"Alexa, Can I Trust You?" Chung, Hyunji; Iorga, Michaela; Voas, Jeffrey ...
Computer,
09/2017, Letnik:
50, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Several recent incidents highlight significant security and privacy risks associated with intelligent virtual assistants (IVAs). Better diagnostic testing of IVA ecosystems can reveal such ...vulnerabilities and lead to more trustworthy systems.
Motor induksi 1 phasa merupakan motor listrik arus bolak balik yang bekerja berdasarkan induksi medan magnet dari kumparan ratornya. Sistem ini berfungsi untuk memonitoring dan kontrol motor ...menggunankan Dimmer, Sensor suhu, RPM (Revolution per minute), dan LCD yang diletakan pada panel. Selain untuk sistem kontrol alat ini juga akan membuat sistem proteksinya agar komponen listrik dan motor tidak terjadi kerusakan. Tujuan dari penelitian ini adalah untuk memberikan kemudahan untuk mengoperasikan suatu peralatan dan memanfaatkan suatu fitur Wifi yang terdapat di smartphone. Sehingga dapat dikendalikan dari jarak jauh. Metode pada penelitian ini menggunakan metode SDLC (System Development Life Cycle) waterfall dengan Langkah awal analisis, desain, pengembangan, pengetesan, dan perbaikan. Hasil penelitian berhasil dimana perintah yang diberikan pada Google Assistant sesuai dengan output pada Relay, karena pada perintah yang telah dibuat pada IFTTT (If This, Then That) sebelumnya telah terkoneksikan dengan feed yang ada pada Adafruit IO dan untuk jarak maksimal terbaik koneksi wifi antara 0-15 m. Jika Google Assistant tidak mengenali perintah yang dibuat dan data yang terkoneksikan dengan IFTTT maka Google Assistant akan merespon dengan output suara bahwa perintah tidak dapat diproses dan untuk hasil monitoring terhadap sensor RPM tingkat akurasinya mencapai 98,95% dan Sensor Suhu rata-rata 97,1%.
•A financial expert system for predicting the monthly stock price.•“Knowledge base” captures the impact of traditional and online sources.•The “engine” uses four ensemble machine learning ...methods.•The error for most ensembles considered is < 1%.•The system is hosted online and freely available.
With the ubiquity of the Internet, platforms such as: Google, Wikipedia and the like can provide insights pertaining to firms’ financial performance as well as capture the collective interest of traders through search trends, number of web page visitors and/or financial news sentiment. Information emanating from these platforms can significantly affect, or be affected by, changes in the stock market. The overarching goal of this paper is to develop a financial expert system that incorporates these features to predict short term stock prices. Our expert system is comprised of two main modules: a knowledge base and an artificial intelligence (AI) platform. The “knowledge base” for our expert system captures: (a) historical stock prices; (b) several well-known technical indicators; (c) counts and sentiment scores of published news articles for a given stock; (d) trends in Google searches for the given stock ticker; and (e) number of unique visitors for pertinent Wikipedia pages. Once the data is collected, we use a structured approach for data preparation. Then, the AI platform trains four machine learning ensemble methods: (a) a neural network regression ensemble; (b) a support vector regression ensemble; (c) a boosted regression tree; and (d) a random forest regression. In the cross-validation phase, the AI platform picks the “best” ensemble for a given stock. To evaluate the efficacy of our expert system, we first present a case study based on the Citi Group stock ($C) with data collected from 01/01/2013 - 12/31/2016. We show the expert system can predict the 1-day ahead $C stock price with a mean absolute percent error (MAPE) ≤ 1.50% and the 1–10 day ahead with a MAPE ≤ 1.89%, which is better than the reported results in the literature. We show that the use of features extracted from online sources does not substitute the traditional financial metrics, but rather supplements them to improve upon the prediction performance of machine learning based methods. To highlight the utility and generalizability of our expert system, we predict the 1-day ahead price of 19 additional stocks from different industries, volatilities and growth patterns. We report an overall mean for the MAPE statistic of 1.07% across our five different machine learning models, including a MAPE of under 0.75% for 18 of the 19 stocks for the best ensemble (boosted regression tree).
Background
Scabies, a contagious skin infestation caused by Sarcoptes scabiei, is a significant public health concern 1. Traditional surveillance methods for scabies suffer from time lag and ...incomplete data, hindering early detection and response 5. The widespread use of the internet and search engines, such as GoogleTM, offer new opportunities for alternative surveillance approaches.
Objective
This study aimed to explore the association between scabies search volumes on Google TrendsTM (GTs) and scabies incidence at the state level across the United States.
Methods
GTs data for each U.S. state and scabies incidence from 2011 to 2019 were analyzed for summary statistics and association.
Results
The mean Spearman correlation coefficient for the period of 2011-2019 indicated a strong positive correlation between GTs RSVs for “scabies” and the incidence of scabies in the United States. Using an unpaired t-test, this correlation was found to be statistically significant.
Conclusions
In resource-scarce environments where access to care is a common barrier, healthcare providers and departments can leverage this information to effectively target populations and employ resources for scabies prevention and treatment. Analyzing search engine term patterns can enhance our understanding of people's behavior when they suspect a scabies infestation.
