University of Maryland, Baltimore County
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Identification Of Magnitudes And Locations Of Loads On Slender Beams Using Strain Gage Based Methods With Application To Portable Army Bridges
No full textUnique strain gage based methods were developed to identify magnitudes and locations of loads on a non-continuous, non-homogenous, slender beam with variable cross sections, welded and bolted joints, and pinned, firm rest, soft rest, pinned-fixed, and fixed boundary conditions. Four uniaxial strain gages mounted to the bottom surface of the beam created a force transducer capable of identifying the magnitude and location of a load inside the weight area. By combining individually scaled strain gage outputs, the bending moment diagram was constructed. For the case of multiple loads separated by two or more strain gage locations, uniaxial strain gages forming multiple force transducers can still identify the magnitudes and locations of all the loads. A calibration method was developed to account for the discrepancies between the theoretical and actual scaling factors arising from stress concentrations and unpredictable stress patterns in the beams due to the presence of the joints. The strain gage based force transducer methodology was experimentally validated on prismatic beams with firm rest, soft rest, firm rest-fixed, and fixed boundary conditions; an aluminum beam with a bolted joint; and a half aluminum and half steel beam with two different cross sections and a bolted joint. It was also experimentally validated on a continuous aluminum beam with a linearly varying cross section and rest boundary conditions, a tapered aluminum beam with a series of welded joints, and a full scale portable army bridge at the US Army Aberdeen Test Center. The force transducer methodology is independent of the boundary conditions of the beam and the error from strain gage drift due to uniform thermal expansion on a prismatic beam can cancel out. When there are multiple loads separated by only one strain gage location, the problem is ill posed for the force transducer methodology. Another method has been developed using two shear gages mounted on the neutral axis of the beam, one on each side of a load, to identify the magnitude of the load in this case. A combination of two uniaxial strain gages and two shear gages, with one uniaxial strain gage and one shear gage at the same location on each side of a load, can be used to identify the location of the load. The strain gage based methods were experimentally validated on a prismatic beam with rest boundary conditions
Mining Commonsense Knowledge from the Web: Towards Inducing Script-like Structures From Large-scale Text Sources
No full textKnowing the sequences of events in situations such as eating at a restaurant is an example of commonsense knowledge needed for a broad range of cognitive tasks (e.g., language understanding). This thesis outlines an approach to mine information about sequential, every day situations in a topic-driven fashion to produce declarative, script-like representations (c.f., Schank's scripts). Given a topic such as eating at a restaurant, we produce graphs of temporally ordered events involved with the activity referenced by the topic. Our work utilizes large-scale data sources (e.g., the Web) to avoid data sparseness issues of narrow corpora. We describe steps that address the scale and noisiness of the Web to make it accessible for script extraction. Boilerplate elements (e.g., navigation bars and advertising) on web pages skew distributional statistics of words and obstruct information retrieval tasks. To make the web usable as a corpus, we introduce a machine learning technique to separate boilerplate elements from content in arbitrary web pages. A key element for commonsense knowledge extraction is the generation of a topic-specific corpus that facilitates script extraction in a topic-driven manner. We introduce Concept Modeling for Scripts as an efficient method to induce concepts containing script elements (e.g., events, people, and objects) from topic-specific corpora. Our experiments and user studies conducted on the 2011 ICWSM Spinn3r dataset show that our method outperforms state of the art topic-modeling approaches such as Latent Dirichlet Allocation (LDA) on this task when applied to unbalanced (topic-specific) corpora. Concept Modeling serves as a starting point for automated methods to discover events relevant to a script. We demonstrate event detection methods in topic-specific corpora based on (1) learned dependency paths indicative of individual event structures, (2) semantic cohesiveness of event pairs, and (3) surface structures indicative of golden sentences containing sequential information. Events extracted for a given topic can be arranged in a graph. The detection methods exploit graph analysis methods to identify strongly connected components to prune the event set such that related and central events are predominant in the structure. User studies demonstrate that (1) the Web is suitable for mining script-like knowledge and (2) the resulting graph structures portray events strongly related to a given topic. Script-like structures, by definition, impose temporal ordering on the events contained within the structure. This work also presents a novel method to induce ordering information from topic-specific corpora based on a counting framework to judge the presence and strength of a temporal happens-before relation. The framework is extensible to several counting methods, where a counting method provides co-occurrence and ordering statistics. We present, among others, a novel naive counting method that uses a simple sentence position assumption for temporal order. Comparisons to existing temporal resources show that our naive method, in conjunction with connected components analysis, induces temporal relationship with similar accuracy to more sophisticated methods, yet with a smaller computational footprint
