Quality characteristics of edible vegetable oil blends

Two edible oil blends, namely groundnut oil:rice-bran oil and mustard oil:rice-bran oil, were prepared in different proportions and stored for a period of three years. Their physicochemical characteristics were determined. The results agreed with expected values except for free fatty acid percents and butyrorefrac-tometer readings, presumably due to rancidity. Fatty acid compositions of the blends were determined and ratios of characteristic fatty acids, like lignoceric to palmitic for groundnut oil:rice-bran oil blends, and erucic to palmitic for mustard oil:rice-bran oil blends, were calculated to identify individual oils in the blend.     

Performance models of storage contention in cloud environments

We propose simple models to predict the performance degradation of disk requests due to storage device contention in consolidated virtualized environments. Model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same server. We first propose a trace-driven approach that evaluates a queueing network with fair share scheduling using simulation. The model parameters consider Virtual Machine Monitor level disk access optimizations and rely on a calibration technique. We further present a measurement-based approach that allows a distinct characterization of read/write performance attributes. In particular, we define simple linear prediction models for I/O request mean response times, throughputs and read/write mixes, as well as a simulation model for predicting response time distributions. We found our models to be effective in predicting such quantities across a range of synthetic and emulated application workloads.     

Performing Efficient NURBS Modeling Operations on the GPU

We present algorithms for evaluating and performing modeling operations on NURBS surfaces using the programmable fragment processor on the Graphics Processing Unit (GPU). We extend our GPU-based NURBS evaluator that evaluates NURBS surfaces to compute exact normals for either standard or rational B-spline surfaces for use in rendering and geometric modeling. We build on these calculations in our new GPU algorithms to perform standard modeling operations such as inverse evaluations, ray intersections, and surface-surface intersections on the GPU. Our modeling algorithms run in real time, enabling the user to sketch on the actual surface to create new features. In addition, the designer can edit the surface by interactively trimming it without the need for retessellation. Our GPU-accelerated algorithm to perform surface-surface intersection operations with NURBS surfaces can output intersection curves in the model space as well as in the parametric spaces of both the intersecting surfaces at interactive rates. We also extend our surface-surface intersection algorithm to evaluate self-intersections in NURBS surfaces.     

Location and Sizing of Defects in Coated Metallic Pipes Using Limited View Scattered Data in Frequency Domain

The inverse problem of reconstructing the location and size of defects in a coated metallic pipe from single frequency limited view electromagnetic scattered field is considered. Specifically, the paper addresses the problem of assessing shape changes in the shadow region entailed by limited view data in 2D by operating in an intermediate size parameter (ka) range. The inverse scattering problem is formulated as a non-linear optimization problem solved through genetic algorithm that seeks to minimize in the least-squared sense the difference between measured data and simulated data through iterations of the solution to a forward problem. The hybrid finite element boundary integral formulations were used to solve the forward problem of coated metallic pipe with defects. The proposed inversion methodology was applied for shadow region shape change assessment to determine whether a metal pipe is coated or not, and to reconstruct the location and size of corrosion-like defect, over a range of size parameters. The study is carried out using transverse electric and transverse magnetic polarized fields. To understand the effect of coating on backscattered fields, parametric studies are conducted using numerical data. A range for size parameter \(2.0\le ka\le 4\) was found to produce the highest contrast between defect free pipe and coated metallic pipes with defects in the deep shadow region. The experiments are carried out using vector network analyzer in an anechoic chamber. The inversion results obtained using measured data were found be in good agreement with inversion results obtained using synthetic data. Estimated extent of corrosion in deep shadow region of a coated metallic pipe was found to be within 9 % of actual extent of corrosion.     

