• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.89-101
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• 2019

Many researchers have been focused on designing beauty product recommendation system for a long time because of increased need of customers for personalized and customized recommendation in beauty product domain. In addition, as the application of the deep neural network technique becomes active recently, various collaborative filtering techniques based on the deep neural network have been introduced. In this context, this study proposes a deep neural network model suitable for beauty product recommendation by applying Neural Collaborative Filtering and Generalized Matrix Factorization (NCF + GMF) to beauty product recommendation. This study also provides an implementation of web API system to commercialize the proposed recommendation model. The overall performance of the NCF + GMF model was the best when the beauty product recommendation problem was defined as the estimation rating score problem and the binary classification problem. The NCF + GMF model showed also high performance in the top N recommendation.

• Advances in concrete construction
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• v.13 no.1
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• pp.1-10
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• 2022

Concrete is a brittle material and weak in tension. Traditionally, web reinforcement in the form of vertical stirrups is used in reinforced concrete (RC) beams to take care of principal stresses that may cause failure when they are subjected to shear stresses. In recent decades, the potential of various types of fibers for improving post-cracking behavior of RC beams and replacing stirrups completely or partially have been studied. It has been shown that the use of steel fibers randomly dispersed and oriented in concrete has a significant potential for enhancing mechanical properties of RC beams. However, the studies on deep steel fiber reinforced concrete (SFRC) beams are limited when compared to those focusing on slender beams. An experimental program consisting of three RC and nine SFRC deep beams without stirrups were conducted in this study. Besides, various models developed for predicting the ultimate shear strength and diagonal cracking strength of SFRC deep beams without stirrups were applied to experimental data obtained from the literature and this study.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.133-143
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• 2023

In this study, we propose a big data set of strawberry pests collected directly for diagnosis model learning and an automatic pest diagnosis model architecture based on deep learning. First, a big data set related to strawberry pests, which did not exist anywhere before, was directly collected from the web. A total of more than 12,000 image data was directly collected and classified, and this data was used to train a deep learning model. Second, the deep-learning-based automatic pest diagnosis module is a module that classifies what kind of pest or disease corresponds to when a user inputs a desired picture. In particular, we propose a model architecture that can optimally classify pests based on a convolutional neural network among deep learning models. Through this, farmers can easily identify diseases and pests without professional knowledge, and can respond quickly accordingly.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.203-225
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• 2004

This study is to investigate the characteristics of the Invisible Web and many search services designed to serve as gateways to the Invisible Web and to evaluate searching the Invisible Web in the Services. The four services for searching the Invisible Web were selected to search the Invisible Web with 11 queries, that are Google as portals, ProFusion and Search.com as Invisible Web meta search engines, and IncyWincy as Invisible Web search engines. It was found that the effectiveness of Google's Invisible Web searching was better compared with the three Invisible Web search tools but the difference between the four systems was not significant((${\alpha}$=.055) The Invisible Web meta searching was better than the Web meta searching in the three search tools at the statistically significant level. The effectiveness measurement based on the ranks and relevance degree(quality) of relevant documents retrieved seemed appropriate to the ranked search results.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.91-98
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• 2003

Visitors who browse the web from wireless PDAs, cell phones are frequently frustrated by interfaces. Simply replacing graphics with text and reformatting tables does not solve this problem, because deep link structures can still require more time. To solve this problem, in the paper we propose an algorithm, Minimal Path Algorithm that automatically improves wireless web navigation by suggesting useful shortcut links in real time. In the result of this paper, Minimal Path algorithm offer the shortcut and the number of shortest links to web users.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.05a
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• pp.121-124
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• 2002

This paper resents a virtual forming system to simulate deep drawing process for stress-strain information by utilizing virtual system designed using Virtual Reality Modeling Language (VRML) and computer aided analysis (CAE) tool. The CAE tool to calculate stress, strain, and deformation is designed using Finite Element Method. Stress distributions and deformation profiles as well as the operation of forming machine can be simulated and visualized in the web. The developed system consists of three modules, input module, virtual forming machine module, and output module. The input nodule was designed using HTML and ASP. The input data for FEM calculation is directed to the forming machine module for calculation. The results from the forming machine module can be visualized through output module as well as the forming process simulation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.245-251
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• 2023

