sábado, 21 de abril de 2018

Big Data Analytics: an Editor Q+A - On Biology

Big Data Analytics: an Editor Q+A - On Biology

Joseph Hasan

Journal Development Editor at BioMed Central


Big Data Analytics: an Editor Q+A

Big Data Analytics launches today as a new journal aiming to provide a platform for the dissemination of research, current practices and future trends in the emerging discipline of big data analytics. We asked the Editor-in-Chief, Amir Hussain, more about the journal.
AmirHussainAmir Hussain obtained his BEng and PhD from the University of Strathclyde in Glasgow. Following a Research Fellowship at the University of Paisley and a research Lectureship at the University of Dundee, he joined the University of Stirling in 2000, where he is currently Professor of Computing Science and founding Director of the Cognitive Big Data Informatics (CogBID) Laboratory.

Big Data Analytics | Home page

Big Data Analytics | Home page

Chinese text-line detection from web videos with fully convolutional networks. Yang et al.

Big Data Analytics





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Chinese text-line detection from web videos with fully convolutional networks | Big Data Analytics | Full Text

Chinese text-line detection from web videos with fully convolutional networks | Big Data Analytics | Full Text



Chinese text-line detection from web videos with fully convolutional networks

  • Chun Yang,
  • Wei-Yi Pei,
  • Long-Huang Wu and
  • Xu-Cheng YinEmail author
Contributed equally
Big Data Analytics20183:2
Received: 8 December 2017
Accepted: 27 December 2017
Published: 5 January 2018

Abstract

Background

In recent years, video becomes the dominant resource of information on the Web, where the text within video usually carries significant semantic
information. Video text extraction and recognition plays an essential role in web multimedia understanding and retrieval for big visual data analytics and applications. To deal with challenging backgrounds and embedding noises, most conventional approaches usually tend to design sophisticated pre-processing and post-progressing steps before and after text detection. In this paper, we present a simple yet powerful pipeline that directly and uniformly detects Chinese text lines for embedded captions from web videos.

Results

In this Chinese text-line detection system, a fully convolutional network with local context is adopted to localize via an end-to-end learning way. The produced caption predictions are with the word level that could be directly fed into the character classifier. Text-line construction is then performed by heuristic strategies. A variety of experiments are conducted on several real-world web video datasets and demonstrated the effectiveness and efficiency of our proposed method.

Conclusion

The proposed system can directly detect the English word and Chinese characters in the caption text-lines without word or character segmentation with the high performance on real-world web video datasets.

Keywords

Video text detectionText segmentationFully convolutional networksEmbedded captionsWeb videos

Sleepiness while driving and shiftwork patterns among Korean bus drivers | Annals of Occupational and Environmental Medicine | Full Text

Sleepiness while driving and shiftwork patterns among Korean bus drivers | Annals of Occupational and Environmental Medicine | Full Text



Sleepiness while driving and shiftwork patterns among Korean bus drivers

  • Seyoung Lee,
  • Hyoung-Ryoul KimEmail author,
  • Junsu Byun and
  • Taewon Jang
Annals of Occupational and Environmental MedicineThe official journal of the Korean Society of Occupational and Environmental Medicine201729:48
Received: 11 April 2017
Accepted: 21 September 2017
Published: 9 October 2017

Abstract

Background

Sleepiness while driving has been regarded as a major cause of death due to traffic accidents. We compared the degree of sleepiness across five different working time periods (first, morning, post-lunch, afternoon, and last) among Korean bus drivers with different shift types (Daily two shift/Alternating day shift).

Method

We interviewed 332 bus drivers with two shift types (Daily two shift, 128; Alternating day shift, 204). The questionnaire included demographic information (age, alcohol consumption and history of disease), a sleep disorder diagnosed by a doctor, job duration, the number of workdays in the past month, average working hours per workday and week, sleepiness while driving (Karolinska Sleepiness Scale), and sleeping time for both workdays and off-days. We conducted log-binomial regression analyses and produced prevalence ratios (PRs) of severe sleepiness (KSS ≥ 7) while driving with 95% confidence intervals (95% CI) to identify the difference in sleepiness for five working times between both groups.