Sub‐Micron Anisotropic InP‐based III–V Semiconductor Material Deep Etching for On‐Chip Laser Photonics Devices

Two InP‐based III–V semiconductor etching recipes are presented for fabrication of on‐chip laser photonic devices. Using inductively coupled plasma system with a methane free gas chemistry of chlorine and nitrogen at a high substrate temperature of 250 °C, high aspect ratio, anisotropic InP‐based nano‐structures are etched. Scanning electron microscopy images show vertical sidewall profile of 90° ± 3°, with aspect ratio as high as 10. Atomic Force microscopy measures a smooth sidewall roughness root‐mean‐square of 2.60 nm over a 3 × 3 μm scan area. The smallest feature size etched in this work is a nano‐ring with inner diameter of 240 nm. The etching recipe and critical factors such as chamber pressure and the carrier plate effect are discussed. The second recipe is of low temperature (?10 °C) using Cl₂ and BCl₃ chemistry. This recipe is useful for etching large areas of III–V to reveal the underlying substrate. The availability of these two recipes has created a flexible III–V etching platform for fabrication of on‐chip laser photonic devices. As an application example, anisotropic InP‐based waveguides of 3 μm width are fabricated using the Cl₂ and N₂ etch recipe and waveguide loss of 4.5 dB mm^?1 is obtained.

     

GPU-accelerated minimum distance and clearance queries

We present practical algorithms for accelerating distance queries on models made of trimmed NURBS surfaces using programmable Graphics Processing Units (GPUs). We provide a generalized framework for using GPUs as coprocessors in accelerating CAD operations. By supplementing surface data with a surface bounding-box hierarchy on the GPU, we answer distance queries such as finding the closest point on a curved NURBS surface given any point in space and evaluating the clearance between two solid models constructed using multiple NURBS surfaces. We simultaneously output the parameter values corresponding to the solution of these queries along with the model space values. Though our algorithms make use of the programmable fragment processor, the accuracy is based on the model space precision, unlike earlier graphics algorithms that were based only on image space precision. In addition, we provide theoretical bounds for both the computed minimum distance values as well as the location of the closest point. Our algorithms are at least an order of magnitude faster and about two orders of magnitude more accurate than the commercial solid modeling kernel ACIS.     

Graphical models for optimal power flow

Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithm for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. Numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.     

Preoperative radiotherapy for adenocarcinoma of the rectosigmoid

Ninety-seven patients with adenocarcinoma of the rectosigmoid have been treated with high dose (5000-6000 rad) preoperative irradiation from 1960 through 1972 at the University of Oregon Health Sciences Center. Fifty-seven were initially clinically resectable and 40 were initially inoperable. Forty of the 57 initially clinically resectable patients had "curative" resections and are at risk for more than 5 years. An increase in 5-year survival (from 38% to 53%) and an absence of pelvic recurrence have occurred in those patients receiving preoperative irradiation and "curative" resection. Four of the 40 initially inoperable patients are alive without tumor. Three of the four survivors had irradiation and surgery; one had irradiation only. An additional four patients had no evidence of tumor at death. Tumor was totally sterilized by irradiation and nine patients and reduced to microfocal extent in an additional three of the 97 patients. Incidence of complications was no greater than has been reported in a surgical series from the same institution.     

Formal Verification Successes at Motorola

Formal tools are either too labor intensive or are completely impractical for industrial-size problems. This paper describes two formal verification tools used within Motorola, Versys2 and CBV, that challenge this assertion. The two tools are being used in current design verification flows and have shown that it is possible to seamlessly integrate formal tools into existing design flows.     

Deep packet inspection using parallel bloom filters

There is a class of packet processing applications that inspect packets deeper than the protocol headers to analyze content. For instance, network security applications must drop packets containing certain malicious Internet worms or computer viruses carried in a packet payload. Content forwarding applications look at the hypertext transport protocol headers and distribute the requests among the servers for load balancing. Packet inspection applications, when deployed at router ports, must operate at wire speeds. With networking speeds doubling every year, it is becoming increasingly difficult for software-based packet monitors to keep up with the line rates. We describe a hardware-based technique using Bloom filters, which can detect strings in streaming data without degrading network throughput. A Bloom filter is a data structure that stores a set of signatures compactly by computing multiple hash functions on each member of the set. This technique queries a database of strings to check for the membership of a particular string. The answer to this query can be false positive but never a false negative. An important property of this data structure is that the computation time involved in performing the query is independent of the number of strings in the database provided the memory used by the data structure scales linearly with the number of strings stored in it. Furthermore, the amount of storage required by the Bloom filter for each string is independent of its length.