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    Structure theorems of mixable shuffle algebras

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    DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion

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    In this paper, we study the task of detecting semantic parts of an object, e.g., a wheel of a car, under partial occlusion. We propose that all models should be trained without seeing occlusions while being able to transfer the learned knowledge to deal with occlusions. This setting alleviates the difficulty in collecting an exponentially large dataset to cover occlusion patterns and is more essential. In this scenario, the proposal-based deep networks, like RCNN-series, often produce unsatisfactory results, because both the proposal extraction and classification stages may be confused by the irrelevant occluders. To address this, [25] proposed a voting mechanism that combines multiple local visual cues to detect semantic parts. The semantic parts can still be detected even though some visual cues are missing due to occlusions. However, this method is manually-designed, thus is hard to be optimized in an end-to-end manner. In this paper, we present DeepVoting, which incorporates the robustness shown by [25] into a deep network, so that the whole pipeline can be jointly optimized. Specifically, it adds two layers after the intermediate features of a deep network, e.g., the pool-4 layer of VGGNet. The first layer extracts the evidence of local visual cues, and the second layer performs a voting mechanism by utilizing the spatial relationship between visual cues and semantic parts. We also propose an improved version DeepVoting+ by learning visual cues from context outside objects. In experiments, DeepVoting achieves significantly better performance than several baseline methods, including Faster-RCNN, for semantic part detection under occlusion. In addition, DeepVoting enjoys explainability as the detection results can be diagnosed via looking up the voting cues

    The molecular spiral arms of NGC 6946

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    From CO-12(J=1 to 0) observations at 45 seconds resolution Tacconi and Young (1989) have found evidence for enhancements in both the CO emissivity and the massive star formation efficiency (MSFE) on optical spiral arms of the bright spiral galaxy NGC 6946. In the optically luminous and well-defined spiral arm in the NE quadrant, there are enhancements in both the H2 surface density and MSFE relative to the interarm regions. In contrast, a poorly defined arm in the SW shows no arm-interarm contrast in the MSFE. To further investigate the molecular gas content of these two spiral arms, researchers have made CO-12 J=2 to 1 and 3 to 2 observations with the James Clerk Maxwell Telescope. In the J=2 to 1 line, they made observations of the NE and SW spiral arm and interarm regions in 4 x 9 10 seconds spaced grids (36 points per grid). Because of decreased sensitivity in the J=3 to 2 line, they were limited to mapping the two arm regions in 2 x 3 10 seconds spaced grids (6 points per grid). The centers of each of the grids lie 2.4 minutes to the NE and 2.3 minutes to the SW of the nucleus of NGC 6946. With the CO J=2 to 1 data researchers are able to fully resolve the two observed spiral arms in NGC 6946. In both cases the CO emission is largely confined to the optical spiral arm regions with the peak observed T asterisk sub A being up to 4 times higher on the spiral arms than in the interarm regions. Researchers are currently estimating massive star formation efficiencies on and off the spiral arms through direct comparison of the CO maps with an H alpha image. They are also comparing the CO J=2 to 1 data with an HI map made at similar resolution. Thus, they will be able to determine structure in all components of the IS on scales of less than 20 inches

    An Ultra-Low-Power Oscillator with Temperature and Process Compensation for UHF RFID Transponder

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    This paper presents a 1.28MHz ultra-low-power oscillator with temperature and process compensation. It is very suitable for clock generation circuits used in ultra-high-frequency (UHF) radio-frequency identification (RFID) transponders. Detailed analysis of the oscillator design, including process and temperature compensation techniques are discussed. The circuit is designed using TSMC 0.18μm standard CMOS process and simulated with Spectre. Simulation results show that, without post-fabrication calibration or off-chip components, less than ±3% frequency variation is obtained from –40 to 85°C in three different process corners. Monte Carlo simulations have also been performed, and demonstrate a 3σ deviation of about 6%. The power for the proposed circuitry is only 1.18µW at 27°C
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