A Broadband Dual Circularly Polarized Compact Printed Monopole Antenna

Wireless Personal Communications - Now-a-days the most common pretentious disease is the lung cancer, which has become more prevalent in the world that primarily infects the pulmonary nodules of...     

Nutritional components as mitigators of cellular senescence in organismal aging: a comprehensive review

Food Science and Biotechnology - The process of cellular senescence is rapidly emerging as a modulator of organismal aging and disease. Targeting the development and removal of senescent cells is...     

Effect of 100 KeV Ar+ ion beam irradiation on ZnO thin films – Influence of morphology vis-a-vis electrode/electrolyte interface and its impact on photoelectrochemical water splitting

The present study attempts quantitative determination of changes in the morphological surface features viz. fractal dimension, lower and upper cut off length scale through Power Spectral Density analysis prior to and after irradiation of 100 KeV Ar⁺ ion beam at incidence angles of 0°, 40° and 60° on ZnO thin films. All the unirradiated and irradiated samples are subjected to photoelectrochemical characterization and a correlation between photoelectrochemical performance and morphological parameters is established. Sample irradiated at 40° angle at the fluence of 5 × 10¹⁶ ions/cm² is found to possess maximum fractal dimension of 2.72, lower and upper cut off length scale of 3.16 nm and 63.00 nm respectively. This sample exhibits maximum photocurrent density of 3.19 mA/cm² and applied bias photon-to-current efficiency of 1.12% at 1.23 V/RHE. Hydrogen gas collected for duration of 1 h for the same sample was ~4.83 mLcm^?2.     

Effects of DEM Source,Spatial Resolution and Drainage Area Threshold Values on Hydrological Modeling

Water Resources Management - Automated computation of hydrological and morphometric parameters of any watershed are not only depended on Digital Elevation Model (DEM) resolution but also affected...     

Blind OFDM symbol synchronization in ISI channels

We present a new algorithm for blind symbol synchronization in orthogonal frequency division multiplexing (OFDM) systems. The new algorithm declares symbol synchronization when a certain autocorrelation matrix, constructed from the received signal, achieves minimum rank. Unlike previously proposed blind algorithms, the new rank method guarantees correct symbol synchronization, even in the presence of intersymbol interference. Also, it does not assume that the OFDM time samples are i.i.d. In particular, the rank method works even with OFDM systems that employ pulse shaping. The increased complexity of the algorithm would be acceptable for systems, such as fixed-receiver broadcast systems, that require guaranteed synchronization under all conditions.     

Fuzzy Multiobjective and Linear Programming Based Management Models for Optimal Land-Water-Crop System Planning

In this article, linear programming and fuzzy optimization models are developed for planning and management of available land-water-crop system of Mahanadi-Kathajodi delta in eastern India. The models are used to optimize the economic return, production and labour utilization, and to search the related cropping patterns and intensities with specified land, water, fertilizer and labour availability, and water use pattern constraints. Due to extreme backwardness of the study area, it has been decided to keep all the three objectives of the linear programming models at the same priority level to obtain the compromised solution in a fuzzy environment that incorporates the imprecision in fuzzy goals and fuzzy constraints. These non-structural models facilitate the conjunctive use of available surface water and groundwater resources. A comparative evaluation along with the benefit-cost ratios of the existing and proposed farming systems is also presented.     

Electroless Plating of Copper on Fluorinated Polyimide Films Modified by Plasma Graft Copolymerization and UV‐induced Graft Copolymerization with 4‐Vinylpyridine

Surface modification of two types of fluorinated polyimide (FPI) films, either by plasma polymerization and deposition of 4‐vinylpyridine (4VP) or by UV‐induced graft copolymerization with 4VP under atmospheric conditions, was carried out for adhesion enhancement with the electrolessly deposited copper. X‐ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) results revealed that the pyridine groups in the plasma polymerized 4VP (pp‐4VP) layer could be preserved to a large extent under proper glow discharge conditions. The grafted 4VP layer with well‐preserved pyridine groups was used not only as the chemisorption sites for the palladium complexes (without the need for prior sensitization by SnCl₂) during the electroless plating of copper, but also as an adhesion promotion layer for the electrolessly deposited copper. The T‐peel adhesion strength of the electrolessly deposited copper with both the 4VP plasma‐polymerized FPI (pp‐4VP‐FPI) film and the 4VP graft‐copolymerized FPI (4VP‐g‐FPI) film was much higher than that of the electrolessly deposited copper with the pristine or the Ar plasma‐treated FPI films. The high adhesion strength between the electrolessly deposited copper and the surface‐modified FPI film was attributed to the fact that the plasma‐polymerized and the UV graft‐copolymerized 4VP chains were covalently tethered on the FPI surfaces, as well as the fact that these grafted 4VP polymer chains were spatially and reactively distributed into the copper matrix.

