Design of 5.5 GHz linear low noise amplifier using post distortion technique with body biasing

A highly linear 5.5 GHz low noise amplifier (LNA) has been designed exploiting source inductive degeneration topology by using post distortion linearization techniques in 0.18 m CMOS technology. This technique improves the input third order intercept point \((IIP_{3})\) of a low noise amplifier. For enhancing the linearity, this technique used a diode connected MOSFET as IMD sinker and forward body biased which is done in cadence tool. The proposed low noise amplifier achieves high \(IIP_{3}\) by using two transistors, main and auxiliary transistors. Also source inductive degeneration topology is employed in the proposed LNA to optimize the noise figure (NF) and \(S_{11}\) at high frequency. In order to reduce power consumption and threshold voltage, Forward Body Biased technique was implemented. In this paper, the first section discusses the most widely used eight linearization techniques and in the second section, the proposed circuit is represented along with its employed topology, techniques and the simulated results. The proposed LNA achieves a simulated third order input intercept \((IIP_{3})\) of 9.20 dBm while consuming 10.8 mW from a power supply of 1.8 V. it also exhibits a measured gain of 11.34 dB and NF, NF of 2.33 dB.     

Multi‐band pattern reconfigurable Yagi‐Uda antenna

In this study, novel designs of single‐band and tri‐band pattern reconfigurable antennas are proposed. The design of single‐band pattern reconfigurable antenna is accomplished by the use of varactor diodes with the parasitic elements placed on both sides of the driven conventional printed dipole antenna. By tuning the capacitance of varactor, the antenna operates in four different configurations of radiation pattern which include bi‐directional end‐fire, broadside, and uni‐directional end‐fire radiation patterns. The tri‐band pattern reconfigurable antenna design is achieved by the use of parasitic elements on both sides of a tri‐band driven dipole antenna. Dual‐band LC resonators are used as loading elements along the arms of printed dipole to get two lower order modes in addition to the reference dipole mode, resulting in a triband operation of the driven element. The electrical lengths of the parasitic elements with respect to the tri‐band driven element are controlled by suitably embedding varactor and PIN diodes with them. The proposed tri‐band antenna operates in ten different configurations of radiation patterns in the three operating bands. Fully functional prototypes of single‐band and tri‐band pattern reconfigurable antennas along with the DC bias networks have been fabricated to validate the results obtained in simulation.     

On negative results when using sentiment analysis tools for software engineering research

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact of the choice of a sentiment analysis tool on software engineering studies by conducting a simple study of differences in issue resolution times for positive, negative and neutral texts. We repeat the study for seven datasets (issue trackers and Stack Overflow questions) and different sentiment analysis tools and observe that the disagreement between the tools can lead to diverging conclusions. Finally, we perform two replications of previously published studies and observe that the results of those studies cannot be confirmed when a different sentiment analysis tool is used.     

Improved gait recognition by gait dynamics normalization

Potential sources for gait biometrics can be seen to derive from two aspects: gait shape and gait dynamics. We show that improved gait recognition can be achieved after normalization of dynamics and focusing on the shape information. We normalize for gait dynamics using a generic walking model, as captured by a population Hidden Markov Model (pHMM) defined for a set of individuals. The states of this pHMM represent gait stances over one gait cycle and the observations are the silhouettes of the corresponding gait stances. For each sequence, we first use Viterbi decoding of the gait dynamics to arrive at one dynamics-normalized, averaged, gait cycle of fixed length. The distance between two sequences is the distance between the two corresponding dynamics-normalized gait cycles, which we quantify by the sum of the distances between the corresponding gait stances. Distances between two silhouettes from the same generic gait stance are computed in the linear discriminant analysis space so as to maximize the discrimination between persons, while minimizing the variations of the same subject under different conditions. The distance computation is constructed so that it is invariant to dilations and erosions of the silhouettes. This helps us handle variations in silhouette shape that can occur with changing imaging conditions. We present results on three different, publicly available, data sets. First, we consider the HumanlD Gait Challenge data set, which is the largest gait benchmarking data set that is available (122 subjects), exercising five different factors, i.e., viewpoint, shoe, surface, carrying condition, and time. We significantly improve the performance across the hard experiments involving surface change and briefcase carrying conditions. Second, we also show improved performance on the UMD gait data set that exercises time variations for 55 subjects. Third, on the CMU Mobo data set, we show results for matching across different walking speeds. It is worth noting that there was no separate training for the UMD and CMU data sets.     

