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- Genre: Doctoral Dissertation
- Creators: Li, Baoxin
Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
In recent years, machine learning and data mining technologies have received growing attention in several areas such as recommendation systems, natural language processing, speech and handwriting recognition, image processing and biomedical domain. Many of these applications which deal with physiological and biomedical data require person specific or person adaptive systems. The greatest challenge in developing such systems is the subject-dependent data variations or subject-based variability in physiological and biomedical data, which leads to difference in data distributions making the task of modeling these data, using traditional machine learning algorithms, complex and challenging. As a result, despite the wide application of machine learning, efficient deployment of its principles to model real-world data is still a challenge. This dissertation addresses the problem of subject based variability in physiological and biomedical data and proposes person adaptive prediction models based on novel transfer and active learning algorithms, an emerging field in machine learning. One of the significant contributions of this dissertation is a person adaptive method, for early detection of muscle fatigue using Surface Electromyogram signals, based on a new multi-source transfer learning algorithm. This dissertation also proposes a subject-independent algorithm for grading the progression of muscle fatigue from 0 to 1 level in a test subject, during isometric or dynamic contractions, at real-time. Besides subject based variability, biomedical image data also varies due to variations in their imaging techniques, leading to distribution differences between the image databases. Hence a classifier learned on one database may perform poorly on the other database. Another significant contribution of this dissertation has been the design and development of an efficient biomedical image data annotation framework, based on a novel combination of transfer learning and a new batch-mode active learning method, capable of addressing the distribution differences across databases. The methodologies developed in this dissertation are relevant and applicable to a large set of computing problems where there is a high variation of data between subjects or sources, such as face detection, pose detection and speech recognition. From a broader perspective, these frameworks can be viewed as a first step towards design of automated adaptive systems for real world data.
ContributorsChattopadhyay, Rita (Author) / Panchanathan, Sethuraman (Thesis advisor) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
Integrated photonics requires high gain optical materials in the telecom wavelength range for optical amplifiers and coherent light sources. Erbium (Er) containing materials are ideal candidates due to the 1.5 μm emission from Er3+ ions. However, the Er density in typical Er-doped materials is less than 1 x 1020 cm-3, thus limiting the maximum optical gain to a few dB/cm, too small to be useful for integrated photonics applications. Er compounds could potentially solve this problem since they contain much higher Er density. So far the existing Er compounds suffer from short lifetime and strong upconversion effects, mainly due to poor quality of crystals produced by various methods of thin film growth and deposition. This dissertation explores a new Er compound: erbium chloride silicate (ECS, Er3(SiO4)2Cl ) in the nanowire form, which facilitates the growth of high quality single crystals. Growth methods for such single crystal ECS nanowires have been established. Various structural and optical characterizations have been carried out. The high crystal quality of ECS material leads to a long lifetime of the first excited state of Er3+ ions up to 1 ms at Er density higher than 1022 cm-3. This Er lifetime-density product was found to be the largest among all Er containing materials. A unique integrating sphere method was developed to measure the absorption cross section of ECS nanowires from 440 to 1580 nm. Pump-probe experiments demonstrated a 644 dB/cm signal enhancement from a single ECS wire. It was estimated that such large signal enhancement can overcome the absorption to result in a net material gain, but not sufficient to compensate waveguide propagation loss. In order to suppress the upconversion process in ECS, Ytterbium (Yb) and Yttrium (Y) ions are introduced as substituent ions of Er in the ECS crystal structure to reduce Er density. While the addition of Yb ions only partially succeeded, erbium yttrium chloride silicate (EYCS) with controllable Er density was synthesized successfully. EYCS with 30 at. % Er was found to be the best. It shows the strongest PL emission at 1.5 μm, and thus can be potentially used as a high gain material.
