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This paper introduces a new concept of the shaft generation system applied in marine industry where both the grid-connected operation and the stand-alone operation are required. Detailed analysis of implementing these two modes and the smooth transfer between each other are given. Experiments are also carried out to validate the usefulness and practicality of the proposed control structure.

In this work, an efficient organic upconversion device (OUD) employing the bilayer charge generation layer (CGL) of chloroaluminum phthalocyanine (ClAlPc) and C 70 was demonstrated. As a result, the current gain ratio of OUD with the sublimated ClAlPc was improved from 1 000 to 40 000 as compared the non-sublimated ones. This is because the mechanism of impurity-induced at the interface of CGL/ITO was mainly dominated the total amount of dark current density in our proposed OUD. Thus, the CGL with poor blocking efficiency might result in an increase in the hole carriers into the device.

Low-quality images are usually not only with low-resolution, but also suffer from compression artifacts (blocking artifact is treated as an example in this paper). Directly performing image super-resolution (SR) to a highly compressed (low-quality) image would also simultaneously magnify the blocking artifacts, resulting in unpleasing visual quality. In this paper, we propose a self-learning-based SR framework to simultaneously achieve single-image SR and compression artifact removal for a highly-compressed image. We argue that individually performing deblocking first, followed by SR to an image, would usually inevitably lose some image details induced by deblocking, which may be useful for SR, resulting in worse SR result. In our method, we propose to self-learn image sparse representation for modeling the relationship between low and high-resolution image patches in terms of the learned dictionaries, respectively, for image patches with and without blocking artifacts. As a result, image SR and deblocking can be simultaneously achieved via sparse representation and MCA (morphological component analysis)-based image decomposition. Experimental results demonstrate the efficacy of the proposed algorithm.

We propose a method to minimize the buffer size for applications requiring internal multiple clock frequencies and discontinuous data access. The buffer needs not only to handle synchronization between different frequencies, but also to deal with non-first-in-first-out (FIFO) type data access patterns. The proposed method transforms the minimization problem into a graph representation and adopts vertex coloring to minimize the buffer size while meeting the throughput constraints. The experimental results show that the maximum area of the buffer designed by the proposed method is 66.28% smaller than that of a comparable buffer.

This paper is concerned with sampled-data stabilization for Takagi-Sugeno (T-S) fuzzy systems by using the property of membership function deviations. A new lemma is presented to obtain an explicit estimate for the bounds of membership function deviations in sampled-data fuzzy control systems and to establish the quantitative relationship between the deviation bounds and the upper bound of sampling intervals. By using a piecewise Lyapunov-Krasovskii functional and a generalized Jensen integral inequality, a stability criterion is derived. Based on the stability criterion, a membership function deviation approach for designing a sampled-data fuzzy controller is proposed. Compared with some existing ones, the obtained results can reduce the conservativeness, which are confirmed by a numerical example.

This paper proposes a new membership function deviation approach to investigate network-based H ∞ fuzzy static output feedback control for Takagi-Sugeno fuzzy systems, where the bilateral network channels with network-induced delays and data-packet dropouts are considered. A novel lemma about the deviations of membership functions in a network environment is first established, which presents a method of determining such deviations and formulates explicitly the quantitative relationship between the deviation bounds and the maximum allowable equivalent delay bound of such a system. Then by combining the above lemma and a matrix decoupling technique, a shape-dependent design approach of H ∞ fuzzy controller is proposed in term of linear matrix inequalities. Finally, an example is given to demonstrate the effectiveness of the proposed method.

Large quantities of mullite nanowires were synthesized on mica substrates. The nanowires were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy and photoluminescence (PL) spectroscopy. The results indicate that the nanowire composition is Al5.65Si 0.35O9.175, which fits the general mullite formula of Al4+2xSi2-2xO10-x. The nanowires have a diameter range of 50-100 did and lengths of several micrometers. Aligned nanowires can also been observed at the substrate edge. Raman microscopy indicated a change in the substrate surface occurred following the formation of nanowires. The nanowires have strong photoluminescence (PL) emission bands at 310, 397, 452 and 468 nm and the oxygen-related defect in the nanowires were supposed to be responsible for these emissions