185 resultados para Electronic cameras
Resumo:
Audio-visualspeechrecognition, or the combination of visual lip-reading with traditional acoustic speechrecognition, has been previously shown to provide a considerable improvement over acoustic-only approaches in noisy environments, such as that present in an automotive cabin. The research presented in this paper will extend upon the established audio-visualspeechrecognition literature to show that further improvements in speechrecognition accuracy can be obtained when multiple frontal or near-frontal views of a speaker's face are available. A series of visualspeechrecognition experiments using a four-stream visual synchronous hidden Markov model (SHMM) are conducted on the four-camera AVICAR automotiveaudio-visualspeech database. We study the relative contribution between the side and central orientated cameras in improving visualspeechrecognition accuracy. Finally combination of the four visual streams with a single audio stream in a five-stream SHMM demonstrates a relative improvement of over 56% in word recognition accuracy when compared to the acoustic-only approach in the noisiest conditions of the AVICAR database.
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Person re-identification involves recognising individuals in different locations across a network of cameras and is a challenging task due to a large number of varying factors such as pose (both subject and camera) and ambient lighting conditions. Existing databases do not adequately capture these variations, making evaluations of proposed techniques difficult. In this paper, we present a new challenging multi-camera surveillance database designed for the task of person re-identification. This database consists of 150 unscripted sequences of subjects travelling in a building environment though up to eight camera views, appearing from various angles and in varying illumination conditions. A flexible XML-based evaluation protocol is provided to allow a highly configurable evaluation setup, enabling a variety of scenarios relating to pose and lighting conditions to be evaluated. A baseline person re-identification system consisting of colour, height and texture models is demonstrated on this database.
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The incidence of all skin cancers, including melanoma, continues to rise. It is well known that ultraviolet (UV) radiation is the main environmental risk factor for skin cancer, and excessive exposure at a young age increases the risk of developing skin cancer. The aim of this study was to determine the acceptability and feasibility of delivering sun protection messages via electronic media such as short message services (SMS) to people 18-40 years, and explore factors associated with their acceptability. Overall, 80% of participants agreed that they would like to receive some form of sun protection advice; of these, 20% prefer to receive it via SMS and 42% via email. Willingness to receive electronic messages about the UV index was associated with being unsure about whether a suntanned person would look healthy and greater use of sun protection in the past. Careful attention to message framing and timing of message delivery and focus on short-term effects of sun exposure such as sunburn and skin ageing should increase the acceptability of such messages to young people. We conclude that sun protection messages delivered to young adults via electronic media appear feasible and acceptable.
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This article will outline the impact of the Electronic Conveyancing National Law (ECNL) and the draft Model Participation Rules (MPR) on conveyancing practice and the obligations of lawyers and conveyancers.
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Measurements of the electrical conductivity, Seebeck coefficient and Hall mobility from -300K to -1300K have been carried out on multiphase hotpressed samples of the nominal composition B6Si. In all samples the conductivity and the p-type Seebeck coefficient both increase smoothly with increasing temperature. By themselves, these facts suggest small-polaronic hopping between inequivalent sites. The measured Hall mobilities are always low, but vary in sign. A possible explanation is offered for this anomalous behavior.
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Purpose – Integrated supplier management (ISM), new product development (NPD) and knowledge sharing (KS) practices are three primary business activities utilised to enhance manufacturers' business performance (BP). The purpose of this paper is to empirically investigate the relationships between these three business activities (i.e. ISM, NPD, KS) and BP in a Taiwanese electronics manufacturing context. Design/methodology/approach – A questionnaire survey is first administered to a sample of electronic manufacturing companies operating in Taiwan to elicit the opinions of technical and managerial professionals regarding business activities and BP within their companies. A total of 170 respondents from 83 companies respond to the survey. Factor, correlation and path analysis are undertaken on this quantitative data set to derive the key factors which leverage business outcomes in these companies. Following empirical analysis, six semi-structured interviews are undertaken with manufacturing executives to provide qualitative insights into the underlying reasons why certain business activity factors are the strongest predictors of BP. Findings – The investigation shows that the ISM, NPD and KS constructs all play an important role in the success of company operations and creating business outcomes. Specifically, the key factors within these constructs which influenced BP are: supplier evaluation and selection; design simplification and modular design; information technology infrastructure and systems and open communication. Accordingly, sufficient financial and human resources should be allocated to these important activities to derive accelerated rates of improved BP. These findings are supported by the qualitative interviews with manufacturing executives. Originality/value – The paper depicts the pathways to improved manufacturing BP, through targeting efforts into the above-mentioned factors within the ISM, NPD and KS constructs. Based on the empirical path model, and the specific insights derived from the explanatory interviews with manufacturing executives, the paper also provides a number of practical implications for manufacturing companies seeking to enhance their BP through improved operational activities.
