Deep convolutional artificial neural networks (ANNs) are the leading class of candidate models of the mechanisms of visual processing in the primate ventral stream. While initially inspired by brain anatomy, over the ...
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A majority of electricity generation in the US is produced by thermoelectric power plants which require a constant supply of water for cooling. Many of these plants eject large quantities of hot water that was used fo...
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This paper presents a method to leverage mobile interaction design knowledge for low-literacy, moving from falsifiable hypotheses (claims) to actionable solutions (patterns). In prior work, claims and patterns have be...
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ISBN:
(纸本)9781450346498
This paper presents a method to leverage mobile interaction design knowledge for low-literacy, moving from falsifiable hypotheses (claims) to actionable solutions (patterns). In prior work, claims and patterns have been used separately for different application areas and in different contexts. This research asserts that the transition from claims to patterns will enhance the design value, leveraging claims for uncertain situations and inexplicit user behavior and patterns for proven solutions for recurrent problems. This paper examines how these two structures can be combined in a claims-to-patterns approach to leverage mobile interaction design for low-literacy. To demonstrate this method, an example that highlights how claims evolve into patterns through research and design is discussed.
作者：
Abhishek KumarR. DhanuskodiR. KaliappanK. NandakumarAbhishek Kumar teaches design philosophies at Anant National University
Ahmedabad. He earned his Ph.D in Management from Pondicherry University. He is an Economics graduate from Calcutta University and MBA from BIM Trichy. He has published more than 20 articles in reputed international journals has authored two books written articles and columns for newspapers and is quoted on issues related to leadership and marketing by various media platforms. His research work comprises construction of brand personality scale for media aesthetics and phenomenological design. His recent publications are on philosophy of a photograph hermeneutic reality of product and on philosophy of intimate spaces. R. Dhanuskodi has nearly 40 years of R&D experience at BHEL
India in technical areas applicable for thermal power plants. He is a life member of The Institution of Engineers (India) and The Combustion Institute. He has won two BHEL’s Excel awards under the best author category for technical papers. He has visited France Netherlands and Germany under Indo-Europe Clean Coal Development Program. He has guided 42 UG PG and PhD project works. He holds 11 patents 40 copyrights and 2 design registrations. He has presented papers in 20 conferences and published in 10 national and international journals. R. Kaliappan completed his bachelors in electrical and electronics engineering and Masters in Computer Science. He has 36 years of research experience in different fields of power generation and power plant subsystems such as heat transfer studies on boiler circulation
efficiency improvements of boiler subsystems product improvements/ enhancements and setting up test facilities for research studies. He has published a number of technical papers on MHD power generation and heat transfer studies in various national and international journals. He has more than 25 patents and copyrights on products development related to power boilers. He has won BHEL’S gold medal for product development for Smart Wall Blowing system. K. Nandakumar
Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of n...
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Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of n...
Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of neurons in the primate brain's visual system. However, biological visual systems have two ubiquitous architectural features not shared with typical CNNs: local recurrence within cortical areas, and long-range feedback from downstream areas to upstream areas. Here we explored the role of recurrence in improving classification performance. We found that standard forms of recurrence (vanilla RNNs and LSTMs) do not perform well within deep CNNs on the ImageNet task. In contrast, novel cells that incorporated two structural features, bypassing and gating, were able to boost task accuracy substantially. We extended these design principles in an automated search over thousands of model architectures, which identified novel local recurrent cells and long-range feedback connections useful for object recognition. Moreover, these task-optimized ConvRNNs matched the dynamics of neural activity in the primate visual system better than feedforward networks, suggesting a role for the brain's recurrent connections in performing difficult visual behaviors.
There can be no debate that Information Mining Projects cause processing tools to arise with the sole purpose of converting available organization data into useful knowledge on account of decision-making. Considering ...
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作者：
Griffin, Joan M.Malcolm, CariWright, PamelaCampbell, Emily HagelKabat, MargaretBangerter, Ann K.Sayer, Nina A.Joan M. Griffin
PhD is Robert D. and Patricia E. Kern scientific director Kern Center for the Science of Healthcare Delivery and associate professor Division of Health Care Policy and Research Mayo Clinic 200 1st Avenue SW Rochester MN 55905 e-mail: griffin.joan@mayo.edu. Cari Malcolm
LCSW is caregiver support program management analyst and Pamela Wright BSE MSW LCSW-R is VA Caregiver Support Line national program manager Care Management and Social Work Services Veterans Health Administration Washington DC. Emily Hagel Campbell MS is a statistician Center for Chronic Disease Outcomes Research Minneapolis VA Health Care Systems. Margaret Kabat LCSW-C CCM is VA Caregiver Support Program national director Care Management and Social Work Services Veterans Health Administration Washington DC. Ann K. Bangerter BS is a computer scientist Center for Chronic Disease Outcomes Research Minneapolis VA Health Care Systems. Nina A. Sayer PhD is deputy director Center for Chronic Disease Outcomes Research Minneapolis VA Health Care Systems and associate professor of medicine and psychiatry University of Minnesota Minneapolis. This project was supported by the Department of Veterans Affairs Veterans Health Administration Office of Research and Development and the Polytrauma/Blast Related Quality Enhancement Research Initiative (PT/BRI QUERI QLP 56-011). The findings and conclusions presented in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or the Office of Research and Development. Search for other works by this author on: Oxford Academic PubMed Google ScholarJoan M. Griffin
PhD is Robert D. and Patricia E. Kern scientific director Kern Center for the Science of Healthcare Delivery and associate professor Division of Health Care Policy and Research Mayo Clinic 200 1st Avenue SW Rochester MN 55905 e-mail: griffin.joan@mayo.edu. Cari Malcolm
LCSW is caregiver support program management analyst and Pamela
The U.S. Department of Veterans Affairs (VA) established the national Caregiver Support Line (CSL) in February 2011. The CSL is operated by licensed master’s degree social workers who provide caregivers of veterans w...
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The U.S. Department of Veterans Affairs (VA) established the national Caregiver Support Line (CSL) in February 2011. The CSL is operated by licensed master’s degree social workers who provide caregivers of veterans with information about caregiver benefits and services, counseling, and referrals to a caregiver support coordinator at the nearest VA medical center. The authors compared differences in veteran health care utilization patterns in the six months before and after a caregiver call to the CSL, hypothesizing that veterans with caregivers using the CSL had improved access to health care services and improved access increased utilization of health care. A pre- and posttest design was used. CSL calls that resulted in referrals to VA health care services or to local VA caregiver support coordinators were included in the sample. Data were extracted from the CSL database and matched to veteran care utilization data using veteran medical record data. Veteran inpatient stays for general medicine, hospice, respite, and long-term care significantly increased after the CSL call, but other inpatient stays (surgery, neurology) did not. Outpatient services for home health, respite, and mental health all significantly increased. Caregivers’ use of the national CSL may help facilitate access for veterans to needed care services.
Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factor...
Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a
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