A uniplanar printed antenna with an inverted L‐shaped coupling feed for LTE/GSM/DCS/PCS/UMTS operations

A novel uniplanar printed antenna with a total size of 115 × 40 mm² is proposed for mobile device application. By using an inverted L‐shaped feeding mechanism and a meandered shorting strip, a dual‐band operation with wideband characteristic can be achieved. Here, the lower operating band is able to cover the LTE 700 and GSM 850/900 operations, while the higher operating band allows DCS 1800, PCS 1900, UMTS, and LTE 2300 operations. Furthermore, in order to increase the bandwidth of the higher operating band so that LTE 2500 operation can also be covered, an additional parasitic stub is attached to the feed line to excite a resonant frequency at around 2.72 GHz. Parametric studies via simulation are carried out, and prototype of the proposed antenna is also experimentally investigated to validate the simulated results. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

Adaptive spatial information-theoretic clustering for image segmentation

The incorporation of spatial context into clustering algorithms for image segmentation has recently received a significant amount of attention. Many modified clustering algorithms have been proposed and proven to be effective for image segmentation. In this paper, we propose a different framework for incorporating spatial information with the aim of achieving robust and accurate segmentation in case of mixed noise without using experimentally set parameters based on the original robust information clustering (RIC) algorithm, called adaptive spatial information-theoretic clustering (ASIC) algorithm. The proposed objective function has a new dissimilarity measure, and the weighting factor for neighborhood effect is fully adaptive to the image content. It enhances the smoothness towards piecewise-homogeneous segmentation and reduces the edge blurring effect. Furthermore, a unique characteristic of the new information segmentation algorithm is that it has the capabilities to eliminate outliers at different stages of the ASIC algorithm. These result in improved segmentation result by identifying and relabeling the outliers in a relatively stronger noisy environment. Comprehensive experiments and a new information-theoretic proof are carried out to illustrate that our new algorithm can consistently improve the segmentation result while effectively handles the edge blurring effect. The experimental results with both synthetic and real images demonstrate that the proposed method is effective and robust to mixed noise and the algorithm outperforms other popular spatial clustering variants.     

Reduction of flow-induced noise in a household air purifier

Journal of Mechanical Science and Technology - In this study, we propose a design for a household air purifier that reduces the flow-induced noise caused by the impeller of the fan system. The...     

Broadly wavelength-tunable external cavity lasers with extremely low power variation over tuning range

Tunable external-cavity lasers with low power variation over a broad tuning range are demonstrated using asymmetric multiple quantum-wells with a wide and flat gain. For a 2.8-/spl mu/m-wide ridge waveguide laser of cavity length 380 /spl mu/m, when used in a grating external cavity and with an antireflection coating on one facet of laser diode chip, the power variation of less than -1 dB is obtained over a range of 80 nm. This extremely low power variation is a direct result of the spectrally flat gain.     

Collision Detection and Safe Reaction Algorithm for Non-backdrivable Manipulator with Single Force/Torque Sensor

The paper presents a robust control law for homing of an autonomous robot. The proposed work aims to solve this problem for practical conditions such as random errors in commanded velocities and unknown distance sensor characteristics. The proposed steering control aligns the robot’s orientation with homing vector using arbitrary real valued distance function providing the capability to work in changing environment conditions. Finite time convergence to the equilibrium using proposed control law is achieved in the presence of bounded random velocity errors regardless of the initial position and orientation. Just the sign information as feedback supports applicability of proposed control law with any distance function. A matching parameter between panoramic images obtained at home and current positions is a function of distance between home and current positions. However, explicit relation between distance and image matching parameter is unknown. This work demonstrates the application of proposed method for visual homing based on image distance function rendering the benefit of minimal image processing. Various simulation and experimental results are presented for visual homing to support the theory presented in this paper. Advantage of proposed visual homing is also explored in changing environment conditions.     

Detecting people in dense crowds

We propose a scheme to detect individuals in any image frame of a video sequence showing densely crowded scenes against cluttered backgrounds. The method uses only spatial information, and in an initial pass through the image a trained Viola–Jones-type local detector is used to locate individuals in the densely crowded scene. This yields a large number of false alarms. Hence, in a second step, we seek to reduce the false alarms, and propose two methods for this. In the first, color information from the initially detected windows is passed to a classifier to reduce the false alarms. This classifier consists of a cascade of boosted classifiers with Haar-like features as input and is trained with color information from local windows. In the second method, a weak perspective model of an uncalibrated camera is used to further reduce the false alarm rate while maintaining the detection rate. This is based on the size and locations of the detections in the image frame, without the use of any 3D world information. Results are presented in the form of receiver operating characteristic curves. For instance, at a 79.0% detection accuracy, the false alarm rate is 20.3%.     

Metabolomics of Genetically Modified Crops

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.     

Nonwoven Ni–NiO/carbon fibers for electrochemical water oxidation

The development of technologically efficient anodes for water oxidation is crucial to improve hydrogen production via water splitting. Electrodes based on metallic active sites dispersed in carbon matrices have been shown to be an attractive way to attain this goal. However, challenges remain to prevent catalyst agglomeration that otherwise can result in a decrease of performance over time.In this work, we report an alternative and efficient method to produce nickel-nickel oxide nanoparticles-embedded in carbon nanofibers (Ni–NiO/C), by the solution blow spinning (SBS) process. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses show the carbon nanofibrillar matrix as a robust support, with well-dispersed nickel nanoparticles on the surface. The responses of the linear scanning voltammetry, cyclic voltammetry and electrochemical impedance spectroscopy demonstrate how a small fraction of nickel on the fiber surface (≈1.2–5.3%) is enough to promote substantial improvement in performance (η = 278 and 309 mV vs RHE for 10 mA cm^?2) and a significant turnover frequency (TOF) values of 1.38 (η = 278) and 1.30 s^?1 (η = 309). These promising results are correlated with a large amount of Ni³⁺ present on the fiber surfaces, as identified by X-ray Photoelectron Spectroscopy (XPS). This work provides a low-cost and rapid preparation technique that can be extended for the manufacture of a wide variety of electrodes based on metals supported on carbon nanofibers.     

A simultaneous sample-and-filter strategy for robust multi-structure model fitting

In many robust model fitting methods, obtaining promising hypotheses is critical to the fitting process. However the sampling process unavoidably generates many irrelevant hypotheses, which can be an obstacle for accurate model fitting. In particular, the mode seeking based fitting methods are very sensitive to the proportion of good/bad hypotheses for fitting multi-structure data. To improve hypothesis generation for the mode seeking based fitting methods, we propose a novel sample-and-filter strategy to (1) identify and filter out bad hypotheses on-the-fly, and (2) use the remaining good hypotheses to guide the sampling to further expand the set of good hypotheses. The outcome is a small set of hypotheses with a high concentration of good hypotheses. Compared to other sampling methods, our method yields a significantly large proportion of good hypotheses, which greatly improves the accuracy of the mode seeking-based fitting methods.