330 research outputs found
The role of part structure in the perceptual localization of a shape
No full textThe process of object localization may be accomplished with respect to a particularreference location, such as the center of gravity, COG (eg Vishwanath and Kowler, 2003 VisionResearch 43 1637-1653). Here, we investigated how part structure affects an object's referencelocation. The reference location was evaluated with a measure of the illusory displacement of an internal target element embedded within a larger object (Morgan et al, 1990 Vision Research 30 1793-1810). To examine whether the reference location is different for shapes with part structure, two shapes were tested: circle (small and large; no part structure) and bell (shape with two parts, one larger than the other). Results were examined with respect to two predictions: either the location of an object is based on its shape as a whole, disregarding part structure (ie a single, overall COG), or the parts are processed separately (different COGs).With the circles, the results showed a systematic illusory displacement of the internal target toward the COG. With the bell, the illusion was significantly weaker than with both circles--even though the main part of the bell had the same size as the small circle, and its horizontal axis had the same extent as the large circle. Moreover, the distance judgments for the bell were consistent with a (weaker) reference point being located at the COG of the larger part, rather than at the COG of the entire bell. These results show that the part structure of a shape plays a role in the representation of its location, and that for complex shapes the perceived location of an embedded element depends more on the parts within which it is embedded, rather than on the whole shape.Supported by the Air Force Office of Scientific Research, Grant AF 49620- 02-1-0112, Life Sciences Directorate to Eileen Kowler, and by NSF, Grant BCS-0216944 to Manish Singh.AF 29620-02-1-0112; to Eileen KowlerNSF BCS-0216944; to Manish SinghDenisova, Kristina, Manish Singh, Eileen Kowler, 2006. The definitive, peer-reviewed and edited version of this article is published in Perception, 35, 1073-1087, DOI:10.1068/p5518
Dynamic modeling and forecasting algorithms for financial data systems
No full textIt is a valid question that why a Control Systems Engineer would be interested in dealing with financial instruments. Financial instruments involving option theory are very elegant, math oriented and practical. These mathematical tools have created a new industry known as 'Derivative Industry' or 'Hedge-Fund Industry' or so called 'Risk-Management Industry'. This thesis is aimed at developing investment strategies involving the decision making needs via control system techniques. The problem, in general, is computationally challenging particularly when investment of many securities is involved resulting in a high dimensional computational framework. Furthermore, complications may arise due to realistic restrictions and non-linearities. The various areas of financial engineering are very fertile for the application of the system methodology and control theory techniques. Modeling, optimization, identification and computational methods used in the Systems Engineering can be successfully applied to the financial instruments. The ideas developed in this thesis are more about the scientific reasoning involving financial instruments rather than specific situations alone. Major contribution of this thesis is the time series optimal prediction filter and the development of the Dynamic Modeling and Forecasting Algorithm (DMFA). The proposed algorithm predicts the next data point of the financial time series while dynamically computing the parameters from existing data. The computation of the parameters is optimized by use of the recursive matrix inversion algorithm. The system is solved via an innovative technique of inversion such that it avoids explicit inversion of more than a 2 X 2 matrix and computation of higher dimensional determinants and co-factors. This results in new contributions to computation finance and numerical methodology along with arbitrage decision and hedging strategies under market uncertainties as well as robust control applications. The minimum mean-square algorithm used assures system stability via poles within the unit circle. The DMFA method is a superior auto regression (AR) model as a general system of time-series realizations in-order to calculate the coefficients that fit the model for a better prediction. Theoretical modeling and market specific volatility models, updated volatility computation are derived from the observation data.Ph.D.Includes bibliographical referencesIncludes vitaby Manish Mahaja
The relationship between spatial pooling and attention in saccadic and perceptual tasks
