7940 research outputs found
Sort by
Terrain Exploration, Stability Control and Trajectory Planning of Humanoid Robots employing Several Navigational Strategies
No full textResearch investigation on the navigation of humanoid robots is a prevalent aspect in robotics nowadays because scientists develop robots to function together with maximum cooperation in their workspaces. The robot’s potential to maintain stability while standing, moving in the environment, evading barriers, stepping over a barrier is essential to protect itself and the operator from percussion. This research aims to address a portion of the trajectory mapping challenges for achieving steady movement. To address the challenges, the present research work is focused on the concept, formulation and application of several state-of-the-art algorithms for smooth, percussion-free and efficient locomotion of humanoid robots in various terrains. Humanoid NAO is preferred as a robotic platform for evaluating the designed trajectory mapping algorithms. The kinematic analysis of humanoid NAO is carried out using the DH (Denavit-Hartenberg) parameter strategy to better understand mobility limitation criteria. The dynamic analysis of humanoid NAO is performed by employing Whole-Body Control aided Simulated Annealing approach to integrate human-like intellect into designing and represent it accurately. Here, Particle Swarm Optimization (PSO) tuned Proportional-Integral-Derivative controller (PID), Dynamic Window Approach (DWA) and Teaching-Learning-Based Optimization (TLBO) Approach and Multi-Objective Sunflower Optimization (MOSFO) tuned Modified Multiple Adaptive Neuro-Fuzzy Inference System controller (MANFIS) are outlined for trajectory mapping of single and multiple humanoid NAOs in terrains with several challenges. The navigation of humanoid NAO on unstructured terrains is controlled using a novel 3D-Multilinked Dual Spring-Loaded Inverted Pendulum integrated with BFGS Quasi-Newton tuned Artificial Potential Field (APF) controller. For multiple humanoid NAOs navigation, dining philosopher controller are designed and integrated into the base strategies. The established trajectory mapping strategies are evaluated on simulated humanoid NAO in WEBOT and accredited in actual humanoid NAO under real-time scenarios. Their results are compared, and the margin of error is obtained under the 6%. The formulated strategies are also compared with various conventional trajectory mapping algorithms that display considerable performance enhancements between 5% to 13%. Ultimately, the applicability of present research investigations is discussed, along with prospective expansion prospects
On the Development of Indian TSR Systems using Machine Learning Techniques
No full textAdvanced driver-assistance systems (ADAS) is a typically growing aspect of the automobile industry. Famous automobile brands like Brenzo have introduced various automated configurations like Traffic sign recognition (TSR), cruise control, speed control, crewless vehicles etc. TSR refers to systems or techniques that aim at automatic recognition of traffic signs. Traffic signs are markers at the side of roads that instruct or inform the drivers about the road rules and conditions ahead of them. TSR is targeted at reducing human-car interaction and aimed at automated systems in vehicles for the recognition of traffic signs. It is needless to say that the current death rate in the globe due to traffic accidents is alarming. The same situation prevails in India as well. Therefore, automated systems like TSR has become indispensable part of ADAS. This thesis aims at developing efficient practically implementable architectures emphasizing on datasets. In this line, an Indian dataset has been proposed to strengthen the research further. In this context, four different schemes have been proposed for TSR architectures. In isolation, each scheme has been validated using three standard databases, namely GTSRB, BTSC and IRSDBv1.0. The achieved accuracy is promising classification accuracy compared to the existing schemes elaborated in each chapter. In this thesis, the second chapter presents a wholesome review of the related works. To eliminate the lack of an Indian traffic sign dataset, the first contribution presents a fully annotated Indian traffic sign dataset named IRSDBv1.0 which is now available in public domain. The second contribution aims at designing an efficient Deep neural network (DNN) scheme, namely MDEffNet. MDEffNet achieves high accuracy on GTSRB and BTSC despite having low number of parameters. But MDEffNet didn’t give expected results in case of IRSDBv1.0 dataset due to limited image samples probably. The following chapters are in line with these findings. The third contribution explores the efficiency of wavelet descriptors. Along with the descriptors, three classifiers, namely CNN, CNN ensemble and LSTM, have been deployed to analyse the effectiveness of the proposed scheme. The fourth contribution eliminates the bottleneck created by wavelet descriptors by using curvelet descriptors along with Shannon entropy in its framework. Besides increasing the attained accuracy, this approach reduces the feature vector length considerably. All the presented architecture works on the assumption that the input images are free of visual challenges like occlusion, blur etc. Considering occlusion being the most common visual challenge, in fifth contribution a modified ResNet50 DNN architecture has been proposed, namely GDNN, that performs well on partially occluded signs. All the three datasets viz; GTSRB, BTSC, and IRSDBv1.0 have been used to validate the proposed schemes. Finally, the overall concluding remark is laid out in the last chapter along with future directions
