A Modification and Application of Parametric Continuation Method to Variety of Nonlinear Boundary Value Problems in Applied Mechanics

In the field of engineering, researches often come across strong nonlinear boundary value problems which cannot be solved easily. Numerical convergence for many problems, typically solved by the Newton-Raphson linearization algorithm, is sensitive to the initial approach, relaxation parameters and differential topology. Emphasis in the present work is placed on the alternative approach, the so called parametric imbedding of a particular problem into the family of problems. While this may appear to complicate rather than to simplify the problem, its justification lies in the fact that a relation between infinitesimally close neighboring processes results in a simple Cauchy problem with respect to the introduced parameter. Many problems in applied mechanics are reduced to the solutions of systems of nonlinear algebraic, transcendental, differential or integral-differential equations containing an explicit parameter. These are problems in the areas of thermo-fluids, gas dynamics, deformable solids, heat transfer, biomechanics, analytical dynamics, catastrophe theory, optimal control and others. A parameter found in these models is not unique, and may be easily identified as a load which could be geometric, structural, and physical or it could be introduced artificially. An important aspect of these problems is a question of the variation of the solution when parameter is incrementally changed. The growing interest in nonlinear problems in engineering has been intensified by the use of digital computers. This paved a way in development of the solution procedures which can be applied to a large class of nonlinear problems containing a parameter. An important aspect of these problems is the variation of the solution of with the parameter. Hence, method of continuing the solution with respect to the parameter is a natural and universal tool for the analysis. It was originally introduced by Ambarzumian and Chandrasekar, and intensively studied by Bellman, Kalaba and others. Different problems of applied mechanics and physics with dominant nonlinearities due to convective phenomena, constituent models, finite deformation, bifurcation and others are analyzed and solved in the present work. The choice of the optimal continuation parameter, which ensures the best conditioning of the corresponding system of nonlinear equations, is discussed. Some modifications for stiff systems of ordinary nonlinear differential equations are suggested and applied. Effectiveness of the continuation method is demonstrated by comparing the results with the stiff boundary value problem numerical solvers implemented using commercial softwares. The objective of the research is to investigate applicability of the method as a universal approach to the wide range of nonlinear boundary value problems in different areas of mechanics: nonlinear mechanics of solids, bifurcation problems, Newtonian and Non-Newtonian fluids, thermo-fluids, gas-dynamics, control, inverse problems

Clinical, magnetic resonance imaging and arthroscopic findings in diagnosis of meniscal tears: a prospective study

Background: In developing countries like India the need for cost conscious medical practice has a major role in the economy of the country. The extensive use of costly investigative modalities puts huge burden on the patient needing proper medical care. This study is undertaken to assess the role of different diagnostic tools like clinical diagnosis, magnetic resonance imaging (MRI) and arthroscopy in diagnosis of meniscal tears.Methods: A prospective study was conducted among 90 individuals with knee injuries due to various causes attending orthopaedic department of The Oxford Medical College and research centre, Bangalore from October 2018 to May 2019. All patients aged 18 to 60 years with history of knee injury who underwent clinical examination, radiographic examination, MRI and arthroscopy. The data was entered in MS Excel and analysed using SPSS.Results: The study consisted of patients aged between 18-60 years (mean age 32.5 years). Out of which 59 were male and 31 were female. There were 54 patients with suspect diagnosis of medial meniscal tear and 36 with lateral meniscal tear. The difference in diagnostic values between the clinical andMRI findings in diagnosing the medial and lateral meniscal injuries were minimal.Conclusions: Ligament injuries of knee are more common with sports injuries and high velocity trauma. A well-trained surgeon can be more reliable than MRI in diagnosing the ligament injuries. Since MRI is expensive, it can be skipped and used only in more doubtful and complex knee injuries.