Single Women in the Borders: Religion and Philanthropy as Paths to Social Action in Victorian Britain
No full textThis project examines how so-called redundant women used religion and philanthropy as a means for social action in Victorian Britain. I will argue that some women skillfully negotiated the borders between public and private by first engaging in philanthropy, which then led to public speaking, and then service in various national organizations, reform efforts, and even local government bodies. I will show how four lesser-known Victorian women were pioneers of the feminist movement although they were uninterested in suffrage. The foundation of this project are case studies of four women, for whom I examine both their private and public writing and their philanthropic and social reform activities. Mary Carpenter (1807 - 1877) helped reform the education of impoverished children and became a renowned pioneer of the Ragged School movement. Carpenter's research would lead to the passage of two parliamentary Acts in the mid-1850s. Louisa Twining (1820 - 1912) began her work as an unpaid district visitor, but she would eventually be elected as a Poor Law Guardian. Twining ultimately transformed healthcare of the pauper sick and helped reform the nursing profession; her work led to the passage of the Metropolitan Poor Bill in 1867. Honnor Morten (1861 - 1913) furthered Twining's work in nursing reform and helped professionalize nursing, as well as serving in local government, most particularly the London School Board. Emily Faithfull (1835 - 1895) took philanthropy to the level of professional work by broadening the options for respectable ladies' employment. Faithfull trained middle-class women in printing, established the Victoria Press, and edited/wrote a number of practical publications advocating women's work opportunities. The final section of this dissertation looks at women's work in the context of fiction rather than fact. Drawing on a selection of novels by Elizabeth Gaskell and Charles Dickens, I will argue that the significant work being done by women such as Carpenter, Twining, Morten, and Faithfull, was not adequately represented in the fiction of the period. The middle-class, single women studied here all pushed the boundaries of the separate spheres ideology, but their work was too radical to be depicted adequately in didactic Victorian fiction
AmpA: A Link Between Actin Polymerization and Cell Migration, Cell Adhesion, and Endocytosis
No full textThe ampA gene encodes a secreted protein that modulates cell adhesion, actin polymerization, endocytosis, and cell migration. AmpA is secreted into the supernatant during development, and remains cell associated during growth. AmpA loss in growing cells results in an increase in cell adhesion, and a reduction in F actin. Over expression of AmpA reduces adhesion and increases F actin. As a result of these changes in the cytoskeleton and in adhesion, I have shown AmpA influences cell migration. AmpA knockout cells are defective in migration on top of agar compared to wild type. AmpA over expressing cells migrate better than wild type on top of agar. This defect in the knockout can be rescued by placing the cells in a 3D environment where they migrate under agar. Knockout cells migrate better than wild type under these conditions and over expressing cells migrate about the same as wild type. In order to visualize actin dynamics in live cells, wild type, AmpA KO and AmpA over-expressing strains were created containing an actin binding domain fused to GFP. In stationary cells, over expressers make more actin rich endosomal cups, which form repeatedly in the same area of the membrane, leading to an increased rate of endocytosis. Knockout cells have significantly reduced F-actin, but make relatively normal endosomal cups. In order to determine how AmpA affects these processes, localization analyses were performed. Immuno-fluorescence analysis using AmpA tagged to the Tap tag and to mRFP show that AmpA is localized in possible vesicles throughout the cell and also show some localization with calnexin, an ER marker, at discrete sites surrounding the nucleus. These sites co-localize with p25, a marker for an endosomal recycling compartment. AmpA can also be found at the cell periphery under certain staining conditions. Some vesicles should be secretory vesicles, but results indicate that AmpA on the surface is endocytosed back into the cells. This indicates that AmpA is likely bound to the membrane through an interaction with its receptor where it could possibly regulate cell adhesion and actin polymerization. It is actively endocytosed and proceeds through the membrane recycling pathway
