In-Vivo Skin Capacitive Image Classification Using AlexNet Convolution Neural Network

© 2018 IEEE. Skin water content is very important for its cosmetic properties and its barrier functions, however, to measure it is very difficult. We have recently developed a novel hand-held probe for in-vivo skin hydration imaging based on the capacitance measurement principle. It is more repeatable, reproducible and easier to calibrate than the existing commercial devices. Our latest research is to assess the performance of deep learning in in-vivo skin capacitive image analysis using AlexNet model. As we know the AlexNet model can be used for image classification and recognition with high accuracy. Our object is to design a model to classify more than one specific features, i.e. not just the one with highest probability. We trained the image classifier using the pretrained model to implement the specific feature extraction, prediction and classification specifically for the skin hydration level, skin damage level and gender. There are over 1000 skin images which are measured by two experiments: repeatability of different instruments in in-vivo skin measurement; and skin damage measurements by different instruments. The objective of the research has been divided into three parts: feature extraction implementation using the pretrained model AlexNet; accuracy assessment of the model; further improve the system for multiple features classification. The image classification programme shows a good result which has accuracy 0.98, and the test images were classified correctly comparing with the experimental results of skin hydration, skin damaged level and the gender of the volunteers

A Sino-German 6cm polarisation survey of the Galactic plane - VIII. Small-diameter sources

Information of small-diameter sources is extracted from the Sino-German 6cm polarisation survey of the Galactic plane carried out with the Urumqi 25-m telescope. We performed two-dimensional elliptical Gaussian fits to the 6cm maps to obtain a list of sources with total-intensity and polarised flux densities. The source list contains 3832 sources with a fitted diameter smaller than 16 arcmin and a peak flux density exceeding 30 mJy, so about 5 times the rms noise, of the total-intensity data. The cumulative source count indicates completeness for flux densities exceeding about 60 mJy. We identify 125 linearly polarised sources at 6cm with a peak polarisation flux density greater than 10 mJy, so about 3 times the rms noise, of the polarised-intensity data. Despite lacking compact steep spectrum sources, the 6cm catalogue lists about 20 percent more sources than the Effelsberg 21cm source catalogue at the same angular resolution and for the same area. Most of the faint 6cm sources must have a flat spectrum and are either HII regions or extragalactic. When compared with the Green Bank 6cm (GB6) catalogue, we obtain higher flux densities for a number of extended sources with complex structures. Polarised 6cm sources density are uniformly distributed in Galactic latitude. Their number density decreases towards the inner Galaxy. More than 80 percent of the polarised sources are most likely extragalactic. With a few exceptions, the sources have a higher percentage polarisation at 6cm than at 21cm. Depolarisation seems to occur mostly within the sources with a minor contribution from the Galactic foreground emission.Comment: A&A accepted, 9 pages, 5 figures, Tables 1 and 2 are accessible from http://zmtt.bao.ac.cn/6cm

The sino-german 6cm polarization survey of the galactic plane: A summary

We have finished the 6cm polarization survey of the Galactic plane using the Urumqi 25m radio telescope. It covers 10deg<l<230deg in Galactic longitude and |b| <5deg in Galactic latitude. The new polarization maps not only reveal new properties of the diffuse magnetized interstellar medium, but also are very useful for studying individual objects such as Hii regions, which may act as Faraday screens with strong regular magnetic fields inside, and supernova remnants for their polarization properties and spectra. The high sensitivity of the survey enables us to discover two new SNRs G178.2-4.2 and G25.3-2.1 and a number of Hii regions.Comment: 10 pages, 1 figure. International Journal of Modern Physics: Conference Series (IJMPCS) for Proceedings of 3rd Galileo-Xu Guangqi meetin

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

Probing electronic excitations in molecular conduction

We identify experimental signatures in the current-voltage (I-V) characteristics of weakly contacted molecules directly arising from excitations in their many electron spectrum. The current is calculated using a multielectron master equation in the Fock space of an exact diagonalized model many-body Hamiltonian for a prototypical molecule. Using this approach, we explain several nontrivial features in frequently observed I-Vs in terms of a rich spectrum of excitations that may be hard to describe adequately with standard one-electron self-consistent field (SCF) theories.Comment: Significantly different content -- inadequacy of SCF approach described with simple model, and a whole new class of experiments showing gate modulated current steps discussed in terms of excitations in the molecular many-body spac

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

Controlling soliton interactions in Bose-Einstein condensates by synchronizing the Feshbach resonance and harmonic trap

We present how to control interactions between solitons, either bright or dark, in Bose-Einstein condensates by synchronizing Feshbach resonance and harmonic trap. Our results show that as long as the scattering length is to be modulated in time via a changing magnetic field near the Feshbach resonance, and the harmonic trapping frequencies are also modulated in time, exact solutions of the one-dimensional nonlinear Schr\"{o}dinger equation can be found in a general closed form, and interactions between two solitons are modulated in detail in currently experimental conditions. We also propose experimental protocols to observe the phenomena such as fusion, fission, warp, oscillation, elastic collision in future experiments.Comment: 7 pages, 7 figure