• Structural Engineering and Mechanics
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• v.51 no.4
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• pp.581-599
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• 2014

In this paper the overall dynamic response of simple railway bridges subjected to high-speed trains is investigated numerically based on the mechanical models of simply supported single-span and continuous two-span Bernoulli-Euler beams. Each axle of the train, which is composed of rail cars and passenger cars, is considered as moving concentrated load. Distance, magnitude, and maximum speed of the moving loads are adjusted to real high-speed trains and to load models according to Eurocode 1. Non-dimensional characteristic parameters of the train-bridge interaction system are identified. These parameters permit a spectral representation of the dynamic peak response. Response spectra assist the practicing engineers in evaluating the expected dynamic peak response in the design process of railway bridges without performing time-consuming time history analyses.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.324-330
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• 2021

Agriculture is one of the essential needs of human life on planet Earth. It is the source of food and earnings for many individuals around the world. The economy of many countries is associated with the agriculture sector. Lots of diseases exist that attack various fruits and crops. Apple Tree Leaves also suffer different types of pathological conditions that affect their production. These pathological conditions include apple scab, cedar apple rust, or multiple diseases, etc. In this paper, an automatic detection framework based on deep learning is investigated for apple leaves disease classification. Different pre-trained models, VGG16, ResNetV2, InceptionV3, and MobileNetV2, are considered for transfer learning. A combination of parameters like learning rate, batch size, and optimizer is analyzed, and the best combination of ResNetV2 with Adam optimizer provided the best classification accuracy of 94%.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.159-168
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• 2019

Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have the same features with fire, which may result in high false alarms rate. This paper presents a new video-based, image processing forest fires detection method, which consists of four stages. First, a background-subtraction algorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIE $L{\ast}a{\ast}b{\ast}$ color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-like objects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is used to classify the region of interest to either real fire or non-fire. The final experimental results verify that the proposed method effectively identifies the forest fires.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.223-229
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• 2021

Classification of different blood cell types is an essential task for human's medical treatment. The white blood cells have different types of cells. Counting total White Blood Cells (WBC) and differential of the WBC types are required by the physicians to diagnose the disease correctly. This paper used transfer learning methods to the pre-trained deep learning models to classify different WBCs. The best pre-trained model was Inception ResNetV2 with Adam optimizer that produced classification accuracy of 98.4% for the dataset comprising four types of WBCs.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.100-106
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• 2021

Over the past few decades, natural language processing research has not made much. However, the widespread use of deep learning and neural networks attracted attention for the application of neural networks in natural language processing. Sentiment analysis is one of the challenges of natural language processing. Emotions are things that a person thinks and feels. Therefore, sentiment analysis should be able to analyze the person's attitude, opinions, and inclinations in text or actual text. In the case of emotion analysis, it is a priority to simply classify two emotions: positive and negative. In this paper we propose the deep learning based sentimental analysis system according to various optimizer that is SGD, ADAM and RMSProp. Through experimental result RMSprop optimizer shows the best performance compared to others on IMDB data set. Future work is to find more best hyper parameter for sentimental analysis system.

• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.2
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• pp.167-171
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• 2021

We describe the successful insertion of a nasotracheal tube following repeated cuff rupture. The patient was a 55-year-old woman with a history of nasal trauma and multiple rhinoplasties, who underwent elective Lefort I osteotomy and bilateral sagittal split osteotomy for correction of skeletal facial deformity. During fiberoptic bronchoscope-guided nasal intubation after the induction of general anesthesia, the tracheal tube repeatedly ruptured in both nares, despite extensive preparation of the nasal airways. We covered the cuff with a one-inch tape, intubated to the level of the oropharynx, pulled the tracheal tube out through the mouth, and removed the tape. The tracheal tube was then backed out to the level of the uvula, and was successfully advanced.

• Communications of the Korean Mathematical Society
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• v.37 no.1
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• pp.45-56
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• 2022

In this paper, we introduce and study the class of rings in which every ideal consisting entirely of zero divisors is a d-ideal, considered as a generalization of strongly duo rings. Some results including the characterization of AA-rings are given in the first section. Further, we examine the stability of these rings in localization and study the possible transfer to direct product and trivial ring extension. In addition, we define the class of d_E-ideals which allows us to characterize von Neumann regular rings.

• Communications of the Korean Mathematical Society
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• v.38 no.1
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• pp.121-122
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• 2023

In this erratum, we correct a mistake in the proof of Proposition 2.7. In fact the equivalence (3) ⇐ (4) "R is a quasi-regular ring if and only if R is a reduced ring and every principal ideal contained in Z(R) is a 0-ideal" does not hold as we only have Rx ⊆ O(S).

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1576-1578
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• 2011

우리나라는 지리적 위치로 인해 매년 황사의 직접적인 피해를 보고 있다. 이에 황사에 대한 예보 정보를 효과적으로 전달하여 피해를 최소화하는 예방이 중요하다. 본 논문은 기상청 ADAM으로 생성된 황사 예측 결과 자료를 Google Earth 상에서 3차원 애니메이션으로 실감 있게 표현할 수 있는 기법을 연구하고, 이를 프로그램으로 구현하여 그 결과를 검증한다.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.