22 research outputs found
Reliability of Ultimate Limit State Design in Finite Elements and Compliance with Eurocode 7
No full textGeotechnical design problems may be characterized by a certain degree of uncertainty, due to insufficient soil data and transformation of test results in soil parameters. In common practice, engineers perform deterministic analyses according to design standards as Eurocode 7, where the uncertainties are taken into account through partial factors for loads and soil properties to attain certain specified target reliabilities. Forcomplexsoilstructureinteractionproblems, partialfactormethodis difficult to adopt, as the design standards consider geotechnical standards with singlefailuremechanism. ThisisespeciallyproblematicforUltimateLimitstatedesigns where both stiffness and strength properties are dominant. With the advent of limit state design philosophy in Eurocodes, the use of reliability methods in Finite Element Analysis for complex situations has become more and more of interest. Reliability analyses allow to explicitly define the single uncertainties in the model by using an appropriate probabilistic distribution for each source of uncertainty. The reliability index and the probability of failure with respect to a predefined condition are calculated. The problem with using reliability based probabilistic design is the absence of simple computational approaches that can be easily implemented. MonteCarlosimulationsarecommonly usedto solvesoil structureinteraction problems. For a large and complex soil-structure interaction problem, it is computationally intensive to complete even a single run. This practical disadvantage can be solved only by a computationally efficient method. A special purpose application to perform probabilistic analysis in PLAXIS 2D, called PROBANA has been recently developed at Plaxis B.V. PROBANA performs direct probabilistic calculations in the finite element framework, using First Order Reliability Method or Monte Carlo Method. In this thesis, PROBANA (FORM) is used to perform reliability analysis for three benchmarks, and the results from PROBANA – FORM are compared with Point Estimate Method (PEM) and other stochastic Methods. The results from FORM are found to be comparable with that of PEM. It is concludedthatPEMislessaccurateduetoassumptionsmadebyPEMintheunderlying output distribution and FORM is more accurate and practical as it is computationally less intensive compared to other stochastic methods such as the Monte Carlo analysis. An extensive comparison of the reliability based method with Eurocode design method shows possibilities to implement reliability methods with EC7. One such approach is proposed, and demonstrated with the benchmarks
A Low Distortion Reversible Data Hiding Technique Using Improved PPVO Predictor
No full textAbstractReversible data hiding is a technique that embeds additional information into some distortion-unacceptable cover media, such as military images, in a reversible manner so that the original cover image can be restored after extraction of the hidden information. This work extends a recently proposed reversible data hiding (RDH) scheme of Qu et al. which is based on pixel-based pixel- value-ordering(PPVO) and prediction-error expansion. In Qu et al.’s method, each pixel is predicted using its sorted context pixels. In this work, the pixel neighborhood of each pixel is expanded to optimize the embedding performance in terms of capacity- distortion behavior. This can better exploit image redundancy; achieve superior embedding performance and low distortion. Thus, the proposed method is able to embed adequate data into a cover image with limited distortion. The superiority of this predictor is verified through extensive experimental results. The proposed method outperforms prior works in terms of PSNR. The PSNR of a modified image versus its original one is guaranteed to be above 57.0dB
Sensitivity Analysis of Rectangular Microcantilever Structure with Piezoresistive Detection Technique Using Coventorware FEA
No full textAbstractMicro Electro Mechanical Systems (MEMS) based microcantilever is a micromachined device similar to the miniaturized version of a diver's board, longer as compared to width, and has a thickness much smaller than its length or width. The merits of MEMS microcantilever sensors are its high sensitivity, design simplicity, portability and high speed. In this paper, a microcantilever sensor is designed to meet the requirements of a biosensor that detects tuberculosis. The addition of mass on the microcantilever surface makes it to bend and its stressed elements deform.The deflection underwent by microcantilever is detected by piezoresistive detection mechanism. The behavior of piezoresistive microcantilever structure is investigated using various beam materials and geometric dimensions. The advantage of incorporating SCR (Stress Concentrated Region) on the piezoresistive microcantilever is studied and the optimal position of placing the piezoresistor on the microcantilever beam is investigated using load analysis and corresponding stress distribution results. CoventorWare® is used to do the analysis of micromachined cantilever. The results show that sensitivity increases with increase in length and incorporation of SCR but decreases with increase in thickness
Physical and Chemical Properties of Oil.
