1,721,009 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Delivering and evaluating on-line degree programs in culinary arts/management: perceptions of educators and industry practitioners
No full textThis quantitative research examines the perceptions of culinary arts/management educators and culinary industry practitioners on the future of online culinary arts education. Specifically pertaining to the recommended procedures by educators and chefs to judge and critique the quality of food products in terms sensory modalities, and what the key quality indicators for online culinary arts programs may be. While much of the current literature concerning perceptions of online culinary arts education relates to students and faculty, little focus is on the design of effective online culinary arts curricula. Therefore, this study informs culinary arts educators who seek to understand how to teach practical culinary arts skills effectively and appropriately through online media.
An electronic survey was sent via email to 1,250 members of the American Culinary Federation (ACF) and the International Council of Hotel, Restaurant and Institutional Educators (ICHRIE). Undeliverable emails resulted in 1,204 potential participants. Participation was 18.8% (n = 226).
This study found significant differences between the two groups on the importance ratings of three of the professional courses and four of the general educational courses. Significant differences between the two groups were also found on the measures of importance on the factors of quality for an online culinary arts program. The results also demonstrated that there are no significant differences between culinary arts/management educators and industry practitioners on the recommended procedures to judge and critique the quality of the food products in terms of sensory modalities.
The findings of this study suggest that online culinary arts programs develop a curriculum that meets the essential demands for future culinarians. The design of such a program should incorporate more hands-on rather than theoretical content. Furthermore, curriculum should be designed to take into account gaps in knowledge of culinary arts students. (Author abstract)Ryll, S. (2017). Delivering and evaluating on-line degree programs in culinary arts/management: perceptions of educators and industry practitioners. Retrieved from http://academicarchive.snhu.eduEducational LeadershipSchool of Educatio
Automated Inspection of Railway Track Faults Based on Image Datasets
No full textManual inspections of railway tracks continue to have an impact on the number of accidents they cause each year. The lack of accuracy of the human factor continues to cause catastrophes in the railway sector. In recent years, thanks to advances in technology, artificial intelligence is being applied to various sectors to improve and streamline inspection and maintenance processes. Focusing on the railway sector, this paper analyses three of the most innovative object detection models: YOLOv5, Faster RCNN and EfficientDet. In the literature review there are several studies that have applied machine learning in the sector, but few studies have studied defect detection using object detection tools. Furthermore, there is a lack of studies which compare different models using the same source of information, the same dataset. This paper compares the 3 models by testing a dataset with 31 images containing 3 different railway track elements. This dataset contains both faulty and non-faulty images to obtain the most detailed results possible, as six different classes have been differentiated in the training of the programmes: 3 faulty and 3 non-faulty. The results obtained highlight the good precision (equivalent to 1) of the 3 models in detecting non- defective elements. On the other hand, the recall obtained for defective elements is not so high, led by Faster RCNN with a value of 0.9375, followed by EfficientDet with 0.8125 and finally YOLOv5 with a value of 0.6875. It should be noted that the lack of images of some of the defective elements has led to this low recall for some of the classes.Outgoin
Automated Inspection of Railway Track Faults Based on Image Datasets
No full textManual inspections of railway tracks continue to have an impact on the number of accidents they cause each year. The lack of accuracy of the human factor continues to cause catastrophes in the railway sector. In recent years, thanks to advances in technology, artificial intelligence is being applied to various sectors to improve and streamline inspection and maintenance processes. Focusing on the railway sector, this paper analyses three of the most innovative object detection models: YOLOv5, Faster RCNN and EfficientDet. In the literature review there are several studies that have applied machine learning in the sector, but few studies have studied defect detection using object detection tools. Furthermore, there is a lack of studies which compare different models using the same source of information, the same dataset. This paper compares the 3 models by testing a dataset with 31 images containing 3 different railway track elements. This dataset contains both faulty and non-faulty images to obtain the most detailed results possible, as six different classes have been differentiated in the training of the programmes: 3 faulty and 3 non-faulty. The results obtained highlight the good precision (equivalent to 1) of the 3 models in detecting non- defective elements. On the other hand, the recall obtained for defective elements is not so high, led by Faster RCNN with a value of 0.9375, followed by EfficientDet with 0.8125 and finally YOLOv5 with a value of 0.6875. It should be noted that the lack of images of some of the defective elements has led to this low recall for some of the classes.Outgoin
Variations on the Author
Full text link“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
Panditravikantshastri
No full textPandit Ravi Kant Shastri is the popular name for astrology. He has done a depth study and research on Vedic astrology, numerology, palmistry, gem therapy, mantra and Vastu Shastra. He can solve your all problems using astrology. He is known as world famous astrologer in India. Call us at +91-9878895
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Wind Turbine Accidents : A Data Mining Study
No full textTrabajo de Fin de Grado en Ingeniería de Software, Facultad de Informática UCM, Departamento de de Arquitectura de Computadores y Automática, Curso 2021/2022.En la lucha contra el cambio climático la energía eólica está jugando un papel crucial en la sustitución de energías fósiles. Como aún se trata de una tecnología en fase de expansión y desarrollo los accidentes son eventos que suceden de manera recurrente y en este trabajo nos planteamos realizar un análisis de estos. Este trabajo presenta los resultados obtenidos tras el estudio de 273 accidentes en aerogeneradores por todo el mundo.
Para ello procederemos a un análisis estadístico con la finalidad de ver la cuales son los elementos más relevantes a tener en cuenta en el accidente y como se relacionan estos con la posibilidad de que el accidente resulte en muertes o lesiones. Para este cometido emplearemos diversas herramientas estadísticas para abordar el análisis desde diversos enfoques. También procederemos a emplear métodos de selección y ranking de atributos, así como un análisis exploratorio de datos. La finalidad de estos procesos es ampliar el análisis a un estudio no solo de la relación entre los atributos, sino también a un estudio de los valores de esos atributos.
Finalmente, crearemos modelos predictivos utilizando varios algoritmos de clasificación para, en futuros casos, poder prever y evitar accidentes basándonos en los atributos estudiados. Los algoritmos empleados son de dos tipos, de aprendizaje supervisado como puede ser el algoritmo de ’random forest’ o ’k-nearest neighbor’ y algoritmos de aprendizaje no supervisados como pueden los algoritmos de ’k-means’ o ’affinity propagation’. En este segundo grupo también se estudiarán un par de arquitecturas de redes neuronales.In the fight against climate change, wind energy is playing a crucial role in the substitution of fossil fuels. As it is still a technology in a phase of expansion and development, accidents are recurrent events and in this paper we propose to analyze them. This paper presents the results obtained after the study of 273 wind turbine accidents around the world.
We will proceed to a statistical analysis in order to see which are the most relevant elements to take into account in the accident and how they are related to the possibility of the accident resulting in deaths or injuries. For this purpose we will use various statistical tools to approach the analysis from different approaches.
We will also perform attribute selection and ranking procedures, as well as exploratory data analysis. The purpose of these processes is to extend the analysis to a study not only of the relationship between attributes, but also to a study of the values of those attributes.
Finally, we will create predictive models using various classification algorithms in order to, in future cases, be able to predict and avoid accidents based on the attributes studied. The algorithms used are of two types, supervised learning algorithms such as the ’random forest’ or ’k-nearest neighbor’ algorithm and unsupervised learning algorithms such as the ’k-means’ or ’affinity propagation’ algorithms. In this second group, a couple of neural network architectures will also be studied.Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Full text linkWe 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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