ContributorsYin, Leijun (Author) / Ning, Cun-Zheng (Thesis advisor) / Chamberlin, Ralph (Committee member) / Yu, Hongbin (Committee member) / Menéndez, Jose (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation is focused on material property exploration and analysis using computational quantum mechanics methods. Theoretical calculations were performed on the recently discovered hexahydride materials A2SiH6 (A=Rb, K) to calculate the lattice dynamics of the systems in order to check for structural stability, verify the experimental Raman and infrared spectrospcopy results, and obtain the theoretical free energies of formation. The electronic structure of the systems was calculated and the bonding and ionic properties of the systems were analyzed. The novel hexahydrides were compared to the important hydrogen storage material KSiH3. This showed that the hypervalent nature of the SiH62- ions reduced the Si-H bonding strength considerably. These hydrogen rich compounds could have promising energy applications as they link to alternative hydrogen fuel technology. The carbide systems Li-C (A=Li,Ca,Mg) were studied using \emph{ab initio} and evolutionary algorithms at high pressures. At ambient pressure Li2C2 and CaC2 are known to contain C22- dumbbell anions and CaC2 is polymorphic. At elevated pressure both CaC2 and Li2C2 display polymorphism. At ambient pressure the Mg-C system contains several experimentally known phases, however, all known phases are shown to be metastable with respect to the pure elements Mg and C. First principle investigation of the configurational space of these compounds via evolutionary algorithms results in a variety of metastable and unique structures. The binary compounds ZnSb and ZnAs are II-V electron-poor semiconductors with interesting thermoelectric properties. They contain rhomboid rings composed of Zn2Sb2 (Zn2As2) with multi-centered covalent bonds which are in turn covalently bonded to other rings via two-centered, two-electron bonds. Ionicity was explored via Bader charge analysis and it appears that the low ionicity that these materials display is a necessary condition of their multicentered bonding. Both compounds were found to have narrow, indirect band gaps with multi-valley valence and conduction bands; which are important characteristics for high thermopower in thermoelectric materials. Future work is needed to analyze the lattice properties of the II-V CdSb-type systems, especially in order to find the origin of the extremely low thermal conductivity that these systems display.
ContributorsBenson, Daryn Eugene (Author) / Häussermann, Ulrich (Thesis advisor) / Shumway, John (Thesis advisor) / Chamberlin, Ralph (Committee member) / Sankey, Otto (Committee member) / Treacy, Mike (Committee member) / Arizona State University (Publisher)
Created2013
Description
The theory of quantum electrodynamics predicts that beta decay of the neutron into a proton, electron, and anti-neutrino should be accompanied by a continuous spectrum of photons. A recent experiment, RDK I, reported the first detection of radiative decay photons from neutron beta decay with a branching ratio of (3.09 ± 0.32) × 10-3 in the energy range of 15 keV to 340 keV. This was achieved by prompt coincident detection of an electron and photon, in delayed coincidence with a proton. The photons were detected by using a single bar of bismuth germanate scintillating crystal coupled to an avalanche photodiode. This thesis deals with the follow-up experiment, RDK II, to measure the branching ratio at the level of approximately 1% and the energy spectrum at the level of a few percent. The most significant improvement of RDK II is the use of a photon detector with about an order of magnitude greater solid angle coverage than RDK I. In addition, the detectable energy range has been extended down to approximately 250 eV and up to the endpoint energy of 782 keV. This dissertation presents an overview of the apparatus, development of a new data analysis technique for radiative decay, and results for the ratio of electron-proton-photon coincident Repg to electron-proton coincident Rep events.