Thermopneumatic Analysis and Process Design of Closed Cycle Cryocoolers
No full textThe cryocooler is a tabletop size machine, which extracts heat from an object to decrease its temperature below the cryogenic temperature limit. Cryocoolers are used in the cooling of high-temperature superconducting (HTS) magnets, HTS motors, HTS generators, and HTS transformers, etc. to retain their superconductivity state. Furthermore, they are used in liquefaction of permanent gases, cooling of space satellites, night vision camera, infrared sensors, cryosurgical probes, magnetic resonance imaging (MRI), etc. to name a few. It is believed that with the development of compact, efficient, miniature, and portable cryocoolers, its application domain will further increase in other fields of modern science and technology. In this research, numerical simulation is conducted to illustrate the thermo-fluidic processes occurring inside the regenerative cryocoolers. The heat transfer and fluid flow processes of regenerative cryocoolers are governed by a set of non-linear, coupled partial differential equations. The governing equations of the compressible working fluid are conservation of mass, momentum, and energy. Moreover, the conservation of the solid/ matrix energy equation is coupled with the fluid energy equation by means of film heat transfer. By adopting the finite volume discretization method, the partial differential equations are converted into algebraic equations. The first and second-order implicit schemes are used for the discretization of time coordinate, and a combination of first and second-order upwind schemes are used for the discretization of space coordinates. The first-order implicit scheme is used for the first time step, and the second-order implicit scheme is used for the remaining time steps in a cycle. The boundary nodes of the computational domain are discretized by the first-order upwind scheme and internal nodes are discretized by the second-order upwind scheme. By applying the ideal gas equation-of-state, both continuity and momentum equations are converted into a single equation, which upon solution yields pressure distribution. Therefore, one discretized algebraic equation is circumvented in the iterative solution process and thereby increases the computational speed. The resulting set of algebraic equations are solved iteratively by Tri-diagonal and Penta-diagonal matrix algorithm. After completion of the first time step, the final computed values are used as initial conditions for successive time steps, and this process is continued until a cyclic steady state is achieved. Once a cyclic steady state is achieved, the performance parameters of the cryocooler like work input, cooling capacity, enthalpy flow, energy flow, exergy flow, entropy generation, etc. can be computed from the physical quantities like pressure, mass flow rate, temperature, density, fluid properties, and matrix properties, etc. In this work, the one-dimensional model is extended by introducing the influence of turbulent conduction, eddy mixing and thermal dispersion with the help of a gas axial- conduction enhancement factor in the fluid energy equation. The effect of zero gas conductivity, molecular conductivity, and both molecular conductivity and eddy conductivity on the oscillating flow processes have been examined for an inline inertance pulse tube cryocooler. Subsequently, simulation is conducted to study the effect of zero conductivity and corrected conductivity on the gas flow and heat transfer processes of a coaxial pulse tube cryocooler. After considering the influence of the gas axial-conduction enhancement factor in the numerical model, it is noticed that the phase angle of each physical quantity like flow rate, pressure, temperature, density changes at every location of the cryocooler. Multi-dimensional CFD simulation of inertance pulse tube cryocooler is conducted to visualize various second-order loss mechanisms inside the pulse tube, which cannot be usually analyzed by the one-dimensional model. The one-dimensional numerical model is further modified for a GM cryocooler by modifying the boundary conditions and neglecting the influence of inertia term in the one-dimensional momentum equation. By using the numerical model, the effect of waiting period, and opening angle difference between intake and exhaust valves on the thermodynamic processes of mechanical drive GM cryocooler is studied. Then, a previously established first-order thermodynamic model for mechanical drive GM cryocooler is extended for a pneumatic drive GM cryocooler by implementing the complex displacer dynamics in its governing equations. The thermodynamic processes happening within the cold heads of both mechanical drive GM cryocooler and pneumatic drive GM cryocooler is examined. Subsequently, the effect of opening-closing intervals of drive chamber intake and exhaust valves of pneumatic drive GM cryocooler on the thermodynamic processes have been studied. The simulation results will be useful for a better understanding of the thermo-fluidic processes of GM cryocooler and design of an efficient rotary valve. It is noticed that, with an increase in the waiting period, the P-V power in the expansion chamber and compression chamber reduces due to the decrease in an enclosed area of the P-V diagram of both gas chambers. Multi-dimensional CFD simulation of a mechanical drive GM cryocooler is carried out by commercial code Fluent®, to identify the second-order loss mechanism and formation of recirculation patterns inside the individual gas chambers. The influence of uniform mesh regenerator and multi-mesh regenerator on the cooling rate is examined. In addition, the basic configuration of the displacer is modified by making an annular extruded portion at its cold end so as to