Speech-based metadata generation for web map search

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesMetadata is indispensable for data discoverability and interoperability. Most datasets utilize automatic techniques to create metadata; nevertheless, metadata creation still requires manual interventions and editions, yet manually metadata creation is a tedious task. The study proposes a prototype that introduces speech recognition in the metadata creation process. Users can generate content by speaking. Afterward, the prototype transforms it into metadata with JSON-LD format, a popular metadata format and utilized by mainstream search engines. A user study was conducted to understand the impact of speech-based interaction on user performance and user satisfaction. The result showed no signi cant performance di erence between speech-based and typebased by the e ciency, slip rate, and di culty rating evaluation. In the user experience evaluation, participants consider the type-based metadata creation is pragmatic, and speech-based metadata creation is hedonic. It suggests that the mix-mode can complement mutually with the advantages of each and optimize the user experience

Mergers Simulation and Demand Analysis for the U.S. Carbonated Soft Drink Industry

Replaced with revised version of paper on 09/29/09. Former title: Mergers, Price Competition for the U.S. Carbonated Soft Drink Industrydistance metrics, demand, merger simulation, Agribusiness, Industrial Organization, Marketing, L13, C14,

On aggregation bias in structural demand models

Consumer demand analysis attracts considerable attention. It remains an open question, however, whether estimating demand with aggregate data is reliable when disaggregate store-level data is given. Demand models may produce biased results when applied to data aggregated across stores with different pricing strategies. In this study, the graphical model is used to investigate the following question: Do we find the same structure when we fit causal models on sub-groupings of stores, as we find when we fit models on aggregate data from all stores?causal analysis, aggregation bias, Demand and Price Analysis, C01,

Causal Connection Search and Structural Demand Modeling on Retail-Level Scanner Data

Many researchers would be interested in one question: If a change of X is made, will Y be influenced in response? However, while a lot of statistical methods are developed to analyze association between variables, how to find a causal relationship among variables is relatively neglected. The PC algorithm, developed on the basis of Pearl, Sprites, Glymour, and Scheines‟s studies, is used to find the causal pattern of the real-world observed data. However, PC in Tetrad produces a class of directed acyclic graphs (DAGs) that are statistically equivalent under a normal distribution, and therefore such a distributional assumption causes a series of unidentifiable DAGs because of the same joint probability. In 2006 Shimizu, Hoyer, Hyvärinen, and Kerminen developed the Linear Independent Non-Gaussian Model (LiNGAM) to do a causal search based on the independently non-Gaussian distributed disturbances by applying higher-order moment structures. The research objective of this dissertation is to examine whether the LiNGAM is helpful relative to the PC algorithm, to detect the causal relation of non-normal data. The LiNGAM algorithm is implemented by first doing independent component analysis (ICA) estimation and then discovering the correct ordering of variables. Thus, the procedures of ICA estimation and the process of finding the correct causal orderings in LiNGAM are illustrated. Next, we do a causal search on the retail-level scanner data to investigate the pricing interaction between the manufacturer and the retailer by applying these two algorithms. While PC generates the set of indistinguishable DAGs, LiNGAM gives more exact causal patterns. This work demonstrates the algorithm based on the non-normal distribution assumption makes causal associations clearer. In Chapter IV, we apply a classical structural demand model to investigate the consumer purchase behavior in the carbonated soft drink market. Unfortunately, when further restrictions are imposed, we cannot get reasonable results as most researchers require. LiNGAM is applied to prove the existence of endogeneity for the brand‟s retail price and verify that the brand‟s wholesale price is not a proper instrument for its retail price. Therefore, consistent estimates cannot be derived as the theories suggest. These results imply that economic theory is not always found in restriction applied to observational data