Psychosis risk screening in youth: A validation study of three self-report measures of attenuated psychosis symptoms
No full textRecent research linking the duration of untreated psychosis to illness course and outcome highlights the need for earlier intervention for individuals with schizophrenia. Early intervention efforts hinge on the ability of clinicians to reliably detect early symptoms and risk factors for psychosis in real-world settings. The Structured Interview for Psychosis Risk Syndromes (SIPS) has emerged as the most frequently utilized tool for diagnosing high-risk status, but this lengthy, clinician-administered instrument is impractical for use in large samples. Brief self-report questionnaires that assess for attenuated symptoms have the potential to quickly and effectively screen many people who may benefit from clinical monitoring or early intervention. This study examined the validity of three recently developed screening tools for attenuated symptoms by administering these tools alongside the SIPS in a sample of adolescents and young adults seeking mental health services. Screening instruments were evaluated as both continuous and dichotomized predictors of psychosis risk. Using screening thresholds recommended by instrument authors as well as thresholds empirically derived within the current sample, the sensitivity, specificity, and positive predictive value of each self-report measure with regard to SIPS diagnosis was obtained. Although all three screeners appear to be useful and valid assessment tools for attenuated symptoms, relative benefits of particular instruments are discussed. The validation of attenuated symptoms screening tools is an important step toward enabling early, wide-reaching identification of individuals on a course toward psychotic illness
Defacing of head CT scans using additive perturbation
No full textThis study developed new image processing algorithms for de-identifying the facial features of the patients undergoing head CT scans. Inter-laboratory sharing of CT image scans is commonly done through public data repositories to improve the diagnostic ability of the CT scans. However, public sharing of patient head CT scan data directly violates HIPAA regulations which classifies ""full-face photographic images and any comparable images"" as a protected health information (PHI). To ensure privacy of patient scans, we developed three new image-processing algorithms namely: shear defacing, image warping and digital mask method to deform the facial features in the scans. In particular, our digital mask method is based on hiding the face using a smoothed facemask made of skin-pixels. The ability of our digital algorithms in hiding the facial features is evaluated by applying the technique to CT image- sets of 29 patient subjects. A comparison metrics was developed to evaluate the advantages and disadvantages of each method. Results from our patient study showed that the smoothed digital mask method was applicable for de-identifying the patient faces. In future, this method could be incorporated to commercial and open-source CT reconstruction software to ensure protection of patient privacy while obtaining CT scans
Distributed Model Consensus for Models of Locally Biased Measurements in Wireless Sensor Networks
No full textWireless sensor networks (WSNs) consist of interconnected microsensors, each of which collects measurements from its local environment, which are often used in monitoring and control applications. These applications make inferences about the global and local states of the deployment environment. However, due to the limited communication and energy resources at the sensors, gathering all the raw data at a central fusion/control point is impractical. Hence, it is essential to have distributed learning and inference in WSNs, such as learning a consensus model from the locally learned models. Consensus is challenging due to the limited resources of the sensors and the inherent bias of the individual sensor models learned from their local sensing environments. Two leading approaches for this problem are the approach by Zheng et al which uses loopy belief propagation on a certain graphical model based on the WSN topology and the local models, and the approach by Xiao et al which relies on gossip averaging of the parameters of the local models. We focus on multivariate linear regression models, such as Bayesian, Ridge, and LASSO regression models. We analyze and extend the loopy Gaussian belief propagation (GaBP) approach to model consensus, and compare its performance to the gossip averaging approach. We experimentally find that GaBP tends to converge much faster than gossip averaging, but to a less accurate estimated consensus model (especially in the presence of multiple cycles in its corresponding graphical model). We also find that gossip averaging along paths in the WSN, tends to provide much faster convergence to more accurate estimated consensus models as compared to GaBP