construct a multiplex structure. It is noticed that, the extruded portion has an adverse effect on the cooling performance due to the compression of gas parcels in the slots of the extruded portion. One-dimensional numerical simulation is conducted for a GM-type pulse tube cryocooler. By using the one-dimensional numerical model, the effect of geometrical parameters (i.e., regenerator length and diameter, pulse tube length and diameter, orifice and double inlet valve flow coefficients), and operating parameters (i.e., mean pressure and pressure ratio) on the cooling capacity and no load temperature is studied. It is seen that, an increase in mean pressure increases the cooling capacity. It is also noticed that the optimum value of orifice valve opening and double inlet valve opening to attain a minimum no load temperature and a maximum cooling capacity varies with the geometrical parameters of the cryocooler. An experimental investigation is carried out to validate the results of the one-dimensional numerical model. CFD simulation is carried out for a GM-type orifice pulse tube cryocooler to visualize the oscillating gas flow behavior. The process of vortex street formation in an orifice pulse tube cryocooler is also explained. Multi-objective optimization of input parameters of GM pulse tube cryocooler is also carried out using response surface methodology to maximize the cooling capacity and percentage Carnot efficiency
Development of Fast Quenching Methodologies and their Effects on Mechanical Properties
No full textThe continuous requirement of high tensile strength and hardenability steels with uniform quenching rate for numerous applications such as nuclear power plant: railway tracks for Indian railways: aircrafts and automobile industries have forced the current generation researchers to ponder beyond the conventional cooling methodologies. The cooling rate attained by the existing quenching methodologies cannot mitigate the requirements of the industries due to the Leidenfrost effect. Therefore: in the current investigation: by using downward facing: upward facing and bothside spray cooling methodologies: the above work has been tried to accomplish. Before the experimentations: all the spray and nozzle parameters were optimized for achieving maximum heat transfer rate. First: the heat transfer analysis was studied for downward facing sprays by considering two coolants that are oilin- water emulsion and sodium carbonate added water. Although the enhancement was achieved: but it was not sufficient and hence: the cooling was conducted from the bottom (Upward facing spray) by using various additives. It was noticed that due to the horizontal movement of vapour and liquid layer from the surface and less residence time of the droplets on the surface: the heat transfer rate was significantly enhanced. For further enhancement: additives such as benzene: n-Hexane: acetone: Tween 20: NaCl and ethanol have been used. Among all: maximum heat transfer is achieved in case of ethanol (500 ppm) added water. In addition: for the achievement of uniform cooling rate along with uniform microstructure and mechanical properties in both the side of the surfaces: bothside facing spray cooling methodology was used. For this: two different grades of steel (AISI 304 and AISI 1020) were considered. Initially: the heat transfer analysis were performed on the AISI 304 plates by using numerous coolants. The results reveal that the maximum and minimum heat transfer were attained by using ethanol (500 ppm) added water (CHF = 2.57 MW/m2) and benzene (1600 ppm) added water (CHF = 1.87 MW/m2): respectively. Furthermore: for the simultaneous investigation on quenching rate: microstructure and mechanical properties: steel plate (AISI 1020) depicting minimum scale effect was used. The heat transfer analysis of bothside spray cooling with AISI 1020 plate illustrates the existence of oxide layer that drastically reduces the CHF. The heat treated samples were further characterized for the determination of microstructure phases: phase percentages: hardness and tensile strength. The microstructure and hardness analysis were carried out at various locations of the surfaces in the thickness direction. The microstructural investigation shows that for all the quenching methodologies: at the impinging surface: martensite and retained austenite phases were formed. The maximum phase percentage of martensite and retained austenite were achieved to be 83.5 and 16.5: respectively for bothside facing spray. Similarly: the hardness values enhances with the increasing cooling rates and decreases in the thickness direction from impinging to bottom surface. The maximum hardness at the highest cooling rate was found to be 488.7 HV0.1. In addition to the above: it is also observed that for the production of moderate hardenability steel: upward facing spray quenching methodology was found to be appropriate. The surface interaction of the used coolants with the plate at high temperature were carried out by determining various coolant and plate parameters. The analysis revealed that the interior interaction could be avoided if quenching rate is more than 252 0C/s and the renewal rate is 17.9 × 107/s. Furthermore: the surface interaction is made insignificant if the coolant corrosion potential is maintained around -0.625 V and this value further shrinks in case of quenching performed by either upward spray or downward spray
Stimulation of Autophagy by Soybean Lectin (SBL) And Its Antimycobacterial Response in Human Macrophages
