An evolutionary approach to automatic synthesis of high-performance analog integrated circuits

This paper presents an analog integrated circuit synthesis system based on an evolutionary approach. The system contains several novel features. One of these is the high-performance optimization algorithm, which is a combination of evolutionary strategies and simulated annealing. Modeling of dc parameters is done via a fast dc simulator developed for this purpose whereas modeling of ac parameters can be done either with user-defined equations or with neural-fuzzy performance models trained from SPICE simulations. Another novel feature of the system is the incorporation of matching properties of devices. This way, the optimized circuit becomes tolerant to process variations. The synthesis system has been tested on several independent examples and synthesized circuits have been verified functionally with SPICE simulations. Finally, a prototype chip composed of the three examples has been manufactured. The measurement results have demonstrated the validity of the synthesis system on silicon.     

All Solution‐Based Fabrication of Copper Oxide Thin Film/Cobalt‐Doped Zinc Oxide Nanowire Heterojunctions

Versatile and intriguing solution‐based processes are utilized to synthesize nanostructured materials for device applications to reduce material production and device fabrication costs. This study presents results on the fabrication and characterization of copper oxide (CuO) coated cobalt‐doped zinc oxide nanowires (Co‐doped ZnO NWs)‐based heterojunction diodes prepared by a two‐step synthesis route through combined hydrothermal growth and sol–gel spin coating. Highly dense, well‐ordered, undoped, and Co‐doped ZnO NWs were successfully grown by hydrothermal method. Complementary CuO thin films were synthesized by sol–gel method and subsequently coated onto both undoped and Co‐doped ZnO NWs through spin‐coating technique. Enhanced diode properties with a rectification ratio of 10³ at ±2 V and an ideality factor of n = 2.4 (in dark) were obtained for Co‐doped ZnO NWs‐based heterojunction diodes. The obtained results demonstrated that the investigated heterojunction diode structure fabricated by facile and cost‐effective solution‐based processes can be a promising candidate for the next generation optoelectronic devices.     

A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques

Localization of a wireless device using the time-ofarrivals (TOAs) from different base stations has been studied extensively in the literature. Numerous localization algorithms with different accuracies, computational complexities, a-priori knowledge requirements, and different levels of robustness against non-line-of-sight (NLOS) bias effects also have been reported. However, to our best knowledge, a detailed unified survey of different localization and NLOS mitigation algorithms is not available in the literature. This paper aims to give a comprehensive review of these different TOA-based localization algorithms and their technical challenges, and to point out possible future research directions. Firstly, fundamental lower bounds and some practical estimators that achieve close to these bounds are summarized for line-of-sight (LOS) scenarios. Then, after giving the fundamental lower bounds for NLOS systems, different NLOS mitigation techniques are classified and summarized. Simulation results are also provided in order to compare the performance of various techniques. Finally, a table that summarizes the key characteristics of the investigated techniques is provided to conclude the paper.     

Evolution-based design of neural fuzzy networks using self-adaptinggenetic parameters

In this paper, an evolution-based approach to design of neural fuzzy networks is presented. The proposed strategy optimizes the whole fuzzy system with minimum rule number according to given specifications, while training the network parameters. The approach relies on an optimization tool, which combines evolution strategies and simulated annealing algorithms in finding the global optimum solution. The optimization variables include membership function parameters and rule numbers which are combined with genetic parameters to create diversity in the search space due to self-adaptation. The optimization technique is independent of the topology under consideration and capable of handling any type of membership function. The algorithmic details of the optimization methodology are discussed in detail, and the generality of the approach is illustrated by different examples     

Local linear perceptrons for classification

A structure composed of local linear perceptrons for approximating global class discriminants is investigated. Such local linear models may be combined in a cooperative or competitive way. In the cooperative model, a weighted sum of the outputs of the local perceptrons is computed where the weight is a function of the distance between the input and the position of the local perceptron. In the competitive model, the cost function dictates a mixture model where only one of the local perceptrons give output. Learning of the local models' positions and the linear mappings they implement are coupled and both supervised. We show that this is preferable to the uncoupled case where the positions are trained in an unsupervised manner before the separate, supervised training of mappings. We use goodness criteria based on the cross-entropy and give learning equations for both the cooperative and competitive cases. The coupled and uncoupled versions of cooperative and competitive approaches are compared among themselves and with multilayer perceptrons of sigmoidal hidden units and radial basis functions (RBFs) of Gaussian units on the application of recognition of handwritten digits. The criteria of comparison are the generalization accuracy, learning time, and the number of free parameters. We conclude that even on such a high-dimensional problem, such local models are promising. They generalize much better than RBF's and use much less memory. When compared with multilayer perceptrons, we note that local models learn much faster and generalize as well and sometimes better with comparable number of parameters.     

