1,721,001 research outputs found
Archimedes optimization algorithm for DNA motif discovery
No full textThis research work introduces a novel metaheuristic method named Archimedes Optimization Algorithm (AOA) for solving biomedical problems. Two case studies on Motif Discovery (MD) and Optic Disc (OD) are also analysed. AOA is based on the concept of Archimedes’ principle in physics. It assumes that a buoyant force exerted upwards on an object in a fluid is equal to the weight of the displaced fluid. In our case studies, the motif part encapsulates the motifs’ essential features in DNA sequences, the suggested solution emulates the huddling behaviour of Archimedes’ law while incorporating the motif characteristics to detect the desired motif. The effectiveness of the AOA optimizer is tested using both real & synthetic datasets of motif discovery, and optic disc. Based on the results comparison with various common algorithms (including DREME, PMbPSO, MEME, MACS, and XXmotif), it can be confirmed that AOA can efficiently solve hard motif discovery problems. In addition, efficiency and flexibility of the proposed AOA are further validated on a biomedical problem, Optic Disc (OD) extraction from 369 retinal fundus images of four publicly available datasets. Results confirm the robustness of AOA and demonstrate its value as a OD finding tool with a 100% success rate for images from well-known datasets like DRIVE, and DRIONS-DB datasets, while achieving 98.5% and 98.8% for DIARETDB0 and DIARETDB1 datasets respectively; which is surpassing the state-of-the-art methods
Artificial Neural Networks for Stock Market Prediction: A Comprehensive Review
No full textThe forecasting of stock market is known to be a remarkable effort and a great deal of attention, as forecasting stock prices can effectively steer to desirable profits by making sound investment choices. It is a challenging job due to highly non-linear, blaring, and unpredictable data. Currently, a variety of useful methods have been developed to predict stock prices. This chapter provides a thorough analysis of 48 research papers proposing artificial neural networks-based stock price prediction methodologies. Here, the reported research is categorized on the basis of various prediction techniques. Moreover, the studies are evaluated based on databases used, performance assessment indicators, and prediction targets. The collective evidence suggests that stock market prediction involves numerous factors that need to be efficiently and precisely addressed
A Review of Metaheuristic Optimization Algorithms in Wireless Sensor Networks
No full textThe proliferation of wireless sensor network (WSNs) applications span different domains of life, including medicine, engineering, industry, agriculture, and military. A notable part of research pertaining to WSNs relates to metaheuristic algorithms, implemented to address difficulties in the deployment of these networks. Due to robust and cost effective optimization ability, these algorithms efficiently optimize sensor locations for maximum coverage and extended energy consumption. This chapter presents the definitions of metaheuristic intelligence, wireless sensor network, and their respective types. Also, a wide range of scientific research works that include improving the performance of wireless sensor networks in terms of deployment, localization, and energy using optimization algorithms. Finally, the evaluation criteria for deployment and localization in wireless sensor networks are introduced
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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