On symbolic analysis of cryptographic protocols

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 91-94).The universally composable symbolic analysis (UCSA) framework layers Dolev-Yao style symbolic analysis on top of the universally composable (UC) secure framework to construct computationally sound proofs of cryptographic protocol security. The original proposal of the UCSA framework by Canetti and Herzog (2004) focused on protocols that only use public key encryption to achieve 2-party mutual authentication or key exchange. This thesis expands the framework to include protocols that use digital signatures as well. In the process of expanding the framework, we identify a flaw in the framework's use of UC ideal functionality FKE. We also identify issues that arise when combining FKE with the current formulation of ideal signature functionality FSI,. Motivated by these discoveries, we redefine the FPKE and FsIG functionalities appropriately.by Akshay Patil.M.Eng

The Study of Functional Outcomes Using Oxford Knee Score and Pain Visual Analog Scale Among Osteoarthritic Knee Patients Undergoing Total Knee Replacement

Background: Use of a patient-based outcome scoring systems has been advised to evaluate the contentment and quality of life led post knee replacement surgery. However, there exists a large number of scoring systems which obscures a clinician’s outlook while choosing an appropriate tool of evaluation. Objective: To equate the functional outcomes pre- and post-operatively using oxford knee score (OKS) system and visual analog scale (VAS) in total knee replacement (TKR) of osteoarthritic patients.  Methodology: All patients above the age of 50 years with moderate to severe osteoarthritis (according to OKS) with uni-/bi-lateral osteoarthritis were involved. Patients were assessed pre- and post-operatively for functional outcome and pain using the OKS and VAS, respectively. Patients were followed-up at 1st, 3rd, and 6th month post-surgery for evaluation. All data were analyzed using MS Excel 2007 and R-software 1.2.5001. Result: An overall of 20 patients mostly consisting of females (65%) with a median age of 68.95±4.09 years were predominantly diagnosed with bilateral knee osteoarthritis (50%). Most of the patients underwent right TKR (55%). Score obtained during the 1st, 3rd, and 6th month follow-up post-operatively using OKS and VAS were statistically significantly different (P-value <0.0001) compared to pre-operative score. The association of TKR surgery with OKS and VAS was statistically insignificant (P-value >0.05). Conclusion: Both OKS and VAS provided consistent functional outcomes suggesting improved management of pain and better functional movement in TKR of osteoarthritic patients

Crowd Search: Generic Crowd Sourcing Systems Using Query Optimization

We think about the query optimization issue in Generic crowdsourcing system. Generic crowdsourcing is intended to conceal the complexities and calm the client the weight of managing the group. The client is just needed to present a SQL-like question and the framework assumes the liability of arranging the inquiry, creating the execution plan and assessing in the crowdsourcing commercial center. A given query can have numerous options execution arranges and the distinction in crowdsourcing expense between the best and the most exceedingly worst arranges may be a few requests of extent. In this manner, as in social database frameworks, query optimization is imperative to crowdsourcing frameworks that give revelatory question interfaces. In this paper, we propose CROWDOP, an expense based query advancement approach for explanatory crowdsourcing frameworks. CROWDOP considers both cost and latency in query advancement destinations and produces question arranges that give a decent harmony between the cost and latency. We create proficient calculations in the CROWDOP for upgrading three sorts of inquiries: selection queries join queries, and complex selection-join queries. Deco is a far reaching framework for noting decisive questions postured over put away social information together with information got on demand from the group. In this paper we assume Deco's cost based query streamlining agent, expanding on Deco's information model, query dialect, and query execution motor exhibited befor

Butea monosperma Silver Nanoparticles Anticancer Activity Against MCF 7 Human Breast Cancer Cell Line

In this research, silver nanoparticles were synthesized from Butea monosperma for in vitro cytotoxicity efficacy against MCF-7 cells. Silver nanoparticles are deemed the most positive, considering their strong volume surface region, and are of concern for study because of the improved microbial tolerance to antibiotics and medicines. Therefore, green synthesis of nanoparticles of silver using biomolecules derived from various plant sources in the form of extracts can be applied for the screening of different diseases which trigger microorganisms and for the physical and biological characterization of plant-derived silver nanoparticles. The experiment involved the green synthesis of silver nanoparticles (AgNPs) from Butea monosperma leaf extract. Biosynthesized Butea monosperma-AgNPs were characterized by UV-visible spectroscopy, Fourier-transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). The intensity of peak broad range 200-800nm in UV-vis spectra, EDS test. The SEM shows the actual size of the nanoparticles. The MTT assays were carried out for cytotoxicity of various concentrations of biosynthesized silver nanoparticles. The biosynthesized silver nanoparticles showed a significant anticancer activity against both MCF-7. Our study thus revealed an excellent application of greenly synthesized silver nanoparticles. At the Concentration 80µg/ml, Sample Code A, B, C, D samples showed good percent inhibition MCF7cell line as compared to standard drug.The study also suggested the potential therapeutic use of these nanoparticles in cancer study

