Non-line-of-sight ultraviolet single-scatter path loss model

A novel non-line-of-sight ultraviolet single-scatter path loss model for coplanar geometries is proposed on the basis of spherical coordinate system. In comparison with the classical single-scatter analytical model based on the prolate-spheroidal coordinate system, it is of a simple integral form which only depends on the variables of the zenith and receiver elevation angles. Additionally, analytical approximation for the proposed single-scatter path loss model is presented. Numerical examples on path loss are presented for various system geometries. Correspondingly, the results are verified with the classical single-scatter analytical model, which demonstrates the validity of our path loss model and the reasonability of the analytical approximation.     

Proactive defragmentation in elastic optical networks under dynamic load conditions

The main weakness of elastic optical networks (EON), under dynamic traffic conditions, stems from spectrum fragmentation. A lot of research efforts have been dedicated during recent years to spectrum defragmentation. In this work, a thorough study about proactive defragmentation is carried out. Effects of the different defragmentation parameters on the EON performance are analyzed, and appropriate values of the defragmentation period, which guarantee suitable network performance while keeping the network control complexity at reasonable values, are obtained by means of extensive simulations. Benefit obtained by applying different defragmentation strategies, in terms of increase in the supported load at a given bandwidth blocking probability, is also reported. Different traffic conditions and network topologies are simulated to assess the validity of the obtained results.     

Tough and Self‐Recoverable Thin Hydrogel Membranes for Biological Applications

Tough and self‐recoverable hydrogel membranes with micrometer‐scale thickness are promising for biomedical applications, which, however, rarely be realized due to the intrinsic brittleness of hydrogels. In this work, for the first time, by combing noncovalent DN strategy and spin‐coating method, we successfully fabricated thin (thickness: 5–100 µm), yet tough (work of extension at fracture: 10⁵–10⁷ J m^?3) and 100% self‐recoverable hydrogel membranes with high water content (62–97 wt%) in large size (≈100 cm²). Amphiphilic triblock copolymers, which form physical gels by self‐assembly, were used for the first network. Linear polymers that physically associate with the hydrophilic midblocks of the first network, were chosen for the second network. The inter‐network associations serve as reversible sacrificial bonds that impart toughness and self‐recovery properties on the hydrogel membranes. The excellent mechanical properties of these obtained tough and thin gel membranes are comparable, or even superior to many biological membranes. The in vitro and in vivo tests show that these hydrogel membranes are biocompatible, and postoperative nonadhesive to neighboring organs. The excellent mechanical and biocompatible properties make these thin hydrogel membranes potentially suitable for use as biological or postoperative antiadhesive membranes.     

Lateral‐Polarity Structure of AlGaN Quantum Wells: A Promising Approach to Enhancing the Ultraviolet Luminescence

Aluminum‐gallium‐nitride alloys (Al _x Ga_{1– x} N, 0 ≤ x ≤ 1) can emit light covering the ultraviolet spectrum from 210 to 360 nm. However, these emitters have not fulfilled their full promise to replace the toxic and fragile mercury UV lamps due to their low efficiencies. This study demonstrates a promising approach to enhancing the luminescence efficiency of AlGaN multiple quantum wells (MQWs) via the introduction of a lateral‐polarity structure (LPS) comprising both III and N‐polar domains. The enhanced luminescence in LPS is attributed to the surface roughening, and compositional inhomogeneities in the N‐polar domain. The space‐resolved internal quantum efficiency (IQE) mapping shows a higher relative IQE in N‐polar domains and near inversion domain boundaries, providing strong evidence of enhanced radiative recombination efficiency in the LPS. These experimental observations are in good agreement with the theoretical calculations, where both lateral and vertical band diagrams are investigated. This work suggests that the introduction of the LPS in AlGaN‐based MQWs can provide unprecedented tunability in achieving higher luminescence performance in the development of solid state light sources.     

A novel algorithm to study the impact of the mismatch on analog building blocks: a case study in basic 35 nm CMOS amplifiers

In this paper, the context of modeling of the impact of mismatch and statistical variations on analogue circuit building blocks is emphasized. The aim is to develop a new algorithm which predicts the statistical behavior of important parameters of an amplifier including output resistance, voltage gain and trans-conductance. The relative error of standard deviation of statistical parameters will remain less than 5% compared with the most accurate Monte-Carlo (MC) simulations using atomistic library model-cards. In comparison with other models which are based on the normal distribution of parameters, the proposed model does not need this limiting presumption. On the other hand, the proposed algorithm is more efficient compared with time consuming MC atomistic simulations.     

