• Title/Summary/Keyword: Image Layer

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Rithy Panh's Practices on Archive Images and Methods of Historiography in La France est notre patrie (리티 판의 다큐멘터리 <우리의 모국 프랑스>에 나타난 아카이브 활용 양상과 역사서술 방식)

  • Yoo, Jisu Klaire
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.8
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    • pp.209-221
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    • 2019
  • A found-footage film La France est notre patrie is a documentary, in which archive images are juxtaposed with intertitles, non-diegetic music and foley, by borrowing an audiovisual strategy of silent films. The filmmaker Rithy Panh has excavated the images, which had been taken during the same period as the film history of the end of the 19th and early 20th centuries in Southeast Asia and Africa under French colonial rule. This paper examines the filmmaker's methods of historiography when utilizing archive images in order to represent the past by referring to Walter Benjamin's concept of historical montage and dialectical image. As the analysis illustrates the singularity of constructive methods, which include multi-layer viewpoints and montage styles of compilation and collage, it reveals how La France est notre patrie elicits the essay film modes through its self-reflexivity, leads audience to the threshold of critical thinking about time and history and creates a discourse of counter-memory.

Study of Machine Learning based on EEG for the Control of Drone Flight (뇌파기반 드론제어를 위한 기계학습에 관한 연구)

  • Hong, Yejin;Cho, Seongmin;Cha, Dowan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.249-251
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    • 2022
  • In this paper, we present machine learning to control drone flight using EEG signals. We defined takeoff, forward, backward, left movement and right movement as control targets and measured EEG signals from the frontal lobe for controlling using Fp1. Fp2 Fp2 two-channel dry electrode (NeuroNicle FX2) measuring at 250Hz sampling rate. And the collected data were filtered at 6~20Hz cutoff frequency. We measured the motion image of the action associated with each control target open for 5.19 seconds. Using Matlab's classification learner for the measured EEG signal, the triple layer neural network, logistic regression kernel, nonlinear polynomial Support Vector Machine(SVM) learning was performed, logistic regression kernel was confirmed as the highest accuracy for takeoff and forward, backward, left movement and right movement of the drone in learning by class True Positive Rate(TPR).

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Ag Sintering Die Attach Technology for Wide-bandgap Power Semiconductor Packaging (Wide-bandgap 전력반도체 패키징을 위한 Ag 소결 다이접합 기술)

  • Min-Su Kim;Dongjin Kim
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.1
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    • pp.1-16
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    • 2023
  • Recently, the shift to next-generation wide-bandgap (WBG) power semiconductor for electric vehicle is accelerated due to the need to improve power conversion efficiency and to overcome the limitation of conventional Si power semiconductor. With the adoption of WBG semiconductor, it is also required that the packaging materials for power modules have high temperature durability. As an alternative to conventional high-temperature Pb-based solder, Ag sintering die attach, which is one of the power module packaging process, is receiving attention. In this study, we will introduce the recent research trends on the Ag sintering die attach process. The effects of sintering parameters on the bonding properties and methodology on the exact physical properties of Ag sintered layer by the realization 3D image are discussed. In addition, trends in thermal shock and power cycle reliability test results for power module are discussed.

An Embedded Text Index System for Mass Flash Memory (대용량 플래시 메모리를 위한 임베디드 텍스트 인덱스 시스템)

  • Yun, Sang-Hun;Cho, Haeng-Rae
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.6
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    • pp.1-10
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    • 2009
  • Flash memory has the advantages of nonvolatile, low power consumption, light weight, and high endurance. This enables the flash memory to be utilized as a storage of mobile computing device such as PMP(Portable Multimedia Player). Potable device with a mass flash memory can store various multimedia data such as video, audio, or image. Typical index systems for mobile computer are inefficient to search a form of text like lyric or title. In this paper, we propose a new text index system, named EMTEX(Embedded Text Index). EMTEX has the following salient features. First, it uses a compression algorithm for embedded system. Second, if a new insert or delete operation is executed on the base table. EMTEX updates the text index immediately. Third, EMTEX considers the characteristics of flash memory to design insert, delete, and rebuild operations on the text index. Finally, EMTEX is executed as an upper layer of DBMS. Therefore, it is independent of the underlying DBMS. We evaluate the performance of EMTEX. The Experiment results show that EMTEX can outperform th conventional index systems such as Oracle Text and FT3.