A simple strategy for calibrating the geometry of light sources

We present a methodology for calibrating multiple light source locations in 3D from images. The procedure involves the use of a novel calibration object that consists of three spheres at known relative positions. The process uses intensity images to find the positions of the light sources. We conducted experiments to locate light sources in 51 different positions in a laboratory setting. Our data shows that the vector from a point in the scene to a light source can be measured to within 2.7±4° at α=.05 (6 percent relative) of its true direction and within 0.13±.02 m at α=.05 (9 percent relative) of its true magnitude compared to empirically measured ground truth. Finally, we demonstrate how light source information is used for color correction     

Reducing the overhead of dynamic compilation

The execution model for mobile, dynamically‐linked, object‐oriented programs has evolved from fast interpretation to a mix of interpreted and dynamically compiled execution. The primary motivation for dynamic compilation is that compiled code executes significantly faster than interpreted code. However, dynamic compilation, which is performed while the application is running, introduces execution delay. In this paper we present two dynamic compilation techniques that enable high performance execution while reducing the effect of this compilation overhead. These techniques can be classified as (1) decreasing the amount of compilation performed, and (2) overlapping compilation with execution. We first present and evaluate lazy compilation, an approach used in most dynamic compilation systems in which individual methods are compiled on‐demand upon their first invocation. This is in contrast to eager compilation, in which all methods in a class are compiled when a new class is loaded. In this work, we describe our experience with eager compilation, as well as the implementation and transition to lazy compilation. We empirically detail the effectiveness of this decision. Our experimental results using the SpecJVM Java benchmarks and the Jalapeño JVM show that, compared to eager compilation, lazy compilation results in 57% fewer methods being compiled and reductions in total time of 14 to 26%. Total time in this context is compilation plus execution time. Next, we present profile‐driven, background compilation, a technique that augments lazy compilation by using idle cycles in multiprocessor systems to overlap compilation with application execution. With this approach, compilation occurs on a thread separate from that of application threads so as to reduce intermittent, and possibly substantial, delay in execution. Profile information is used to prioritize methods as candidates for background compilation. Methods are compiled according to this priority scheme so that performance‐critical methods are invoked using optimized code as soon as possible. Our results indicate that background compilation can achieve the performance of off‐line compiled applications and masks almost all compilation overhead. We show significant reductions in total time of 14 to 71% over lazy compilation. Copyright © 2001 John Wiley & Sons, Ltd.     

Ferromagnetic mixed tribridged dinuclear copper(II) complex [Cu2(OAc)2(OH)(dpa)2]PF6 · H2O (dpa = 2,2′-dipyridylamine): 3D superstructure based on hydrogen bond and π…π interaction

A new dinuclear complex [Cu₂(OAc)₂(OH)(dpa)₂] PF₆ · H₂O (1) is prepared and structurally and magneto-structurally characterized. The monocationic core contains one acetate in familiar bidentate η¹:η¹:μ₂-bridge and another in the rare monoatomic bridge along with one hydroxo intermediary. 1 packs through N–H…O and O–H…O hydrogen bonds and π…π interaction resulting a 3D supramolecular continuum and displays high-energy intraligand ¹(π − π^*) fluorescence and intraligand ³(π − π^*) phosphorescence in glassy solution.     

Statistical motion model based on the change of feature relationships: human gait-based recognition

We offer a novel representation scheme for view-based motion analysis using just the change in the relational statistics among the detected image features, without the need for object models, perfect segmentation, or part-level tracking. We model the relational statistics using the probability that a random group of features in an image would exhibit a particular relation. To reduce the representational combinatorics of these relational distributions, we represent them in a Space of Probability Functions (SoPF), where the Euclidean distance is related to the Bhattacharya distance between probability functions. Different motion types sweep out different traces in this space. We demonstrate and evaluate the effectiveness of this representation in the context of recognizing persons from gait. In particular, on outdoor sequences: (1) we demonstrate the possibility of recognizing persons from not only walking gait, but running and jogging gaits as well; (2) we study recognition robustness with respect to view-point variation; and (3) we benchmark the recognition performance on a database of 71 subjects walking on soft grass surface, where we achieve around 90 percent recognition rates in the presence of viewpoint variation.     

Determination of various impurities in synthetic diamond powder

Impurities in industrial synthetic diamond powder samples were analyzed by X-ray diffraction (XRD) and Flame Atomic Absorption Spectrometry (FAAS). Specimen for FAAS is required in solution form. Diamonds are chemically inert to most acids and alkalies. Carbon was removed as CO₂ on heating and estimated gravimetrically. The remaining residue was fused with di-lithium tetraborate and dissolved in nitric acid. Impurities such as Si, Al, Fe, Ca, Mg, W, Na, Co and Ni were then determined by FAAS. Crystalline phases of major impurities were identified by XRD.