3,012 research outputs found
The Massett-Graham Island Coal Company: the Nearest Coal Fields to Prince Rupert:
No full textThis little booklet is compiled to show the possibilities of the property controlled by this company in The Graham Island Coal Fields, near Prince Rupert, British Columbia Canada.--P. [1
sj-docx-1-ggm-10.1177_23337214241246843 – Supplemental material for The Acceptability of a Community-Based Perturbation-Based Balance Training to Older Adults and Healthcare Professionals
No full textSupplemental material, sj-docx-1-ggm-10.1177_23337214241246843 for The Acceptability of a Community-Based Perturbation-Based Balance Training to Older Adults and Healthcare Professionals by Justin Whitten, Bryant O’Leary, David Graham, Michelle Grocke-Dewey, Julie Riley, Danielle Harper and Dawn Tarabochia in Gerontology and Geriatric Medicine</p
Asexuality: Classification and characterization
No full textThis is a post-print version of the article. The official published version can be obtaineed at the link below.The term “asexual” has been defined in many different ways and asexuality has received very little research attention. In a small qualitative study (N = 4), individuals who self-identified as asexual were interviewed to help formulate hypotheses for a larger study. The second larger study was an online survey drawn from a convenience sample designed to better characterize asexuality and to test predictors of asexual identity. A convenience sample of 1,146 individuals (N = 41 self-identified asexual) completed online questionnaires assessing sexual history, sexual inhibition and excitation, sexual desire, and an open-response questionnaire concerning asexual identity. Asexuals reported significantly less desire for sex with a partner, lower sexual arousability, and lower sexual excitation but did not differ consistently from non-asexuals in their sexual inhibition scores or their desire to masturbate. Content analyses supported the idea that low sexual desire is the primary feature predicting asexual identity
The DSM diagnostic criteria for female orgasmic disorder
No full textThis is the post-print version of the article. The official published version can be found at the link below.This article reviews the DSM diagnostic criteria for Female Orgasmic Disorder (FOD). Following an overview of the concept of female orgasm, research on the prevalence and associated features of FOD is briefly reviewed. Specific aspects of the DSM-IV-TR criteria for FOD are critically reviewed and key issues that should be considered for DSM-V are discussed. The DSM-IV-TR text on FOD focused on the physiological changes that may (or may not) accompany orgasm in women; one of the major recommendations here is that greater emphasis be given to the subjective aspects of the experience of orgasm. Additional specific recommendations are made for revision of diagnostic criteria, including the use of minimum severity and duration criteria, and better acknowledgment of the crucial role of relationship factors in FOD
Estimation of energy consumption in machine learning
No full textEnergy consumption has been widely studied in the computer architecture field for decades. While the adoption of energy as a metric in machine learning is emerging, the majority of research is still primarily focused on obtaining high levels of accuracy without any computational constraint. We believe that one of the reasons for this lack of interest is due to their lack of familiarity with approaches to evaluate energy consumption. To address this challenge, we present a review of the different approaches to estimate energy consumption in general and machine learning applications in particular. Our goal is to provide useful guidelines to the machine learning community giving them the fundamental knowledge to use and build specific energy estimation methods for machine learning algorithms. We also present the latest software tools that give energy estimation values, together with two use cases that enhance the study of energy consumption in machine learning.open accessFunding textEva García-Martín and Håkan Grahn work under the research project “Scalable resource-efficient systems for big data analytics” funded by the Knowledge Foundation (grant: 20140032 ) in Sweden. Crefeda Faviola Rodrigues and Graham Riley are funded under the European FP7-INFRASTRUCTURES-2012-1 call (grant: 312979 ) and part-funded by ARM Ltd., UK under a Ph.D. Studentship Agreement. Eva Garcia-Martin is a Ph.D. student in Machine Learning at Blekinge Institute of Technology, in Sweden. She is working under the project Scalable resource- efficient systems for big data analytics funded by the Knowledge Foundation, advised by Niklas Lavesson and Håkan Grahn. The main focus of her thesis is on making machine learning algorithms more energy efficient. In particular, she has studied the energy consumption patterns of streaming algorithms, and then proposed new algorithm extensions that reduce their energy consumption. Personal website: https://egarciamartin.github.io/. Crefeda Faviola Rodrigues is a Ph.D. student in Advanced Processor Technology (APT) group at The University of Manchester and she is supervised by Mr. Graham Riley and Dr. Mikel Lujan. Her research is part funded by ARM and IS-ENES2 Project. Her research topic is “Efficient execution of Convolutional Neural Networks on low power heterogeneous systems”. The main focus of her thesis is to enable