No full textAbstractSaccades aimed at spatially extended targets land reliably at central locations determined by pooling information across the target shape [Melcher, D., & Kowler, E. (1999). Shape, surfaces and saccades. Vision Research, 39, 2929–2946; Vishwanath, D., & Kowler, E. (2003). Localization of shapes: Eye movements and perception compared. Vision Research, 43, 1637–1653]. Previous findings of saccadic errors when attempting to look at a target in the midst of distractors encouraged suggestions that pooling occurs indiscriminately, with little or no influence of a selective filter to eliminate the influence of nearby distractors. To determine the effectiveness of filtering, saccadic localization was studied for saccades made to a set of target elements (discs) interleaved with an equivalent set of distractors of a different color. With such interleaved elements, selection and spatial pooling are constrained to occur over the same spatial region. The results showed that filtering was effective and saccadic landing position was determined mainly by the target elements. Concurrent perceptual judgments made about the same stimuli (estimating the mean size of either target or distractor discs) showed better performance for the target discs than distractors, confirming that perceptual attention was allocated to the set of target elements. These results: (1) support the role of attention in setting the input to the spatial pooling process that guides saccades to spatially extended targets, and (2) show that perceptual judgments of mean value, often thought to impose modest attentional demands, are not immune to the constraints of this pre-saccadic filter
Adaptive particle encapsulation using digital opto-fluidic lithography
No full textEncapsulation of living cells using microgels has a wide range of applications in pharmaceutical research, tissue engineering, regenerative medicine, and personalized drug screening. Various cell encapsulation techniques have been proposed thus far focusing on creating cell-laden microgel particles. However, current techniques have limited control over the shape and size of the encapsulating particles and lack ability to address individual cells. This research aims to develop a method for adaptive encapsulation of particles with geometrically and biochemically complex micro-particles. To this end, we demonstrate image-based particle detection in a microfluidic channel and real-time in-flow lithography to encapsulate suspended particle employing a digital micro display as a dynamically reconfigurable virtual photomask. Digital dynamic mask is economical and offers the flexibility of rapidly changing the mask on demand. Microfluidic environment allows for mass production of micro-particles having various chemical composition in a continuous manner. Combining these unique capabilities, we present encapsulation of individual particles with graphically encoded information. Visual information (shape, size, and location) of polystyrene micro-beads suspended in a photo-curable liquid resin is acquired through digital imaging and subsequent image analysis, based on which desired digital patterns, possibly with graphical information, are created and optically projected on the target beads for lithographical in-flow encapsulation. The work presented in this thesis provides a new method for particle encapsulation, which has the potential to lead to a breakthrough solution in pharmaceutical engineering, cancer research, and tissue engineering.M.S.Includes bibliographical referencesby Manish Boorug
Biomolecular transport at and through two-dimensional materials
No full textTwo-dimensional (2D) materials have transformed single molecule nanoscale manipulation and molecular detection. Graphene is one such 2D material whose single-atom thickness and high in-plane electrical conductivity enables potential nanopore sensing applications for controllable nanofluidics and nanopore sensing applications conducive towards biomolecule sequencing. A nanopore sequencer operates by recording the ionic current as a single-stranded DNA molecule is electrophoretically driven through a nanopore; ionic current blockades unique to each nucleotide provide a key to the sequence readout. 2D materials provide the ultimate resolution by isolating one or two nucleotides in the nanopore at a given instance. A major challenge limiting the applications of nanopores for sequencing is the stochastic transport of DNA through the nanopore contributing to noise in the readout.
Experiments have tested DNA transport though graphene nanopores however the strong hydrophobic interactions between DNA and graphene limit DNA capture and transport. To increase throughput, exper- iments tested geometric modifications and chemical functionalization of the nanopore as well as altering the solvent conditions to control the passage of DNA through the nanopore with varying degrees of success. To optimize and test the design of nanopores in 2D materials, an atomistic description of these processes is extremely valuable.