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Piezoelectric transducers convert electrical energy to mechanical energy and play a great role in ultrasound systems. Ultrasound power transducer performance is strongly related to the applied electrical excitation. To have a suitable excitation for maximum energy conversion, it is required to analyze the effects of input signal waveform, medium and input signal distortion on the characteristic of a high power ultrasound system (including ultrasound transducer). In this research, different input voltage signals are generated using a single-phase power inverter and a linear power amplifier to excite a high power ultrasound transducer in different medium (water and oil) in order to study the characteristic of the system. We have also considered and analyzed the effect of power converter output voltage distortions on the performance of the high power ultrasound transducer using a passive filter.
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Graphene has promised many novel applications in nanoscale electronics and sustainable energy due to its novel electronic properties. Computational exploration of electronic functionality and how it varies with architecture and doping presently runs ahead of experimental synthesis yet provides insights into types of structures that may prove profitable for targeted experimental synthesis and characterization. We present here a summary of our understanding on the important aspects of dimension, band gap, defect, and interfacial engineering of graphene based on state-of-the-art ab initio approaches. Some most recent experimental achievements relevant for future theoretical exploration are also covered.
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This paper presents an adaptive metering algorithm for enhancing the electronic screening (e-screening) operation at truck weight stations. This algorithm uses a feedback control mechanism to control the level of truck vehicles entering the weight station. The basic operation of the algorithm allows more trucks to be inspected when the weight station is underutilized by adjusting the weight threshold lower. Alternatively, the algorithm restricts the number of trucks to inspect when the station is overutilized to prevent queue spillover. The proposed control concept is demonstrated and evaluated in a simulation environment. The simulation results demonstrate the considerable benefits of the proposed algorithm in improving overweight enforcement with minimal negative impacts on nonoverweighed trucks. The test results also reveal that the effectiveness of the algorithm improves with higher truck participation rates in the e-screening program.
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This paper looks at the accuracy of using the built-in camera of smart phones and free software as an economical way to quantify and analyse light exposure by producing luminance maps from High Dynamic Range (HDR) images. HDR images were captured with an Apple iPhone 4S to capture a wide variation of luminance within an indoor and outdoor scene. The HDR images were then processed using Photosphere software (Ward, 2010.) to produce luminance maps, where individual pixel values were compared with calibrated luminance meter readings. This comparison has shown an average luminance error of ~8% between the HDR image pixel values and luminance meter readings, when the range of luminances in the image is limited to approximately 1,500cd/m2.
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This paper addresses the problem of automatically estimating the relative pose between a push-broom LIDAR and a camera without the need for artificial calibration targets or other human intervention. Further we do not require the sensors to have an overlapping field of view, it is enough that they observe the same scene but at different times from a moving platform. Matching between sensor modalities is achieved without feature extraction. We present results from field trials which suggest that this new approach achieves an extrinsic calibration accuracy of millimeters in translation and deci-degrees in rotation.
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Introduction The onset of Personally Controlled Electronic Health Records in Australia demand healthcare decision making processes to comprise, understand and accept electronic health records (EHR). Nurses play a key, central role in the healthcare decision making process and their perceptions and attitudes of EHRs are significant [1], which develop during their academic life. However, studies aimed at nursing students’ attitudes of EHRs are very limited [2-4]. A proper understanding of these attitudes and how they evolve with academic progress is important. This paper presents results from a survey conducted at a leading University in Queensland, Australia as a first step to filling this gap.
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In this paper we demonstrate passive vision-based localization in environments more than two orders of magnitude darker than the current benchmark using a 100 webcam and a 500 camera. Our approach uses the camera’s maximum exposure duration and sensor gain to achieve appropriately exposed images even in unlit night-time environments, albeit with extreme levels of motion blur. Using the SeqSLAM algorithm, we first evaluate the effect of variable motion blur caused by simulated exposures of 132 ms to 10000 ms duration on localization performance. We then use actual long exposure camera datasets to demonstrate day-night localization in two different environments. Finally we perform a statistical analysis that compares the baseline performance of matching unprocessed greyscale images to using patch normalization and local neighbourhood normalization – the two key SeqSLAM components. Our results and analysis show for the first time why the SeqSLAM algorithm is effective, and demonstrate the potential for cheap camera-based localization systems that function across extreme perceptual change.
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This research was a step forward in developing a data integration framework for Electronic Health Records. The outcome of the research is a conceptual and logical Data Warehousing model for integrating Cardiac Surgery electronic data records. This thesis investigated the main obstacles for the healthcare data integration and proposes a data warehousing model suitable for integrating fragmented data in a Cardiac Surgery Unit.