Rational engineering of nanoporous anodic alumina optical bandpass filters

First published online 07 Jul 2016Herein, we present a rationally designed advanced nanofabrication approach aiming at producing a new type of optical bandpass filters based on nanoporous anodic alumina photonic crystals. The photonic stop band of nanoporous anodic alumina (NAA) is engineered in depth by means of a pseudo-stepwise pulse anodisation (PSPA) approach consisting of pseudo-stepwise asymmetric current density pulses. This nanofabrication method makes it possible to tune the transmission bands of NAA at specific wavelengths and bandwidths, which can be broadly modified across the UV-visible-NIR spectrum through the anodisation period (i.e. time between consecutive pulses). First, we establish the effect of the anodisation period as a means of tuning the position and width of the transmission bands of NAA across the UV-visible-NIR spectrum. To this end, a set of nanoporous anodic alumina bandpass filters (NAA-BPFs) are produced with different anodisation periods, ranging from 500 to 1200 s, and their optical properties (i.e. characteristic transmission bands and interferometric colours) are systematically assessed. Then, we demonstrate that the rational combination of stacked NAA-BPFs consisting of layers of NAA produced with different PSPA periods can be readily used to create a set of unique and highly selective optical bandpass filters with characteristic transmission bands, the position, width and number of which can be precisely engineered by this rational anodisation approach. Finally, as a proof-of-concept, we demonstrate that the superposition of stacked NAA-BPFs produced with slight modifications of the anodisation period enables the fabrication of NAA-BPFs with unprecedented broad transmission bands across the UV-visible-NIR spectrum. The results obtained from our study constitute the first comprehensive rationale towards advanced NAA-BPFs with fully controllable photonic properties. These photonic crystal structures could become a promising alternative to traditional optical bandpass filters based on glass and plastic.Abel Santos, Taj Pereira, Cheryl Suwen Law and Dusan Losi

The Mark 3 Haploscope

A computer-operated binocular vision testing device was developed as one part of a system designed for NASA to evaluate the visual function of astronauts during spaceflight. This particular device, called the Mark 3 Haploscope, employs semi-automated psychophysical test procedures to measure visual acuity, stereopsis, phoria, fixation disparity, refractive state and accommodation/convergence relationships. Test procedures are self-administered and can be used repeatedly without subject memorization. The Haploscope was designed as one module of the complete NASA Vision Testing System. However, it is capable of stand-alone operation. Moreover, the compactness and portability of the Haploscope make possible its use in a broad variety of testing environments

LONG-TERM MULTI-DIMENSIONAL INTERACTIVE TIME-LAPSE PHOTOGRAPHY USING MICROSOFT KINECT

In this thesis, a method is presented for the capture and interactive presentation of long-term multi-dimensional time-lapse photography. Time-lapse capture is commonly used for the observation based study of relatively long term phenomena such as plant growth and weather patterns. In terms of filmic devices, the visual time compression effect is complementary to slow motion and is nearly as prevalent. In this project, commonly available camera and computer equipment is used to capture images autonomously with minimal system supervision. A set of images is established, using long term, short interval continuous capture at a fixed position. Results are presented demonstrating dynamic movement within this set using the Microsoft Kinect sensor for Xbox 360 to evaluate participant gestures in real-time. Viewers\u27 tracked movements and positions motivate specific frame selection and playback order, allowing independent navigation through the time-lapse, independently by time of day, time of season, and in any order participants can obtain with their own movement and performance

Photojournalism : the ultimate

ThesisThere are no specific rules in photography. The most important "rule" is to see. Photography is all about detail. It is about noticing small things, for example how many clouds there were in the sky this morning, or from what side the wind was blowing. To become a good photographer, one has to start focusing constantly on small detail like this. For the past three years I have been involved in many photojournalistic assignments, often working with photojournalists from a local newspaper, as well as with some of the best photographers in the world. During this time, I have learned a great deal about photography in practice. There are of course a huge difference between photography in the classroom, and photography in a real life situation, where you have to think on your feet and where each second is of tremendous importance. A second missed can be a photograph missed, and the opportunity will be gone forever. For me, photojournalism is the ultimate form of photography. The adrenalin of the situation, the immediacy of events and the feeling of satisfaction after seeing the photograph~, makes it all worth while

The BG News December 18, 1995

The BGSU campus student newspaper December 18, 1995. Volume 78 - Issue 75https://scholarworks.bgsu.edu/bg-news/6943/thumbnail.jp