Photo-Transistors Based on Bulk-Heterojunction Organic Semiconductors for Underwater Visible-Light Communications (가시광 수중 무선통신을 위한 이종접합 유기물 반도체 기반 고감도 포토트랜지스터 연구)

  • Jeong-Min Lee;Sung Yong Seo;Young Soo Lim;Kang-Jun Baeg
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.36 no.2
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    • pp.143-150
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    • 2023
  • Underwater wireless communication is a challenging issue for realizing the smart aqua-farm and various marine activities for exploring the ocean and environmental monitoring. In comparison to acoustic and radio frequency technologies, the visible light communication is the most promising method to transmit data with a higher speed in complex underwater environments. To send data at a speedier rate, high-performance photodetectors are essentially required to receive blue and/or cyan-blue light that are transmitted from the light sources in a light-fidelity (Li-Fi) system. Here, we fabricated high-performance organic phototransistors (OPTs) based on P-type donor polymer (PTO2) and N-type acceptor small molecule (IT-4F) blend semiconductors. Bulk-heterojunction (BHJ) PTO2:IT-4F photo-active layer has a broad absorption spectrum in the range of 450~550 nm wavelength. Solution-processed OPTs showed a high photo-responsivity >1,000 mA/W, a large photo-sensitivity >103, a fast response time, and reproducible light-On/Off switching characteristics even under a weak incident light. BHJ organic semiconductors absorbed photons and generated excitons, and efficiently dissociated to electron and hole carriers at the donor-acceptor interface. Printed and flexible OPTs can be widely used as Li-Fi receivers and image sensors for underwater communication and underwater internet of things (UIoTs).

Hierarchical Flow-Based Anomaly Detection Model for Motor Gearbox Defect Detection

  • Younghwa Lee;Il-Sik Chang;Suseong Oh;Youngjin Nam;Youngteuk Chae;Geonyoung Choi;Gooman Park
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1516-1529
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    • 2023
  • In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

Classification of Fiber Tracts Changed by Nerve Injury and Electrical Brain Stimulation Using Machine Learning Algorithm in the Rat Brain (신경 손상과 전기 뇌 자극에 의한 흰쥐의 뇌 섬유 경로 변화에 대한 기계학습 판별)

  • Sohn, Jin-Hun;Eum, Young-Ji;Cheong, Chaejoon;Cha, Myeounghoon;Lee, Bae Hwan
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.701-702
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    • 2021
  • The purpose of the study was to identify fiber changes induced by electrical stimulation of a certain neural substrate in the rat brain. In the stimulation group, the peripheral nerve was injured and the brain area associated to inhibit sensory information was electrically stimulated. There were sham and sham stimulation groups as controls. Then high-field diffusion tensor imaging (DTI) was acquired. 35 features were taken from the DTI measures from 7 different brain pathways. To compare the efficacy of the classification for 3 animal groups, the linear regression analysis (LDA) and the machine learning technique (MLP) were applied. It was found that the testing accuracy by MLP was about 77%, but that of accuracy by LDA was much higher than MLP. In conclusion, machine learning algorithm could be used to identify and predict the changes of the brain white matter in some situations. The limits of this study will be discussed.

