1,720,962 research outputs found
An effective crypto-biometric system for secure payment systems
No full textThis thesis was scanned from the print manuscript for digital preservation and is copyright the author.
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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
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
A Heterogeaneous Dataset–Driven Ensemble Learning Framework for Malicious URL Detection
Full text linkModern cyberattacks are increasingly associated with phishing campaign, malware distribution, and website defacement, which are often delivered through malicious Uniform Resource Locator (URL) originating from diverse source. This paper examine malicious URL detection using an ensemble learning framework evaluated on large scale heterogeneous dataset composed of URL aggregated from multiple public threat intelligence source. The dataset include benign, phishing, malware, and defacement URL, thereby reflecting real world variability in attack pattern and data distribution. Three ensemble based classifier, namely Decision Tree (DT), Random Forest (RF), and Gradient Boosting (GB), are evaluated with respect to detection accuracy and computational efficiency. In addition to classification performance, this study present a detailed analysis of training and detection time in order to identify most suitable model for practical deployment. Experimental results indicate that the DT model achieves a training time of 4.14 seconds with macro and weighted accuracies of 94.11% and 91.71%, respectively, and a per category detection time of 0.2162 seconds. The RF model attains macro and weighted accuracies of 93.64% and 90.94%, with training and detection times of 9.73 seconds and 0.2420 seconds, respectively. Although the GB model exhibits the longest training time of 45.38 seconds, it achieves the fastest per category detection time of 0.2151 seconds. Despite its comparatively lower overall accuracy of 92.48% for macro averaging and 89.42s% for weighted averaging, the rapid inference capability of GB makes it a strong candidate for real time malicious URL detection in heterogeneous cybersecurity environments
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
Confidence in iris biometric matching
No full textWith the proliferation of mobile devices and the availability of network bandwidth, more services are offered online, it becomes imperative that users to be authenticated before providing the services to them. Most of the current applications use either a combination of username and password, or one time token, or passcode to verify the identity of a user. With heavy emphasis on authentication to access various services and applications, using individual biometrics as a method of verification is gaining popularity due their unique nature as well as their unforgeability. Biometric authentication is successfully employed in a number of different applications, such as frequent flyer programs, criminals identification, border security and airport passenger screening, to name a few.
In all of the above applications, the environment in which the biometric is captured is controlled, hence the quality of the captured image is guaranteed. However, utilization of biometric authentication by a casual user poses additional problems. The primary ones lie in (i) the devices that are necessary to capture a user's biometric and transmit to the application server; (ii) the variability in the capturing environments which introduces unpredictable errors to the captured image; and (iii) the impracticality to achieve zero error rate unlike the techniques that use password or PINs-based authentication. These issues are preventing the deployment of biometrics as means of authentication and identification.
With the popularity of smartphones with their built-in cameras, it is now possible for users to capture their biometric image and send it to the applications to be authenticated. However, errors in the capturing environments needs to be identified and corrected before the matching process. Unfortunately, one may not know in advance the kind of errors that will occur, thus any pre-processing strategies cannot be applied to remove all of those unknown errors. On the contrary, using only error-free partial information of a biometric will reduce the useful features that can be used in the matching process for identification.
This thesis addresses the methods to overcome the above limitations by proposing post-processing techniques that can improve the confidence in biometric matching. This is achieved by incorporating strategies that can compensate the errors that are being introduced due to variability in the capturing environments, proposing a metric of similarity that can confidently decide whether a query biometric belongs to the genuine person or not, and using as much information as possible from the captured biometric.
The major contributions of the thesis are:
First, the errors that are being introduced in the capturing environments is modelled as a noisy communication channel, then uses the principle of error correcting codes to transform the query biometric so as to be closer to the user's registered biometric.
Second, in order to improve the confidence level in the matching and identification process, a modified similarity metric in the form of the length of the common substring is used. This metric aims to give maximum and minimum similarity scores for the genuine user and impostor matching respectively.
Third, a non-uniform matching strategy to further improve the confidence in the matching process is presented. In reality, certain users tend to produce high degree of errors and create overlap. Hence, we identify these users and design the error correcting codes to tackle these errors rather than removing the biometrics of such users.
Finally, the performance of the proposed techniques is evaluated quantitatively by running experiments on a number of iris datasets and the results are then compared with other known techniques
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
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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