Facial expression recognition plays a significant role in understanding human emotional states. With the advancement of AI and computer vision technologies, extensive research has been conducted in various fields, including improving customer service, medical diagnosis, and assessing learners' understanding in education. In this study, we develop a model that can infer emotions in real-time from a webcam using transfer learning with TensorFlow.js and MobileNet. While existing studies focus on achieving high accuracy using deep learning models, these models often require substantial resources due to their complex structure and computational demands. Consequently, there is a growing interest in developing lightweight deep learning models and transfer learning methods for restricted environments such as web browsers and edge devices. By employing MobileNet as the base model and performing transfer learning, our study develops a deep learning transfer model utilizing JavaScript-based TensorFlow.js, which can predict emotions in real-time using facial input from a webcam. This transfer model provides a foundation for implementing facial expression recognition in resource-constrained environments such as web and mobile applications, enabling its application in various industries.

• Journal of Biomedical Engineering Research
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• v.43 no.3
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• pp.131-135
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• 2022

Due to COVID-19, Correct method of wearing mask is important to prevent COVID-19 and the other respiratory tract infections. And the deep learning technology in the image processing has been developed. The purpose of this study is to create the type of mask wearing dataset for deep learning models and select the deep learning model to detect the wearing mask correctly. The Image dataset is the 2,296 images acquired using a web crawler. Deep learning classification models provided by tensorflow are used to validate the dataset. And Object detection deep learning model YOLOs are used to select the detection deep learning model to detect the wearing mask correctly. In this process, this paper proposes to validate the type of mask wearing datasets and YOLOv5 is the effective model to detect the type of mask wearing. The experimental results show that reliable dataset is acquired and the YOLOv5 model effectively recognize type of mask wearing.

• Structural Engineering and Mechanics
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• v.37 no.1
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• pp.39-59
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• 2011

Results of an experimental investigation on the behavior and ultimate shear capacity of 27 reinforced concrete Transfer (deep) beams are summarized. The main variables were percent longitudinal(tension) steel (0.28 to 0.60%), percent horizontal web steel (0.60 to 2.40%), percent vertical steel (0.50to 2.25%), percent orthogonal web steel, shear span-to-depth ratio (1.10 to 3.20) and cube concrete compressive strength (32 MPa to 48 MPa).The span of the beam has been kept constant at 1000 mm with100 mm overhang on either side of the supports. The result of this study shows that the load transfer capacity of transfer (deep) beam with distributed longitudinal reinforcement is increased significantly. Also, the vertical shear reinforcement is more effective than the horizontal reinforcement in increasing the shear capacity as well as to transform the brittle mode of failure in to the ductile mode of failure. It has been observed that the orthogonal web reinforcement is highly influencing parameter to generate the shear capacity of transfer beams as well as its failure modes. Moreover, the results from the experiments have been processed suitably and presented an analytical model for design of transfer beams in high-rise buildings for estimating the shear capacity of beams.

• Archives of design research
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• v.16 no.1
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• pp.297-304
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• 2003

The purpose of this study is to explore and understand correlation between an appearance of the web-graphics and rhetorical analysis. This paper was adopted semiotic approaches and four rhetorical tropes as follows metaphor, metonymy, synecdoche, irony. The web-graphics are parts of the web-contents that are increased continuously in the web-space these days. To investigate cgaracteristic of individual web-graphic this study selected semiotic framework and analysis meaning of the rhetorical tropes. The results of this study can be founded as follows: · Rhetorical graphics we produced linguistic features between human and signs for the fundamental characteristic of the signification. · Rhetorical graphics offer to the users the due of the decoding precesses through the narrative structures to symbolic schema. besides, these are operated limited framework of condensation and displacement. · The web-graphics participate human's recognition processes and rhetorical codes in order to investigate the sign-vehicle of the deep-structures.