Comparative study of crystallization processes in Sb2Te3 films using laser and thermal annealing techniques

Adherent and pin-hole free amorphous Sb₂Te₃ thin films have been obtained by vacuum evaporation at substrate temperatures ≤25 °C. The films have been crystallized by thermal and laser annealing, and the crystallization processes monitored as a function of annealing temperature and laser scan speed. A comparative study of topography reveals disk-shaped crystallized areas in thermal crystallization and dendrite growth in the laser induced process. The crystallized films in both cases contain a single Sb₂Te₃ phase. Activation energy of 2 eV for crystallization, determined using differential scanning calorimetery indicates good room temperature stability of the amorphous states.     

Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction (MOMPSO)

Software testing plays a pivotal role in entire software development lifecycle. It provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not required. These kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite, fault-tolerance, defects due to uncovered-statements and overall-performance at the time of execution. With this objective, the proposed a new Modified Particle Swarm optimization used for multi-objective test suite optimization. The experiment results involving six subject programs show that MOMPSO method can outer perform with respect to both reduction rate (90.78% to 100%) and failure detection rate (44.56% to 55.01%). Results proved MOMPSO outperformed the other stated algorithms.     

Sources of New Ideas for Charity Fundraising: An Empirical Study

Intense competition in the UK charity fundraising market and the near continuous need for charities to acquire new supporters, reactivate lapsed donors and encourage first time donors to make further gifts has resulted in charities needing repeatedly to initiate novel fundraising campaigns. The starting point for an innovative campaign is an idea or set of ideas that will attract public attention, differentiate a charity from other fundraising organizations and distinguish the charity's current marketing activities from those undertaken in the past. An important but neglected issue in the charity idea creation field is the question of where and how fundraising organizations source their ideas for new campaigns. This empirical study identified (i) the main sources of fresh ideas for fundraising employed by a sample of 417 British charities, and (ii) certain antecedents of a charity's use of various categories of sources. Potential connections between particular types of idea source and managerial satisfaction with both the creative quality of the ideas obtained and the financial revenues derived from these ideas were also examined.     

Impact of applying pre-processing techniques for improving classification accuracy

Image denoising is a procedure aimed at removing noise from images while retaining as many important signal features as possible. Many images suffer from poor contrast due to inadequate illumination or finite sensitivity of the imaging device, electronic sensor noise or atmospheric disturbances. This paper proposes a hybrid directional lifting technique for image denoising to retain the original information present in the images. The primary objective of this paper is to show the impact of applying preprocessing techniques for improving classification accuracy. In order to classify the image accurately, effective preservation of edges and contour details of an image is essential. The discrete wavelet transform-based interpolation technique is developed for resolution enhancement. The image is then classified using support vector machine classifier, which is well suitable for image classification. The efficiency of the classifier is analyzed based on receiver operating characteristic (ROC) curves. The quantitative performance measures peak signal to noise ratio and ROC analysis show the significance of the proposed techniques.     

Nitrites Derived From Foneiculum Vulgare (Fennel) Seeds Promotes Vascular Functions

Abstract: Recent evidence has demonstrated that nitrites play an important role in the cardiovascular system. Fennel (Foneiculum vulgare) seeds are often used as mouth fresheners after a meal in both the Indian sub‐continent and around the world. The present study aims to quantify the nitrite and nitrates in fennel seeds as well as elucidating the effect of fennel derived‐nitrites on vascular functions. Results from our study show that fennel seeds contain significantly higher amount of nitrites when compared to other commonly used post‐meal seeds. Furthermore our study confirmed the functional effects of fennel derived‐nitrites using in vitro and ex vivo models that describe the promotion of angiogenesis, cell migration, and vasorelaxation. We also showed that chewing fennel seeds enhanced nitrite content of saliva. Thus our study indicates the potential role of fennel derived‐nitrites on the vascular system. Practical Application: This study is focused on determining the effect of fennel‐derived nitrites on angiogenesis (the formation of new blood vessels from pre‐existing ones), cell migration, and vasorelaxation (dilation of blood vessels) thereby preserving cardiovascular health.     

Estimation of Effect of Fog on Terrestrial Free Space Optical Communication Link

Wireless Personal Communications - Free Space Optical Communication Technology is expected as the successor to the existing communication technologies as many of its features like high bandwidth,...     

Tensile Response of Hoop Reinforced Multiaxially Braided Thin Wall Composite Tubes

This paper presents the tensile response of thin-walled composite tubes with multi-axial fibre architecture. A hybrid braid-wound layup has the potential to optimise the composite tube properties, however, stacking sequence plays a role in the failure mechanism. A braid-winding method has been used to produce stacked overwound braid layup [(±45°/0°)₅/90°₄]_T. Influence of stacking sequence on premature failure of hoop layers has been reported. Under tensile loading, a cross-ply composite tube with the alternate stacking of hoop and axial fibre show hoop plies splitting similar to the overwound braided composite tube. However, splitting has been restricted by the surrounding axial plies and contained between the adjacent axial fibre tows. This observation suggests hoop layers sandwiched between braid layers will improve structural integrity. A near net shape architecture with three fibre orientation in a triaxial braid will provide additional support to prevent extensive damage for plies loaded in off-axis. Several notable observations for relatively open braid structures such as tow scissoring, high Poisson’s ratio and influence of axial tow crimp on the strain to failure have been reported. Digital Image Correlation (DIC) in conjunction with surface strain gauging has been employed to capture the strain pattern.     

Robustness of group delay representations for noisy speech signals

This paper demonstrates the robustness of group delay based features to additive noise. First, we analytically show the robustness of group delay based representations. The analysis makes use of the fact that, for minimum-phase signals, the group delay function can be represented in terms of the cepstral coefficients of the log-magnitude spectrum. Such a representation results in the speech spectrum dominating over the noise spectrum, both at low and high SNRs. Further, we experimentally demonstrate the robustness of the representation on a voice activity detection (VAD) task, comparing a group delay based VAD algorithm with standard VAD methods as well as a magnitude-spectrum based method.     

Normalized cuts in 3-D for spinal MRI segmentation

Segmentation of medical images has become an indispensable process to perform quantitative analysis of images of human organs and their functions. Normalized Cuts (NCut) is a spectral graph theoretic method that readily admits combinations of different features for image segmentation. The computational demand imposed by NCut has been successfully alleviated with the Nystr?m approximation method for applications different than medical imaging. In this paper we discuss the application of NCut with the Nystr?m approximation method to segment vertebral bodies from sagittal T1-weighted magnetic resonance images of the spine. The magnetic resonance images were preprocessed by the anisotropic diffusion algorithm, and three-dimensional local histograms of brightness was chosen as the segmentation feature. Results of the segmentation as well as limitations and challenges in this area are presented.