Analysis of multistage amplifiers with hybrid cascode feedforward compensation using a modified model for load impedance

Hybrid cascode feedforward compensation (HCFC) is an effective technique to stabilize nano-scale three-stage amplifiers driving ultra-large load capacitors. It divides the compensation capacitance and shares it between two high-speed local feedback loops embedded within the amplifier core. In this article, a systematic approach to analyze the transfer function and to evaluate the pole expressions of nano-scale HCFC amplifiers is presented. For the first time, the equivalent output impedance is successfully modeled to approximate the complicated transfer function of the HCFC amplifier without the need for lengthy pencil-and-paper calculations. An HCFC amplifier is designed and simulated in 90-nm CMOS technology, to verify the effectiveness of the new analytic approach. The simulated transfer function of the amplifier is almost identical to a calculated transfer function derived based on the new model.     

A new deep spatial transformer convolutional neural network for image saliency detection

In this paper we propose a novel deep spatial transformer convolutional neural network (Spatial Net) framework for the detection of salient and abnormal areas in images. The proposed method is general and has three main parts: (1) context information in the image is captured by using convolutional neural networks (CNN) to automatically learn high-level features; (2) to better adapt the CNN model to the saliency task, we redesign the feature sub-network structure to output a 6-dimensional transformation matrix for affine transformation based on the spatial transformer network. Several local features are extracted, which can effectively capture edge pixels in the salient area, meanwhile embedded into the above model to reduce the impact of highlighting background regions; (3) finally, areas of interest are detected by means of the linear combination of global and local feature information. Experimental results demonstrate that Spatial Nets obtain superior detection performance over state-of-the-art algorithms on two popular datasets, requiring less memory and computation to achieve high performance.     

Multilayer Graphene Broadband Terahertz Modulators with Flexible Substrate

Fabrication of terahertz modulators as simple devices with high modulation depth across a broad bandwidth is still very challenging. In this study, four different chemical vapor deposition grown multilayer graphene (MLG) modulators based on MLG/ionic liquid/gold sandwich structures have been investigated. Flexible substrates (PVC and PE) were chosen as host materials, and devices were fabricated with three different thicknesses. The resultant MLG devices can be operated at low voltages between 0 and 3.4 V providing nearly complete modulation between 0.2 and 1.5 THz with low insertion losses. Even with such low gate voltages, the devices have been doped significantly inducing 7–11-fold improvement in their sheet conductivities depending on device thickness. In addition, sheet conductivity has been improved more than three times as the graphene layer number increased from 30 to 100. With the demonstration of promising device performances, the proposed modulators can be potential candidates for applications in terahertz and related optoelectronic technologies.     

An Improved LEACH Routing Algorithm for Wireless Sensor Network

Optimization of energy consumption is major concern for the design and planning of wireless sensor networks (WSNs). Recent research has demonstrated that organizing nodes in clusters has higher energy efficiency. LEACH is the most popular routing protocol for cluster-based in WSNs, and FCM algorithm is used for the optimum number of the clusters and their location. Aiming at the shortcomings of LEACH and FCM-LEACH, which including inaccurate cluster centers, unreasonable clustering and sole data transmission mode. This paper proposes a new energy efficient routing algorithm (NF-LEACH). In the new algorithm, There are many factors have considered to prolong the network life cycle that they are the degree of membership, residual energy, base station distance and data transmission mode. Finally, the comparison among LEACH, FCM-LEACH, and NF-LEACH has been done. The results show that the NF-LEACH has the longest lifetime and the most evenly distributed amongst three algorithms.     

Fault Tolerance Mechanisms for FPGA-Based Regular Expression Matching

Traditional fault-tolerance techniques relying on spatial and temporal redundancy typically imply high power, delay, and area overheads. Cost-effective solutions often depend on system’s design and hardware platform at hand. Particularly for Field-Programmable Gate Arrays (FPGAs), soft errors on the configuration memory are a significant dependability threat. In this work, we present an extended and comprehensive fault tolerance mechanism especially suited for dealing with configuration faults on FPGA-based systems that must deal multiple failure modes. Each failure mode may present different criticality and probability of occurrence, and these properties are measured and exploited to provide low-cost solutions when compared to standard approaches such as triple modular redundancy. The exploited properties are typically found in critical monitoring systems that may trigger security- or safety-critical alarms and warnings in general. In such systems, failing to trigger an alarm when necessary is frequently regarded as more critical than providing an occasional false alarm. For instance, Regular Expression Matching (REM), a compute-intensive mechanism heavily used to perform Deep Packet Inspection in critical network applications, presents such properties, and it can be greatly accelerated by FPGAs to meet performance constraints in high-throughput networks. Therefore, we use FPGA-based REM engines as a case study to demonstrate the effectiveness of the proposed techniques. Additionally, a mutually-aware placement and scrubbing mechanism is introduced to reduce the repair time, improving the system reliability and availability. Experimental results show that the failure rate and the repair time can be reduced by 95 and 90% respectively while avoiding the costs of triplication.