3D Visualization Modules for Chemical Engineering – A Web-Based Approach Using Java and OpenGL

The main objective of this work is to implement web-based educational modules for chemical engineering students. Phase behavior is a topic with which the students seem to struggle with, particularly for mixtures, where a 2-D representation of the phase diagram falls far short of the understanding a 3-D model can provide. Using the platform-independence of Java and the graphics capability of OpenGL, three phase diagram Java applets have been developed. Users can view these web-based 3D applets by installing a plug-in. These modules provide users with an ability to rotate the 3D models, slice through them, zoom into them and view their various 2D projections. Also, a molecular simulation applet for measuring chemical potential of binary mixtures has been developed, using a Java-based molecular simulation application-programming interface (API). First, the thesis presents a brief overview of phase diagrams and explains why modeling them using computer graphics is useful. While visualization involves the merging of data with the display of geometric objects through computer graphics, it is important to study the software issues involved in web-based visualization. The paper explains the visualization framework by describing the visualization pipeline and then using it as a guideline for the development of the modules. Next, the paper describes the development of the molecular simulation applet using a molecular simulation API - Etomica. The Java applet provides for dynamic modification and interrogation of the simulation, while it is in progress, which enables students to see directly the effect of changing state conditions or molecular interactions on the behavior of the molecules and on the outcome of the simulation. It is hoped that by using these web-based 3D phase diagrams the chemical engineering students would gain a better understanding of the complicated 3D models, making this package a useful instructional aid. It is also hoped that the molecular simulation applet would be an effective tool to help students understand molecular simulations

Privacy-Preserving Secret Shared Computations using MapReduce

Data outsourcing allows data owners to keep their data at \emph{untrusted} clouds that do not ensure the privacy of data and/or computations. One useful framework for fault-tolerant data processing in a distributed fashion is MapReduce, which was developed for \emph{trusted} private clouds. This paper presents algorithms for data outsourcing based on Shamir's secret-sharing scheme and for executing privacy-preserving SQL queries such as count, selection including range selection, projection, and join while using MapReduce as an underlying programming model. Our proposed algorithms prevent an adversary from knowing the database or the query while also preventing output-size and access-pattern attacks. Interestingly, our algorithms do not involve the database owner, which only creates and distributes secret-shares once, in answering any query, and hence, the database owner also cannot learn the query. Logically and experimentally, we evaluate the efficiency of the algorithms on the following parameters: (\textit{i}) the number of communication rounds (between a user and a server), (\textit{ii}) the total amount of bit flow (between a user and a server), and (\textit{iii}) the computational load at the user and the server.\BComment: IEEE Transactions on Dependable and Secure Computing, Accepted 01 Aug. 201

Results with Random Fuzzy Metric Spaces

In this paper we obtain some fixed point results in random fuzzy metric space of two mappings. Keywords: Fixed point, Random  Fuzzy metric space. Mathematical Subject Classification: 45H10, 54H25

Fixed Point Results in Fuzzy F Menger Metric Space

In this paper we prove fixed point theorems in Fuzzy F menger space with non compatible condition and rational expression. AMS Classification: 47H10, 54H25. Key Words: Fuzzy F Menger Space, Non-Compatible Mappings, Common Fixed Points, Discontinuity, R-weak commutative of type (Ag)

Random Fuzzy metric space with cyclic contraction

In the paper, we define a random fuzzy cyclic contraction and prove the existence and uniqueness of fixed points in a random fuzzy metric space

Combined Scheduling, Memory Allocation and Tensor Replacement for Minimizing Off-Chip Data Accesses of DNN Accelerators

Specialized hardware accelerators have been extensively used for Deep Neural Networks (DNNs) to provide power/performance benefits. These accelerators contain specialized hardware that supports DNN operators, and scratchpad memory for storing the tensor operands. Often, the size of the scratchpad is insufficient to store all the tensors needed for the computation, and additional data accesses are needed to move tensors back and forth from host memory during the computation with significant power/performance overhead. The volume of these additional data accesses depends on the operator schedule, and memory allocation (specific locations selected for the tensors in the scratchpad). We propose an optimization framework, named COSMA, for mapping DNNs to an accelerator that finds the optimal operator schedule, memory allocation and tensor replacement that minimizes the additional data accesses. COSMA provides an Integer Linear Programming (ILP) formulation to generate the optimal solution for mapping a DNN to the accelerator for a given scratchpad size. We demonstrate that, using an off-the-shelf ILP solver, COSMA obtains the optimal solution in seconds for a wide-range of state-of-the-art DNNs for different applications. Further, it out-performs existing methods by reducing on average 84% of the non-compulsory data accesses. We further propose a divide-and-conquer heuristic to scale up to certain complex DNNs generated by Neural Architecture Search, and this heuristic solution reduces on average 85% data accesses compared with other works

Expanding the complexity and functional diversity of bis-amino acid building blocks

We are developing a unique approach to the synthesis of macromolecules with programmable shape. These scaffolds are assembled from stereochemically pure orthogonally protected bis-amino acids that are interconnected by two amide bonds. This ladder-like arrangement restricts the conformational flexibility of bis-amino acids to a large extent which in turn drastically reduces the number of allowed conformations for an oligomer. As a result, significantly lesser computing power is needed for the final three-dimensional structure prediction. Several stereochemically pure bis-amino acid monomers have been synthesized by our research group and incorporated into a number of homo- and hetero-oligomers.In this dissertation we present the synthesis of a new pipecolic acid-based bis-amino acid building block pip5(2S5S). Assembly of this monomer into a short spiroladder oligomer utilizing solid-phase synthesis followed by in situ activation by dicyclohexylcarbodiimide and N-hydroxysuccinimide has been demonstrated. The structure of the oligomer was determined in aqueous solution using two-dimensional NMR. We report improved conditions for rapidly and simultaneously closing multiple diketopiperazines on solid support. These new conditions involve either heating of a suspension of solid supported amino-tetrafluoropropyl esters in acetic acid/triethylamine catalyst solution in a microwave oven or continuous flow of catalyst solution through the resin, heated in a special flow cell apparatus.Finally, the synthesis of the first functionalized bis-amino acid monomer proAc(2S3S4R) that carries an acetyl side chain is presented. This monomer was incorporated into a short oligomer and the solution phase structure was determined using two-dimensional nuclear magnetic resonance. The solution structure confirmed the intended connectivity and stereochemistry of the oligomer. This first functionalized bis-amino acid represents a milestone towards functionalized bis-peptide nanostructures for catalytic, molecular recognition and nanotechnology applications