Performance analysis for coexistence of LTE-LAA and Wi-Fi systems in the spatial, time, spectrum domain

Chuyen Khoa Huynh,윤덕원,최주평,이원철 한국통신학회 2019 ICT Express Vol.5 No.1

The focus of this paper is the development of a solution regarding the coexistence of the LTE-LAA and Wi-Fi networks in the 5 GHz bandwidth by using an interference analysis and traffic optimization for which channel selection schemes are used. By implementing an analysis tool based on the Monte Carlo method, named “3DMCAT”, a simulation is applied with the LBT protocol in both the time and frequency domains on the frame based equipment of the spatial, time, spectrum domain; this tool is implemented by combining a Microsoft Excel calculation and the corresponding VBA. 3DMCAT shows the results of transmission performance analysis for the coexistence schemes of the Wi-Fi and LTE-LAA systems in the 5 GHz frequency bands.

A Feasibility Study on Application of a Deep Convolutional Neural Network for Automatic Rock Type Classification

Chuyen Pham(추엔 팜),Hyu-Soung Shin(신휴성) 한국암반공학회 2020 터널과지하공간 Vol.30 No.5

암종 분류은 현장의 지질학적 또는 지반공학적 특성 파악을 위해 요구되는 매우 기본적인 행위이나 암석의 성인, 지역, 지질학적 이력 특성에 따라 동일 암종이라 하여도 매우 다양한 형태와 색 조성을 보이므로 깊은 지질학적 학식과 경험 없이는 쉬운 일은 아니다. 또한, 다른 여러 분야의 분류 작업에서 딥러닝 영상처리 기법들이 성공적으로 적용되고 있으며, 지질학적 분류나 평가 분야에서도 딥러닝 기법의 적용에 대한 관심이 증대되고 있다. 따라서, 본 연구에서는 동일 암종임에도 다양한 형태와 색을 갖게 되는 실제 상황을 감안하여, 정확한 자동 암종 분류를 위한 딥러닝 기법의 적용 가능성에 대해 검토하였다. 이러한 기법은 향후에 현장 암종분류 작업을 수행하는 현장 기술자들을 지원할 수 있는 효과적인 툴로 활용 가능할 것이다. 본 연구에서 사용된 딥러닝 알고리즘은 매우 깊은 네트워크 구조로 객체 인식과 분류를 할 수 있는 것으로 잘 알려진 ’ResNet’ 계열의 딥러닝 알고리즘을 사용하였다. 적용된 딥러닝에서는 10개의 암종에 대한 다양한 암석 이미지들을 학습시켰으며, 학습 시키지 않은 암석 이미지들에 대하여 84% 수준 이상의 암종 분류 정확도를 보였다. 본 결과로 부터 다양한 성인과 지질학적 이력을 갖는 다양한 형태와 색의 암석들도 지질 전문가 수준으로 분류해 낼 수 있는 것으로 파악되었다. 나아가 다양한 지역과 현장에서 수집된 암석의 이미지와 지질학자들의 분류 결과가 학습데이터로 지속적으로 누적이 되어 재학습에 반영된다면 암종분류 성능은 자동으로 향상될 것이다. Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

An Interference Avoidance Method Using Two Dimensional Genetic Algorithm for Multicarrier Communication Systems

Chuyen Khoa Huynh,이원철 한국통신학회 2013 Journal of communications and networks Vol.15 No.5

In this article, we suggest a two-dimensional geneticalgorithm (GA) method that applies a cognitive radio (CR) decisionengine which determines the optimal transmission parametersfor multicarrier communication systems. Because a CR is capableof sensing the previous environmental communication information,CR decision engine plays the role of optimizing the individualtransmission parameters. In order to obtain the allowable transmissionpower of multicarrier based CR system demands interferenceanalysis a priori, for the sake of efficient optimization, a twodimensionalGAstructure is proposed in this paper which enhancesthe computational complexity. Combined with the fitness objectiveevaluation standard, we focus on two multi-objective optimizationmethods: The conventional GA applied with the multi-objectivefitness approach and the non-dominated sorting GA with Paretooptimalsorting fronts. After comparing the convergence performanceof these algorithms, the transmission power of each subcarrieris proposed as non-interference emission with its optimalvalues in multicarrier based CR system.

3D Tunnel Face Modelling for Discontinuities Characterization: A Comparison of Lidar and Photogrammetry Approaches

Chuyen Pham,Hyu-Soung Shin 대한토목학회 2022 대한토목학회 학술대회 Vol.2022 No.10

3D Tunnel Face Modelling for Discontinuities Characterization: A Comparison of Lidar and Photogrammetry Approaches

Chuyen Pham,Hyu-Soung Shin 대한토목학회 2022 대한토목학회 학술대회 Vol.2022 No.10

Mobility Prediction Algorithms Using User Traces in Wireless Networks

Chuyen Luong,Son Do,Hyukro Park,Deokjai Choi 한국멀티미디어학회 2014 멀티미디어학회논문지 Vol.17 No.8

Automatic Fracture Detection in CT Scan Images of Rocks Using Modified Faster R-CNN Deep-Learning Algorithm with Rotated Bounding Box

