1,721,288 research outputs found
Feature Extraction, Pattern Recognition and Classification in X-ray Image Data
No full textExcellence of food products highly depends on the quality checks at different stages while preparation and processing at industry. With the evolution of technology, traditional methods are being put back and state of the art equipment taking the position. Being fast, efficient and automatic, computers and machines are potentially replacing the human deployment in the food industry. One of the early stages of food preparation is the ingredient evaluation on feeding belt. This is still carried out mostly by humans; however efforts have been made for the development of such system which is capable to inspect the ingredient quality in an automatic way. The research work involves developing and estimating such an arrangement which provide the quality information of ingredient without human deployment. X-ray imaging was employed for internal analysis of ingredients: pine, pistachio and hazelnuts. A captured x-ray image containing few non-overlapping ingredients was analyzed using image processing techniques to develop a method for automatic detection and extraction of independent ingredient. Individual ingredient image samples were further analyzed to calculate the strong features on the global as well as local level. A number of features including statistical, texture and moment invariant properties were extracted from each image sample and were organized in diverse combinations to be utilized further. Different databases have different percentage of representation for healthy and unhealthy nuts so correspondingly several classification techniques were exercised including logistic regression, artificial neural network, anomaly detection and support vector machines. In addition to accuracy, the percentage of correct recognition unhealthy ingredients was observed which is vital. Concluding fine classification accuracy was observed with comparatively better false positive rate than related studie
Sportivate: a case study of sports policy implementation and impact on the sustainability of community physical activity programmes
No full textWith trends pointing toward shortcomings in delivering London 2012 legacy promises, a review was administered on research and policy from 2005 onwards to ascertain how sports policy can impact the delivery of sustainable community sport and physical activity programmes. A case study design was adopted and secondary data was obtained from Sport England’s Year 4 of national Sportivate data. These results were compared with aspects of government policy via the theoretical concept lenses of sustainability and policy implementation. Secondary data from Sport England for Year 4 (2014–15) of their Sportivate programme displays a boom in participation leading up to the Olympic Games, but plateaus following London 2012. In line with requirements issued by government policy, completed participants primarily consist of younger children. While findings display a closing gender gap in participation, the same cannot be said of sustainability measures in place for the Sportivate programme. With the prevalence of external factors impeding sustainable sports participation, voluntary sports organisations are advised to capitalise on partnership approach methods for delivering sport and physical activity. As participation retention decreased in Year 4, the theoretical concept of sustainability offers calls for a change in culture, despite policy implementation perspectives highlighting the synthesis of both top-down and bottom-up approaches. A centralised system creates greater emphasis on the “professionalization” of voluntary sports organisations, which seems to steer deliverers toward short-term impact rather than long-term goals. Recommendations suggest expanding collaborative measures between organisations to help facilitate sustainable participation after a funded physical activity programme has completed. Further research is recommended to further examine factors that influence the sustainable delivery of community sports and physical activity
Using time proportionate intensity images with non-linear classifiers for hand gesture recognition
No full textGestures are spatiotemporal signals that contain valuable information. Humans can understand gestures with ease, but for computers or robots it is a challenging task involving thousands of computations per video frame. Current state of the art gesture recognition systems treat gestures as Markov Chains. Then the task of gesture recognition is to match the incoming video sequence to these Markov Chains. Each Markov State is modeled with spatial features such as hand location and temporal features like the motion vectors. The main problem with this approach is the high order of computational complexity. In this paper we propose a novel gesture recognition technique based on projecting the temporal axis information onto the spatial plane. Then this spatial intensity image is fed to a machine learning classifier (SVM in our case) for recognition. We show that the proposed algorithm achieves an accuracy that is comparable to the current state of the art approaches, but with a (much) reduced computational burde
Conserving Energy Through Neural Prediction of Sensed Data
No full textThe constraint of energy consumption is a serious problem in wireless sensor networks to which many solutions have been proposed in recent years. In one line of research, scholars suggest data driven approaches to help conserve energy by reducing the amount of required communication in the network. This paper is an attempt in this area and proposes that sensors be powered on intermittently. A neural network will then simulate sensors' data during their idle periods. The success of this method relies heavily on a high correlation between the points making a time series of sensed data. To demonstrate the effectiveness of the idea, we conduct a number of experiments. In doing so, we train a nonlinear autoregressive network against various datasets of sensed humidity and temperature in different environments. By testing on actual data, it is shown that the predictions by the device greatly obviates the need for sensed data during sensors' idle periods and saves over 65 percent of energ
The Folio: F. C. C. Magazine
No full textImtiaz Ahmad Khan-Editorial. pp. 1; Rice, C.H.-Speech-Books, Balls and Bells. pp. 2-4; Imtiaz Ahmad Khan-Article-Life and Art. pp. 4-6; Khan, M. Anwarullah-The Introduction week. pp. 6-7; Sports-Basket Ball. pp. 8; Moinuddin Ahmad-Story-A Night Among Pine Trees. pp. 9-13; Poetry-A Psalm of Wife. pp. 14; Ikramullah, M.-My First Impressions of the Forman Christian College. pp. 15-16; K. Habib Ullah-Divorce Your Parents. pp. 16-17; Mohd. Nasim-ur-Riaz-That was my First. pp. 17-19; Mohd. Naseer Butt-The Messenger of Hope and Light. pp. 19-20; Khan, T.F.S.-New Species. pp. 21; Jivanandham, N.J.-Words, Words, Words. pp. 21-22; Manry, J.C.-Article-Christmas in Modern American Poetry. pp. 22-24; Khan, Manawara Shadi-C's. pp. 25; The Folio [Urdu] 32 p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
No full text“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
No full textWe 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
No full textWe 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
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