Informatics Publishing Limited

Prabhat Ranjan ¹, Sushant Kumar ¹, Uttam Kumar ²

Affiliations
1 Department of Computer Science, Central University of South Bihar, BIT Campus, Patna – 800014, Bihar, IN
2 Department of Computer Science, Central University of South Bihar, BIT Campus, Patna – 800014, Bihar

Abstract

Objectives: Software fault prediction is a vital activity in software development to make software more efficient, economic and produce quality software. This is a fruitful approach to decreases the testing efforts (cost and time) of the software testing. Methods: Existence of faults not only reduces the standard of the software, but also increases its development cost and time. In this paper, the detailed survey has done on software fault prediction for categorize software modules as faulty or non-faulty. The goal of this paper is to find the techniques that has used in software fault prediction. The computational intelligence techniques like soft computing, data mining and machine learning based software fault prediction approaches have included. The classification accuracy rate of different methods which is used for fault prediction has explored. Finding: From the survey, it is found that the fuzzy logic and McCabe based metrics are better way to handle the software fault prediction. The McCabe metrics has independent from the programming language. It performs good result for different size of the software. Application: This survey will helpful to select the model which have high accuracy rate for early phase software testing to provide the quality software. The survey also helps to reduce the cost and time of software testing.

Keywords

Fuzzy Logic, Software Testing, Software Fault Prediction, Software Fault Detection, Soft Computing

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Shubhodip Saha ¹, Jainath Yadav ¹, Prabhat Ranjan ¹

Affiliations
1 Department of Computer Science, Central University of South Bihar, Patna – 800014, Bihar, IN

Abstract

Background: Sarcasm detection in twitter is a very important task as it had helped in the analysis of tweets. With the help of sarcasm detection, companies could analyze the feelings of user about their products. This is helpful for companies, as the companies could improve their quality of product. Methods: For preprocessing of data TextBlob is used. TextBlob is a package installed in Natural Language Toolkit. The preprocessing steps include tokenization, part of speech tagging and parsing. The stop words are removed using python programming. The stop words corpus which consist of 2400 stop words and which is distributed with NLTK have been used. RapidMiner is used for finding polarity and subjectivity of tweets. TextBlob is used for finding the polarity and subjectivity confidence. Weka is used for calculating the accuracy of tweets based on Naïve Bayes classifier and SVM classifiers. Findings: The paper provides the polarity of tweets which include whether the tweet is positive, negative or neutral. Polarity confidence and subjectivity confidence are also found. Accuracy of tweets are found using Naïve Bayes and SVM classifiers. Applications: Sarcasm Detection could be helpful in analyzing the exact opinion of the user about a certain thing.

Keywords

Polarity, Polarity Confidence, Sarcasm Detection, Subjectivity, Subjectivity Confidence.

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Prabhat Ranjan ¹, S. Harsha ¹, Megha Agrawal ¹

Affiliations
1 Central Manufacturing Technology Institute, Bangalore, IN

Abstract

This signal conditioning circuit design is a micro-power, three terminal electrochemical cell amplifier that uses less than 1-μA total supply current for battery-powered or energy-harvested sensor applications. Electrochemical cells necessitate constant bias, which requires the amplifier circuit to be powered continuously to eliminate sensor start-up and settling times. The design is assembled on a dotted board compatible with the development Kit platform to allow testing with an MSP430 ultra-low-power processor to utilize the launchpad processor analog to digital converters (ADCs) and liquid crystal display (LCD) for stand-alone operation. The whole design consideration is done after taking into consideration of three-terminal screen printed electrode that can have several applications as verified by experimentations and results. The design can be used for agricultural applications as a wide range of sensor current has been taken into design consideration. This needs simple modification based on sensitivity and response time of sensor.

Keywords

MSP430, Op-Amp, Screen Printed Electrode, Trans-Impedance Amplifier, Potentiostat, Current Source.

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Prabhat Ranjan ¹, Prabhat Ranjan ², Anuj Sharma ³, Tribeni Roy ⁴, Tribeni Roy ⁵

Affiliations
1 Bhabha Atomic Research Centre, Mumbai, India, IN
2 Homi Bhabha National Institute, Mumbai, India, IN
3 Cardiff University, Cardiff, UK, IN
4 BITS Pilani, Pilani India, IN
5 London South Bank University, London, UK, IN

Abstract

A rough surface of any engineering material exhibits high surface energy which results in higher potential energy or cohesive energy of the material, and it affects both optical as well as chemical properties. In this paper, stainless steel 304 (or SS304) is selected for nano-finishing through diamond abrasive using MD simulations. It is found that the diamond abrasive creates new bonds with Cr and Fe atoms by rise in local temperature and stresses. Moreover, Ni atom diffuses inside the abrasive as it does not chemically bond with C atom. The abrasion on steel due to diamond also leads to phase transformation on both abrasive as well as the workpiece. Subsequently, the transformed phase is removed from the workpiece due to the newly formed chemical bonds, however, in the process, the abrasive particle deteriorates by phase transformation and materials loading. Thus, the present study is useful in optimising nano-finishing or nano-cutting process on stainless steel.

Keywords

Nano-Finishing, Polishing, Molecular Dynamics Simulation, Stainless Steel, Corrosion Resistance.

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Prabhat Ranjan ¹, Ashok K. Wankhede ¹

Affiliations
1 Bhabha Atomic Research Centre Mumbai, Homi Bhabha National Institute Mumbai, IN

Abstract

Additive Manufacturing (AM) process has potential to manufacture complex structures to cater the design requirement and process requirement for any specific application. However, this process is expensive as compared to the traditional and on-going advanced manufacturing process. The cost of AM process depends on volume/mass and size of the parts, and due to this, the AM manufactured part needs to be topologically optimised before manufacturing. In view of this, the manufacturer has to ensure the functionality and acceptability of design parameters about the computer aided design (CAD) model through a reliable numerical modelling technique for the topology optimisation (TO). Moreover, the CAD model also needs to be compatible for ease of manufacturing by AM process which is possible by post analysis and CAD modification. In the present paper, TO was implemented for a high-speed rotating impeller of a turbo-molecular pump (TMP) followed by manufacturing to achieve better performance.

Keywords

Topology Optimisation, Additive Manufacturing, Turbo-Molecular Pump, Rotor-Dynamics, Finite Element Analysis

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