94 research outputs found

    Managing risks and harms associated with the use of anabolic steroids

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    Background: People using AAS may adopt a range of strategies to prevent and treat adverse health conditions potentially associated with the use of these substances (AAS-HC). These strategies include seeking support from physicians, using the needle and syringe exchange programme (NSP) and seeking support from informal sources such as coaches and online forums. The process of identifying risks and harms, adopting and modifying health-related strategies is similar to the methods of risk-management employed in other fields of human activity. This approach recognises the importance of the informal body of knowledge produced by decades of AAS-related folk-pharmacology and seeks to understand harm-reduction from the users’ perspective.Objectives: The primary objective of this thesis is to investigate the strategies adopted by people using AAS to prevent and treat AAS-HC. Secondary objectives include to explore the factors associated with the adoption of health strategies and the occurrence of AAS-HC, as well as the barriers and facilitators experienced by AAS users when accessing health services and other sources of support.Methods: To achieve the objectives above, three work packages (WP) were produced as part of a mixed-methods research design. WP1 is a systematic review and meta-analysis of the prevalence of AAS users seeking support from physicians. WP2 is a cross-sectional online survey that identified AAS-HC, risk factors and health-related strategies adopted by AAS users in the UK. WP3 is a qualitative study based on in-depth interviews to discuss the experiences of AAS users and their risk-management strategies (RMS).Results: The estimated overall prevalence of AAS users seeking support from physicians is 37.1%. Higher prevalence rates were observed in studies from Australia (67.3%) and amongst clients of the NSP (54.1%), whilst the lowest was observed among adolescents (17.3%). The health conditions most commonly reported by the 883 participants of the online survey were insomnia (33.3%) and anxiety (32.2%). Most participants adopted preventive strategies such as having blood tests in the last 12 months (86.2%) and seeking a GP to treat AAS-HC (55.0%). Those who sought a GP for AAS-related information were 76% less likely to report an AAS-HC in the last 12 months. The interviews described AAS users’ RMS as a continuous process of awareness and behavioural changes. Participants described an extensive use of private health services and other sources of support to bypass the barriers experienced by AAS users engaging with the public health system.Conclusion: A large number of AAS users refrain from seeking support from physicians. Health professionals should be trained to recognise and manage the most common AAS-HC and help users improve their RMS. Further studies should investigate the efficacy of AAS-related RMS and the subpopulations of AAS users more likely to experience AAS-HC and less likely to engage with health services.<br/

    Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

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    Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/

    Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

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    Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/

    Performance Analysis of Different Optimization Algorithms for Multi-Class Object Detection

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    Object recognition is a significant approach employed for recognizing suitable objects from the image. Various improvements, particularly in computer vision, are probable to diagnose highly difficult tasks with the assistance of local feature detection methodologies. Detecting multi-class objects is quite challenging, and many existing researches have worked to enhance the overall accuracy. But because of certain limitations like higher network loss, degraded training ability, improper consideration of features, less convergent and so on. The proposed research introduced a hybrid convolutional neural network (H-CNN) approach to overcome these drawbacks. The collected input images are pre-processed initially through Gaussian filtering to eradicate the noise and enhance the image quality. Followed by image pre-processing, the objects present in the images are localized using Grid Guided Localization (GGL). The effective features are extracted from the localized objects using the AlexNet model. Different objects are classified by replacing the concluding softmax layer of AlexNet with Support Vector Regression (SVR) model. The losses present in the network model are optimized using the Improved Grey Wolf (IGW) optimization procedure. The performances of the proposed model are analyzed using PYTHON. Various datasets are employed, including MIT-67, PASCAL VOC2010, Microsoft (MS)-COCO and MSRC. The performances are analyzed by varying the loss optimization algorithms like improved Particle Swarm Optimization (IPSO), improved Genetic Algorithm (IGA), and improved dragon fly algorithm (IDFA), improved simulated annealing algorithm (ISAA) and improved bacterial foraging algorithm (IBFA), to choose the best algorithm. The proposed accuracy outcomes are attained as PASCAL VOC2010 (95.04%), MIT-67 dataset (96.02%), MSRC (97.37%), and MS COCO (94.53%), respectively

    Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

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    Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/

    Dataset Structural Index: Leveraging a machine's perspective towards visual data

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    With advances in vision and perception architectures, we have realized that working with data is equally crucial, if not more, than the algorithms. Till today, we have trained machines based on our knowledge and perspective of the world. The entire concept of Dataset Structural Index(DSI) revolves around understanding a machine`s perspective of the dataset. With DSI, I show two meta values with which we can get more information over a visual dataset and use it to optimize data, create better architectures, and have an ability to guess which model would work best. These two values are the Variety contribution ratio and Similarity matrix. In the paper, I show many applications of DSI, one of which is how the same level of accuracy can be achieved with the same model architectures trained over less amount of data

    Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

    Get PDF
    Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/

    Mixing Methods: Practical Insights from the Humanities in the Digital Age

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    The digital transformation is accompanied by two simultaneous processes: digital humanities challenging the humanities, their theories, methodologies and disciplinary identities, and pushing computer science to get involved in new fields. But how can qualitative and quantitative methods be usefully combined in one research project? What are the theoretical and methodological principles across all disciplinary digital approaches? This volume focusses on driving innovation and conceptualising the humanities in the 21st century. Building on the results of 10 research projects, it serves as a useful tool for designing cutting-edge research that goes beyond conventional strategies

    The extent of Kuwaiti Islamic banks restrict the use of Islamic financing tools in their financial operations: a field study

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    This research aims to identify the extent to of Kuwaiti Islamic banks adhere to the use of Islamic financing tools in their financial operations. The study population consists of all (5) banks listed on the Kuwait Stock Exchange. As for the study sample, (100) respondents were selected from Financial managers, accountants, and workers in finance and investment departments work in these banks. The questionnaire was used as a tool for collecting primary data. The results showed that Kuwaiti Islamic banks adhere to the use of Islamic financing tools represented in Murabaha, Musharaka and Mudaraba in their financial operations to a high degree. The study recommended that Kuwaiti Islamic banks should be encouraged to play a more role in Murabaha operations and find appropriate solutions to technical obstacles and culture-related procedures that prevent the provision of Islamic financing through Murabaha

    IoT Applications Computing

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    The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing
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