Test bed for characterization and predistortion of power amplifiers

A platform of high accuracy and reliability is crucial for power amplifier (PA) designers to assess the characteristics of the PA prototype, and for the digital predistorter engineers to validate their models and algorithms. Digital processing techniques for building a test bed of high performance for PA characterization and predistortion (PD) are discussed in this article. We also proposed a novel technique to characterize the frequency responses of the vector signal generator and vector signal analyzer independently without using any other instrument. The techniques described in this article are quite useful, especially for narrowband vector transmitters and receivers, to improve their performance. These techniques were experimentally evaluated, both for characterization and PD of a class‐F PA. Test results show that using such techniques can successfully build a test bed of high accuracy and wide bandwidth. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Carbon felt-based bioelectrocatalytic flow-through detectors: Highly sensitive amperometric determination of H2O2 based on a direct electrochemistry of covalently modified horseradish peroxidase using cyanuric chloride as a linking agent

Horseradish peroxidase (HRP) was chemically modified using cyanuric chloride (CC) as a linking agent onto a carbon felt (CF), which is a microelectrode ensemble of micro carbon fiber (>7 μm, diameter) with a random three-dimensional structure. The resulting HRP-modified CF (HRP-ccCF) exhibited well-defined redox waves based on the HRP heme Fe^III/Fe^II redox couple at −0.23 V vs. Ag/AgCl (at pH 7.0), while the HRP-adsorbed CF (HRP-CF) showed no apparent redox couple in the same potential range, indicating that the chemical modification of HRP via CC facilitated the direct electron transfer (DET) between HRP and CF. The apparent heterogeneous electron transfer rate constant k_s was estimated to be 35 s⁻¹. Cyclic voltammetry and electrochemical impedance spectroscopy revealed that the interfacial properties (i.e., structure, morphology of enzyme-layer) of covalently modified HRP (HRP-ccCF) and physically adsorbed HRP (HRP-CF) are different, resulting in the difference in the electron transfer properties. The HRP-ccCF was successfully used as a working electrode unit in bioelectrocatalytic flow-through detector for highly sensitive amperometric determination of H₂O₂. Under the optimized conditions (i.e., applied potential, 0 V vs. Ag/AgCl; carrier flow rate, 3.25 ml/min; and carrier pH 7.0), the cathodic peak current of H₂O₂ linearly increased up to 3 μM (sensitivity, 1.94 μA/μM; the detection limit, 0.08 μM [S/N = 3]) with sample through-put of ca. 90 samples/h.     

An empirical anisotropy correction model for estimating land surface albedo for radiation budget studies

Land surface albedo is one of the key parameters in the radiation budget, the hydrological cycle and climate modeling studies. It is now widely understood that large errors may occur in the estimation of surface albedo without taking into consideration the anisotropy reflectance effect, which is a general feature of the earth surface. Two major anisotropic correction methods exist for the retrieval of land surface albedo under clear sky conditions. One method involves linearly converting from top of the atmosphere (TOA) albedo to surface albedo, and another is based on the inversion of the Bidirectional Reflectance Distribution Function (BRDF) model of the surface. In the present study, a new approach that utilizes an empirical model for estimating surface albedo has been proposed for snow free land surfaces under clear sky conditions. We analyzed the bidirectional reflectance data set with numerous samples representing various land cover types, which derived from POLDER/ADEOS-1 multi-angle imagery data and distributed by MEDIAS-France. Through the analysis, an empirical relation between bidirectional reflectance and albedo was established and has been discussed in detail. The proposed model can be used for direct estimation of surface albedo from a single BRF observation when the sun-target-sensor geometry is known. No BRDF model inversion scheme is necessary. The present model has no or weak dependence on the existing land surface classifications, and is insensitive to wavelength. The theoretical absolute accuracy of the estimated albedo is approximately 0.010 for visible (0.4-0.7 μm), 0.023 for near infrared (0.7-3.0 μm) and 0.016 for shortwave (0.2-3.0 μm), respectively. Albedo consistency with viewing geometry has been verified, resulting in good agreement for albedo estimated from various viewing directions. Validation of the satellite estimated albedo derived by the proposed method, using field observations were also presented and results show it can give reasonably accurate estimation. The proposed method is expected to be a suitable candidate for practical applications of albedo estimation for sensors that do not perform multi-angle observations.     

Face relighting using discriminative 2D spherical spaces for face recognition

As part of the face recognition task in a robust security system, we propose a novel approach for the illumination recovery of faces with cast shadows and specularities. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients by using the face spherical spaces properties. First, an illumination training database is generated by computing the properties of the spherical spaces out of face albedo and normal values estimated from 2D training images. The training database is then discriminately divided into two directions in terms of the illumination quality and light direction of each image. Based on the generated multi-level illumination discriminative training space, we analyze the target face pixels and compare them with the appropriate training subspace using pre-generated tiles. When designing the framework, practical real-time processing speed and small image size were considered. In contrast to other approaches, our technique requires neither 3D face models nor restricted illumination conditions for the training process. Furthermore, the proposed approach uses one single face image to estimate the face albedo and face spherical spaces. In this work, we also provide the results of a series of experiments performed on publicly available databases to show the significant improvements in the face recognition rates.     

