21 resultados para Application specific algorithm
Resumo:
Direct imaging of extra-solar planets in the visible and infrared region has generated great interest among scientists and the general public as well. However, this is a challenging problem. Diffculties of detecting a planet (faint source) are caused, mostly, by two factors: sidelobes caused by starlight diffraction from the edge of the pupil and the randomly scattered starlight caused by the phase errors from the imperfections in the optical system. While the latter diffculty can be corrected by high density active deformable mirrors with advanced phase sensing and control technology, the optimized strategy for suppressing the diffraction sidelobes is still an open question. In this thesis, I present a new approach to the sidelobe reduction problem: pupil phase apodization. It is based on a discovery that an anti-symmetric spatial phase modulation pattern imposed over a pupil or a relay plane causes diffracted starlight suppression sufficient for imaging of extra-solar planets. Numerical simulations with specific square pupil (side D) phase functions, such as ... demonstrate annulling in at least one quadrant of the diffraction plane to the contrast level of better than 10^12 with an inner working angle down to 3.5L/D (with a = 3 and e = 10^3). Furthermore, our computer experiments show that phase apodization remains effective throughout a broad spectrum (60% of the central wavelength) covering the entire visible light range. In addition to the specific phase functions that can yield deep sidelobe reduction on one quadrant, we also found that a modified Gerchberg-Saxton algorithm can help to find small sized (101 x 101 element) discrete phase functions if regional sidelobe reduction is desired. Our simulation shows that a 101x101 segmented but gapless active mirror can also generate a dark region with Inner Working Distance about 2.8L/D in one quadrant. Phase-only modulation has the additional appeal of potential implementation via active segmented or deformable mirrors, thereby combining compensation of random phase aberrations and diffraction halo removal in a single optical element.
Resumo:
In this study, the use of magnesium as a Hall thruster propellant was evaluated. A xenon Hall thruster was modified such that magnesium propellant could be loaded into the anode and use waste heat from the thruster discharge to drive the propellant vaporization. A control scheme was developed, which allowed for precise control of the mass flow rate while still using plasma heating as the main mechanism for evaporation. The thruster anode, which also served as the propellant reservoir, was designed such that the open area was too low for sufficient vapor flow at normal operating temperatures (i.e. plasma heating alone). The remaining heat needed to achieve enough vapor flow to sustain thruster discharge came from a counter-wound resistive heater located behind the anode. The control system has the ability to arrest thermal runaway in a direct evaporation feed system and stabilize the discharge current during voltage-limited operation. A proportional-integral-derivative control algorithm was implemented to enable automated operation of the mass flow control system using the discharge current as the measured variable and the anode heater current as the controlled parameter. Steady-state operation at constant voltage with discharge current excursions less than 0.35 A was demonstrated for 70 min. Using this long-duration method, stable operation was achieved with heater powers as low as 6% of the total discharge power. Using the thermal mass flow control system the thruster operated stably enough and long enough that performance measurements could be obtained and compared to the performance of the thruster using xenon propellant. It was found that when operated with magnesium, the thruster has thrust ranging from 34 mN at 200 V to 39 mN at 300 V with 1.7 mg/s of propellant. It was found to have 27 mN of thrust at 300 V using 1.0 mg/s of propellant. The thrust-to-power ratio ranged from 24 mN/kW at 200 V to 18 mN/kW at 300 volts. The specific impulse was 2000 s at 200 V and upwards of 2700 s at 300 V. The anode efficiency was found to be ~23% using magnesium, which is substantially lower than the 40% anode efficiency of xenon at approximately equivalent molar flow rates. Measurements in the plasma plume of the thruster—operated using magnesium and xenon propellants—were obtained using a Faraday probe to measure off-axis current distribution, a retarding potential analyzer to measure ion energy, and a double Langmuir probe to measure plasma density, electron temperature, and plasma potential. Additionally, the off axis current distributions and ion energy distributions were compared to measurements made in krypton and bismuth plasmas obtained in previous studies of the same thruster. Comparisons showed that magnesium had the largest beam divergence of the four propellants while the others had similar divergence. The comparisons also showed that magnesium and krypton both had very low voltage utilization compared to xenon and bismuth. It is likely that the differences in plume structure are due to the atomic differences between the propellants; the ionization mean free path goes down with increasing atomic mass. Magnesium and krypton have long ionization mean free paths and therefore require physically larger thruster dimensions for efficient thruster operation and would benefit from magnetic shielding.
Resumo:
Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.
Resumo:
Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.
Resumo:
In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.
Resumo:
FEAST is a recently developed eigenvalue algorithm which computes selected interior eigenvalues of real symmetric matrices. It uses contour integral resolvent based projections. A weakness is that the existing algorithm relies on accurate reasoned estimates of the number of eigenvalues within the contour. Examining the singular values of the projections on moderately-sized, randomly-generated test problems motivates orthogonalization-based improvements to the algorithm. The singular value distributions provide experimentally robust estimates of the number of eigenvalues within the contour. The algorithm is modified to handle both Hermitian and general complex matrices. The original algorithm (based on circular contours and Gauss-Legendre quadrature) is extended to contours and quadrature schemes that are recursively subdividable. A general complex recursive algorithm is implemented on rectangular and diamond contours. The accuracy of different quadrature schemes for various contours is investigated.