A fuzzy rule-based generation algorithm in interval type-2 fuzzy logic system for fault prediction in the early phase of software development

Reliability, a measure of software, deals in total number of faults count up to a certain period of time. The present study aims at estimating the total number of software faults during the early phase of software life cycle. Such estimation helps in producing more reliable software as there may be a scope to take necessary corrective actions for improving the reliability within optimum time and cost by the software developers. The proposed interval type-2 fuzzy logic-based model considers reliability-relevant software metric and earlier project data as model inputs. Type-2 fuzzy sets have been used to reduce uncertainties in the vague linguistic values of the software metrics. A rule formation algorithm has been developed to overcome inconsistency in the consequent parts of large number of rules. Twenty-six software project data help to validate the model, and a comparison has been provided to analyse the proposed model’s performance.     

Study of device parameters for work function engineered gate recessed S/D SOI MOSFET incorporating quantum mechanical effects

For the first time analytical modeling of nanoscale work function engineered gate recessed S/D SOI MOSFET including quantum mechanical effects has been presented based on the solution of 1 D Schrödinger and 2 D Poisson’s equation. As classical models are insufficient in nanoscale regime, quantization effect has been incorporated in this model to explore the actual potential profile characteristics along the film thickness. An extensive calculation has been carried out with proper boundary condition to solve the 2-D Poisson’s equation for device parameters. The value of deviated quantum threshold voltage has been calculated from classical model, and then these two are added to resolve the final quantum threshold voltage. Channel length modulation has also been taken into consideration during drain current modeling for this structure. A comparative study based on the threshold voltage, drain current, transconductance and drain conductance has been presented for the classical and quantum model. The results are also compared with the simulation of SILVACO Deck build, Deck Editor Version 4.2.5.R (aka 4.2.5.R) device simulator to validate the proposed model.

     

Integration of hybrid communication and remote sensing for ITS application

Telecommunication Systems - Intelligent transportation system is a prominent technology solution for the vehicle manufacturers in this present scenario. The manufacturers are trying to deploy an...     

Wide‐bandwidth multifrequency circularly polarized monopole antenna for wireless communication applications

In this article, wideband circularly polarized monopole antennas with multiresonating frequencies are presented for Bluetooth, WLAN, WiMAX, and X‐band applications. The designed antennas have dimensions of 50 × 35 × 1.6 mm³. Two different substrates (FR4‐epoxy and PTFE) are used for fabricating the antennas. The antennas consist of corner truncated I‐shaped and C‐shaped strips excited by a 50 Ω microstrip feed line. The parametric analyses are performed with the help of Ansoft HFSS V.11 EM simulator. Both antennas have been fabricated and measured. The measured percentage bandwidth of the antenna made by FR4 substrate is 31.32% (centered at 1.66 GHz), and 64.85% (centered at 5.69 GHz). The percentage bandwidth of antenna made by PTFE substrate is 20.57% (centered 2.43 GHz) and 68.74% (centered at 7.39 GHz). In addition to that, there exists 3 dB AR bandwidth for LHCP of about 1050 MHz for 5.2 GHz WLAN‐band. The reflection coefficient, radiation patterns, and the gains of both the antennas are studied in detail. It is found that the measured and simulated results are in good agreement.     

Development and Characterization of a Diaphragm-Shaped Force Transducer for Static Force Measurement

There are different types of force transducers, used over the years, comprising of different principles and have different grades of uncertainty. Force transducers may be analog or digital and may be strain gauged, tuning fork type, piezoresistive type, Hall Effect based etc. Though different types of force transducers have been developed in last few decades, still strain gauged force transducers are used over the larger scale due to practical viability and reliability for force measurement. The paper describes low-cost indigenous development of a force transducer, which has been developed for a nominal capacity of 5 kN with ease of design and manufacturing. It has strain gauges applied at suitable locations to form a Wheatstone bridge. The force transducer has been calibrated according to the standard calibration procedures based on ISO 376 and IS 4169 standards. Measurement results and an uncertainty analysis have been presented. The uncertainty of measurement of the force transducer is found up to 0.06%. The paper also discusses the implications of applying multiple strain gauges at a single location in series to enhance the sensitivity of the force transducer. Two strain gauges are arranged in series for the given location and the sensitivity of the force transducer is enhanced. It also indicates that the uncertainty of measurement of the force transducer in such case is enhanced up to 0.05% or better to make force transducer suitable for most of metrological and industrial applications.     

Photo-electrocatalytic methanol oxidation on Pd decorated BiOI nanoparticles in alkali

Journal of Materials Science - Palladium–bismuth oxoiodide nanocomposites of various molar ratios of Pd and BiOI have been synthesized by the facile solvothermal method following the chemical...     

A position and rotation invariant framework for sign language recognition (SLR) using Kinect

Multimedia Tools and Applications - Sign language is the only means of communication for speech and hearing impaired people. Using machine translation, Sign Language Recognition (SLR) systems...     

A bayesian belief network based model for predicting software faults in early phase of software development process

It is always better to have an idea about the future situation of a present work. Prediction of software faults in the early phase of software development life cycle can facilitate to the software personnel to achieve their desired software product. Early prediction is of great importance for optimizing the development cost of a software project. The present study proposes a methodology based on Bayesian belief network, developed to predict total number of faults and to reach a target value of total number of faults during early development phase of software lifecycle. The model has been carried out using the information from similar or earlier version software projects, domain expert’s opinion and the software metrics. Interval type-2 fuzzy logic has been applied for obtaining the conditional probability values in the node probability tables of the belief network. The output pattern corresponding to the total number of faults has been identified by artificial neural network using the input pattern from similar or earlier project data. The proposed Bayesian framework facilitates software personnel to gain the required information about software metrics at early phase for achieving targeted number of software faults. The proposed model has been applied on twenty six software project data. Results have been validated by different statistical comparison criterion. The performance of the proposed approach has been compared with some existing early fault prediction models.     

Use of Spectral Clustering Combined with Normalized Cuts (N-Cuts) in an Iterative k-Means Clustering Framework (NKSC) for Superpixel Segmentation with Contour Adherence

Superpixel segmentation methods are generally used as a pre-processing step to speed up image processing tasks. They group the pixels of an image into homogeneous regions while trying to respect existing contours. In this paper, we propose a fast Superpixels segmentation algorithm with Contour Adherence using spectral clustering, combined with normalized cuts in an iterative k-means clustering framework. It produces compact and uniform superpixels with low computational costs. Normalized cut is adapted to measure the color similarity and space proximity between image pixels. We have used a kernel function to estimate the similarity metric. Kernel function maps the pixel values and coordinates into a high dimensional feature space. The objective functions of weighted K-means and normalized cuts share the same optimum point in this feature space. So it is possible to optimize the cost function of normalized cuts by iteratively applying simple K-means clustering algorithm. The proposed framework produces regular and compact superpixels that adhere to the image contours. On segmentation comparison benchmarks it proves to be equally well or better than the state-of-the-art super pixel segmentation algorithms in terms of several commonly used evaluation metrics in image segmentation. In addition, our method is computationally very efficient and its computational complexity is linear.