1,720,954 research outputs found
Building and Safety Department Android Mobile Application
Full text linkResearch has found that Americans spend 4.5 hours watching television, 1.5 hours listening to the radio, about half an hour reading print and spend a whooping five plus hours per day in digital media (online, mobile, other). Out of these five hours, two hours and twenty minutes are spent on a mobile device (phone or tablet), which is a massive increase of about 575 percent from the twenty-four minutes that was reported in 2010. Flurry, an analytic app company, released data about their tracking of more than 300,000 apps in 2013, and they found the average time spent per day on mobile devices is two hours and thirty-eight minutes. They further found that 80 percent of the time is spent on apps and only 20 percent on the actual browser itself. Based off these findings, it can be concluded that Americans are spending more time online than on any other media, that digital time is on mobile devices, and that mobile time is spent mostly on apps (Samson, 2015).
Businesses are catching on to the fact that people are spending more time on their mobile devices doing activities that they once did with computers such as shopping, maintaining their calendars, and playing games. They are creating apps to accommodate these activities on mobile devices. In order to keep current customers and attract new ones businesses realize that portability is the future in how a business interacts with customers. Companies realize that to have an effective mobile presence requires more than just creating a website that is mobile friendly. So, small to medium-sized companies are creating their own dedicated apps to try an even the playing field against the big boys like Walmart and Starbucks
Data Poisoning: A New Threat to Artificial Intelligence
Full text linkArtificial Intelligence (AI) adoption is rapidly being deployed in a number of fields, from banking and finance to healthcare, robotics, transportation, military, e-commerce and social networks. Grand View Research estimates that the global AI market was worth 93.5 billion in 2021 and that it will increase at a compound annual growth rate (CAGR) of 38.1% from 2022 to 2030. According to a 2020 MIT Sloan Management survey, 87% of multinational corporations believe that AI technology will provide a competitive edge. Artificial Intelligence relies heavily on datasets to train its models. The more data, the better it learns and predicts. However, the downside to AI is data, data that can be manipulated or poisoned. A new type of threat is emerging, and that threat is data poisoning. Data Poisoning is challenging and time consuming to spot and when it is discovered, the damage is already extensive. Unlike traditional attack that is caused by errors found in code, this new threat is attacking the AI training data used in its algorithm. Data is now being weaponized. It requires minimal effort but can cause substantial damages. It only takes 1-3% of data to be poisoned to severely diminish an AI’s ability to produce accurate predictions
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
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
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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