Here, several modalities of controlling DNA and ion transport through graphene nanopores are compre- hensively investigated using all-atom molecular dynamics simulations. The first modality is an application of local electric potentials on the surface of free-standing graphene membranes to limit the transport speed of DNA. Charge on the graphene membrane was discovered to limit DNA transport as well as effect the conformation of adsorbed DNA on the surface of graphene. Similar potentials applied on the surface of graphene-silica-graphene hetrostructures were found to modulate the ion selectivity and induce ionic current rectification useful to serve as elements of a nanofluidic circuit. The second modality focuses on a con- trolled method of DNA delivery to the nanopore by harnessing the strong physioadsorption of DNA onto graphene and defects naturally present on the surface of graphene to guide the lateral transport of DNA to the nanopore opening. The defect guided delivery method may be potentially be used for precise delivery, concentration and storage of scarce biomolecular species and on-demand chemical reactions. Transport of DNA through the 2D material MoS2 in a specialized viscosity gradient was also investigated to determine the nature of molecular transport in unique solvent conditions. Lipid transport diffusion on graphene and the osmotic permeability and selectivity of the biological nanopore OmpF were characterized in conjunction with experiments. Results presented in this dissertation provide key insights into the design of solid-state nanopore based DNA sequencing devices.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-12-01The student, Manish Shankla, accepted the attached license on 2019-11-20 at 09:29.The student, Manish Shankla, submitted this Dissertation for approval on 2019-11-20 at 09:38.This Dissertation was approved for publication on 2019-11-21 at 11:09.DSpace SAF Submission Ingestion Package generated from Vireo submission #14572 on 2020-02-28 at 17:36:27Made available in DSpace on 2020-03-02T22:38:45Z (GMT). No. of bitstreams: 2
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The impact of visual production management on construction project controls: a case-based reasoning
No full textOver the past decade, production control theories such as the Last Planner System by Ballard, G., (2000) have emerged that stabilize workflows by shielding the direct work from upstream variation and uncertainty. Although theories have been well documented, yet their full-scale implementation is not realized, and the root-causes for this are not entirely understood. A large body of empirical observations suggest that successful implementation of control mechanisms requires dedicated facilitators and engages practitioners in a relatively deep learning process. Sustaining this level of commitment for the duration of a project is difficult, and in its absence, project teams revert to traditional project control practices. These barriers are in part attributed to the people and organizational processes involved in implementing lean principles, however there is a growing recognition among researchers that the functional aspects of production control techniques need close re-examination to understand better, predict, and analyze reliability in performance, and preserve effective and timely flow of information both to and from the workforce.
To address these knowledge gaps, Lin and Golparvar-Fard (2016) proposes a visual project control system that a) improves understanding of how construction performance can be captured, communicated, and analyzed in form of a production system; b) predicts the reliability of the weekly work plan and look-ahead schedule, supports root-cause assessment on plan failure at both project and task-levels; c) facilitates information flows; and d) decentralizes decision-making. The web-based system which is built on visual data analytics maps the current state of production on construction sites in 3D and exposes waste at both project and task-levels and it then forecasts reliability in the future state of production to highlight potential issues in a location-driven scheme.
The platform also supports collaborative decision making that eliminates root causes of waste and provides visual interfaces between people and information that enable effective pull flow, decentralize work tracking, and facilitate in-process quality control and hand-overs among contractors. To ensure their implementation does not take away from actual productivity, it extends the value of 4D Building Information Models (BIM) commonly used for constructability review as a benchmark for performance. It also leverages images and videos frequently collected by project participants or professional services via consumer-grade, time-lapse, smartphone cameras and Unmanned Aerial Vehicles (UAVs) to visually document actual performance.
To better understand, assess, and improve the performance of this visual production system, a case-based reasoning study is conducted in this thesis using case studies based on two real-world construction projects. The use of simple and effective visuals of work-in-progress and at risk locations on construction sites offered through visual production management is assessed to better understand if such systems can improve reliability of short-term planning, enhance situational awareness, enable easy and quick root-cause assessment of plan failures, and facilitate flow of information onsite and during coordination sessions. The lessons learned and areas for further development in theory and technology are discussed in detail.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-12-01The student, Manish Patidar, accepted the attached license on 2016-12-06 at 14:24.The student, Manish Patidar, submitted this Thesis for approval on 2016-12-06 at 14:35.This Thesis was approved for publication on 2016-12-07 at 11:30.DSpace SAF Submission Ingestion Package generated from Vireo submission #10454 on 2017-02-28 at 14:43:15Made available in DSpace on 2017-03-01T17:02:05Z (GMT). No. of bitstreams: 3
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Supplemental figures and tables for "Bayesian approaches to smooth pursuit of random dot kinematograms: effects of varying RDK noise and the predictability of RDK direction"
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