基于双面反射镜的N×N光开关的特性分析和实验研究

报道了基于双面反射镜的N×N光开关器件。介绍了使用双面反射镜的2×2, 4×4光开关的集成光路设计和工作原理; 采用Benes网络, 以2×2和4×4光开关为基本单元的N×N光开关器件的整体结构, 并根据“一笔画”原理, 分析了4×4, 8×8和16×16光开关矩阵的可重排无阻塞特性和光开关矩阵的光路选择算法。最后, 基于2×2, 4×4光开关技术制备了16×16光开关矩阵。测试表明, 该器件具有良好的插入损耗、回波损耗、串扰和开关时间等性能, 从而验证了设计思想和工艺的可行性。在基于双面反射镜的光开关矩

Improving performance of polymer photovoltaic devices using an annealing-free approach via construction of ordered aggregates in solution

Low crystalline order has been proved to be one of the main hindrances for achieving high performance devices based on thin films composed of crystallizable polymer. In this work, we use a facile method to substantially improve crystallinity of poly(3-hexylthiophene) (P3HT) in its pure or composite film via the construction of ordered precursors in the solution used for thin film deposition. These improvements have been confirmed by bright-field transmission electron micrography, electron diffraction, UV-Vis absorption and wide-angle X-ray diffraction.

Solvent-vapor treatment induced performance enhancement of poly(3-hexylthiophene): methanofullerene bulk-heterojunction photovoltaic cells

The authors report enhanced poly(3-hexylthiophene) (P3HT):methanofullerene (PCBM) bulk-heterojunction photovoltaic cells via 1,2-dichlorobenzene (DCB) vapor treatment and thermal annealing. DCB vapor treatment can induce P3HT self-organizing into ordered structure leading to enhanced absorption and high hole mobility. Further annealing the device at a high temperature, PCBM molecules begin to diffuse into aggregates and together with the ordered P3HT phase form bicontinuous pathways in the entire layer for efficient charge separation and transport. Compared to the control device that is merely annealed, optical absorption, short-circuit current, and power conversion efficiency are increased for the DCB vapor-treated cell.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79, 1.45, 1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

Dynamic power management approaches based on neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79 . 1.45 . 1.18-competitive separately for traditional timeout PM . adaptive predictive PM and stochastic PM.

Transport-determined early growth and development of jack mackerel Trachurus japonicus juveniles immigrating into Sagami Bay, Japan

Oceanographic conditions and transport processes are often critical factors that affect the early growth, survival and recruitment of marine fishes. Sagittal otoliths were analysed to determine age and early growth for 381 jack mackerel (Trachurus japonicus) juveniles from Sagami Bay on the Pacific coast of Japan. Two separate hatching periods ( December and February-March) were identified. They originated from the spawning grounds in the East China Sea. Early growth and developmental rates of December-hatching fish were lower than those for February-March-hatching fish. It is likely that these differences were determined in the Kuroshio Current during transport from the spawning grounds to Sagami Bay, and the lower December water temperatures in the bay. Origin and hatch dates of juveniles in Sagami Bay were in contrast to previous research on Fukawa Bay, where April-or-later-hatching fish from spawning grounds in the coastal waters of southern Japan constituted about half of the juvenile population. Management of these two jack mackerel stocks needs to consider these differences in hatch date composition and spawning origins, as these differences could affect early growth and subsequent mortality.

hyo-xtm: a set of hyper-graph operations on xml topic map toward knowledge management

Knowledge management is a critical issue for the next-generation web application, because the next-generation web is becoming a semantic web, a knowledge-intensive network. XML Topic Map (XTM), a new standard, is appearing in this field as one of the structures for the semantic web. It organizes information in a way that can be optimized for navigation. In this paper, a new set of hyper-graph operations on XTM (HyO-XTM) is proposed to manage the distributed knowledge resources.HyO-XTM is based on the XTM hyper-graph model. It is well applied upon XTM to simplify the workload of knowledge management.The application of the XTM hyper-graph operations is demonstrated by the knowledge management system of a consulting firm. HyO-XTM shows the potential to lead the knowledge management to the next-generation web.