Design, Simulation and Fabrication of Insulated Gate Bipolar Transistors (IGBT)

This project serves as a study to determine the feasibility of the current CMOS toolsets and processes available at Semiconductor & Microsystems Fabrication Laboratory (SMFL) for the fabrication of whole wafer power devices. Several designs and devices were explored. The Insulated Gate Bipolar Transistor (~LGBT) is a device widely used for high power electronic applications and was selected for this study. This device has bipolar current flow and a MOS gate thus combining advantages of both the Double diffused MOS (DMOS) and Power Bipolar junction transistor. Prototypes consisting of transistors with varying densities, gate lengths and gate widths were fabricated to characterize these devices Attempts were made to study the effect of field oxide thickness on breakdown voltage. Photomask were designed in mentor graphics. Process was designed to obtain required power rating. The desIgn was simulated in ATHENA to verify the process conditions. The IGBTs were fabricated as per the design on standard 4” high resistivity n-type wafers. 8 device wafers and 4 control wafers were used for the process, which involved 4 mask levels. Two additional wafers were processed with this lot to obtain DMOS. The fabricated devices were tested to determine electrical characteristics. The IV characteristics obtained for both the DMOS and IGBT exhibit field effect. However this field effect is in parallel with a parasitic conductance and limits the transistor from turning off. It is also observed that the devices are operational as depletion mode devices instead of enhancement mode devices. The shortcomings of the current process and device designed have been listed and required modifications have been suggested

Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs

The idea of computer vision as the Bayesian inverse problem to computer graphics has a long history and an appealing elegance, but it has proved difficult to directly implement. Instead, most vision tasks are approached via complex bottom-up processing pipelines. Here we show that it is possible to write short, simple probabilistic graphics programs that define flexible generative models and to automatically invert them to interpret real-world images. Generative probabilistic graphics programs consist of a stochastic scene generator, a renderer based on graphics software, a stochastic likelihood model linking the renderer's output and the data, and latent variables that adjust the fidelity of the renderer and the tolerance of the likelihood model. Representations and algorithms from computer graphics, originally designed to produce high-quality images, are instead used as the deterministic backbone for highly approximate and stochastic generative models. This formulation combines probabilistic programming, computer graphics, and approximate Bayesian computation, and depends only on general-purpose, automatic inference techniques. We describe two applications: reading sequences of degraded and adversarially obscured alphanumeric characters, and inferring 3D road models from vehicle-mounted camera images. Each of the probabilistic graphics programs we present relies on under 20 lines of probabilistic code, and supports accurate, approximately Bayesian inferences about ambiguous real-world images.Comment: The first two authors contributed equally to this wor

Perceptions of the Use of Blueprinting in a Formative Theory Assessment in Pharmacology Education

Objectives: This study aimed to assess perceptions of the use of a blueprint in a pharmacology formative theory assessment. Methods: This study took place from October 2015 to February 2016 at a medical college in Gujurat, India. Faculty from the Department of Pharmacology used an internal syllabus to prepare an assessment blueprint. A total of 12 faculty members prepared learning objectives and categorised cognitive domain levels by consensus. Learning objectives were scored according to clinical importance and marks were distributed according to proportional weighting. A three-dimensional test specification table of syllabus content, assessment tools and cognitive domains was prepared. Based on this table, a theory paper was created and administered to 126 pharmacology students. Feedback was then collected from the faculty members and students using a 5-point Likert scale. Results: The majority of faculty members agreed that using a blueprint ensured proper weighting of marks for important topics (90.00%), aligned questions with learning objectives (80.00%), distributed questions according to clinical importance (100.00%) and minimised inter-examiner variations in selecting questions (90.00%). Few faculty members believed that use of the blueprint created too many easy questions (10.00%) or too many difficult questions (10.00%). Most students felt that the paper had a uniform distribution of questions from the syllabus (90.24%), that important topics were appropriately weighted (77.23%), was well organised (79.67%) and tested indepth subject knowledge (74.80%). Conclusion: These findings indicate that blueprinting should be an integral part of written assessments in pharmacology education

Trust Management In Ad-hoc Networks: A Social Network Based Approach

A social network is a social structure made up of individuals called œnodes, which are connected by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange, dislike, or relationships of beliefs, knowledge or prestige.Social network analysis views social relationships in terms of network theory consisting of nodes and ties (also called edges, links, or connections). Nodes are the individual actors within the networks, and ties are the relationships between the actors. The resulting graph-based structures are often very complex. There can be many kinds of ties between the nodes. Research in a number of academic fields has shown that social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals succeed in achieving their goals.We propose a social network based approach for trust management in ad-hoc networks, where nodes trust, help and interact with each other to create a complex trust-worthy network. Keywords: Trust management, ad-hoc network, social network, attack