No full textHost-directed therapy is considered a novel anti-TB strategy to tackle the ever-threatening global tuberculosis (TB) burden. In the past few years, autophagy has been one such strategy manipulated through various inducers to curtail the growth of intracellular Mycobacterium tuberculosis (M. tb). In the present study, the mechanism of action for the anti-tubercular role of soybean lectin (SBL), a lectin isolated from Glycine max (Soybean) has been investigated. SBL restricted intracellular mycobacterial growth by inducing autophagy in differentiated THP-1 (dTHP-1) cells. Mechanistic studies revealed that SBL exerts its antimycobacterial effect in P2RX7-NF-κB dependent manner through ROS generation in dTHP-1 cells. Further, the immunomodulatory effect of SBL in dTHP-1 cells was dissected. A significant increase in IL-6 expression was observed in uninfected and mycobacterial infected dTHP-1 cells through the P2RX7 mediated pathway via PI3K/Akt/CREB-dependent signalling after SBL treatment. Interestingly, the IL-6 receptor (IL-6Rα) was also remarkably expressed on the surface of SBL treated cells. Inhibition of IL-6 level using IL-6 neutralizing antibody or associated signalling significantly enhanced the mycobacterial load in SBL treated dTHP-1 cells, indicating the host defensive role of IL-6. Further, autocrine signalling of IL-6 through its receptor-induced Mcl-1 expression activates autophagy via JAK2/STAT3 pathway, and inhibition of this pathway affected autophagy. Finally, blocking the IL-6 regulated autophagy through NSC 33994 (a JAK2 inhibitor) or S63845 (an Mcl-1 inhibitor) led to a notable increase in intracellular mycobacterial growth in SBL treated dTHP-1 cells. In conclusion, these results indicate that SBL interacts with P2RX7 to regulate PI3K/Akt/CREB network to release IL-6 in dTHP-1 cells. The released IL-6, in turn, activates the JAK2/STAT3/Mcl-1 pathway upon interaction with IL-6Rα to modulate autophagy to control mycobacterial growth in macrophages. So this present study elucidated the mechanistic regulation of autophagy by SBL in dTHP-1 cells and highlighted the fact that triggering autophagy with natural compounds like SBL may be harnessed to develop better therapeutics against TB
Investigations of Phase Transitions and Magneto-electric Properties in Single Phase and Composite Multiferroic Systems
No full textThe research and development on magneto-electric (ME) multiferroic systems received significant attention among the scientific community since its discovery due to the enigmatic theory behind the ME coupling as well as tremendous technological applications in multifunctional devices. Multiferroics are those materials, which simultaneously exhibit two or more primary ferroic ordering like ferroelectric (FE), ferromagnetic (FM), and ferroelastic. The term magneto-electric is associated with the coupling between ferroelectric and magnetic order parameters. The magneto-electric multiferroics are available in single phase as well as in composite form. Single phase multiferroics are very rare in nature due to the chemical incompatibility and mutual exclusiveness for the occurrence of ferroelectricity and magnetism. However, few single phase multiferroics exist in nature by the consequences of several phenomena such as mixed perovskites with d0 and dn ions, ferroelectricity due to lone pair effect, ferroelectricity due to charge ordering, geometric driven ferroelectricity and spin driven mechanisms. The single phase multiferroics further classified in to type-I and type-II depending upon the origin of ferroelectricity in these classes of materials. Type-II multiferroic materials display stronger magneto-electric properties (because of the magnetic origin of ferroelectricity) as compared to type-I multiferroics systems. DyMnO3 (DMO) belongs to the perovskite structure is one of the promising candidate among the rare earth manganite; RMnO3 (R = rare earth ion) systems which comes under type-II multiferroic systems. It lies on the phase boundary between hexagonal and orthorhombic phase and can be crystalized either in orthorhombic or hexagonal phase depending upon the synthesis condition. Orthorhombic phase of DMO undergoes three magnetic phase transitions: antiferromagnetic ordering of Mn ion around 38-43 K, lock-in temperature below which ferroelectricity is observed around 18-23 K and antiferromagnetic ordering of Dy ion below 10 K. Orthorhomic DyMnO3 (single crystal) exhibits giant magneto-capacitance behaviour ( 500%) around 18 K and it shows larger ferroelectric polarization value which is much higher compared to other RMnO3 systems like TbMnO3. So, orthorhombic phase of DyMnO3 is the ultimate choice for investigations on different aspects. In the present study, rare earth element Gd which has comparatively larger ionic radius than Dy is substituted on the Dy-site of DyMnO3 to stabilize the orthorhombic phase. Acrylamide based gel template method has been adopted to synthesize single phase Dy1-xGdxMnO3 (DGMO, x = 0, 0.05, 0.1, 0.15, 0.2) ceramics. The Rietveld refinement of X-ray diffraction (XRD) patterns recorded at room temperature suggest that DGMO ceramics stabilized in orthorhombic crystal structure with Pnma space group. Gd3+cation plays an important role in stabilizing the orthorhombic phase and the unit cell volume increases with x. The magnetic transition temperatures corresponding to TN(Dy) and Tlock decrease with increase in Gd concentration as inferred from the temperature dependent magnetization data (M-T curve). The magnetization value increases with increase in Gd concentration below TN(Dy) as observed from the M-T plot. The magnetic hysteresis loop is fitted to extract ferromagnetic (FM), antiferromagnetic/paramagnetic (AFM/PM) contributions for each composition x. Fittings of M-H loops indicate the increase in magnetic contribution below TN(Dy) upon increasing the Gd concentrations, while that decreases above TN(Dy). The temperature dependent specific heat data identifies these magnetic