Articles written in Sadhana

    • Design and development of long-period grating sensors for temperature monitoring

      Smita Chaubey Purushottam Joshi Manoj Kumar Rajesh Arya A K Nath Sanjay Kher

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      Long Period Gratings (LPGs) have been developed using carbon dioxide laser in a standard optical fibre. LPGs with a periodicity of 600 𝜇m and grating length of 24 mm have been inscribed on standard single mode fibre. Such gratings have been used in designing temperature sensors and temperature is monitored up to 80°C. The sensitivity of such type of sensor is 0·06 nm/° C where as for standard Fibre Bragg Grating (FBG) it is 0·011 nm/°C. The LPG performance is also evaluated after 𝛾-ray irradiation for total dose of 5 KGy and has not shown any effect on transmission spectrum.

    • Space vector-based analysis of overmodulation in triangle-comparison based PWM for voltage source inverter

      Manoj Kumar Modi S Venugopal G Narayanan

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      The equivalence of triangle-comparison-based pulse width modulation (TCPWM) and space vector based PWM (SVPWM) during linear modulation is well-known. This paper analyses triangle-comparison based PWM techniques (TCPWM) such as sine-triangle PWM (SPWM) and common-mode voltage injection PWM during overmodulation from a space vector point of view. The average voltage vector produced by TCPWM during overmodulation is studied in the stationary (a–b) reference frame. This is compared and contrasted with the average voltage vector corresponding to the well-known standard two-zone algorithm for space vector modulated inverters. It is shown that the two-zone overmodulation algorithm itself can be derived from the variation of average voltage vector with TCPWM. The average voltage vector is further studied in a synchronously revolving (d-q) reference frame. The RMS value of low-order voltage ripple can be estimated, and can be used to compare harmonic distortion due to different PWM methods during overmodulation. The measured values of the total harmonic distortion (THD) in the line currents are presented at various fundamental frequencies. The relative values of measured current THD pertaining to different PWM methods tally with those of analytically evaluated RMS voltage ripple.

    • Optimization of Weibull deteriorating items inventory model under the effect of price and time dependent demand with partial backlogging


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      In this study, we have discussed the development of an inventory model when the deterioration rate of the item follows Weibull two parameter distributions under the effect of selling price and time dependent demand, since, not only the selling price, but also the time is a crucial factor to enhance the demand in the market as well as affecting the overall finance. In the present model, shortages are approved and also partially backlogged. Optimum inventory level, the optimal length of a cycle and the expressions for profit function under various cost considerations are obtained using differential equations. These are illustrated graphically with the help of numerical examples. The sensitivity analysis of the standards of the parameters has been performed tostudy the effect on inventory optimizations.

    • An integrated framework for software vulnerability detection, analysis and mitigation: an autonomic system


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      Nowadays, the number of software vulnerabilities incidents and the loss due to occurrence of software vulnerabilities are growing exponentially. The current existing security strategies, the vulnerability detection and remediating approaches are not intelligent, automated, self-managed and not competent to combat against the vulnerabilities and security threats, and to provide secured self-managed software environment to the organizations. Hence, there is a strong need to devise an intelligent and automated approach to optimize security and prevent the occurrence of vulnerabilities or mitigate the vulnerabilities. The autonomic computing is a nature-inspired and self-management-based computational model. In this paper, an autonomic-computing-based integrated framework is proposed to detect, fire the trigger of alarm, assess, classify, prioritize, mitigate and manage the software vulnerability automatically. The proposed framework uses a knowledge base and inference engine, which automatically takes the remediating actions on future occurrence of software security vulnerabilities through self-configuration, self-healing, self-prevention and self-optimization as per the needs. The proposed framework is beneficial to industry and society in various aspects because it is an integrated, crossconcern and intelligent framework and provides more secured self-managed environment to the organizations. The proposed framework reduces the security risks and threats, and also monetary and reputational loss. It canbe embedded easily in existing software and incorporated or implemented as an inbuilt integral component of the new software during software development.

© 2017 Indian Academy of Sciences, Bengaluru.