 95 sources, 44 were detected in both sub-mm continuum and N2H+ emission and were classified as Group A (the VeLLOs), and 51 sources detected in either sub-mm emission or N2H+ emission were classified with Group B as candidate VeLLOs. We find that these VeLLOs and the candidates are forming in environments different from those of the likely VeLLOs. Seventy-eight sources are embedded within their molecular clouds, and thus are likely VeLLOs forming in a dense environment. The remaining 17 sources are located in low-level extinction regions (Av < 1) connected to the clouds, and can be either background sources or candidate substellar objects forming in an isolated mode. The VeLLOs and the candidates are likely more luminous and their envelopes tend to be more massive in denser environments. The VeLLOs and the candidates are more populous in the clouds where more YSOs form, indicating that they form in a manner similar to that of normal YSOs. The bolometric luminosities and temperatures of the VeLLOs are compared to predictions of episodic accretion models, showing that the low luminosities for most VeLLOs can be well explained by their status in the quiescent phases of a cycle of episodic mass accretion.

• Smart Structures and Systems
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• v.14 no.4
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• pp.719-741
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• 2014

Monitoring surface cracks is important to ensure the health of concrete structures. However, traditional visual inspection to monitor the concrete cracks has disadvantages such as subjective inspection nature, associated time and cost, and possible danger to inspectors. To alter the visual inspection, a complete procedure for automated crack assessment based on adaptive digital image processing has been proposed in this study. Crack objects are extracted from the images using the subtraction with median filter and the local binarization using the Niblack's method. To adaptively. determine the optimal window sizes for the median filter and the Niblack's method without distortion of crack object an optimal filter size index (OFSI) is proposed. From the extracted crack objects using the optimal size of window, the crack objects are decomposed to the crack skeletons and edges, and the crack width is calculated using 4-connected normal line according to the orientation of the local skeleton line. For an image, a crack width nephogram is obtained to have an intuitive view of the crack distribution. The proposed procedure is verified from a test on a concrete reaction wall with various types of cracks. From the crack images with different crack widths and patterns, the widths of cracks in the order of submillimeters are calculated with high accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.149-157
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• 2008

In the field of computing service, there is a copernican revolution indebted to development of network & computer technology. Computer system, which is set to mainframe in the 1960's, is advancing torwards to the paradigm of server based computing, so-called thin-client. In thin-client computing, network is the platform which is responsible for transfer of application, so that client execute application installed on server. It is also possible that each system share the computing resource connected with network. In this parer, we suggest component & distributed computing technology as a measn for the implementation of thin-client architecture hence, make the best use of COM(Component Object Model and PYRO(PYthon Remote Objects). We talk about the concept and mechanism of thin-client at the beginning, and propose the design of network architecture for the implementation thin-client.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.11
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• pp.1133-1144
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• 2019

Recently, the amount of image on the Internet has rapidly increased, due to the advancement of smart devices and various approaches to effective image retrieval have been researched under these situation. Existing image retrieval methods simply detect the objects in a image and carry out image retrieval based on the label of each object. Therefore, the semantic gap occurs between the image desired by a user and the image obtained from the retrieval result. To reduce the semantic gap in image retrievals, we connect the module for multiple objects classification based on deep learning with the module for human behavior classification. And we combine the connected modules with a behavior ontology. That is to say, we propose an image retrieval system considering the relationship between objects by using the combination of deep learning and behavior ontology. We analyzed the experiment results using walking and running data to take into account dynamic behaviors in images. The proposed method can be extended to the study of automatic annotation generation of images that can improve the accuracy of image retrieval results.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.941-948
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• 2024

BIM (Building Information Modeling) is touted for efficient building maintenance and operation. However, transitioning from construction to maintenance poses challenges in information transfer and definitive data before completion. Existing structures often lack BIM, demanding more modeling. Additionally, few maintenance staff are skilled in BIM tools.On the other hand, there are studies utilizing point clouds for maintenance. Since point cloud data can record the current situation in 3D, it has advantages such as easily representing valve positions of equipment compared to deformed BIM data.Attribute information uses the international standard COBie, which can record and manage data necessary for building asset management.Point cloud data is broken down into groups of objects necessary for maintenance management by referencing the Common Specification for Building Preservation. Each decomposed object is assigned a corresponding Uniclass number.In this system, the point cloud data, which represents the shape information of the building, is decomposed into objects based on the Common Specification. Using COBie, the building database is created and tasks related to the objects are organized. Each database and system is then connected using Uniclass.By implementing this system, even buildings completed can easily create BIM data from point clouds. Furthermore, since it complies with the international standard COBie, maintenance tasks can be performed in a standardized format, serving as a bridge to the maintenance management system.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.