The impact of SiC on high power devices and their applications is analysed using simulations in a very wide range of design voltages. First, a detailed presentation of the anisotropic form of the basic equations and of the physical models for 4H‐SiC used in the simulations is given. Following that the application ranges of unipolar and bipolar devices in the domains of voltage and frequency are predicted in the case of IGBTs versus MOSFETs and PiN versus Schottky rectifiers based on comparisons of the on‐state voltage and of the total losses. The application limit of the MOSFETs compared to IGBTs and of the Schottky rectifiers compared to PiN rectifiers is predicted to be about 4.5 and 2.5 kV, respectively, in the case of the 4H‐SiC polytype. The impact of technological limitations of SiC is illustrated by the case of low channel mobility. The merits of SiC as compared to Si are illustrated by the case of a SiC rectifier operating together with a Si IGBT. Dramatically reduced turn‐on losses are demonstrated. The superiority of SiC from the point of view of dynamic avalanche is predicted and illustrated. Finally, some novel SiC switch structures are introduced in response to the reliability problems encountered in ordinary trench MOSFETs.
Blue diode lasers emitting 5 mW continuous-wave power around 400 nm have recently become available. We report on the use of a blue diode laser together with a 30 mW red diode laser for sum-frequency generation around 254 nm. The ultraviolet power is estimated to be 0.9 nW, and 35 GHz mode-hop-free tuning range is achieved. This is enough to perform high-resolution ultraviolet spectroscopy of mercury isotopes. The possibility to use frequency modulation in the ultraviolet is demonstrated; however, at present the ultraviolet power is too low to give advantages over direct absorption monitoring. Mercury detection at atmospheric pressure is also considered which is of great interest for environmental monitoring.
This paper presents a domain-specific automated image analysis framework for the detection of pre-cancerous and cancerous lesions of the uterine cervix. Our proposed framework departs from previous methods in that we include domain-specific diagnostic features in a probabilistic manner using conditional random fields. Likewise, we provide a novel window-based performance assessment scheme for 2D image analysis which addresses the intrinsic problem of image misalignment. Image regions corresponding to different tissue types are indentified for the extraction of domain-specific anatomical features. The unique optical properties of each tissue type and the diagnostic relationships between neighboring regions are incorporated in the proposed conditional random field model. The validity of our method is examined using clinical data from 48 patients, and its diagnostic potential is demonstrated by a performance comparison with expert colposcopy annotations, using histopathology as the ground truth. The proposed automated diagnostic approach can support or potentially replace conventional colposcopy, allow tissue specimen sampling to be performed in a more objective manner, and lower the number of cervical cancer cases in developing countries by providing a cost effective screening solution in low-resource settings.
A compact fluorosensor with a fiber-optic measurement probe was developed, employing a continuous-wave violet diode laser as an exciting source and an integrated digital spectrometer for the monitoring of fluorescence signatures. The system has the dimensions 22×13×8 cm3, and features 5 nm spectral resolution and an excellent detectivity. Results from measurements on vegetation and human premalignant skin lesions are reported, illustrating the potential of the instrument.
Cervical intraepithelial neoplasia (CIN) exhibits certain morphologic features that can be identified during a colposcopic exam. Immature metaplastic and dysplastic cervical squamous epithelia turn white after application of acetic acid during the exam. The whitening process occurs visually over several minutes and subjectively helps to discriminate between dysplastic and normal tissue. Digital imaging technologies enable us to assist the physician in analyzing acetowhite (acetic-acid-induced) lesions in a fully automatic way. We report a study designed to measure multiple parameters of the acetowhitening process from two images captured with a digital colposcope. One image is captured before the acetic acid application, and the other is captured after the acetic acid application. The spatial change of the acetowhitening is extracted using color and texture information in the post-acetic-acid image; the temporal change is extracted from the intensity and color changes between the post-acetic-acid and pre-acetic-acid images with an automatic alignment. In particular, we propose an automatic means to calculate an opacity index that indicates the grades of temporal change. The imaging and data analysis system is evaluated with a total of 99 human subjects. The proposed opacity index demonstrates a sensitivity and specificity of 94 and 87%, respectively, for discriminating high-grade dysplasia (CIN2+) from normal and low-grade subjects, considering histology as the gold standard.
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