• The Journal of Fisheries Business Administration
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• v.16 no.2
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• pp.1-18
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• 1985

The dispute on the object of study in the business management have been carried out since 1912 in Germany, and then it is the situation of "business management" academic world there is no the confirmed object. But P. F. Drucker has prescribed the large enterprise as the object of his study of management, because the large enterprise it the decisive, the representative, and constitutive in modern industrial country. And it is usual that we would consider the large manufacturing enterprise as the object of study. But, in fisheries management, because large fisheries enterprises are almost attached too much to the pelagic fisheries, it is judged that they are not "decisive". And it is judged that they are not "representative", because the large fisheries enterprises can not sufficiently symbolize the managerial characteristic of fisheries industry. The coastal and inshore fisheries which constitute th real part of fishing industry have been operating by private enterprises which are small business in scale, so the large fisheries enterprises could not be considered "constitutive " Therefore, the private fisheries enterprises is "decisive" because it is distributed in all most fisheries management, "representative" because it is exceedingly symbolize the managerial characteristic of fishing industry, and constitutive because it constitute the real part of fisheries industry. From the above-mentioned, it could be concluded that the object of study is regarded the private fisheries enterprise as appropriate as long as it is engaging in producing fisheries product as good and conducts the pursuit of principle of profit maximization. Because the object of study can not include all the thing which has to be observed in order to study, the materialization of the object is actually necessary. And then as aforesaid we intend to realize the materialization through taking the private fisheries enterprise as the object in fisheries management theory. And the materialization does mean a necessary process in choosing the object of analysis, but not the entity itself.choosing the object of analysis, but not the entity itself.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Proceedings of the KAIS Fall Conference
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• 2010.05a
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• pp.9-13
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• 2010

This paper proposes an object-oriented software development guidance and an evaluation index for the productivity related to Seam Framework. Heavyweight and lightweight architecture to resolve the problem with benefits to support the new architecture is a large size distributed object standardization architecture. This architecture, such as the Seam Framework, to provide all of the architecture is possible. The distributed object standardization architecture is most often used in business Seam Framework is well-known architecture. Therefore, this study is based on the Seam Framework large distributed object architecture, design and implementation of standardization software development productivity and the objective is to provide guidance.

• Spatial Information Research
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• v.21 no.6
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• pp.1-9
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• 2013

Recently, Construction information is being changed from CAD to BIM, and GIS is extending from outdoor to indoor information. In these circumstances, the needs of continuous use of construction information linked with GIS are growing constantly in stages of maintenance, operation and service as well as planning, design and construction. To this end, it is essential element to represent 3-dimensional large object efficiently in establishing BIM-GIS interoperability platform by combination of construction and spatial information. In this study, we design spatial data LOD for making spatial object and texture by level, and develop weight lightening algorithm of large spatial object.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.100-110
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• 2005

The update transactions to be executed in spatial databases usually have been known as interactive and long duration works. To improve the parallelism of concurrent updates, it needs multiple transactions concurrently update a large spatial object which has a spatial extensions larger than workspace of a client. However, under the existing locking protocols, it is not possible to concurrently update a large spatial object because of conflict of a write lock This paper proposes a partial locking scheme of enabling a transaction to set locks on parts of a big object. The partial locking scheme which is an exclusive locking scheme set by user, acquires locks for a part of the big object to restrict the unit of concurrency control to a partial object of a big object. The scheme gives benefits of improving the concurrency of un updating job for a large object because it makes the lock control granularity finer.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.12 s.255
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• pp.1649-1657
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• 2006

Fizeau interferometer is well known optical instrument for measuring the lens profile accurately. The object of this study is focused on the design and optical measuring techniques for large optical components, such as a reflection mirror for astronomical purpose. Measuring of large optical lens, the object could not be moved as small one but the measuring instrument must be moved for the alignment, because of the geometric conditions and the accuracy of the stage. Therefore, a five axis stage is designed to align the Interferometer instead of the measuring object. This instrument will be used for an on machine measuring system in polishing machine for large optical lens.

• Journal of computational fluids engineering
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• v.20 no.3
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• pp.8-14
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• 2015

More and more, spaces are decreasing which satisfy multiple requirements for wind power plants. However, areas which have excellent wind resources and are free to civil complaints occupy a large space, although they are exposed to the cryogenic environment. This study conducted a thermal-fluid analysis of a cryogenic chamber for testing large wind turbine parts exposed to the cryogenic environment. The position of supply air is placed to the upper area to compare each cooling performance for each location of various outlets in mixing ventilated conditions. The study carried out CFD analysis for the chamber both with and without a test object. For the cases without the test object, the air temperature of the upper supply and down extract type chamber was cooled faster by 5-100% than the others. However, for the cases with the test object, the object temperature of upper supply and center extract on the opposite side type chamber was cooled faster by 33-132% than the others. The cooling performance by the air inside the chamber and the test object did not show the same pattern, which implicates the need to consider the cooling performance by not only the air but also the test object in the large cryogenic chamber design for testing large parts.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.5
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• pp.534-544
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• 1997

The permittivity distribution of a two-dimensional high-contrast object with large size, which leads to the global minimum of cost function, is reconstructed by iteratively using the hybrid algorithm of Levenberg-magquardt algorithm(LMA) plus Genetic Algorithm(GA). The scattered fields calculated in a cost function are expanded in angular spectral modes, of which only effective propagating modes are used. The definition of cost function based on the effective propagating modes enables us to formulate the minimum number of incident waves for the reconstruction of object. It is numerically shown that LMA has an advantage of fast convergence but can't reconstruct a high-contrast object with large size and GA can reconstruct a high-contrast object with large size but has an disadvantage of slow convergence, whereas an inverse scattering technique using the hybrid algorithm adopts only advantages of LMA and GA.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.12a
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• pp.769-781
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• 1999

Manufacturing systems are usually large, complex, and concurrent in nature that makes it difficult to model and simulate the behavior in advance. The paper proposes an approach, called OPNets, for modeling and validating manufacturing systems. The approach is based on object-oriented high-level Petri nets in which modeling components of Petri net are constructed into object hierarchy. The objects communicate with each other by passing messages. To enhance the reusability and maintainability, a system are developed by object hierarchy. Inheritance among object hierarchy is also supported in OPNets. The modeling scheme of OPNets tries to resolve the complexity problems of Petri net.