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Governing Intellectual Property Rights Within Publicly Funded Biobanks
No full textGoverning Intellectual Property Rights Within Publicly Funded Biobanks addresses the implications that intellectual property rights (IPRs) have in the context of biobanks and how they need to be addressed in the governance of biobank-based research. The boom in biobanks and health databases as research infrastructures have evoked various legal and ethical debates. Since then numerous new developments have emerged such as digitalization, big-data research, and artificial intelligence that have important implications for biobank-based research and collaborations. This paradigm offers new legal challenges for commercial involvement, particularly within a publicly funded setting. In this innovative book, the author shows that securing maximum social benefit out of the knowledge emanating from the use of biobank resources lies in managing IP inputs and outputs effectively in keeping with the values that are core to such research
Korteweg–deVries–Burgers (KdVB) equation in a five component cometary plasma with kappa described electrons and ions
No full textMachine learning - driven solar forecasting in dust-prone regions for sustainable energy systems
No full textThis research focuses on improving solar energy forecasting in dust-affected regions such as the UAE, where frequent dust storms reduce photovoltaic (PV) efficiency by scattering and absorbing sunlight. Many existing models overlook the impact of dust events, leading to inaccurate forecasts during such conditions. To address this, the study develops machine learning models—including LSTM, GRU, and hybrid LSTM-GRU architectures—that incorporate solar, weather, and dust-related features. The models were evaluated across multiple forecasti24 hoursons (1, 6, 12, and 24 hours), demonstrating that including dust-related variables significantly enhances prediction accuracy, particularly for short-term forecasts. Temporal and seasonal analyses revealed that dust events, most frequent in the late afternoon and early spring, correlate with substantial drops in solar power output. The LSTM model consistently outperformed the others, achieving a Mean Absolute Error (MAE) of 0.018034 for a 1-hour horizon when dust features were included. Statistical tests confirmed that dust events significantly affect forecasting accuracy, reinforcing the importance of dust-related features for reliable predictions. This research contributes to optimizing PV power generation in challenging environments, supporting sustainable energy systems and decarbonization efforts. It also offers insights for further model refinement and the inclusion of additional environmental variables
Total Variation Denoising Based Approach for R-peak Detection in ECG Signals
No full textAbstractDetecting R-peak signal from electrocardiogram or ECG signal plays a vital role in cardiac monitoring system and ECG applications. In this paper, Total Variation Denoising (TVD) based approach is proposed to find the locations of R-peaks in the ECG signal. One advantage of using TVD method is that it preserves the sharp slopes or the peaks in the signal. This motivated to use TVD method for R-peak detection problem. The proposed approach is evaluated using the first channel, 48 ECG records from MIT-BIH Arrhythmia database. The accuracy of TVD based approach is calculated on all the 48 records. The proposed method gives 9 false-negative or FN beats, 126 false-positive or FP beats, positive-predictivity of 99.885%, sensitivity of 99.914%, with an overall accuracy of 99.79%
Open Access Information as A Platform for Sustainable Development: Perspectives From Selected Institutions in India
No full textOpen Access (OA) literature is digital, online, free of charge, and free of most copyright and licensing restrictions, what makes it possible are the internet and the consent of the author or copyright holder. In most fields, scholarly journals do not pay authors, who can, therefore, consent to OA without losing revenue. In this respect, scholars and scientists are very differently situated from most musicians and movie-makers, and controversies about open access to music and movies do not carry over to research literature. Open access is entirely compatible with peer review, and all the major open access initiatives for scientific and scholarly literature insist on its importance, just as authors of journal articles donate their labor, journal editors, and referees participating in peer review. The study shows that out of 456 respondents considered for the study 203 [44.5%] belongs to Arts, 169 [37.1%] belong to Science, 33 [7.2%] Education and 51 [11.2%] belongs to Management. The findings of the study also show that out of 456 respondents considered for the study among which 81 [17.8%] belong to the M. Phil program, 102 [22.4%] belong to Ph.D. Program and 273 [59.9%] are faculty members
