44,818 research outputs found

    The effectiveness of mHealth interventions for maternal, newborn and child health in low- and middle-income countries:Protocol for a systematic review and meta-analysis

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    Rates of maternal, newborn and child (MNCH) mortality and morbidity are vastly greater in low– than in high–income countries and represent a major source of global health inequity. A host of systemic, economic, geopolitical and sociocultural factors have been implicated. Mobile information and communication technologies hold potential to ameliorate several of these challenges by supporting coordinated and evidence–based care, facilitating community based health services and enabling citizens to access health information and support. mHealth has attracted considerable attention as a means of supporting maternal, newborn and child health in developing countries and research to assess the impacts of mHealth interventions is increasing. While a number of expert reviews have attempted to summarise this literature, there remains a need for a fully systematic review employing gold standard methods of evidence capture, critical appraisal and meta–analysis, in order to comprehensively map, quality assess and synthesise this body of knowledge

    Systematic Review of Laser and Other Light Therapy for the Management of Oral Mucositis in Cancer Patients

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    Background The aim of this study was to review the available literature and define clinical practice guidelines for the use of laser and other light therapies for the prevention and treatment of oral mucositis. Methods A systematic review was conducted by the Mucositis Study Group of the Multinational Association of Supportive Care in Cancer/International Society of Oral Oncology. The body of evidence for each intervention, in each cancer treatment setting, was assigned an evidence level. Based onthe evidence level, one of the following three guideline determinations was possible: recommendation, suggestion, and no guideline possible. Results A new recommendation was made for low-level laser (wavelength at 650 nm, power of 40 mW, and each square centimeter treated with the required time to a tissue energy dose of 2 J/cm2 (2 s/point)) for the prevention of oral mucositis in adult patients receiving hematopoietic stem cell transplantation conditioned with high-dose chemotherapy, with or without total body irradiation. A new suggestion was made for low-level laser (wavelength around 632.8 nm) for the prevention of oral mucositis in patients undergoing radiotherapy, without concomitant chemotherapy, for head and neck cancer. No guideline was possible in other populations and for other light sources due to insufficient evidence. Conclusions The increasing evidence in favor of low-level laser therapy allowed for the development of two new guidelines supporting this modality in the populations listed above. Evidence for other populations was also generally encouraging over a range of wavelengths and intensities. However, additional well-designed research is needed to evaluate the efficacy of laser and other light therapies in various cancer treatment settings

    Suggested approach for establishing a rehabilitation engineering information service for the state of California

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    An ever expanding body of rehabilitation engineering technology is developing in this country, but it rarely reaches the people for whom it is intended. The increasing concern of state and federal departments of rehabilitation for this technology lag was the stimulus for a series of problem-solving workshops held in California during 1977. As a result of the workshops, the recommendation emerged that the California Department of Rehabilitation take the lead in the development of a coordinated delivery system that would eventually serve the entire state and be a model for similar systems across the nation

    Analysis of smartphone model identification using digital images

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    This paper is focused on smartphone model identification using image features. A total of 64 image features - broadly categorized into colour features, wavelet features and image quality features - are extracted from high-resolution smartphone images. A binary-class turned to multiclass support vector machine (SVM) is used as the classifier. Experimental results based on 1800 images captured with 10 different smartphone/tablet devices are promising in correctly identifying source smartphone model. Image quality metrics and wavelet features are shown to contain the most useful device/model information compared to colour features. However, compared to colour features, quality and wavelet features are highly sensitive to simple image modifications. The combined set of colour, quality and wavelet features achieves the overall best identification accuracy

    Robustness in blind camera identification

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    Microphone smart device fingerprinting from video recordings

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    This report aims at summarizing the on-going research activity carried out by DG-JRC in the framework of the institutional project Authors and Victims Identification of Child Abuse on-line, concerning the use of microphone fingerprinting for source device classification. Starting from an exhaustive study of the State of Art regarding the matter, this report describes a feasibility study about the adoption of microphone fingerprinting for source identification of video recordings. A set of operational scenarios have been established in collaboration with EUROPOL law enforcers, according to investigators needs. A critical analysis of the obtained results has demonstrated the feasibility of microphone fingerprinting and it has suggested a set of recommendations, both in terms of usability and future researches in the field.JRC.E.3-Cyber and Digital Citizens' Securit

    Bio-inspired broad-class phonetic labelling

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    Recent studies have shown that the correct labeling of phonetic classes may help current Automatic Speech Recognition (ASR) when combined with classical parsing automata based on Hidden Markov Models (HMM).Through the present paper a method for Phonetic Class Labeling (PCL) based on bio-inspired speech processing is described. The methodology is based in the automatic detection of formants and formant trajectories after a careful separation of the vocal and glottal components of speech and in the operation of CF (Characteristic Frequency) neurons in the cochlear nucleus and cortical complex of the human auditory apparatus. Examples of phonetic class labeling are given and the applicability of the method to Speech Processing is discussed
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