transition temperatures TN(Dy), Tlock and TN(Mn). Furthermore, magnetic field dependencies on TN(Dy), Tlock and TN(Mn) are studied in an elaborate manner. Both DMO and DGMO samples are found to be viable candidates for magnetic refrigeration applications in cryogenic temperature region. The true dielectric response of the material is observed up to 160 K and thereafter large increase in dielectric constant may be due to the extrinsic contribution of polarization phenomena as observed from the temperature dependence dielectric constant ( vs. T) plot. For all compositions, vs. T plot shows peak around Tlock which shifted to 17 K for x = 0.2 (19 K for x = 0). Further the magnetic field dependence of Tlock is studied and observed that the peak becomes broader by the application of magnetic field. The magneto-dielectric study reveals that the dielectric constant increases by the application of magnetic field for all the compositions. Multiferroic composites are promising candidates for magnetic field sensors, next-generation low power memory and spintronic devices, as they exhibit much higher magneto-electric coupling at room temperature (RT) compared to the single-phase multiferroics. Hence, the 3-0 type particulate multiferroic composites having general formula (1-Φ) [PbFe0.5Nb0.5O3]-Φ [Co0.6Zn0.4Fe1.7Mn0.3O4] (Φ = 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 1.0, (1-Φ) PFN-Φ CZFMO) are prepared using a hybrid synthesis technique. Preliminary structural and microstructural analysis are carried out using XRD and FESEM techniques, which suggest the formation of 3-0 type particulate composites without the presence of any impurity phases. The multiferroic behaviour of the composites are studied by measuring polarization versus electric field (P-E) and magnetization versus magnetic field (M-H) characteristics at room temperature. The temperature dependent dielectric behaviour of the composites (Φ = 0.3, 0.4, 0.5) show anomalies around ferroelectric phase transition (Tm) for the PFN phase along with broad relaxation peak arising due to CZFMO phase. For lower compositions (Φ = 0.0, 0.1, 0.2), the dielectric properties as a function of temperature show anomaly around Tm due to dominant contribution from PFN phase. However, the parental phase; PFN shows ferroelectric to paraelectric phase transition around 380 K and the CZFMO shows broad relaxation peak around 455 K. In order to examine the magneto-dielectric effect in PFN-CZFMO composites, frequency dependent dielectric measurement is carried out at various magnetic fields at RT. The nature of magneto-electric coupling is investigated elaborately by employing the Landau’s free energy equation along with the magneto-capacitance measurement. This investigation suggests the existence of biquadratic nature of magneto-electric coupling (P2M2). The magneto-electric coupling measurement also suggests that strain mediated domain coupling between the ferroelectric and magnetic ordering is responsible for the magneto-electric behaviour. The obtained value of direct ME coefficient 26.78 mV/cm-Oe for the optimum concentration Φ = 0.3, found to be higher than the well-known single-phase materials and polycrystalline composites. Solid solution of Pb-based relaxor magneto-electric multiferroics as matrix and ferrite as dispersive phase offer a new way for the fabrication of multiferroic composite. The solid solution of PbZr0.53Ti0.47O3 (PZT) and PbFe0.5Ta0.5O3 (PFT) (0.6PZT-0.4PFT, PZTFT) is a new RT single phase multiferroics material with magneto-electric coupling behaviour. The multiferroic composites of (1-Φ) PZTFT-Φ CZFMO (Φ = 0, 0.1, 0.2, 0.3, 0.4, 0.5, 1.0) are prepared using hybrid synthesis technique. The preliminary structural study from the XRD data conveys the formation of particulate composites and the generation of strain in the composites due to the mismatch of lattice size between the parental phases. The FESEM micrograph showed well dispersion of the CZFMO phase in the matrix of the PZTFT phase. The measured P-E loops for the composites indicate the existence of ferroelectric nature of the composites at RT. The soft magnetic nature is observed from the M-H loops for the composites at RT. Thus, the prepared composites exhibit multiferroic behaviour at RT. The vs. T plots show anomaly across Tm due to the PZTFT phase for all values of Φ. For higher composition, Φ = 0.3, 0.4, 0.5, along with Tm another relaxation peaks are observed which is arising due to CZFMO phase. The magneto-dielectric study at RT suggests change of the dielectric parameters by the application of magnetic field suggesting magneto-dielectric behaviour in the composites. The nature of magneto-electric coupling is investigated and found to be biquadratic in nature. The biquadratic nature of ME coupling for the composites arising from the interface coupling between the constituent phases. The composition Φ = 0.3, display direct magneto-electric coefficient of 20.72 mV/cm-Oe which is found to be the optimum composition among the prepared (1-Φ) PZTFT-Φ CZFMO composites. These composites (1-Φ) PFN-Φ CZFMO and (1-Φ) PZTFT-Φ CZFMO with highest magneto-dielectric properties might be suitable for next-generation low power memory, magnetic field sensors and other multi-functional devices
Dynamic Analyses of CNT-based Viscoelastic Composite Shell Structures in Hygrothermal Conditions