     

Effect of AlN addition on the electrical resistivity of pressureless sintered SiC ceramics with B4C and C

The effect of 0–12 wt% AlN addition on the electrical resistivity of SiC ceramics pressureless sintered with 0.7 wt% B₄C and 2.5 wt% C additives was investigated. The elemental analysis of SiC grains revealed a codoping of Al and N in the SiC lattice with a higher N concentration with 1 wt% AlN addition and a higher Al concentration with 12 wt% AlN addition. The electrical resistivity decreased by four orders of magnitude (1.7 × 10⁵ → 8.3 × 10¹ Ω cm) with 1 wt% AlN addition due to the increased carrier density (1.7 × 10¹⁰ → 2.3 × 10¹⁵ cm⁻³) caused by excess N-derived donors. However, subsequent AlN addition (4 → 12 wt%) led to an increase (2.9 × 10³ → 1.2 × 10⁴ Ω‧cm) in electrical resistivity due to (1) increased Al dopants which act as deep acceptors for trapping N-derived carriers causing a decrease in carrier density (2.3 × 10¹⁵ → 5.9 × 10¹³ cm⁻³), (2) the formation of electrically insulating SiC-AlN solid solution, and (3) the presence of electrically insulating AlN grains at the grain boundaries.     

Using dynamic time warping distances as features for improved time series classification

Dynamic time warping (DTW) has proven itself to be an exceptionally strong distance measure for time series. DTW in combination with one-nearest neighbor, one of the simplest machine learning methods, has been difficult to convincingly outperform on the time series classification task. In this paper, we present a simple technique for time series classification that exploits DTW’s strength on this task. But instead of directly using DTW as a distance measure to find nearest neighbors, the technique uses DTW to create new features which are then given to a standard machine learning method. We experimentally show that our technique improves over one-nearest neighbor DTW on 31 out of 47 UCR time series benchmark datasets. In addition, this method can be easily extended to be used in combination with other methods. In particular, we show that when combined with the symbolic aggregate approximation (SAX) method, it improves over it on 37 out of 47 UCR datasets. Thus the proposed method also provides a mechanism to combine distance-based methods like DTW with feature-based methods like SAX. We also show that combining the proposed classifiers through ensembles further improves the performance on time series classification.     

Language independent unsupervised learning of short message service dialect

Noise in textual data such as those introduced by multilinguality, misspellings, abbreviations, deletions, phonetic spellings, non-standard transliteration, etc. pose considerable problems for text-mining. Such corruptions are very common in instant messenger and short message service data and they adversely affect off-the-shelf text mining methods. Most techniques address this problem by supervised methods by making use of hand labeled corrections. But they require human generated labels and corrections that are very expensive and time consuming to obtain because of multilinguality and complexity of the corruptions. While we do not champion unsupervised methods over supervised when quality of results is the singular concern, we demonstrate that unsupervised methods can provide cost effective results without the need for expensive human intervention that is necessary to generate a parallel labeled corpora. A generative model based unsupervised technique is presented that maps non-standard words to their corresponding conventional frequent form. A hidden Markov model (HMM) over a “subsequencized” representation of words is used, where a word is represented as a bag of weighted subsequences. The approximate maximum likelihood inference algorithm used is such that the training phase involves clustering over vectors and not the customary and expensive dynamic programming (Baum–Welch algorithm) over sequences that is necessary for HMMs. A principled transformation of maximum likelihood based “central clustering” cost function of Baum–Welch into a “pairwise similarity” based clustering is proposed. This transformation makes it possible to apply “subsequence kernel” based methods that model delete and insert corruptions well. The novelty of this approach lies in that the expensive (Baum–Welch) iterations required for HMM, can be avoided through an approximation of the loglikelihood function and by establishing a connection between the loglikelihood and a pairwise distance. Anecdotal evidence of efficacy is provided on public and proprietary data.