Cloud Computing Security

Biao Jiang(장표),Eul Gyu Im(임을규) 한국통신학회 2011 한국통신학회 학술대회논문집 Vol.2011 No.6

A Study of Facial Organs Classification System Based on Fusion of CNN Features and Haar-CNN Features

Biao Hao,Hye-Youn Lim,Dae-Seong Kang 한국정보기술학회 2018 한국정보기술학회논문지 Vol.16 No.11

In this paper, we proposed a method for effective classification of eye, nose, and mouth of human face. Most recent image classification uses Convolutional Neural Network(CNN). However, the features extracted by CNN are not sufficient and the classification effect is not too high. We proposed a new algorithm to improve the classification effect. The proposed method can be roughly divided into three parts. First, the Haar feature extraction algorithm is used to construct the eye, nose, and mouth dataset of face. The second, the model extracts CNN features of image using AlexNet. Finally, Haar-CNN features are extracted by performing convolution after Haar feature extraction. After that, CNN features and Haar-CNN features are fused and classify images using softmax. Recognition rate using mixed features could be increased about 4% than CNN feature. Experiments have demonstrated the performance of the proposed algorithm.

A Study of Facial Organs Classification Based on Fusion of CNN Features and Haar Fearture

Biao Hao(학표),Hye-Youn Lim(임혜연),Dae-Seong Kang(강대성) 한국정보기술학회 2018 Proceedings of KIIT Conference Vol.2018 No.6

현재 영상처리의 주류는 인공 지능 시스템이다. 그 중에서도 Deep learning은 인공 지능의 가능성을 크게 향상 시켰다. 본 논문에서는 얼굴의 세부 분류를 구현 하는 방법을 제안한다. 본 논문에서 사용된 방법은 크게 세 부분으로 나눌 수 있다. 첫 번째 부분은 전처리이다. 이 과정에서 Haar 특징을 사용하여 눈, 코, 입을 분리하여 각각의 Dataset을 추출한다. 두 번째 부분은 Convolution network 부분으로 Alexnet convolution 신경망을 사용하여 Convolution 연산을 수행하여 특징을 추출한다. 마지막은 Haar 특징과 CNN 특징을 융합한 특징을 이용하여 Softmax 함수를 이용해 분류 한다. 실험을 통해 제안하는 방법의 성능을 증명 하였다. Currently, the mainstream of image processing is artificial intelligence system. Among them, Deep learning greatly improved the possibility of artificial intelligence. In this paper, we propose a method to implement detailed classification of faces. The method used in this paper can be roughly divided into three parts. The first part is preprocessing. In this process, each dataset is extracted by separating eyes, nose, and mouth using the Haar feature. In the second part, the convergence network is used to perform convolution operation using the Alexnet convolution neural network. Finally, we classify it using Softmax function using the feature that combines Haar feature and CNN feature. Experiments have demonstrated the performance of the proposed method.

Seismic response of steel reinforced concrete frame-bent plant of CAP1400 nuclear power plant considering the high-mode vibration

Biao Liu,Zhengzhong Wang,Bo Zhang,Ningjun Du,Mingxia Gao,Guoliang Bai 국제구조공학회 2023 Steel and Composite Structures, An International J Vol.46 No.2

In order to study the seismic response of the main plant of steel reinforced concrete (SRC) structure of the CAP1400 nuclear power plant under the influence of different high-mode vibration, the 1/7 model structure was manufactured and its dynamic characteristics was tested. Secondly, the finite element model of SRC frame-bent structure was established, the seismic response was analyzed by mode-superposition response spectrum method. Taking the combination result of the 500 vibration modes as the standard, the error of the base reactions, inter-story drift, bending moment and shear of different modes were calculated. Then, based on the results, the influence of high-mode vibration on the seismic response of the SRC frame-bent structure of the main plant was analyzed. The results show that when the 34 vibration modes were intercepted, the mass participation coefficient of the vertical and horizontal vibration mode was above 90%, which can meet the requirements of design code. There is a large error between the seismic response calculated by the 34 and 500 vibration modes, and the error decreases as the number of modes increases. When 60 modes were selected, the error can be reduced to about 1%. The error of the maximum bottom moment of the bottom column appeared in the position of the bent column. Finally, according to the characteristics of the seismic influence coefficient αj of each mode, the mode contribution coefficient γj•Xji was defined to reflect the contribution of each mode to the seismic action.

