1,720,955 research outputs found
Long-Term Nutrient Removal and Nutrient Mass Balance of a Free Water Surface Constructed Wetland Polishing Municipal Lagoon Effluent
No full textA large pilot-scale free water surface (FWS) constructed wetland polishing effluent from an annual (spring) discharge municipal lagoon was operated for ten years followed by eleven years of dormancy and then restarted with an increase in operating depth. No significant effect of system aging was observed on Biological Oxygen Demand (BOD), total phosphorus (TP), and soluble reactive phosphorus (SRP) removal efficiencies, although internal TP water column concentrations in the first wetland and pond cells increased with time due to resuspension of accumulated sediments. Nitrate and ammonium removal efficiencies were higher during the start-up period due to plant establishment, while organic nitrogen and nitrate removal efficiencies increased during the restart period, likely due to a combination of the increased operating depth and accumulated sediments. No seasonal temperature effect was observed for nitrate or BOD removal efficiency, however, TP removal efficiencies increased with increasing influent concentrations due to seasonal algae growth. TSS removal efficiency increased significantly during the restart period, most likely due to an increase in the operating depth. Phosphorus was found to be mostly stored in the soil, followed by sediment and plants, while nitrogen was found to be stored more in plants, followed by soil and sediment. The wetland system was shown to be effective at the long-term removal of organic matter (BOD5 < 10 mg/L) and TP (87% average removal efficiency), while TSS removal efficiency increased to 97% with an increase in operating depth from 25 to 50 cm
WEBOICE: voice enabled web browser
No full textThe goal of this project was to code and assemble a web browser with voice recognition abilities. The project aims to simplify the usage of a web browser. Existing web browsers are complicated to use and focus on feasibility but sometimes lack the user ease. Web browsers, i.e. Chrome, Firefox, and Safari come with voice recognition, but the web browser in this project extends user comfort and has additional features. In particular, this project creates a "Typing- free" experience for a web browser, so that the user is never required to type a web search address. The primary focus is for users with no hands or who have physical disabilities. This smart browser is equipped with natural language (English) recognition capabilities which extract the key commands from sentence. If user asks web browser "open new tab and search what is AI?", the browser would open a new tab and search "what is AI?" using the default search engine which is "google.com".WEBOICE is listening all the times and responds according to the user's command. If the user asks WEBOICE to "open Facebook in a new window," it will open a new window and then open Facebook. The browser is equipped with the traditional browser's functionalities such as forward, backward, stop navigation and the additional feature of motion recognition capabilities which will allow the user to have complete interactive environment. However, WEBOICE does have its limitations, it is not able to differentiate between words with very similar pronunciation i.e. "back/jack"; also it might take a while to execute depending on the speed of the connection with Google API
Vehicle traffic estimation using deep learning
No full textFor commuters, vehicular traffic is an important planning concern. People have access to the weather forecast and the current traffic situation, but there is no application available to estimate traffic congestion and flow in the near future. Similarly, traffic management authorities also seek information about future traffic for traffic management purposes. Thus, we design and develop a machine learning approach which can predict vehicular traffic density and flowrate up to two days in the future based on the weather, calendar and special events data.
First, Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) networks are utilized to predict the number of new vehicles and the total number of vehicles in images captured by a Nova Scotia Webcams (NS Webcams) video camera. The best models provide a Mean Absolute Percentage Error (MAPE) of 20.38% for the number of new vehicles and 18.56% for the total number of vehicles. These values are used to estimate traffic flowrate and density for hourly records over a three-month period.
The hourly traffic data is combined with observed and forecasted weather data, retrieved from the DarkSky.net website and special event data provided by the Port of Halifax to create a time series data. A Multiple Task Learning (MTL) - LSTM model is trained and tested using these data and a K-fold cross-validation approach. The Mean Absolute Error (MAE) and MAPE are used to evaluate the model performance. The MTL-LSTM model achieves a MAPE of 19.35% and 27.50% for flowrate and density using observed weather data, respectively. In the case of forecasted weather data, the MAPE for flowrate and density increases to 20.51% and 31.10%, respectively
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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