• Journal of Information Technology Applications and Management
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• 제26권6호
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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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• 제13권1호
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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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• 제15권2호
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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.

• 정보관리학회지
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• 제21권3호
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• pp.203-225
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• 2004

본 연구는 표준 웹 탐색엔진에 색인되지 않는 Invisible Web에 대한 특성과 Invisible Web 탐색도구들을 파악하고, 이들 도구에서 Invisible Web 탐색의 성능을 비교 평가하기 위해 수행되었다. 표준 웹 탐색엔진이 Google과 Invisible Web 탐색엔진인 Incy Wincy, Invisible Web 메타탐색엔진인 Profusion과 Search. com 에서 11개의 탐색질문이 탐색되었다. Profusion과 Search. com, Incy Wincy에서의 Invisible Web(메타) 탐색 기능은 이 세 엔진에서 제공하는 웹 메타탐색기능과도 비교되었다. 탐색결과 Google이 Invisible Web 탐색에서 Invisible Web 탐색엔진보다 .15 -.35 높은 적합성순위정확률을 보였지만 통계적으로 유의한 차이는 아니었다. (${\alpha}$=.055). Invisible Web 탐색엔진에서 웹 메타탐색은 Invisible Web(메타)탐색보다 통계적으로 유의한 수준에서 더 우수한 것으로 나타났다. 성능평가에 사용된 적합성순위정확률은 검색된 문헌의 질 (적합성)과 적합문헌의 순위를 반영하는 정확률 척도로 사용될 수 있음을 보여주었다.

• 한국산업정보학회논문지
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• 제8권3호
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• pp.91-98
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• 2003

무선 PDA.휴대폰을 통해 웹을 탐색하려는 이용자들은 인터페이스 상의 문제 때문에 어려움을 겪는다. 단지 그래픽을 문자로 바꾸거나 기호체계를 재구성한다고 해서 해결될 문제가 아니다. 심층 연계 구조를 통과하는 데에는 많은 시간이 걸리기 때문이다. 이러한 문제들을 해결하기 위해서 본 논문에서는 실시간의 최단경로를 제공하기 위하여 무선 웹 탐색을 자동적으로 개선시키는 Minimal Path 알고리즘을 제안한다. 본 논문의 결과 Minimal Path 알고리즘은 웹 이용자들에 대해 지름길을 제공해 주며, 링크의 숫자가 가장 짧았음을 알 수 있었다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2002년도 춘계학술대회 논문집
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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.

• 디지털산업정보학회논문지
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• 제19권3호
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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.

• 대한의용생체공학회:의공학회지
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• 제43권3호
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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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• 제37권1호
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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.

• 디자인학연구
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• 제16권1호
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• pp.297-304
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• 2003

본 연구의 목적은 수사구조를 이용하여 웹 그래픽에 나타난 특성과 상호 관련성을 밝히고 이를 통해 언어구조에 제한하던 수사학의 활용 범위를 넓히는데 있다. 연구를 위해 네 가지 수사구조(은유, 환유, 제유, 아이러니)를 설정하여 흠 페이지의 웹 그래픽의 재료들을 중심으로 진행하였다. 개별적 그래픽의 특성을 파악하기 위해 기호학적 관점과 접근방법을 통해 분석, 해독하였으며 다음과 같은 결론을 모색 할 수 있었다. · 웹 그래픽은 기호의 본질적 특성인 차이로 인한 기호화 작용에 관여한다. · 웹 그래픽은 서술구조에서 출발하여 상징화구조로 이어지며 이때 응축과 전이작용을 중심으로 해독의 실마리를 제공한다. · 웹 그래픽은 수사학적 코드를 활용하여 기저의미의 해석소를 제공하며 수용자의 인식과정에 작용한다.