Digital platforms have become central to interaction and participation in contemporary societies. New forms of 'platformized education' are rapidly proliferating across education systems, bringing ...logics of datafication, automation, surveillance, and interoperability into digitally mediated pedagogies. This article presents a conceptual framework and an original analysis of Google Classroom as an infrastructure for pedagogy. Its aim is to establish how Google configures new forms of pedagogic participation according to platform logics, concentrating on the cross-platform interoperability made possible by application programming interfaces (APIs). The analysis focuses on three components of the Google Classroom infrastructure and its configuration of pedagogic dynamics: Google as platform proprietor, setting the 'rules' of participation; the API which permits third-party integrations and data interoperability, thereby introducing automation and surveillance into pedagogic practices; and the emergence of new 'divisions of labour', as the working practices of school system administrators, teachers and guardians are shaped by the integrated infrastructure, while automated AI processes undertake the 'reverse pedagogy' of learning insights from the extraction of digital data. The article concludes with critical legal and practical ramifications of platform operators such as Google participating in education.
Topical onychomycosis therapy is commonly prescribed due to its tolerability and low incidence of side effects. There are limited data on adverse events associated with the newer topical ...onychomycosis drugs. The objectives of this study is to classify the most common adverse reactions associated with ciclopirox 8% solution, efinaconazole 10% solution, and tavaborole 5% solution. The United States Food and Drug Administration Adverse Event Reporting (FAERS) database was analyzed for the most common adverse reactions associated with ciclopirox 8% solution, efinaconazole 10% solution, and tavaborole 5% solution. Google Trends was used to examine public interest in these drugs and these data were compared with yearly adverse events in the FAERS database. The most common adverse reactions associated with ciclopirox 8% solution, efinaconazole 10% solution, and tavaborole 5% solution were drug ineffectiveness. Application site erythema and nail discoloration were reported with all three medications. Increased Google searches for efinaconazole and tavaborole were associated with increased in reporting of adverse events to the FDA. Topical antifungals are safe alternatives for patients who have contraindications to oral medications. For improved efficacy, physicians should confirm the diagnosis of onychomycosis and choose appropriate candidates before starting topical therapy. Patients should be given clear instructions on drug usage and counseled about the more common side effects, including application site reactions and nail discoloration.
In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and ...produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24million pages is available at http://google.stanford.edu/
To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from 3years ago. This paper provides an in-depth description of our large-scale web search engine – the first such detailed public description we know of to date.
Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections, where anyone can publish anything they want.
The calculation of modified green view index and the discrepancy of spatial distribution of modified green view index and vegetation cover map. The sizes of the solid dots represent the magnitudes of ...green view index values.
•Google Street View was used for assessment of street-level urban greenery.•Modified green view index was proposed and compared with vegetation coverage to assess the spatial distribution street-level urban greenery.•Google Street View proved to have great potential for future urban environmental planning.
We explored Google Street View (GSV) as a street-level, urban greenery assessment tool. Street-level greenery has long played a critical role in the visual quality of urban landscapes. This living landscape element can and should be assessed for the quality of visual impact with the GSV information, and the assessed street-level greenery information could be incorporated into urban landscape planning and management. Information on street-level views of urban greenery assessment, however, is rare or nonexistent. Planners and managers’ ability to plan and manage urban landscapes effectively and efficiently is, therefore, limited. GSV is one tool that might provide street-level, profile views of urban landscape and greenery, yet no research on GSV for urban planning seems available in literature. We modified an existing Green View Index (GVI) formula and conducted a case study assessment of street greenery using GSV images in the area of East Village, Manhattan District, New York City. We found that GSV to be well suited for assessing street-level greenery. We suggest further that the modified GVI may be a relatively objective measurement of street-level greenery, and that GSV in combination with GVI may be well suited in guiding urban landscape planning and management.
Coastal wetlands, composed of coastal vegetation and non-vegetated tidal flats, play critical roles in biodiversity conservation, food production, and the global economy. Coastal wetlands in China ...are changing quickly due to land reclamation, aquaculture, industrialization, and urbanization. However, accurate and updated maps of coastal wetlands (including vegetation and tidal flats) in China are unavailable, and the detailed spatial distribution of coastal wetlands is unknown. Here, we developed a new pixel- and phenology-based algorithm to identify and map coastal wetlands in China for 2018 using time series Landsat imagery (2798 ETM+/OLI images) and the Google Earth Engine (GEE). The resultant map had a very high overall accuracy (98%). There were 7474.6 km2 of coastal wetlands in China in 2018, which included 5379.8 km2 of tidal flats, 1856.4 km2 of deciduous wetlands, and 238.3 km2 of evergreen wetlands. Jiangsu Province had the largest area of coastal wetlands in China, followed by Shandong, Fujian, and Zhejiang Provinces. Our study demonstrates the high potential of time series Landsat images, pixel- and phenology-based algorithm, and GEE for mapping coastal wetlands at large scales. The resultant coastal wetland maps at 30-m spatial resolution serve as the most current dataset for sustainable management, ecological assessments, and conservation of coastal wetlands in China.
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