Modeling of Suspended Sediment Dynamics in Tropical River Basins

It is proposed to study the suspended sediment transport characteristics of river basins of Kerala and to model suspended sediment discharge mechanism for typical micro-watersheds. The Pamba river basin is selected as a representative hydrologic regime for detailed studies of suspended sediment characteristics and its seasonal variation. The applicability of various erosion models would be tested by comparing with the observed event data (by continuous monitoring of rainfall, discharge, and suspended sediment concentration for lower order streams). Empirical, conceptual and physically distributed models were used for making the comparison of performance of the models. Large variations in the discharge and sediment quantities were noticed during a particular year between the river basins investigated and for an individual river basin during the years for which the data was available. In general, the sediment yield pattern follows the seasonal distribution of rainfall, discharge and physiography of the land. This confirms with similar studies made for other Indian rivers. It was observed from this study, that the quantity of sediment transported downstream shows a decreasing trend over the years corresponding to increase in discharge. For sound and sustainable management of coastal zones, it is important to understand the balance between erosion and retention and to quantify the exact amount of the sediments reaching this eco-system. This, of course, necessitates a good length of time series data and more focused research on the behaviour of each river system, both present and past. In this realm of river inputs to ocean system, each of the 41 rivers of Kerala may have dominant yet diversified roles to influence the coastal ecosystem as reflected from this study on the major fraction of transport, namely the suspended sediments

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Modeling Of Work-Related Musculoskeletal Disorders In Chemical Process Industry In India

In this modern complex world, stress at work is found to be increasingly a common feature in day to day life. For the same reason, job stress is one of the active areas in occupational health and safety research for over last four decades and is continuing to attract researchers in academia and industry. Job stress in process industries is of concern due to its influence on process safety, and worker‘s safety and health. Safety in process (chemical and nuclear material) industry is of paramount importance, especially in a thickly populated country like India. Stress at job is the main vector in inducing work related musculoskeletal disorders which in turn can affect the worker health and safety in process industries. In view of the above, the process industries should try to minimize the job stress in workers to ensure a safe and healthy working climate for the industry and the worker. This research is mainly aimed at assessing the influence of job stress in inducing work related musculoskeletal disorders in chemical process industries in India

Modeling of ALFA Programs Using PVS Theorem Prover

In Safety critical software failure can have a high price. Such software should be free of errors before it is put into operation. Application of formal methods in the Software Development Life Cycle helps to ensure that the software for safety critical missions are ultra reliable. PVS theorem prover, a formal method tool, can be used for the formal verification of software in ADA Language for Flight Software Application (ALFA.). This paper describes the modeling of ALFA programs for PVS theorem prover. An ALFA2PVS translator is developed which automatically converts the software in ALFA to PVS specification. By this approach the software can be verified formally with respect to underflow/overflow errors and divide by zero conditions without the actual execution of the code.

Modeling of ALFA Programs Using PVS Theorem Prover

In Safety critical software failure can have a high price. Such software should be free of errors before it is put into operation. Application of formal methods in the Software Development Life Cycle helps to ensure that the software for safety critical missions are ultra reliable. PVS theorem prover, a formal method tool, can be used for the formal verification of software in ADA Language for Flight Software Application (ALFA.). This paper describes the modeling of ALFA programs for PVS theorem prover. An ALFA2PVS translator is developed which automatically converts the software in ALFA to PVS specification. By this approach the software can be verified formally with respect to underflow/overflow errors and divide by zero conditions without the actual execution of the code

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Modification of Polypropylene and Polystyrene Using Nanosilica

The present work focuses on the modification of the commonly used thermoplastics, polypropylene and polystyrene using nanosilica preparcd from a cheap source of sodium silicate. Melt compounding technique has been used for nanocomposite preparation as it is simple and suited to injection moulding. Nanosilica in a polymer matrix provide significant enhancement in strength, stiffness and impact strength. Incorporation of silica particles in a polymer also improves its thennal stability. To achieve better dispersion of fillers in polymer matrices the mixing was done at different shear rates. The enhancement in material properties indicates that at higher shear rates there is greater interaction between particles and the matrix and it depends on filler concentration and type of polymer used. N anosilica is a useful filler in thennoplastic polymers and has been applied in automotive applications, electronic appliances and consumer goods.This thesis is divided into six chapters. General introduction to the topic is described in chapter 1. Salient features of polymer nanocomposites, their synthesis, properties and applications are presented. A review of relevant literature and the scope and objectives are also mentioned in this chapter.The materials used and the vanous experimental method and techniques employed in the study are described in chapter 2. Preparation of nanocomposites by melt blending using Thenno Haake Rheocord, preparation of samples, evaluation of mechanical and thennal properties using UTM, Impact testing and characterization using DMA, TGA and DSC and morphology by SEM are described.The preparation of nanosilica from a laboratory scale to a pilot plant scale is described in chapter 3. Generation of surface modified silica, evaluation of kinetic parameters of the synthesis reaction, scale up of the reactor and modeling of the reactor are also dealt with in this chapter.The modification of the commodity thennoplastic, Polypropylene using nanosilica is described in chapter 4. Preparation of PP/silica nanocomposites, evaluation of mechanical properties, thermal and crystallization characteristics, water absorption and ageing resistance studies are also presented.The modification of Polystyrene using synthesized nanosilica IS described in chapter 5. The method of preparation of PS/silica nanocomposites, evaluation of mechanical properties (static and dynamic), thermal properties melt flow characteristics using Haake Rheocord, water absorption and ageing resistance of these nanocomposites are studied.

