A Hybrid mosaic and vice versa

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FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks

In this paper, a neural network based real-time speech recognition (SR) system is developed using an FPGA for very low-power operation. The implemented system employs two recurrent neural networks (RNNs); one is a speech-to-character RNN for acoustic modeling (AM) and the other is for character-level language modeling (LM). The system also employs a statistical word-level LM to improve the recognition accuracy. The results of the AM, the character-level LM, and the word-level LM are combined using a fairly simple N-best search algorithm instead of the hidden Markov model (HMM) based network. The RNNs are implemented using massively parallel processing elements (PEs) for low latency and high throughput. The weights are quantized to 6 bits to store all of them in the on-chip memory of an FPGA. The proposed algorithm is implemented on a Xilinx XC7Z045, and the system can operate much faster than real-time.Comment: Accepted to SiPS 201

The Spatial Dimension Of Take-Offs And Sustainability: The Case Of East Asian Countries

This study examines the relationship between the size of a country and its “take-off” for economic development. We find that most countries which experienced economic upheavals in the past decades are relatively small in terms of area. Specifically, take-offs appear to be quicker for smaller landmasses with larger potential workforce and higher population density, controlled for financial markets maturity, corporate governance, economic openness, and human capital development. We also find that take-offs are not sustainable by nature as most countries in East Asia that which experience take-offs are currently facing slow-downs of their economies. Through this finding, we predict that China may experience a slow-down at around 36% and may reach to the 50-60% of income level of the U.S. 

Detection of an intermediate during the unfolding process of the dimeric ketosteroid isomerase

AbstractFailure to detect the intermediate in spite of its existence often leads to the conclusion that two-state transition in the unfolding process of the protein can be justified. In contrast to the previous equilibrium unfolding experiment fitted to a two-state model by circular dichroism and fluorescence spectroscopies, an equilibrium unfolding intermediate of a dimeric ketosteroid isomerase (KSI) could be detected by small angle X-ray scattering (SAXS) and analytical ultracentrifugation. The sizes of KSI were determined to be 18.7Å in 0M urea, 17.3Å in 5.2M urea, and 25.1Å in 7M urea by SAXS. The size of KSI in 5.2M urea was significantly decreased compared with those in 0M and 7M urea, suggesting the existence of a compact intermediate. Sedimentation velocity as obtained by ultracentrifugation confirmed that KSI in 5.2M urea is distinctly different from native and fully-unfolded forms. The sizes measured by pulse field gradient nuclear magnetic resonance (NMR) spectroscopy were consistent with those obtained by SAXS. Discrepancy of equilibrium unfolding studies between size measurement methods and optical spectroscopies might be due to the failure in detecting the intermediate by optical spectroscopic methods. Further characterization of the intermediate using 1H NMR spectroscopy and Kratky plot supported the existence of a partially-folded form of KSI which is distinct from those of native and fully-unfolded KSIs. Taken together, our results suggest that the formation of a compact intermediate should precede the association of monomers prior to the dimerization process during the folding of KSI