Active Coarse-to-Fine Segmentation of Moveable Parts from Real Images

We introduce the first active learning (AL) framework for high-accuracy instance segmentation of moveable parts from RGB images of real indoor scenes. As with most human-in-the-loop approaches, the key criterion for success in AL is to minimize human effort while still attaining high performance. To this end, we employ a transformer that utilizes a masked-attention mechanism to supervise the active segmentation. To enhance the network tailored to moveable parts, we introduce a coarse-to-fine AL approach which first uses an object-aware masked attention and then a pose-aware one, leveraging the hierarchical nature of the problem and a correlation between moveable parts and object poses and interaction directions. Our method achieves close to fully accurate (96% and higher) segmentation results, with semantic labels, on real images, with 82% time saving over manual effort, where the training data consists of only 11.45% annotated real photographs. At last, we contribute a dataset of 2,550 real photographs with annotated moveable parts, demonstrating its superior quality and diversity over the current best alternatives

Synchronization of Solar and MSEB

In this paper we are providing a overview of recent researches synchronization of solar and MSEB. The term ?smart grid? refers to the use of technologies and tools that help electric utilities better meet consumers? needs reliably and affordably by more effectively monitoring power usage demand and system conditions on a near real-time basis. The smart grid combines digital devices, software applications and two-way communications that allow utilities to track the flow of electricity with great precision, and apply logic to relays according to the situation of input. It can also let utilities record consumer electric use in various time intervals and provide consumers with energy usage data. Considering the problem of generation of the ac supply, we aim to design a system, which can utilize the solar power. Due to the use of solar power for home appliances requirement of grid?s power will be reduced. This system results into the efficient use of renewable energy. This system will be used to overcome the problem of load shedding and reducing the electricity bills. The system consisting of solar dc power can be converted into ac power using the solar micro grid inverter. The synchronized output is given to the microcontroller and the source of supply will be selected automatically according to the requirements of load and status of the sources. Advanced facility like GSM will allow the user to control various appliances just through a message. Daily report of usage of power through individual source will be given to the user by a text message. Various parameters like voltage, current, power consumption will be displayed on a LCD to give the notification of status of the system

Advances in Data-Driven Analysis and Synthesis of 3D Indoor Scenes

This report surveys advances in deep learning-based modeling techniques that address four different 3D indoor scene analysis tasks, as well as synthesis of 3D indoor scenes. We describe different kinds of representations for indoor scenes, various indoor scene datasets available for research in the aforementioned areas, and discuss notable works employing machine learning models for such scene modeling tasks based on these representations. Specifically, we focus on the analysis and synthesis of 3D indoor scenes. With respect to analysis, we focus on four basic scene understanding tasks -- 3D object detection, 3D scene segmentation, 3D scene reconstruction and 3D scene similarity. And for synthesis, we mainly discuss neural scene synthesis works, though also highlighting model-driven methods that allow for human-centric, progressive scene synthesis. We identify the challenges involved in modeling scenes for these tasks and the kind of machinery that needs to be developed to adapt to the data representation, and the task setting in general. For each of these tasks, we provide a comprehensive summary of the state-of-the-art works across different axes such as the choice of data representation, backbone, evaluation metric, input, output, etc., providing an organized review of the literature. Towards the end, we discuss some interesting research directions that have the potential to make a direct impact on the way users interact and engage with these virtual scene models, making them an integral part of the metaverse.Comment: Published in Computer Graphics Forum, Aug 202