훈련 자료 자동 추출 알고리즘과 기계 학습을 통한 SAR 영상 기반의 선박 탐지

학위논문 (석사) -- 서울대학교 대학원 : 자연과학대학 지구환경과학부, 2021. 2. 김덕진.Detection and surveillance of vessels are regarded as a crucial application of SAR for their contribution to the preservation of marine resources and the assurance on maritime safety. Introduction of machine learning to vessel detection significantly enhanced the performance and efficiency of the detection, but a substantial majority of studies focused on modifying the object detector algorithm. As the fundamental enhancement of the detection performance would be nearly impossible without accurate training data of vessels, this study implemented AIS information containing real-time information of vessel’s movement in order to propose a robust algorithm which acquires the training data of vessels in an automated manner. As AIS information was irregularly and discretely obtained, the exact target interpolation time for each vessel was precisely determined, followed by the implementation of Kalman filter, which mitigates the measurement error of AIS sensor. In addition, as the velocity of each vessel renders an imprint inside the SAR image named as Doppler frequency shift, it was calibrated by restoring the elliptic satellite orbit from the satellite state vector and estimating the distance between the satellite and the target vessel. From the calibrated position of the AIS sensor inside the corresponding SAR image, training data was directly obtained via internal allocation of the AIS sensor in each vessel. For fishing boats, separate information system named as VPASS was applied for the identical procedure of training data retrieval. Training data of vessels obtained via the automated training data procurement algorithm was evaluated by a conventional object detector, for three detection evaluating parameters: precision, recall and F1 score. All three evaluation parameters from the proposed training data acquisition significantly exceeded that from the manual acquisition. The major difference between two training datasets was demonstrated in the inshore regions and in the vicinity of strong scattering vessels in which land artifacts, ships and the ghost signals derived from them were indiscernible by visual inspection. This study additionally introduced a possibility of resolving the unclassified usage of each vessel by comparing AIS information with the accurate vessel detection results.전천후 지구 관측 위성인 SAR를 통한 선박 탐지는 해양 자원의 확보와 해상 안전 보장에 매우 중요한 역할을 한다. 기계 학습 기법의 도입으로 인해 선박을 비롯한 사물 탐지의 정확도 및 효율성이 향상되었으나, 이와 관련된 다수의 연구는 탐지 알고리즘의 개량에 집중되었다. 그러나, 탐지 정확도의 근본적인 향상은 정밀하게 취득된 대량의 훈련자료 없이는 불가능하기에, 본 연구에서는 선박의 실시간 위치, 속도 정보인 AIS 자료를 이용하여 인공 지능 기반의 선박 탐지 알고리즘에 사용될 훈련자료를 자동적으로 취득하는 알고리즘을 제안하였다. 이를 위해 이산적인 AIS 자료를 SAR 영상의 취득시각에 맞추어 정확하게 보간하고, AIS 센서 자체가 가지는 오차를 최소화하였다. 또한, 이동하는 산란체의 시선 속도로 인해 발생하는 도플러 편이 효과를 보정하기 위해 SAR 위성의 상태 벡터를 이용하여 위성과 산란체 사이의 거리를 정밀하게 계산하였다. 이렇게 계산된 AIS 센서의 영상 내의 위치로부터 선박 내 AIS 센서의 배치를 고려하여 선박 탐지 알고리즘의 훈련자료 형식에 맞추어 훈련자료를 취득하고, 어선에 대한 위치, 속도 정보인 VPASS 자료 역시 유사한 방법으로 가공하여 훈련자료를 취득하였다. AIS 자료로부터 취득한 훈련자료는 기존 방법대로 수동 취득한 훈련자료와 함께 인공 지능 기반 사물 탐지 알고리즘을 통해 정확도를 평가하였다. 그 결과, 제시된 알고리즘으로 취득한 훈련 자료는 수동 취득한 훈련 자료 대비 더 높은 탐지 정확도를 보였으며, 이는 기존의 사물 탐지 알고리즘의 평가 지표인 정밀도, 재현율과 F1 score를 통해 진행되었다. 본 연구에서 제안한 훈련자료 자동 취득 기법으로 얻은 선박에 대한 훈련자료는 특히 기존의 선박 탐지 기법으로는 분별이 어려웠던 항만에 인접한 선박과 산란체 주변의 신호에 대한 정확한 분별 결과를 보였다. 본 연구에서는 이와 함께, 선박 탐지 결과와 해당 지역에 대한 AIS 및 VPASS 자료를 이용하여 선박의 미식별성을 판정할 수 있는 가능성 또한 제시하였다.Chapter 1. Introduction - 1 - 1.1 Research Background - 1 - 1.2 Research Objective - 8 - Chapter 2. Data Acquisition - 10 - 2.1 Acquisition of SAR Image Data - 10 - 2.2 Acquisition of AIS and VPASS Information - 20 - Chapter 3. Methodology on Training Data Procurement - 26 - 3.1 Interpolation of Discrete AIS Data - 29 - 3.1.1 Estimation of Target Interpolation Time for Vessels - 29 - 3.1.2 Application of Kalman Filter to AIS Data - 34 - 3.2 Doppler Frequency Shift Correction - 40 - 3.2.1 Theoretical Basis of Doppler Frequency Shift - 40 - 3.2.2 Mitigation of Doppler Frequency Shift - 48 - 3.3 Retrieval of Training Data of Vessels - 53 - 3.4 Algorithm on Vessel Training Data Acquisition from VPASS Information - 61 - Chapter 4. Methodology on Object Detection Architecture - 66 - Chapter 5. Results - 74 - 5.1 Assessment on Training Data - 74 - 5.2 Assessment on AIS-based Ship Detection - 79 - 5.3 Assessment on VPASS-based Fishing Boat Detection - 91 - Chapter 6. Discussions - 110 - 6.1 Discussion on AIS-Based Ship Detection - 110 - 6.2 Application on Determining Unclassified Vessels - 116 - Chapter 7. Conclusion - 125 - 국문 요약문 - 128 - Bibliography - 130 -Maste