Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional layers getting deeper and deeper in recent years, the enormous computational complexity makes it difficult to be deployed on embedded systems with limited hardware resources. In this paper, we propose two computation-performance optimization methods to reduce the redundant convolution kernels of a CNN with performance and architecture constraints, and apply it to a network for super resolution (SR). Using PSNR drop compared to the original network as the performance criterion, our method can get the optimal PSNR under a certain computation budget constraint. On the other hand, our method is also capable of minimizing the computation required under a given PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on Circuits and Systems (ISCAS

A note on eigenvalues of random block Toeplitz matrices with slowly growing bandwidth

This paper can be thought of as a remark of \cite{llw}, where the authors studied the eigenvalue distribution $\mu_{X_N}$ of random block Toeplitz band matrices with given block order $m$. In this note we will give explicit density functions of $\lim\limits_{N\to\infty}\mu_{X_N}$ when the bandwidth grows slowly. In fact, these densities are exactly the normalized one-point correlation functions of $m\times m$ Gaussian unitary ensemble (GUE for short). The series $\{\lim\limits_{N\to\infty}\mu_{X_N}|m\in\mathbb{N}\}$ can be seen as a transition from the standard normal distribution to semicircle distribution. We also show a similar relationship between GOE and block Toeplitz band matrices with symmetric blocks.Comment: 6 page

The Key Artificial Intelligence Technologies in Early Childhood Education: A Review

Artificial Intelligence (AI) technologies have been applied in various domains, including early childhood education (ECE). Integration of AI educational technology is a recent significant trend in ECE. Currently, there are more and more studies of AI in ECE. To date, there is a lack of survey articles that discuss the studies of AI in ECE. In this paper, we provide an up-to-date and in-depth overview of the key AI technologies in ECE that provides a historical perspective, summarizes the representative works, outlines open questions, discusses the trends and challenges through a detailed bibliometric analysis, and provides insightful recommendations for future research. We mainly discuss the studies that apply AI-based robots and AI technologies to ECE, including improving the social interaction of children with an autism spectrum disorder. This paper significantly contributes to provide an up-to-date and in-depth survey that is suitable as introductory material for beginners to AI in ECE, as well as supplementary material for advanced users.Comment: 39 pages, 9 figures, 4 table

Quantum heat valve and diode of strongly coupled defects in amorphous material

The mechanical strain can control the frequency of two-level atoms in amorphous material. In this work, we would like to employ two coupled two-level atoms to manipulate the magnitude and direction of heat transport by controlling mechanical strain to realize the function of a thermal switch and valve. It is found that a high-performance heat diode can be realized in the wide Piezo voltage range at different temperatures. We also discuss the dependence of the rectification factor on temperatures and couplings of heat reservoirs. We find that the higher temperature differences correspond to the larger rectification effect. The asymmetry system-reservoir coupling strength can enhance the magnitude of heat transfer, and the impact of asymmetric and symmetric coupling strength on the performance of the heat diode is complementary. It may provide an efficient way to modulate and control heat transport's magnitude and flow preference. This work may give insight into designing and tuning quantum heat machines.Comment: 10 pages, 9 figures;Accepted for publication in Physical Review

Quantum heat valve and entanglement in superconducting LCLC resonators

Quantum superconducting circuit with flexible coupler has been a powerful platform for designing quantum thermal machines. In this letter, we employ the tunable coupling of two superconducting resonators to realize a heat valve by modulating magnetic flux using a superconducting quantum interference device (SQUID). It is shown that a heat valve can be realized in a wide parameter range. We find a consistent relation between the heat current and quantum entanglement, which indicates the dominant role of entanglement on the heat valve. It provides an insightful understanding of quantum features in quantum heat machines.Comment: 9 figures, 4 figure

Evaluation the activity of alveolar echinococcosis: A comparison between 18F-FDG PET and spectral CT

AbstractPurposeTo assess the iodine concentration of hepatic alveolar echinococcosis (HAE) using spectral computed tomography (CT) with comparison of [18F] fluorodeoxyglucose positron-emission tomography (18F-FDG PET), and to estimate the value of spectral CT for evaluation of HAE activity.Materials and methods18 patients with histologically confirmed or clinically proved HAE underwent spectral CT and 18F-FDG PET examinations. After three-phase scanning, the quantitative iodine-based material decomposition images and optimal monochromatic image of spectral CT were reconstructed and iodine concentration (IC) was measured in different organizational structures.Results18F-FDG PET identified increased metabolic activity in the corresponding lesions in 13 patients (13/18, 72.2%). The iodine concentration in marginal zone of lesion were significantly higher than in solid component of lesion and normal liver parenchyma during PVP and VP. The iodine value of edge tissue of the lesion and normal liver and iodine value of normal liver tissues showed statistically significant difference (P < 0.001). There was correlation between IC and SUVmax in marginal zone of HAE lesion, it was highest during PVP (r = 0.873, p < 0.001). There was low correlation between CT values and SUVmax.ConclusionThere was good correlation between spectral CT and 18F-FDG PET. Spectral CT could be recommended as a more practical tool in the clinical routine

Enhancing Hydrogen Generation Through Nanoconfinement of Sensitizers and Catalysts in a Homogeneous Supramolecular Organic Framework.

Enrichment of molecular photosensitizers and catalysts in a confined nanospace is conducive for photocatalytic reactions due to improved photoexcited electron transfer from photosensitizers to catalysts. Herein, the self-assembly of a highly stable 3D supramolecular organic framework from a rigid bipyridine-derived tetrahedral monomer and cucurbit[8]uril in water, and its efficient and simultaneous intake of both [Ru(bpy)3 ]2+ -based photosensitizers and various polyoxometalates, that can take place at very low loading, are reported. The enrichment substantially increases the apparent concentration of both photosensitizer and catalyst in the interior of the framework, which leads to a recyclable, homogeneous, visible light-driven photocatalytic system with 110-fold increase of the turnover number for the hydrogen evolution reaction