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        Non-contact damage monitoring technique for FRP laminates using guided waves

        Mohit Garg,Shruti Sharma,등록되었습니다.,Rajeev Mehta 국제구조공학회 2016 Smart Structures and Systems, An International Jou Vol.17 No.5

        A non-contact, in-situ and non-invasive technique for health monitoring of submerged fiber reinforced polymers (FRP) laminates has been developed using ultrasonic guided waves. A pair of mobile transducers at specific angles of incidence to the submerged FRP specimen was used to excite Lamb wave modes. Lamb wave modes were used for comprehensive inspection of various types of manufacturing defects like air gaps and missing epoxy, introduced during manufacturing of FRP using Vacuum Assisted Resin Infusion Molding (VARIM). Further service induced damages like notches and surface defects were also studied and evaluated using guided waves. Quantitative evaluation of transmitted ultrasonic signal in defect ridden FRPs vis-à-vis healthy signal has been used to relate the extent of damage in FRPs. The developed technique has the potential to develop into a quick, real time health monitoring tool for judging the service worthiness of FRPs.

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        An Exploratory Analysis of Online Discussion of Library and Information Science Professionals in India using Text Mining

        Mohit Garg,Uma Kanjilal 한국과학기술정보연구원 2022 Journal of Information Science Theory and Practice Vol.10 No.3

        This paper aims to implement a topic modeling technique for extracting the topics of online discussions among library professionals in India. Topic modeling is the established text mining technique popularly used for modeling text data from Twitter, Facebook, Yelp, and other social media platforms. The present study modeled the online discussions of Library and Information Science (LIS) professionals posted on Lis Links. The text data of these posts was extracted using a program written in R using the package “rvest.” The data was pre-processed to remove blank posts, posts having text in non-English fonts, punctuation, URLs, emails, etc. Topic modeling with the Latent Dirichlet Allocation algorithm was applied to the pre-processed corpus to identify each topic associated with the posts. The frequency analysis of the occurrence of words in the text corpus was calculated. The results found that the most frequent words included: library, information, university, librarian, book, professional, science, research, paper, question, answer, and management. This shows that the LIS professionals actively discussed exams, research, and library operations on the forum of Lis Links. The study categorized the online discussions on Lis Links into ten topics, i.e. “LIS Recruitment,” “LIS Issues,” “Other Discussion,” “LIS Education,” “LIS Research,” “LIS Exams,” “General Information related to Library,” “LIS Admission,” “Library and Professional Activities,” and “Information Communication Technology (ICT).” It was found that the majority of the posts belonged to “LIS Exam,” followed by “Other Discussions” and “General Information related to the Library.”

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        An Adequacy Based Test Data Generation Technique Using Genetic Algorithms

        Malhotra, Ruchika,Garg, Mohit Korea Information Processing Society 2011 Journal of information processing systems Vol.7 No.2

        As the complexity of software is increasing, generating an effective test data has become a necessity. This necessity has increased the demand for techniques that can generate test data effectively. This paper proposes a test data generation technique based on adequacy based testing criteria. Adequacy based testing criteria uses the concept of mutation analysis to check the adequacy of test data. In general, mutation analysis is applied after the test data is generated. But, in this work, we propose a technique that applies mutation analysis at the time of test data generation only, rather than applying it after the test data has been generated. This saves significant amount of time (required to generate adequate test cases) as compared to the latter case as the total time in the latter case is the sum of the time to generate test data and the time to apply mutation analysis to the generated test data. We also use genetic algorithms that explore the complete domain of the program to provide near-global optimum solution. In this paper, we first define and explain the proposed technique. Then we validate the proposed technique using ten real time programs. The proposed technique is compared with path testing technique (that use reliability based testing criteria) for these ten programs. The results show that the adequacy based proposed technique is better than the reliability based path testing technique and there is a significant reduce in number of generated test cases and time taken to generate test cases.

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