• Computers and Concrete
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• v.10 no.6
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• pp.609-630
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• 2012

Currently, the design of reinforced concrete deep beams with web openings is carried out using empirical or semi-empirical methods and hence their scope of application is limited. In particular, high strength concrete deep beams with various web opening configurations have been given little treatment. In view of this, a nonlinear layered finite element method (LFEM) for cracking and failure analysis of reinforced concrete structures is used to conduct a parametric study to investigate reinforced concrete deep beams various web opening behaviours. This paper initially presents comparisons of LFEM output with published test results to numerical techniques. The paper then focuses on a parametric study on the shear strengths of deep beams with varying web opening configurations such as opening sizes and locations. The results confirm that the current design methods are inadequate in predicting the maximum shear strength when web openings are present. A series of parametric study offers insight into the maximum shear strength of the deep beams being critically influenced by the size and location of web openings.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.165-172
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• 2020

Recently, due to exponential growth of access information on the web, the importance of predicting a user's next web page use has been increasing. One of the methods that can be used for predicting user's next web page is deep learning. To predict next web page, web logs are analyzed by data preprocessing and then a user's next web page is predicted on the output of the analyzed web logs using a deep learning algorithm. In this paper, we propose a framework for web page prediction that includes methods for web log preprocessing followed by deep learning techniques for web prediction. To increase the speed of preprocessing of large web log, a Hadoop based MapReduce programming model is used. In addition, we present a web prediction system that uses an efficient deep learning technique on the output of web log preprocessing for training and prediction. Through experiment, we show the performance improvement of our proposed method over traditional methods. We also show the accuracy of our prediction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.367-369
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• 2022

With the development of web technology, the web provides customized information that meets the needs of users. Information is provided according to the input form and the user's query, and a web service that provides information that is difficult to search with a search engine is called an in-depth web. These deep webs contain more information than surface webs, but it is difficult to collect information with general crawling, which collects information at the time of the visit. The deep web provides users with information on the server by running script languages such as javascript in their browsers. In this paper, we propose an algorithm capable of exploring dynamically changing websites and collecting information by analyzing scripts for deep web collection. In this paper, the script of the bulletin board of the Korea Centers for Disease Control and Prevention was analyzed for experiments.

• Computers and Concrete
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• v.15 no.1
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• pp.21-35
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• 2015

The objective of this study is to examine the effect of carbon fiber reinforced polymer (CFRP) on the shear strengths of deep beams with web openings. A total of 18 high-strength concrete deep beams with web openings were tested. Twelve were externally wrapped with four layers of CFRP, six of them strengthened in the horizontal direction and the others in the vertical direction. The parameters of the configuration of CFRP, the sizes of the openings and the locations of the openings were covered in this study. The test results indicates the shear strengths of deep beams with openings sized $60{\times}40mm$ were about 16% higher than that with openings sized $68{\times}68mm$. For deep beams with openings sized $60{\times}40mm$, the lower the locations of openings the higher the shear strengths were. The test results also indicate the shear strengths of deep beams with web openings strengthened by CFRP wrapped in the vertical direction can be enhanced by about 10%. However, the shear strengths of deep beams with web openings strengthened by CFRP wrapped in the horizontal direction can only be enhanced by about 6%. The shear strengths of deep beam, with different size and location of web openings and strengthened by different configuration of CFRP can be reasonably predicted by the empirical formulas of Kong and Sharp.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.897-902
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• 2001

The purpose of this experimental study is to investigate the shear behavior of high-strength concrete deep beam and to grasp the conservatism of ACI Building Code. Experimental results on 12 deep beams under two equal symmetrically placed point loads are reported. Main variables are vertical and horizontal web reinforcement and shear span-to-overall depth ratio. Test results indicated that web reinforcement dose not affect on formation of inclined cracks but shear span-to-overall depth ratio affect on inclined shear cracks and ultimate shear strength. Addition of vertical web reinforcement improves ultimate shear strength of H.S.C. deep beams that shear span-to-overall depth ratio is 1.0. Considerable increase in ultimate shear strength of H.S.C. deep beams with increasing horizontal web reinforcement that shear span-to-overall depth ratio is 0.5. Especially with increasing concrete strength($f_{ck}$) the ACI code is conservative in estamating the ultimate shear strength of deep beams.

• Structural Engineering and Mechanics
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• v.19 no.4
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• pp.361-379
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• 2005

Reinforced concrete deep beams have useful applications in tall buildings and foundations. Over the past two decades, numerous design models for deep beams were suggested. However even the latest design manuals still offer little insight into the design of deep beams in particular when complexities exist in the beams like web openings. A method commonly suggested for the design of deep beams with openings is the strut-and-tie model which is primarily used to represent the actual load transfer mechanism in a structural concrete member under ultimate load. In the present study, the development of the strut-and-tie model is transformed to the topology optimization problem of continuum structures. During the optimization process, both the stress and displacement constraints are satisfied and the performance of progressive topologies is evaluated. The influences on the strut-and-tie model in relation to different size, location and number of openings, as well as different loading and support conditions in deep beams are examined in some detail. In all, eleven deep beams with web openings are optimized and compared in nine groups. The optimal strut-and-tie models achieved are also compared with published experimental crack patterns. Numerical results have shown to confirm the experimental observations and to efficiently represent the load transfer mechanism in concrete deep beams with openings under ultimate load.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.97-105
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• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.1-7
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• 2023

Deep web collection means entering a query in a search form and collecting response results. It is estimated that the information possessed by the deep web has about 450 to 550 times more information than the statically constructed surface web. The static method does not show the changed information until the web page is refreshed, but the dynamic web page method updates the necessary information in real time and provides real-time information without reloading the web page, but crawler has difficulty accessing the updated information. Therefore, there is a need for a way to automatically collect information on these deep webs using a crawler. Therefore, this paper proposes a method of utilizing scripts as general links, and for this purpose, an algorithm that can utilize client scripts like regular URLs is proposed and experimented. The proposed algorithm focused on collecting web information by menu navigation and script execution instead of the usual method of entering data into search forms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• Architectural research
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• v.7 no.2
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• pp.55-60
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• 2005

Based on an experimental study, this study provides an equation to describe the shear strength of high-strength concrete deep beams with rectangular openings and without web reinforcements. Twenty-four concrete deep beams were tested with the variables of concrete strength, size of web opening, and shear span-to-depth ratio. The proposed equation is expressed as the sum of the shear strength provided by longitudinal bars and concrete. It is illustrated that the proposed equation predicts the load-carrying capacity of the deep beams more properly than the experimental equations proposed by other researchers.