Effects of shear keys on seismic performance of an isolation system

Biao Wei,Chaobin Li,Xiaolong Jia,Xuhui He,Menggang Yang 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.24 No.3

The shear keys are set in a seismic isolation system to resist the long-term service loadings, and are cut off to isolate the earthquakes. This paper investigated the influence of shear keys on the seismic performance of a vertical spring-viscous damper-concave Coulomb friction isolation system by an incremental dynamic analysis (IDA) and a performance-based assessment. Results show that the cutting off process of shear keys should be simulated in a numerical analysis to accurately predict the seismic responses of isolation system. Ignoring the cutting off process of shear keys usually leads to untrue seismic responses in a numerical analysis, and many of them are unsafe for the design of isolated structure. And those errors will be increased by increasing the cutting off force of shear keys and decreasing the spring constant of shear keys, especially under a feeble earthquake. The viscous damping action postpones the cutting off time of shear keys during earthquakes, and reduces the seismic isolation efficiency. However, this point can be improved by increasing the spring constant of shear keys.

Delivering IPTV Service over a Virtual Network: A Study on Virtual Network Topology

Biao Song,Mohammad Mehedi Hassan,허의남 한국통신학회 2012 Journal of communications and networks Vol.14 No.3

In this study, we design an applicable model enabling internet protocol television (IPTV) service providers to use a virtual network (VN) for IPTV service delivery. The model addresses the guaranteed service delivery, cost effectiveness, flexible control,and scalable network infrastructure limitations of backbone or IP overlay-based content networks. There are two major challenges involved in this research: i) The design of an efficient, cost effective,and reliable virtual network topology (VNT) for IPTV service delivery and the handling of a VN allocation failure by infrastructure providers (InPs) and ii) the proper approach to reduce the cost of VNT recontruction and reallocation caused by VNT allocation failure. Therefore, in this study, we design a more reliable virtual network topology for solving a single virtual node, virtual link, or video server failure. We develop a novel optimization objective and an efficient VN construction algorithm for building the proposed topology. In addition, we address the VN allocation failure problem by proposing VNT decomposition and reconstruction algorithms. Various simulations are conducted to verify the effectiveness of the proposed VNT, as well as that of the associated construction,decomposition, and reconstruction algorithms in terms of reliability and efficiency. The simulation results are compared with the findings of existing works, and an improvement in performance is observed.

Object-Based Change Detection of Very High Resolution Satellite Imagery Using the Cross-Sharpening of Multitemporal Data

Biao Wang,Seokkeun Choi,Younggi Byun,Soungki Lee,Jaewan Choi IEEE 2015 IEEE geoscience and remote sensing letters Vol.12 No.5

<P>In this letter, we present a method for unsupervised change detection based on the cross-sharpening of multitemporal images and image segmentation. Our method effectively reduces the change detection errors caused by relief or spatial displacement between multitemporal images with different acquisition angles. A total of four cross-sharpened images, including two general pansharpened images, were generated. Then, two pairs of cross-sharpened images were analyzed using change detection indexes. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation.</P>

TiO2 Branched Nanostructure Anode Material Prepared by Seeding Method for High-performance Lithium Ion Batteries

Biao Han,김시진,황보미,황의택,박한철,고문현,박경원 한국전기화학회 2013 한국전기화학회지 Vol.16 No.2

We demonstrate rutile TiO2 branched nanostructure (TiO2-BN) electrodes synthesized by seeding method for enhanced lithium intercalation properties. The morphology and crystal-line nature of the TiO2-BN were clearly observed by field-emission transmission electron microscopy and fast Fourier transform pattern. The TiO2-BN electrodes showed excellent capac-ity and high rate performance. The improved lithium-ion intercalation properties of the TiO2-BN may be attributed to relatively large specific surface area and short transport distance of the branched nanostructure.

Numerical investigation of heat transfer characteristics for Subsea Xmas tree assembly

Biao Hu,Hongwu Zhu,Kuang Ding,Fangling Xu,Youjiang Zhang 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.11

This study focuses on the heat transfer characteristic of a horizontal subsea Xmas tree assembly at a high spatial resolution. Computationalfluid dynamics (steady Reynolds-averaged Navier-Stokes) in combination with Low Reynolds number modelling (LRNM) isadopted for heat transfer analysis, which has been validated against a full scale underwater gate valve heat transfer experiment with goodagreements. The characteristics of cold sea water flowing through the subsea tree, and of convection heat transfer between the subsea treeand ambient cold water are obtained. The typical “hot spots,” which have high Convection heat transfer coefficient (CHTC) and creategreat large amounts of heat loss, are numerically determined. Under the designed water depth, the effects of installation orientation, seawater velocity, and inner oil temperature on convection heat transfer are investigated as well. Such work is significant for thermal designof the subsea tree to increase structural reliability and flow assurance level.

A Survey of Anomaly-based Botnet Detection

Biao Jiang,Eul Gyu Im 한국통신학회 2011 한국통신학회 학술대회논문집 Vol.2011 No.2

Botnets are increasingly popular threats which endanger everyday life of both individuals and organizations. Information security experts have taken measures to cope. This survey specially focuses on the most important area of the defense against botnets -anomaly-based botnet detection. The survey first introduces basics of botnets and botnet defense, then provides an overview of anomaly-based botnet detection, and finally summarizes findings and predicts future trends of botnet detection.