Chuyen Pham(추엔 팜),Li Zhang(장리),Sun Yeom(염선),Hyu-Soung Shin(신휴성) 한국암반공학회 2021 터널과지하공간 Vol.31 No.5

본 논문에서는 암석시료의 CT 촬영 이미지상의 균열을 자동으로 탐지하는 새로운 인공지능 딥러닝 기법을 제안한다. 본 제안 기법은 2단계 딥러닝 객체인식 알고르즘인 Faster R-CNN을 기반으로 회전 가능한 경계박스(bounding box) 개념을 도입하여 알고리즘을 개조하였다. 회전 경계박스의 도입은 관심 균열 영역 밖의 배경의 불균질성 및 균열의 크기와 형태에 영향을 받는 딥러닝 객체인식기법 상의 고유한 어려움을 극복하기 위한 핵심 역할을 한다. 본 회전형 경계박스의 사용은 일반적으로 사용되는 영상 수평 축과 평행한 경계박스 사용의 경우와 비교하여 긴 형태의 균열 형상 특성에 매우 잘 부합된다. 즉, 좋지 않은 영향을 끼치는 경계박스 내 균열 이외 배경영역의 비율을 최소화 시킬 수 있다. 이외에도, 회전 경계 박스의 추가적인 이점은 인식된 균열의 방향에 따라 회전하여 추론되는 경계박스를 통해 균열의 방향과 길이에 대한 정보를 직접적으로 얻을 수 있다. 본 제안기법의 적용성을 검증하기 위하여, 이미지상에서 매우 불균질한 화강암 시료에 인공적으로 균열을 발생시킨 다수의 암석시료 영상을 딥러닝 학습에 사용하고 추론 성능 실험을 진행하였다. 그 외에도, 동일 조건에서 사암과 셰일 암석 시료에도 적용하여 검증하였다. 결론적으로, 제안된 기법을 통해 균열 객체 인식의 평균 추론정확도(mAP)값이 0.89 정도 수준의 우수한 추론 성능을 보였으며, 기존 기법에 비해 추론된 경계박스 내 균열과 배경 영역의 비율 측면에 서 배경의 비율이 획기적으로 최소화되는 유리한 추론 검증 결과를 보였다. In this study, we propose a new approach for automatic fracture detection in CT scan images of rock specimens. This approach is built on top of two-stage object detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The use of rotated bounding box plays a key role in the future work to overcome several inherent difficulties of fracture segmentation relating to the heterogeneity of uninterested background (i.e., minerals) and the variation in size and shape of fracture. Comparing to the commonly used bounding box (i.e., axis-align bounding box), rotated bounding box shows a greater adaptability to fit with the elongated shape of fracture, such that minimizing the ratio of background within the bounding box. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. To validate the applicability of the proposed approach, we train and test our approach with a number of CT image sets of fractured granite specimens with highly heterogeneous background and other rocks such as sandstone and shale. The result demonstrates that our approach can lead to the encouraging results on fracture detection with the mean average precision (mAP) up to 0.89 and also outperform the conventional approach in terms of background-to-object ratio within the bounding box.

Study on Power Allocation and Channel Assignment Schemes for TVWS Smart Metering System

Chuyen Khoa Huynh(코아추옌),Kyu Min Park(박규민),Won Cheol Lee(이원철) 한국통신학회 2014 한국통신학회 학술대회논문집 Vol.2014 No.6

An Efficient Channel Selection and Power Allocation Scheme for TVWS based on Interference Analysis in Smart Metering Infrastructure

Chuyen Khoa Huynh,이원철 한국통신학회 2016 Journal of communications and networks Vol.18 No.1

Nowadays, smart meter (SM) technology is widely effectivelyused. In addition, power allocation (PA) and channel selection(CS) are considered problems with many proposed approaches. In this paper, we will suggest a specific scenario for anSM configuration system and show how to solve the optimizationproblem for transmission between SMs and the data concentratorunit (DCU), the center that collects the data from several SMs,via simulation. An efficient CS with PA scheme is proposed in theTV white space system, which uses the TV band spectrum. On thebasic of the optimal configuration requirements, SMs can have atransmission schedule and channel selection to obtain the optimalefficiency of using spectrum resources when transmitting data tothe DCU. The optimal goals discussed in this paper are the maximumcapacity or maximum channel efficiency and the maximumallowable power of the SMs used to satisfy the quality of servicewithout harm to another wireless system. In addition, minimizationof the interference to the digital television system and otherSMs is also important and needs to be considered when the solvingcoexistence scenario. Further, we propose a process that performsan interference analysis scheme by using the spectrum engineeringadvanced Monte Carlo analysis tool (SEAMCAT), whichis an integrated software tool based on a Monte-Carlo simulationmethod. Briefly, the process is as follows: The optimization processimplemented by genetic evolution optimization engines, i.e., agenetic algorithm, will calculate the best configuration for the SMsystem on the basis of the interference limitation for each SM bySEAMCAT in a specific configuration, which reaches the solutionwith the best defined optimal goal satisfaction.

Comparison between two different types of geophysical log from Logging While Drilling and Wireline Logging

( Chuyen Ngoc Pham ),( Chandong Chang ) 대한지질공학회 2016 대한지질공학회 학술발표회논문집 Vol.2016 No.2