energy efficiency in deep learning algorithms such as Convolutional Neural Networks or ConvNets on embedded platforms like the Jetson TX1 and Snapdragon 820. Personal website: https://personalpages.manchester.ac.uk/staff/crefeda.rodrigues/. Graham Riley is a Lecturer in the School of Computer Science at the University of Manchester and hold a part-time position in the Scientific Computing Department (SCD) at STFC, Daresbury. His research is application-driven and much of his research has been undertaken in collaboration with computational scientists in application areas such as Earth System Modeling (including the U.K. Met Office) and, previously, computational chemistry and biology. His aim is to apply his experience in high performance computing and software engineering for (principally) scientific computing to new application domains. He is also interested in techniques and tools to support flexible coupled modeling in scientific computing and in performance modeling techniques for large-scale heterogeneous HPC systems, where energy efficiency is increasingly key. Personal website: http://www.manchester.ac.uk/research/graham.riley/. Håkan Grahn is professor of computer engineering since 2007. He received a M.Sc. degree in Computer Science and Engineering in 1990 and a Ph.D. degree in Computer Engineering in 1995, both from Lund University. His main interests are computer architecture, multicore systems, GPU computing, parallel programming, image processing, and machine learning/data mining. He has published more than 100 papers on these subjects. During 1999–2002 he was head of department for the Dept. of software engineering and computer science, and during 2011–2013, he was Dean of research at Blekinge Institute of Technology. Currently he is project leader for BigData@BTH – “Scalable resource-efficient systems for big data analytics”, a research profile funded by the Knowledge foundation during 2014–2020. Personal website: https://www.bth.se/eng/staff/hakan-grahn-hgr/.</p
Investigating the dynamics of laser induced sparks in atmospheric helium using Rayleigh and Thomson scattering
No full textData set relevant to publication - 'Investigating the dynamics of laser induced sparks in atmospheric helium using Rayleigh and Thomson scattering', Nedanovska, E., Nersisyan, G., Morgan, T. J., Huwel, L., Murakami, T., Lewis, C. L. S., Riley, D. & Graham, W. G. 2015 In : Journal of Applied Physics. 117, 1, 6 p., 013302
Imaging diagnosis-caudal cruciate ligament avulsion in a horse
No full textLR: 20061107; PUBM: Print; JID: 9209635; ppublishSource type: Electronic(1
sj-pdf-1-mso-10.1177_20552173221104918 - Supplemental material for Peripartum disease activity in moderately and severely disabled women with multiple sclerosis
No full textSupplemental material, sj-pdf-1-mso-10.1177_20552173221104918 for Peripartum disease activity in moderately and severely disabled women with multiple sclerosis by Bridget LaMonica Ostrem, Annika Anderson, Sarah Conway, Brian C Healy, Jiwon Oh, Dina Jacobs, Ruth Dobson, Edith Larmon Graham, A Dessa Sadovnick, Vanessa Zimmerman, Yanqing Liu, Riley Bove and Maria Houtchens in Multiple Sclerosis Journal – Experimental, Translational and Clinical</p
The DSM diagnostic criteria for Female Sexual Arousal Disorder
No full textThis article reviews and critiques the DSM-IV-TR diagnostic criteria for Female Sexual Arousal Disorder (FSAD). An overview of how the diagnostic criteria for FSAD have evolved over previous editions of the DSM is presented and research on prevalence and etiology of FSAD is briefly reviewed. Problems with the essential feature of the DSM-IV-TR diagnosis — “an inability to attain, or to maintain…an adequate lubrication-swelling response of sexual excitement” — are identified. The significant overlap between “arousal” and “desire” disorders is highlighted. Finally, specific recommendations for revision of the criteria for DSM-V are made, including use of a polythetic approach to the diagnosis and the addition of duration and severity criteria
Exploring small area demand for grocery retailers in tourist areas
No full textNewing, A., Clarke, G.P. and Clarke, M. 2014. Exploring small area demand for grocery retailers in tourist areas. Tourism Economics, 20(2), pp.407-427This paper uses data from a major loyalty card scheme to draw insights about the characteristics of grocery expenditure by tourists. The authors explore the volume, value and composition of store based visitor expenditure using consumer data from the loyalty card scheme. They focus on grocery spending at selected stores in Cornwall, a popular tourist destination in South West England. Theloyalty card data provide a valuable source rarely available for academic investigations. The authors are able to analyse visitor spend by socio-economic and geodemographic characteristics, drawing a range of comparisons with residential demand from within the store catchment areas. They demonstrate that visitor grocery expenditure is complex and varies by store, destination and type of customer. The paper presents evidence to suggest that the current approaches used to estimate sales uplift and local-level economic impact from visitor demand are unable to account for the complexities of this form of expenditure. Based on these insights, the authors recommend that sophisticated modelling is employed to estimate the impact of visitor expenditure
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