Sea Surface Temperature-Convection Relationship in Tropical Oceans with Special Emphasis to Intraseasonal Variability of Indian Summer Monsoon

The SST convection relation over tropical ocean and its impact on the South Asian monsoon is the first part of this thesis. Understanding the complicated relation between SST and convection is important for better prediction of the variability of the Indian monsoon in subseasonal, seasonal, interannual, and longer time scales. Improved global data sets from satellite scatterometer observations of SST, precipitation and refined reanalysis of global wind fields have made it possible to do a comprehensive study of the SST convection relation. Interaction of the monsoon and Indian ocean has been discussed. A coupled feedback process between SST and the Active-Break cycle of the Asian summer monsoon is a central theme of the thesis. The relation between SST and convection is very important in the field of numerical modeling of tropical rainfall. It is well known that models generally do very well simulating rainfall in areas of tropical convergence zones but are found unable to do satisfactory simulation in the monsoon areas. Thus in this study we critically examined the different mechanisms of generation of deep convection over these two distinct regions.The study reported in chapter 3 has shown that SST - convection relation over the warm pool regions of Indian and west Pacific oceans (monsoon areas) is in such a way that convection increases with SST in the SST range 26-29 C and for SST higher than 29-30 C convection decreases with increase of SST (it is called Waliser type). It is found that convection is induced in areas with SST gradients in the warm pool areas of Indian and west Pacific oceans. Once deep convection is initiated in the south of the warmest region of warm pool, the deep tropospheric heating by the latent heat released in the convective clouds produces strong low level wind fields (Low level Jet - LLJ) on the equatorward side of the warm pool and both the convection and wind are found to grow through a positive feedback process. Thus SST through its gradient acts only as an initiator of convection. The central region of the warm pool has very small SST gradients and large values of convection are associated with the cyclonic vorticity of the LLJ in the atmospheric boundary layer. The conditionally unstable atmosphere in the tropics is favorable for the production of deep convective clouds.

Development of Free Space Method for Material Characterisation and GPR Study & A Case Study on Biological Samples

The thesis mainly focuses on material characterization in different environments: freely available samples taken in planar fonn, biological samples available in small quantities and buried objects.Free space method, finds many applications in the fields of industry, medicine and communication. As it is a non-contact method, it can be employed for monitoring the electrical properties of materials moving through a conveyor belt in real time. Also, measurement on such systems at high temperature is possible. NID theory can be applied to the characterization of thin films. Dielectric properties of thin films deposited on any dielectric substrate can be determined. ln chemical industry, the stages of a chemical reaction can be monitored online. Online monitoring will be more efficient as it saves time and avoids risk of sample collection.Dielectric contrast is one of the main factors, which decides the detectability of a system. lt could be noted that the two dielectric objects of same dielectric constant 3.2 (s, of plastic mine) placed in a medium of dielectric constant 2.56 (er of sand) could even be detected employing the time domain analysis of the reflected signal. This type of detection finds strategic importance as it provides solution to the problem of clearance of non-metallic mines. The demining of these mines using the conventional techniques had been proved futile. The studies on the detection of voids and leakage in pipes find many applications.The determined electrical properties of tissues can be used for numerical modeling of cells, microwave imaging, SAR test etc. All these techniques need the accurate determination of dielectric constant. ln the modem world, the use of cellular and other wireless communication systems is booming up. At the same time people are concemed about the hazardous effects of microwaves on living cells. The effect is usually studied on human phantom models. The construction of the models requires the knowledge of the dielectric parameters of the various body tissues. lt is in this context that the present study gains significance. The case study on biological samples shows that the properties of normal and infected body tissues are different. Even though the change in the dielectric properties of infected samples from that of normal one may not be a clear evidence of an ailment, it is an indication of some disorder.ln medical field, the free space method may be adapted for imaging the biological samples. This method can also be used in wireless technology. Evaluation of electrical properties and attenuation of obstacles in the path of RF waves can be done using free waves. An intelligent system for controlling the power output or frequency depending on the feed back values of the attenuation may be developed.The simulation employed in GPR can be extended for the exploration of the effects due to the factors such as the different proportion of water content in the soil, the level and roughness of the soil etc on the reflected signal. This may find applications in geological explorations. ln the detection of mines, a state-of-the art technique for scanning and imaging an active mine field can be developed using GPR. The probing antenna can be attached to a robotic arm capable of three degrees of rotation and the whole detecting system can be housed in a military vehicle. In industry, a system based on the GPR principle can be developed for monitoring liquid or gas through a pipe, as pipe with and without the sample gives different reflection responses. lt may also be implemented for the online monitoring of different stages of extraction and purification of crude petroleum in a plant.Since biological samples show fluctuation in the dielectric nature with time and other physiological conditions, more investigation in this direction should be done. The infected cells at various stages of advancement and the normal cells should be analysed. The results from these comparative studies can be utilized for the detection of the onset of such diseases. Studying the properties of infected tissues at different stages, the threshold of detectability of infected cells can be determined.

Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

Service quality and reliability assessment of mobile communication infrastructure

The service quality of any sector has two major aspects namely technical and functional. Technical quality can be attained by maintaining technical specification as decided by the organization. Functional quality refers to the manner which service is delivered to customer which can be assessed by the customer feed backs. A field survey was conducted based on the management tool SERVQUAL, by designing 28 constructs under 7 dimensions of service quality. Stratified sampling techniques were used to get 336 valid responses and the gap scores of expectations and perceptions are analyzed using statistical techniques to identify the weakest dimension. To assess the technical aspects of availability six months live outage data of base transceiver were collected. The statistical and exploratory techniques were used to model the network performance. The failure patterns have been modeled in competing risk models and probability distribution of service outage and restorations were parameterized. Since the availability of network is a function of the reliability and maintainability of the network elements, any service provider who wishes to keep up their service level agreements on availability should be aware of the variability of these elements and its effects on interactions. The availability variations were studied by designing a discrete time event simulation model with probabilistic input parameters. The probabilistic distribution parameters arrived from live data analysis was used to design experiments to define the availability domain of the network under consideration. The availability domain can be used as a reference for planning and implementing maintenance activities. A new metric is proposed which incorporates a consistency index along with key service parameters that can be used to compare the performance of different service providers. The developed tool can be used for reliability analysis of mobile communication systems and assumes greater significance in the wake of mobile portability facility. It is also possible to have a relative measure of the effectiveness of different service providers.

Numerical Simulation of Two-Part Underwater Towing System

The motion instability is an important issue that occurs during the operation of towed underwater vehicles (TUV), which considerably affects the accuracy of high precision acoustic instrumentations housed inside the same. Out of the various parameters responsible for this, the disturbances from the tow-ship are the most significant one. The present study focus on the motion dynamics of an underwater towing system with ship induced disturbances as the input. The study focus on an innovative system called two-part towing. The methodology involves numerical modeling of the tow system, which consists of modeling of the tow-cables and vehicles formulation. Previous study in this direction used a segmental approach for the modeling of the cable. Even though, the model was successful in predicting the heave response of the tow-body, instabilities were observed in the numerical solution. The present study devises a simple approach called lumped mass spring model (LMSM) for the cable formulation. In this work, the traditional LMSM has been modified in two ways. First, by implementing advanced time integration procedures and secondly, use of a modified beam model which uses only translational degrees of freedoms for solving beam equation. A number of time integration procedures, such as Euler, Houbolt, Newmark and HHT-α were implemented in the traditional LMSM and the strength and weakness of each scheme were numerically estimated. In most of the previous studies, hydrodynamic forces acting on the tow-system such as drag and lift etc. are approximated as analytical expression of velocities. This approach restricts these models to use simple cylindrical shaped towed bodies and may not be applicable modern tow systems which are diversed in shape and complexity. Hence, this particular study, hydrodynamic parameters such as drag and lift of the tow-system are estimated using CFD techniques. To achieve this, a RANS based CFD code has been developed. Further, a new convection interpolation scheme for CFD simulation, called BNCUS, which is blend of cell based and node based formulation, was proposed in the study and numerically tested. To account for the fact that simulation takes considerable time in solving fluid dynamic equations, a dedicated parallel computing setup has been developed. Two types of computational parallelisms are explored in the current study, viz; the model for shared memory processors and distributed memory processors. In the present study, shared memory model was used for structural dynamic analysis of towing system, distributed memory one was devised in solving fluid dynamic equations.

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Development & evaluation of different acoustic models for Malayalam continuous speech recognition

Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.

Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.