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Effect of turbulent motions within the boundary layer on the sediment transport based on the three-dimensional particle image velocimetry (3차원 입자 영상 유속계를 기반으로 한 경계층 내 난류 흐름이 유사에 미치는 영향에 대한 연구)

  • Park, Hyungchul;Hwang, Jin Hwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.24-24
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    • 2021
  • 자연하천 바닥 경계층 내에서는 복잡한 난류 구조가 형성되며 이들은 하상에 강한 모멘텀을 전달한다. 바닥 부근에 분포하는 유사 입자들은 경계층 내에서 발생한 난류 흐름으로부터 모멘텀을 전달받아 소류사 혹은 부유사 형태로 이송되게 되며, 이러한 유사 이송 과정을 역학적으로 설명하기 위해서는 경계층 내 유체 흐름에 대한 이해가 선행되어야한다. 경계층 내 난류 흐름 특성이 유사 입자의 움직임에 미치는 영향에 대해 분석하기 위해서는 바닥 경계층 내 고해상도 유속 자료와 유사 움직임을 동시에 포착할 수 있는 기술이 요구된다. 하지만 현재까지 수행된 대부분의 선행 연구들은 점 유속을 측정할 수 있는 음파 도플러 유속계 (Acoustic Doppler Velocimetry) 혹은 2차원 입자 영상 유속계를 활용하였으며, 이들은 복잡한 3차원 난류 흐름 특성을 분석하기에는 한계가 있다. 본 연구의 목적은 실험실 실험을 통해 바닥 경계층 내 3차원 난류 흐름이 유사 이송에 미치는 영향에 대해 조사하는 것이다. 본 연구에서는 유사 주변에서의 고해상도 3차원 흐름 유동장 및 순간적인 유사 움직임에 대해서는 합성 개구 (synthetic aperture) 기반의 3차원 입자 영상 유속계 및 입자 추적 유속계를 활용하여 취득하였다. 취득된 흐름 유동장을 기반으로 레이놀즈 전단응력을 산정하였으며 이를 통해 유체가 하상에 미치는 모멘텀의 크기를 파악하였다. 복잡한 난류 흐름 구조에 대해서는 팔분원 분석 (octant analysis)을 통해 구분했으며, 유사가 움직이는 순간의 유속장을 기반으로 유사 이송을 발생시키는 지배적인 난류 흐름 특성에 대해 규명하였다. 본 연구는 바닥 경계층 내 복잡한 3차원 난류 흐름과 유사 입자의 움직임을 동시에 분석함으로써 기존에 수행되어왔던 선행 연구들의 한계점을 극복하고 보다 명확한 유사 이송의 발생 원인에 대해 분석했다는 점에 의의가 있다.

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Thickness Estimation of Transition Layer using Deep Learning (심층학습을 이용한 전이대 두께 예측)

  • Seonghyung Jang;Donghoon Lee;Byoungyeop Kim
    • Geophysics and Geophysical Exploration
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    • v.26 no.4
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    • pp.199-210
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    • 2023
  • The physical properties of rocks in reservoirs change after CO2 injection, we modeled a reservoir with a transition zone within which the physical properties change linearly. The function of the Wolf reflection coefficient consists of the velocity ratio of the upper and lower layers, the frequency, and the thickness of the transition zone. This function can be used to estimate the thickness of a reservoir or seafloor transition zone. In this study, we propose a method for predicting the thickness of the transition zone using deep learning. To apply deep learning, we modeled the thickness-dependent Wolf reflection coefficient on an artificial transition zone formation model consisting of sandstone reservoir and shale cap rock and generated time-frequency spectral images using the continuous wavelet transform. Although thickness estimation performed by comparing spectral images according to different thicknesses and a spectral image from a trace of the seismic stack did not always provide accurate thicknesses, it can be applied to field data by obtaining training data in various environments and thus improving its accuracy.

Design and Implementation of Early Warning Monitoring System for Cross-border Mining in Open-pit Mines (노천광산의 월경 채굴 조기경보 모니터링시스템의 설계 및 구현)

  • Li Ke;Byung-Won Min
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.25-41
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    • 2024
  • For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.