No full textComposite materials are well known for light weight and high specific stiffness, and find many engineering applications but conventional carbon fiber reinforced polymer (CFRP) composites are vulnerable under hygrothermal conditions. Since the discovery of carbon nanotubes (CNT), it has fascinated the researchers and being used to improve the damping properties of such conventional composites due to its large aspect ratio. Dynamic mechanical analysis (DMA-8000) is used to conduct the creep test for nanocomposite (NC) samples as per ASTM-D4065 standard and obtained the frequency dependent viscoelastic properties (i.e storage modulus and loss factor) of NC samples using the Prony series. Viscoelastic properties of NC matrix based carbon fiber reinforced polymer (CNT-CFRP) laminated hybrid composite (HC) and functionally graded carbon nanotube reinforced hybrid composite (FG-CNTRHC) materials have also been determined in frequency domain. Furthermore, the vibration and damping characteristics of CNT reinforced laminated hybrid skewed shell structures under hygrothermal environments have been investigated using finite element method. Finite element modelling has been formulated using an eight noded shell element based on the Koiter’s shell formulation. The transverse shear effect is considered based on the first order shear deformation theory. Based on the above obtained frequency dependent viscoelastic properties, dynamic responses of various composite shell skewed shell panels have been determined. The effects of skewing angle and CNT volume fraction on the modal parameters (such first eigenfrequency and modal loss factor) and dynamic responses of various skewed shell structures under hygrothermal conditions have also studied and reported. The frequency dependant viscoelastic properties are directly used to obtain the frequency responses of the skewed shell panel whereas the transient responses are determined with using inverse fast Fourier transform (IFFT). The effects of staking sequence and power law index on the dynamic responses of such CNT based hybrid composite skewed shell structures have also been studied and analyse
Theoretical and Experimental Analysis of Large Deformation Induced Frequency, Static and Transient Responses of Layered Structure with Cutout under Thermo-Mechanical Loading
No full textThe geometrically nonlinear behavior of cutout abided laminated plate/shell panels under the thermo-mechanical loading is being analyzed in this research. It has been performed computationally via a higher-order finite element (FE) formulation to predict the responses, i.e., static bending, free vibration, and transient deflection. The laminated shell physical model is formulated mathematically using an equivalent single layer theory based on the third-order expansion of displacement variables. Thus, the model maintains the necessary shear deformation, corresponding stress, and strain variation through the panel thickness direction. Additionally, the induced large-deformation within the panel due to the geometrical nonlinearity has been integrated mathematically through Green's and von- Karman strain, including Lagrangian description. Hamilton's principle uses the nonlinear governing equation of motion for the layered structure with and without cutout. The approximate nonlinear numerical solutions are calculated using the selective integration scheme (Gauss-Quadrature) associated with Picard's direct iterative method and the isoparametric FE steps. The finite element discretization of the shell panel is being done using a nine-noded (with nine nodal degrees of freedom) quadrilateral Lagrangian element. A generic computational algorithm has been prepared in MATLAB utilizing the current nonlinear mathematical formulation considering all of the nonlinear higher-order strains to maintain the necessary generality. In general, the consistency of the numerical FE solution is checked initially with adequate numbers of convergence tests. Similarly, the numerical solution accuracy is verified with the available published results (numerical and analytical). The numerical results are compared with the experimental data for the second stage verification at the parent institute by utilizing the available/fabricated lab-scale test rig. Subsequently, the role of cutout parameters (size, shape, position, and orientation), including the various geometrical parameters, loading conditions, and edge-support conditions on the nonlinear structural responses, are studied for a clear insight into the damaged structural modeling. Moreover, the parametric study has been carried out using the temperature-dependent elastic properties of the laminate. The temperature distribution over the surface and thickness of the structure is assumed to be uniform. In addition, the effect of nonlinear strain terms on the final structural responses is presented. Based on the observation, the applicability of the full geometrical (Green-Lagrange) strain-displacement relation is established
Development of Efficient Schemes for Detecting Hematological Disorders
No full textHematological disorders like Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML), and Sickle Cell Anemia (SCA) are life-threatening diseases, which severely affect blood cells and the overall health condition as well. Acute Leukemia (ALL or AML) is a fast-spreading blood cancer that starts in the bone marrow and severely damages white blood cells (WBCs). ALL critically affects lymphocytes and produces lymphoblasts, whereas AML seriously damages myeloid cells. Both ALL and AML severely deteriorate the immune system by reducing the ability to fight against infections. On the other hand, SCA critically damages red blood cells (RBCs) and produces sickle cells by replacing healthy hemoglobins with sickle-hemoglobins. It is so dangerous that it reduces the life span of RBCs from 120 days to 10-20 days. Hence, early disease detection and proper treatment are the utmost requirements to save valuable lives and ultimately optimize mortality rates. The microscopic blood-cell analysis is a cost-effective, efficient, less painful, and reliable approach for early hematological disorder detection.
