A comparative analysis of student SQL and relational database knowledge using automated grading tools

This paper evaluates a blended learning methodology for Relational Database Systems. Our module offers students a range of interconnected tools and teaching resources. Among them is \testsql, a query tool giving the students automated feedback on SQL query exercises; but we do not use it to assess the students. Instead assessment is through a range of questions which test not only SQL writing skills, but also other aspects of the field, including questions on optimisation, physical modelling, PL/SQL, and indirect questions on SQL knowledge, such as processing order. The effectiveness of the approach is investigated through a survey of student attitudes', and assessment data. Our analysis shows, unsurprisingly, that the students' use of more resources correlates significantly with better results; but also that success at the different sub-topics tested is not at all well correlated, which shows that students can master some topics while remaining weak at others; and finally, that indirect SQL questions is best predictor of success at each of the other sub-topics. This last result confirms our choice to broaden the testing of SQL skills, and has implications for the use automated SQL assessment tools: we recommend that in automated testing for Database Systems, SQL writing tests be complemented with indirect questions on keyword use, parsing, or error recognition aimed at revealing broader abilities of learners

License plate localization based on statistical measures of license plate features

— License plate localization is considered as the most important part of license plate recognition system. The high accuracy rate of license plate recognition is depended on the ability of license plate detection. This paper presents a novel method for license plate localization bases on license plate features. This proposed method consists of two main processes. First, candidate regions extraction step, Sobel operator is applied to obtain vertical edges and then potential candidate regions are extracted by deploying mathematical morphology operations [5]. Last, license plate verification step, this step employs the standard deviation of license plate features to confirm license plate position. The experimental results show that the proposed method can achieve high quality license plate localization results with high accuracy rate of 98.26 %

Birth data accessibility via primary care health records to classify health status in a multi-ethnic population of children: an observational study

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Empirical Study of Car License Plates Recognition

The number of vehicles on the road has increased drastically in recent years. The license plate is an identity card for a vehicle. It can map to the owner and further information about vehicle. License plate information is useful to help traffic management systems. For example, traffic management systems can check for vehicles moving at speeds not permitted by law and can also be installed in parking areas to se-cure the entrance or exit way for vehicles. License plate recognition algorithms have been proposed by many researchers. License plate recognition requires license plate detection, segmentation, and charac-ters recognition. The algorithm detects the position of a license plate and extracts the characters. Various license plate recognition algorithms have been implemented, and each algorithm has its strengths and weaknesses. In this research, I implement three algorithms for detecting license plates, three algorithms for segmenting license plates, and two algorithms for recognizing license plate characters. I evaluate each of these algorithms on the same two datasets, one from Greece and one from Thailand. For detecting li-cense plates, the best result is obtained by a Haar cascade algorithm. After the best result of license plate detection is obtained, for the segmentation part a Laplacian based method has the highest accuracy. Last, the license plate recognition experiment shows that a neural network has better accuracy than other algo-rithm. I summarize and analyze the overall performance of each method for comparison

Background risk of breast cancer and the association between physical activity and mammographic density

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Interstitial lung disease : raising the index of suspicion in primary care

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Four patients with a history of acute exacerbations of COPD: implementing the CHEST/Canadian Thoracic Society guidelines for preventing exacerbations

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How to match the optimal currently available inhaler device to an individual child with asthma or recurrent wheeze

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The All-Data-Based Evolutionary Hypothesis of Ciliated Protists with a Revised Classification of the Phylum Ciliophora (Eukaryota, Alveolata)

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The file attached is the published version of the article

Stem cell differentiation increases membrane-actin adhesion regulating cell blebability, migration and mechanics

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/K. S. is funded by an EPSRC PhD studentship. S.T. is funded by an EU Marie Curie Intra European Fellowship (GENOMICDIFF)