Ceftriaxone attenuates hypoxic-ischemic brain injury in neonatal rats

<p>Abstract</p> <p>Background</p> <p>Perinatal brain injury is the leading cause of subsequent neurological disability in both term and preterm baby. Glutamate excitotoxicity is one of the major factors involved in perinatal hypoxic-ischemic encephalopathy (HIE). Glutamate transporter GLT1, expressed mainly in mature astrocytes, is the major glutamate transporter in the brain. HIE induced excessive glutamate release which is not reuptaked by immature astrocytes may induce neuronal damage. Compounds, such as ceftriaxone, that enhance the expression of GLT1 may exert neuroprotective effect in HIE.</p> <p>Methods</p> <p>We used a neonatal rat model of HIE by unilateral ligation of carotid artery and subsequent exposure to 8% oxygen for 2 hrs on postnatal day 7 (P7) rats. Neonatal rats were administered three dosages of an antibiotic, ceftriaxone, 48 hrs prior to experimental HIE. Neurobehavioral tests of treated rats were assessed. Brain sections from P14 rats were examined with Nissl and immunohistochemical stain, and TUNEL assay. GLT1 protein expression was evaluated by Western blot and immunohistochemistry.</p> <p>Results</p> <p>Pre-treatment with 200 mg/kg ceftriaxone significantly reduced the brain injury scores and apoptotic cells in the hippocampus, restored myelination in the external capsule of P14 rats, and improved the hypoxia-ischemia induced learning and memory deficit of P23-24 rats. GLT1 expression was observed in the cortical neurons of ceftriaxone treated rats.</p> <p>Conclusion</p> <p>These results suggest that pre-treatment of infants at risk for HIE with ceftriaxone may reduce subsequent brain injury.</p

Do relational norms matter in hotel outsourcing relationships? Lesson learned from hotel sectors

The study examines relational norms in outsourcing relationships. The study analyzes some factors that determine the use of relational norms, such as outsourcing benefits and the competitive strategy (cost leadership and differentiation). In addition, it analyzes the influence of the use of relational norms on the outsourcing success. Based on a sample of 127 outsourcing relationships in two tourist destinations, a PLS structural model was used to test the hypotheses. The findings show that the outsourcing benefits and competitive strategy determine the use of relational norms. They also show that there is a positive relationship between relational norms and outsourcing success. Some differences were found between the two destinations analyzed

Do relational norms matter in hotel outsourcing relationships? Lesson learned from hotel sectors

The study examines relational norms in outsourcing relationships. The study analyzes some factors that determine the use of relational norms, such as outsourcing benefits and the competitive strategy (cost leadership and differentiation). In addition, it analyzes the influence of the use of relational norms on the outsourcing success. Based on a sample of 127 outsourcing relationships in two tourist destinations, a PLS structural model was used to test the hypotheses. The findings show that the outsourcing benefits and competitive strategy determine the use of relational norms. They also show that there is a positive relationship between relational norms and outsourcing success. Some differences were found between the two destinations analyzed

Development and evaluation of a loop-mediated isothermal amplification method for rapid detection and differentiation of two genotypes of porcine circovirus type 2

BackgroundPorcine circovirus type 2 (PCV2) is one of the major swine viral diseases and has caused significant economic loss to pig producers. PCV2 has been divided into two major genotypes: PCV2a, PCV2b. A loop-mediated isothermal amplification (LAMP) method was developed for the detection and differentiation of PCV2a and PCV2b in clinical samples.MethodsLAMP-specific primer sets were designed based on six PCV2a and six PCV2b reference isolates. To determine the analytical specificity of LAMP, DNA samples extracted from 36 porcine virus isolates were tested by LAMP, including eight PCV2a, 11 PCV2b, four PCV type 1, two porcine parvovirus, three pseudorabies virus, and eight porcine reproductive and respiratory virus. To evaluate the analytical sensitivity of the assay, 10-fold serial dilutions of PCV2a and PCV2b recombinant plasmids were performed to prepare the dilutions at concentration from 106 to 1 copy(ies)/μL, and each dilution was tested by both LAMP and nested polymerase chain reaction (nested PCR). A total of 168 clinical samples were analyzed by both LAMP and nested PCR, and the relative sensitivity and specificity of LAMP compared to nested PCR were calculated.ResultsUsing different primer sets of LAMP, LAMP could be completed within 50 minutes. This method was found to be highly analytically specific for PCV2a and PCV2b; only the target gene was detected without cross-reaction. The analytical sensitivity of LAMP for PCV2a and PCV2b were 10 copies/μL, demonstrating analytical sensitivity comparable to that obtained using nested PCR. In addition, the sensitivity and specificity of LAMP relative to those of nested PCR were 97.7% and 100.0%, respectively. The percentage of observed agreement was 98.2%, and the κ statistic was 0.949.ConclusionLAMP is a rapid, specific, and sensitive diagnostic method for the detection and differentiation of PCV2a and PCV2b in clinical samples