Recent advancements in hematological disease detection systems have aimed to improve the disease diagnosis performance and make the system more accurate and faster as well. Current developments in computer vision, deep and machine learning in medical image analysis make the Computer-Aided Diagnosis (CAD) system more popular for automatic disease detection. However, noise, intensity inhomogeneity, weak edges, overlapping, and touched cells make the segmentation and classification more challenging.
In this thesis, the objective is to develop a more efficient CAD-based system for automatic diagnosis of ALL, AML, and SCA yielding more accurate and more precise results. For this purpose, several models have been developed to investigate the performance. In machine learning-based classification models, we emphasize the improvement of classification ability and are equally concerned about more accurate segmentation.
In Chapter 3, a novel hybrid ellipse-fitting-based segmentation model (HEFSM) is proposed by hybridizing a new geometric ellipse-fitting approach (in which minor and major axes are more accurately evaluated depending upon the residue and suggested residue-offset) with algebraic ellipse-fitting. Hence, it yields superior performance than other ellipse-fitting approaches since it retains the benefits of both approaches. Furthermore, least-square-based HEFSM is computationally less expensive as it is a hybrid of noniterative geometric and algebraic ellipse-fitting approaches. Moreover, bounded opening followed by fast radial symmetry (BO-FRS)-based seed-point detection is recommended to attain more accurate detection.
Though the proposed HEFSM outperforms other ellipse-fitting approaches, its segmentation performance is comparatively less accurate than level set methods (LSMs) as the structures of blood cells are not perfectly elliptical. It may also suffer from low break-down point issues due to least-square-based ellipse-fitting. It inspires us to develop a novel level set evolution-based blood cell segmentation model. A new adaptive weight optimized level set evolution (A WOLSE) is proposed, where the significant contribution is to update the weights of the area- and edge- terms adaptively by optimizing the energy functions. Thus, it results in more precise boundary detection. Nevertheless, a hybridization of AWOLSE with the watershed algorithm is performed to achieve proper segmentation of touched and overlapping cells. Computationally efficient adaptive weight optimization and excellent segmentation performance with more accurate boundary detection make it a preferred segmentation scheme for practical implementation.
In chapter 4, several classification models have been developed for more accurate acute leukemia (ALL or AML) detection using machine learning and deep learning.
First, a hybrid machine learning-based acute leukemia (ALL or AML) detection system is developed by hybridizing Support Vector Machine (SVM) with Random Forest (RF). The efficient AWOLSE-based segmentation model (the best performing segmentation model, as discussed in Chapter 2) is applied to yield more accurate contour detection. In addition, a hybridization of A WOLSE and Watershed algorithm is performed to achieve proper segmentation of overlapping cells. Then, Gray Level Co-occurrence Matrices (GLCM)-based feature extraction followed by Principal Component Analysis (PCA)-based feature selection are employed to select more significant features.
Recent advancements in deep learning motivate us to develop deep learning-based classification systems for ALL or AML detection, which does not need additional segmentation steps, unlike machine learning-based systems. However, classical deep learning models are essential for training the models properly to deliver outstanding performance. On the other hand, the major challenging issue in medical image processing research is the unavailability of huge standard databases. Nowadays, transfer learning is becoming an emerging trend of research in the medical image processing field because of its promising performance in small databases. It inspires us to develop efficient transfer learning-based leukemia detection systems.
Second, a lightweight ShufileNet-based blood cancer detection system is developed whose salient features: pointwise-group convolution and channel shuffling are responsible for making the system faster and efficient.