Results

For the first and morning periods, there were no statistically significant differences in the KSS scores between the two groups. However, from lunch to last driving, drivers with Alternating day shift had a much larger proportion of severe sleepiness than those on Daily two shift. Thirteen (10.2%), 2 (1.6%) and 7 (5.5%) Daily two shift workers reported severe sleepiness in the post-lunch, afternoon and last periods. In contrast, 81 (39.7%), 63 (30.9%) and 64 (31.4%) of Alternating day shift drivers experienced severe sleepiness during the post-lunch, afternoon and last driving periods (p < 0.0001). According to the log-binomial regression analyses, Alternating day shift was associated with severe sleepiness from lunch to last driving. After adjusting for job duration, alcohol consumption and sleeping time on workdays, the PRs were 3.97 (95% CI: 2.29–6.90) post-lunch, 18.26 (95% CI: 4.51–73.89) in the afternoon and 5.71 (95% CI: 2.51–12.99) for the last driving period.

Conclusion

We found that Alternating day shift bus drivers suffered from more sleepiness while driving from lunch to last driving than Daily two shift bus drivers. This difference may be because Alternating day shift drivers had more irregular work schedules and longer working hours per day and week.

Keywords

SleepinessShiftworkBus driversKarolinska sleepiness scaleTraffic accidentsOccupational drivers

Annals of Occupational and Environmental Medicine | Home page

Annals of Occupational and Environmental Medicine | Home page

Annals of Occupational and Environmental Medicine

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Articles

Utilization of gabapentin by people in treatment for substance use disorders in Belgium (2011–2014): a cross-sectional study | Archives of Public Health | Full Text

Utilization of gabapentin by people in treatment for substance use disorders in Belgium (2011–2014): a cross-sectional study | Archives of Public Health | Full Text



Utilization of gabapentin by people in treatment for substance use disorders in Belgium (2011–2014): a cross-sectional study

Archives of Public HealthThe official journal of the Belgian Public Health Association201876:17
Received: 12 September 2017
Accepted: 12 January 2018
Published: 19 March 2018

Abstract

Background

Although gabapentin has been licensed in the European Union only for neuropathic pain and epilepsy for patients who have partial seizures, it has also been prescribed in treatment for substance use disorders. Many studies report the potential risk of abuse of gabapentin by people with substance use disorders. The objective of this paper is to determine if people who have been in treatment for substance use disorders bought gabapentin in a time span that could indicate consumption at a dose that exceeded the maximum approved dose of 3600 mg/day.

Methods

This analysis is the result of an observational cross-sectional descriptive study with matching. Two datasets were used and linked at individual level. Subjects were selected based on their first registration in the database of the Treatment Demand Indicator (TDI) between 2011 and 2014, without any exclusion criteria concerning nationality or age. Through linkage with the database of the InterMutualistic Agency (IMA) information on health service use and medication use was determined. In addition, each subject was matched on age, sex and place of residence to four comparators from the general population who were not in specialized treatment. The prevalence of gabapentin purchases in the period between 2008 and 2014 for both populations were compared. Quantification of the amount of gabapentin between two consecutive purchases was used as a proxy for potential abuse.

Results

Out of 30,905 patients in treatment for substance use disorders 2.7% had bought at least once gabapentin in a public pharmacy or received it from a hospital pharmacy, compared to 0.7% in the comparison group (n = 122,142). In both populations, more than half of the patients bought only once or twice gabapentin and about 10.0% bought at least once gabapentin in a time span that could indicate potential abuse. A limitation of the study is that it is only based on reimbursed medication without clinical information.

Conclusion

Through the linkage of the TDI-database and the database of the Belgian health insurance companies, no evidence was found for regular abuse of prescribed gabapentin in Belgium by people in treatment for substance use disorders.

Keywords

Substance use disordersPharmacoepidemiological dataHealth servicesBelgiumGabapentin

Archives of Public Health | Home page

Archives of Public Health | Home page

Archives of Public Health



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