ContributorsO'Neill, Benjamin (Author) / Alarcon, Ricardo (Thesis advisor) / Drucker, Jeffery (Committee member) / Lebed, Richard (Committee member) / Comfort, Joseph (Committee member) / Chamberlin, Ralph (Committee member) / Arizona State University (Publisher)
Created2012
Description
In this dissertation, remote plasma interactions with the surfaces of low-k interlayer dielectric (ILD), Cu and Cu adhesion layers are investigated. The first part of the study focuses on the simultaneous plasma treatment of ILD and chemical mechanical polishing (CMP) Cu surfaces using N2/H2 plasma processes. H atoms and radicals in the plasma react with the carbon groups leading to carbon removal for the ILD films. Results indicate that an N2 plasma forms an amide-like layer on the surface which apparently leads to reduced carbon abstraction from an H2 plasma process. In addition, FTIR spectra indicate the formation of hydroxyl (Si-OH) groups following the plasma exposure. Increased temperature (380 °C) processing leads to a reduction of the hydroxyl group formation compared to ambient temperature processes, resulting in reduced changes of the dielectric constant. For CMP Cu surfaces, the carbonate contamination was removed by an H2 plasma process at elevated temperature while the C-C and C-H contamination was removed by an N2 plasma process at elevated temperature. The second part of this study examined oxide stability and cleaning of Ru surfaces as well as consequent Cu film thermal stability with the Ru layers. The ~2 monolayer native Ru oxide was reduced after H-plasma processing. The thermal stability or islanding of the Cu film on the Ru substrate was characterized by in-situ XPS. After plasma cleaning of the Ru adhesion layer, the deposited Cu exhibited full coverage. In contrast, for Cu deposition on the Ru native oxide substrate, Cu islanding was detected and was described in terms of grain boundary grooving and surface and interface energies. The thermal stability of 7 nm Ti, Pt and Ru ii interfacial adhesion layers between a Cu film (10 nm) and a Ta barrier layer (4 nm) have been investigated in the third part. The barrier properties and interfacial stability have been evaluated by Rutherford backscattering spectrometry (RBS). Atomic force microscopy (AFM) was used to measure the surfaces before and after annealing, and all the surfaces are relatively smooth excluding islanding or de-wetting phenomena as a cause of the instability. The RBS showed no discernible diffusion across the adhesion layer/Ta and Ta/Si interfaces which provides a stable underlying layer. For a Ti interfacial layer RBS indicates that during 400 °C annealing Ti interdiffuses through the Cu film and accumulates at the surface. For the Pt/Cu system Pt interdiffuion is detected which is less evident than Ti. Among the three adhesion layer candidates, Ru shows negligible diffusion into the Cu film indicating thermal stability at 400 °C.
ContributorsLiu, Xin (Author) / Nemanich, Robert (Thesis advisor) / Chamberlin, Ralph (Committee member) / Chen, Tingyong (Committee member) / Smith, David (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2012
Description
The heat transfer enhancements available from expanding the cross-section of a boiling microchannel are explored analytically and experimentally. Evaluation of the literature on critical heat flux in flow boiling and associated pressure drop behavior is presented with predictive critical heat flux (CHF) and pressure drop correlations. An optimum channel configuration allowing maximum CHF while reducing pressure drop is sought. A perturbation of the channel diameter is employed to examine CHF and pressure drop relationships from the literature with the aim of identifying those adequately general and suitable for use in a scenario with an expanding channel. Several CHF criteria are identified which predict an optimizable channel expansion, though many do not. Pressure drop relationships admit improvement with expansion, and no optimum presents itself. The relevant physical phenomena surrounding flow boiling pressure drop are considered, and a balance of dimensionless numbers is presented that may be of qualitative use. The design, fabrication, inspection, and experimental evaluation of four copper microchannel arrays of different channel expansion rates with R-134a refrigerant is presented. Optimum rates of expansion which maximize the critical heat flux are considered at multiple flow rates, and experimental results are presented demonstrating optima. The effect of expansion on the boiling number is considered, and experiments demonstrate that expansion produces a notable increase in the boiling number in the region explored, though no optima are observed. Significant decrease in the pressure drop across the evaporator is observed with the expanding channels, and no optima appear. Discussion of the significance of this finding is presented, along with possible avenues for future work.