Third, a new transfer learning-based acute leukemia detection model is developed. It consists of lightweight MobileNetV2-based feature extraction followed by an SVM-based classification. Inverted residual bottleneck structure, depthwise separable convolution, and tunable hyperparameter make the feature extraction effective and computationally efficient as well. In addition, in SVM, the optimization of hyperplane locations boosts the classification performance.
Fourth, a novel hybrid transfer learning framework is developed to more accurately detect acute leukemia by hybridizing lightweight MobileNetV2 with ResNet18. An efficient weight factor is recommended to achieve efficient hybridization. Thus, the integrated advantages of both MobileNetV2 and ResNet18 (inverted residual bottleneck structure, depthwise separable convolution, tunable multiplier, identity mapping, and residual learning) improve the excellence of the system.
Fifth, a novel Orthogonal Softmax Layer (OSL)-based acute leukemia detection system is developed to improve the performance further. The ResNet18-based feature extraction and OSL-based classification make it more effective. Hence, the merits of ResNet (identity mapping and residual learning) are integrated with the merits of OSL ( enhancement of computational efficiency and feature discrimination ability) to deliver promising classification performance.
In Chapter 5, two new Atrous Convolution-based Hybrid DeepLabV3+ Architectures (ACHDAs): ACHDA-I and ACHDA-11, are designed and developed to yield efficient semantic segmentation for more accurate Sickle Cell Anemia (SCA) detection. These two deep learning-based semantic segmentation schemes can yield more efficient anomaly localization in addition to more accurate disease detection. Here, a Modified DeepLab V3+ Architecture (MDA) is recommended in which lightweight MobileNetV2 or ResNet50 is employed as a base classifier rather than a computationally expensive Xception. Moreover, ACHDA-I is developed by hybridizing MDA-1 (MDA with MobileNetV2-based classification and Adaptive moment (Adam)-based optimization) with MDA-2 (MDA with ResNet50-based classification and Stochastic Gradient descent method (SGDM)-based optimization). Hence, it combines the merits of both the classifiers and both optimizers that result in performance improvement. Furthermore, ACHDA-11 is suggested in which only the input image's saturation information (S-component ofHSV color model) is utilized to minimize false-positive and improve performance further. More importantly, these two schemes: ACHDA-I and ACHDA-11, also retain the benefits due to the employment of Atrous convolution and Atrous Spatial Pyramid-based Pooling (ASPP) for feature extraction and implementation of the efficient decoder module for upgrading the segmentation performance at object boundaries.
The experimental results show that the proposed models yield superior performance than the other models, available in the literature, in respective categories. Among the proposed segmentation models, the A WOLSE-based segmentation model outperforms others, whereas the (OSL)-based acute leukemia detection system exhibits the best classification performance in detecting ALL or AML. The proposed semantic segmentation scheme: ACHDA-11, demonstrates the best SCA detection performance
Influence of High Fat Diet, Bacterial Infection and Clock Mutation on Circadian Rhythm and Sensory Modalities of Drosophila Melanogaster
No full textCircadian clock is an endogenous time keeping system which is conserved from bacteria to human beings. Years of research in vertebrates, suggest close association of circadian clock with parameters like metabolism, physiology, aging, sleep, behavior, neurodegeneration and other metabolic disorder. Several model organisms including Drosophila melanogaster are used to establish the role of circadian rhythm in day to day activity. The current study aims to investigate the role of three key parameters on circadian rhythm. The first parameter is high-fat diet mediated diabesity and its effect on circadian rhythm. For this experiment the larva and adults of D.melanogaster were exposed to high-fat diet (HFD) through oral route. After feeding the larva and adults have excess fat and micronuclei within the gut, fat body, and crop. Larva and adults of HFD showed behavioral defects, impaired metabolite profile, and overexpression of insulin gene (Dilp2) and tribble (trbl) gene confirmed insulin resistance. Elevated ROS level, developmental delay, altered metal level, growth defects, locomotory rhythms, sleep fragmentation, and expression of circadian genes (per, tim, and clock) in HFD larva and adults. In the second objective the effect of host pathogen interaction and its co-relation between circadian rhythm was established. For this study both gram-negative bacteria, Pseudomonas aeruginosa and gram-positive bacteria Staphylococcus aureus was examined on D. melanogaster physiology, behavior and circadian clock. Infections lead to phenotype and behavioral defects, developmental delay, oxidative stress and nuclear damages in larvae as well as adults. Increased level of expression of immune genes and disrupted circadian clock related co-mordities in Drosophila melanogaster were detected. The third objective checked Drosophila clock (ClkJrkst) mutation on behavioral and molecular changes in their eye and hearing organ, defective oxidative state, and status of TRP channel genes, physiology, metabolism, and behavior in Drosophila. The current study suggests the chronobiological consideration towards treatment for type-II diabetes, infectious disease and circadian anomalies