Robot-vision architecture for real-time 6-DOF object localization

This paper presents a new robot-vision system architecture for real-time moving object localization. The 6-DOF (3 translation and 3 rotation) motion of the objects is detected and tracked accurately in clutter using a model-based approach without information of the objects’ initial positions. An object identification task and an object tracking task are combined under this architecture. The computational time-lag between the two tasks is absorbed by a large amount of frame memory. The tasks are implemented as independent software modules using stereo-vision-based methods which can deal with objects of various shapes with edges, including planar to smooth-curved objects, in cluttered environments. This architecture also leads to failure-recoverable object tracking, because the tracking processes can be automatically recovered, even if the moving objects are lost while tracking. Experimental results obtained with prototype systems demonstrate the effectiveness of the proposed architecture.     

Urban growth and change analysis using remote sensing and spatial metrics from 1975 to 2003 for Hanoi,Vietnam

Since the beginning of the ‘Doi Moi’ policy in 1986, Hanoi has witnessed significant changes in its urban areas. Landsat and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes were used to identify built-up areas in Hanoi, and spatial metrics were used to characterize urban change patterns from 1975 to 2003. Firstly, a spatial metric called the ‘percentage of like adjacency’ was used to discern urban growth patterns, which were classified into three sub-patterns: expansion growth, infill growth and outlying growth. Secondly, the driving force underlying the urbanization of the city for the 1975–1984, 1984–1992, 1992–2001, 2001–2003 periods was investigated using a spatial metric analysis programme (FRAGSTATS). The expansion of urban areas along major transportation routes in the latter 1980s was identified as the main form of urbanization in Hanoi. This paper shows the potential application of spatial metrics as secondary sources of information for supporting remotely sensed data and their use to characterize urban growth patterns.     

A Social Robot that Stands in Line

Recent research in mobile robot navigation make it feasible to utilize autonomous robots in service fields. But, such applications require more than just navigation. To operate in a peopled environment, robots should recognize and act according to human social behavior. In this paper, we present the design and implementation of one such social behavior: a robot that stands in line much as people do. The system employs stereo vision to recognize lines of people, and uses the concept of personal space for modeling the social behavior. Personal space is used both to detect the end of a line and to determine how much space to leave between the robot and the person in front of it. Our model of personal space is based on measurements from people forming lines. We demonstrate our ideas with a mobile robot navigation system that can purchase a cup of coffee, even if people are waiting in line for service.     

Spatial indexing of high-dimensional data based on relative approximation

We propose a novel index structure, the A-tree (approximation tree), for similarity searches in high-dimensional data. The basic idea of the A-tree is the introduction of virtual bounding rectangles (VBRs) which contain and approximate MBRs or data objects. VBRs can be represented quite compactly and thus affect the tree configuration both quantitatively and qualitatively. First, since tree nodes can contain a large number of VBR entries, fanout becomes large, which increases search speed. More importantly, we have a free hand in arranging MBRs and VBRs in the tree nodes. Each A-tree node contains an MBR and its children VBRs. Therefore, by fetching an A-tree node, we can obtain information on the exact position of a parent MBR and the approximate position of its children. We have performed experiments using both synthetic and real data sets. For the real data sets, the A-tree outperforms the SR-tree and the VA-file in all dimensionalities up to 64 dimensions, which is the highest dimension in our experiments. Additionally, we propose a cost model for the A-tree. We verify the validity of the cost model for synthetic and real data sets. Edited by T. Sellis. Received: December 8, 2000 / Accepted: March 20, 2002 Published online: September 25, 2002     

Real-Time Omnidirectional Image Sensors

Conventional T.V. cameras are limited in their field of view. A real-time omnidirectional camera which can acquire an omnidirectional (360 degrees) field of view at video rate and which could be applied in a variety of fields, such as autonomous navigation, telepresence, virtual reality and remote monitoring, is presented. We have developed three different types of omnidirectional image sensors, and two different types of multiple-image sensing systems which consist of an omnidirectional image sensor and binocular vision. In this paper, we describe the outlines and fundamental optics of our developed sensors and show examples of applications for robot navigation.     

Numerical prediction of sound generated from flows with a low Mach number

Numerical computations of sound generated from flows with a low Mach number are presented based on Lighthill’s acoustic analogy with an assumption that sound does not alter the flow field from which it is generated. The source fluctuations of the flow field are computed by a large-eddy simulation (LES) with Dynamic Smagorinsky Model (DSM) and they are fed to the following acoustical computation as input data. An explicit/implicit finite element method with second order accuracy both in time and space is used for flow field discretization. The method is applied to the prediction of sound in three different classes of problems: far-field sound generated from flow around a bluff body, sound resulting from blade-stator interaction of turbomachinery and sound due to a turbulent boundary layer on an aerofoil. The computed frequency spectra of the sound show a fairly good agreement with the measured spectra for all the cases.