ContributorsMiner, Mark (Author) / Phelan, Patrick E (Thesis advisor) / Baer, Steven (Committee member) / Chamberlin, Ralph (Committee member) / Chen, Kangping (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
In this research, our goal was to fabricate Josephson junctions that can be stably processed at 300°C or higher. With the purpose of integrating Josephson junction fabrication with the current semiconductor circuit fabrication process, back-end process temperatures (>350 °C) will be a key for producing large scale junction circuits reliably, which requires the junctions to be more thermally stable than current Nb/Al-AlOx/Nb junctions. Based on thermodynamics, Hf was chosen to produce thermally stable Nb/Hf-HfOx/Nb superconductor tunnel Josephson junctions that can be grown or processed at elevated temperatures. Also elevated synthesis temperatures improve the structural and electrical properties of Nb electrode layers that could potentially improve junction device performance. The refractory nature of Hf, HfO2 and Nb allow for the formation of flat, abrupt and thermally-stable interfaces. But the current Al-based barrier will have problems when using with high-temperature grown and high-quality Nb. So our work is aimed at using Nb grown at elevated temperatures to fabricate thermally stable Josephson tunnel junctions. As a junction barrier metal, Hf was studied and compared with the traditional Al-barrier material. We have proved that Hf-HfOx is a good barrier candidate for high-temperature synthesized Josephson junction. Hf deposited at 500 °C on Nb forms flat and chemically abrupt interfaces. Nb/Hf-HfOx/Nb Josephson junctions were synthesized, fabricated and characterized with different oxidizing conditions. The results of materials characterization and junction electrical measurements are reported and analyzed. We have improved the annealing stability of Nb junctions and also used high-quality Nb grown at 500 °C as the bottom electrode successfully. Adding a buffer layer or multiple oxidation steps improves the annealing stability of Josephson junctions. We also have attempted to use the Atomic Layer Deposition (ALD) method for the growth of Hf oxide as the junction barrier and got tunneling results.
ContributorsHuang, Mengchu, 1987- (Author) / Newman, Nathan (Thesis advisor) / Rowell, John M. (Committee member) / Singh, Rakesh K. (Committee member) / Chamberlin, Ralph (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2013
Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT This thesis focuses on structural characterizations and optical properties of Si, Ge based semiconductor alloys. Two material systems are characterized: Si-based III-V/IV alloys, which represent a possible pathway to augment the optical performance of elemental silicon as a solar cell absorber layer, and Ge-based Ge1-ySny and Ge1-x-ySixSny systems which are applicable to long wavelength optoelectronics. Electron microscopy is the primary tool used to study structural properties. Electron Energy Loss spectroscopy (EELS), Ellipsometry, Photoluminescence and Raman Spectroscopy are combined to investigate electronic band structures and bonding properties. The experiments are closely coupled with structural and property modeling and theory. A series of III-V-IV alloys have been synthesized by the reaction of M(SiH3)3 (M = P, As) with Al atoms from a Knudsen cell. In the AlPSi3 system, bonding configurations and elemental distributions are characterized by scanning transmission electron microscopy (STEM)/EELS and correlated with bulk optical behavior. The incorporation of N was achieved by addition of N(SiH3)3 into the reaction mixture yielding [Al(As1-xNx)]ySi5-2yalloys. A critical point analysis of spectroscopic ellipsometry data reveals the existence of direct optical transitions at energies as low as 2.5 eV, well below the lowest direct absorption edge of Si at 3.3 eV. The compositional dependence of the lowest direct gap and indirect gap in Ge1-ySny alloys extracted from room temperature photoluminescence indicates a crossover concentration of yc =0.073, much lower than virtual crystal approximation but agrees well with large atomic supercells predictions. A series of Ge-rich Ge1-x-ySixSny samples with a fixed 3-4% Si content and progressively increasing Sn content in the 4-10% range are grown and characterized by electron microscopy and photoluminescence. The ternary represents an attractive alternative to Ge1-ySny for applications in IR optoelectronic technologies.
ContributorsJiang, Liying (Author) / Menéndez, Jose (Thesis advisor) / Kouvetakis, John (Thesis advisor) / Smith, David J. (Committee member) / Chizmeshya, Andrew V.G (Committee member) / Chamberlin, Ralph (Committee member) / Arizona State University (Publisher)
Created2014