Influence of thermal annealing on microstructural,morphological, optical properties and surface electronic structure of copper oxide thin films

In this study, effect of the post-deposition thermal annealing on copper oxide thin films has been systemically investigated. The copper oxide thin films were chemically deposited on glass substrates by spin-coating. Samples were annealed in air at atmospheric pressure and at different temperatures ranging from 200 to 600°C. The microstructural, morphological, optical properties and surface electronic structure of the thin films have been studied by diagnostic techniques such as X-ray diffraction (XRD), Raman spectroscopy, ultraviolet–visible (UV–VIS) absorption spectroscopy, field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS). The thickness of the films was about 520 nm. Crystallinity and grain size was found to improve with annealing temperature. The optical bandgap of the samples was found to be in between 1.93 and 2.08 eV. Cupric oxide (CuO), cuprous oxide (Cu₂O) and copper hydroxide (Cu(OH)₂) phases were observed on the surface of as-deposited and 600 °C annealed thin films and relative concentrations of these three phases were found to depend on annealing temperature. A complete characterization reported herein allowed us to better understand the surface properties of copper oxide thin films which could then be used as active layers in optoelectronic devices such as solar cells and photodetectors.     

An experimental investigation of flow and heat transfer characteristics over blocked surfaces in laminar and turbulent flows

Flow and heat transfer measurements were obtained over a blocked surface mounted on a low speed wind tunnel in order to investigate the combined the effects of free stream velocities and the different size of rectangular blocks on the flow and heat transfer characteristics. Mean velocity and turbulence intensities were measured by a constant temperature anemometer and wall temperatures by copper-constant thermocouple and static pressures by a micro-manometer, respectively. It was found that the flow separations and reattachments were occurred before the first blocks, on the first blocks, between blocks and after the last blocks. The blocked surface area and flow separation caused not only heat transfer enhancement but higher turbulence levels as well. The average Stanton numbers, for block heights of 10, 15 and 20 mm, were higher than those of flat surface by 82%, 95%, 113% in laminar and 27%, 38%, 50% in turbulent, respectively. These results showed that heat transfer enhancement on the blocked surface increased with block heights and become more pronounced in laminar than that of turbulent flows.     

Photoinduced Electron Transfer Between Pyridine Coated Cadmium Selenide Quantum Dots and Single Sheet Graphene

Interest in graphene as a two‐dimensional quantum‐well material for energy applications and nanoelectronics has increased exponentially in the last few years. The recent advances in large‐area single‐sheet fabrication of pristine graphene have opened unexplored avenues for expanding from nano‐ to meso‐scale applications. The relatively low level of absorptivity and the short lifetimes of excitons of single‐sheet graphene suggest that it needs to be coupled with light sensitizers in order to explore its feasibility for photonic applications, such as solar‐energy conversion. Red‐emitting CdSe quantum dots are employed for photosensitizing single‐sheet graphene with areas of several square centimeters. Pyridine coating of the quantum dots not only enhances their adhesion to the graphene surface, but also provides good electronic coupling between the CdSe and the two‐dimensional carbon allotrope. Illumination of the quantum dots led to injection of n‐carrier in the graphene phase. Time‐resolved spectroscopy reveals three modes of photoinduced electron transfer between the quantum dots and the graphene occurring in the femtosecond and picosecond time‐domains. Transient absorption spectra provide evidence for photoinduced hole‐shift from the CdSe to the pyridine ligands, thereby polarizing the surface of the quantum dots. That is, photoinduced electrical polarization, which favors the simultaneous electron transfer from the CdSe to the graphene phase. These mechanistic insights into the photoinduced interfacial charge transfer have a promising potential to serve as guidelines for the design and development of composites of graphene and inorganic nanomaterials for solar‐energy conversion applications.