Real-Time Global Illumination for VR Applications

Real-time global illumination in VR systems enhances scene realism by incorporating soft shadows, reflections of objects in the scene, and color bleeding. The Virtual Light Field (VLF) method enables real-time global illumination rendering in VR. The VLF has been integrated with the Extreme VR system for real-time GPU-based rendering in a Cave Automatic Virtual Environment.     

Robust self-assembly of graphs

Self-assembly is a process in which small building blocks interact autonomously to form larger structures. A recently studied model of self-assembly is the Accretive Graph Assembly Model whereby an edge-weighted graph is assembled one vertex at a time starting from a designated seed vertex. The weight of an edge specifies the magnitude of attraction (positive weight) or repulsion (negative weight) between adjacent vertices. It is feasible to add a vertex to the assembly if the total attraction minus repulsion of the already built neighbors exceeds a certain threshold, called the assembly temperature. This model naturally generalizes the extensively studied Tile Assembly Model. A natural question in graph self-assembly is to determine whether or not there exists a sequence of feasible vertex additions to realize the entire graph. However, even when it is feasible to realize the assembly, not much can be inferred about its likelihood of realization in practice due to the uncontrolled nature of the self-assembly process. Motivated by this, we introduce the robust self-assembly problem where the goal is to determine if every possible sequence of feasible vertex additions leads to the completion of the assembly. We show that the robust self-assembly problem is co-NP-complete even on planar graphs with two distinct edge weights. We then examine the tractability of the robust self-assembly problem on a natural subclass of planar graphs, namely grid graphs. We identify structural conditions that determine whether or not a grid graph can be robustly self-assembled, and give poly-time algorithms to determine this for several interesting cases of the problem. Finally, we also show that the problem of counting the number of feasible orderings that lead to the completion of an assembly is #P-complete.     

Linearly tapered meander line broadband monopole tag antenna with T‐match for Ultra High Frequency Radio Frequency Identification applications

In this paper, a compact, broadband linearly tapered meandered monopole tag antenna for UHF‐RFID is designed and optimized using particle swarm optimization (PSO) algorithm. An inductive T‐match network is utilized for impedance matching with capacitive Higgs‐4 chip. The optimization goal of PSO was conjugate matching and in consequence the maximization of read range. Equivalent circuit of the proposed tag antenna is derived using ADS software to validate its impedance characteristics. The performance of the proposed tag in terms of tag power sensitivity, read range, realized gain, and differential radar cross section has been experimentally characterized. To check the tolerance of the designed tag to various object platforms, its read range performance is also verified on objects like wood, fiber, plastic, and so forth. Furthermore, read pattern of the proposed tag has been measured and found to have figure of eight in E‐plane and omnidirectional in H‐plane. Experimental results reveal that the proposed tag covers 865‐867 MHz (ETSI band, Europe) and 902‐928 MHz (FCC band, United States) both major RFID bands with a read range of 10 and 12 m, respectively. The proposed tag has 2060 mm³ of volumetric size with maximum measured readable distance of 12 m with EIRP of 3.28 W.     

An efficient algorithm for mass detection and shape analysis of different masses present in digital mammograms

The present study introduces an efficient algorithm for automatic segmentation and detection of mass present in the mammograms. The problem of over and under-segmentation of low-contrast mammographic images has been solved by applying preprocessing on original mammograms. Subtraction operation performed between enhanced and enhanced inverted mammogram significantly highlights the suspicious mass region in mammograms. The segmentation accuracy of suspicious region has been improved by combining wavelet transform and fast fuzzy c-means clustering algorithm. The accuracy of mass segmentation has been quantified by means of Jaccard coefficients. Better sensitivity, specificity, accuracy, and area under the curve (AUC) are observed with support vector machine using radial basis kernel function. The proposed algorithm is validated on Mini-Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM) datasets. Highest 91.76% sensitivity, 96.26% specificity, 95.46% accuracy, and 96.29% AUC on DDSM dataset and 94.63% sensitivity, 92.74% specificity, 92.02% accuracy, and 95.33% AUC on MIAS dataset are observed. Also, shape analysis of mass is performed by using moment invariant and Radon transform based features. The best results are obtained with Radon based features and achieved accuracies for round, oval, lobulated, and irregular shape of mass are 100%, 70%, 64%, and 96%, respectively.     

Approximate Shortest Paths Avoiding a Failed Vertex: Near Optimal Data Structures for Undirected Unweighted Graphs

Let G=(V,E) be an undirected unweighted graph. A path between any two vertices u,v∈V is said to be t-approximate shortest path if its length is at most t times the length of the shortest path between u and v. We address the problem of building a compact data structure which can efficiently answer the following query for any u,v,x∈V and t>1: Report t-approximate shortest path between u and v when vertex x fails. We present data structures for the single source as well as all-pairs versions of this problem. The query time guaranteed by our data structures is optimal up to a constant factor. Moreover, the size of each of them nearly matches the size of the corresponding data structure with no failures.     

The Network as a Storage Device: Dynamic Routing with Bounded Buffers

We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations. In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a natural distributed greedy algorithm, is -competitive, essentially matching a known lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root of the tree. For grid graphs, we show that NTG has a competitive ratio of while no greedy algorithm can achieve a ratio better than . Finally, for arbitrary network topologies, we show that NTG is -competitive, improving upon an earlier bound of O(mn). An extended abstract appeared in the Proceedings of the 8th Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, Berkeley, CA, USA, pp. 1–13, Lecture Notes in Computer Science, vol. 1741, Springer, Berlin. S. Angelov is supported in part by NSF Career Award CCR-0093117, NSF Award ITR 0205456 and NIGMS Award 1-P20-GM-6912-1. S. Khanna is supported in part by an NSF Career Award CCR-0093117, NSF Award CCF-0429836, and a US-Israel Binational Science Foundation Grant. K. Kunal is supported in part by an NSF Career Award CCR-0093117 and NSF Award CCF-0429836.     

Growth of low dislocation density single crystals of nickel

Low dislocation density single crystals of nickel have been grown at high ambient pressure by the Czochralski method. X-ray Laue picture shows that the crystals are strain-free. The dislocation density was determined to be <10³/cm² by the etching procedure. It was found that the necking and cone regions are very critical in the dislocation introduction in the crystals. An increase in the ambient pressure used during the growth seems to aid the crystal quality.     

Novel technique for investigating high-power microwave pulses using Kerr effect

A novel method for the measurement of peak power of microwave pulses up to the few hundred kilowatts level based on the microwave-induced electro-optical Kerr effect in nonlossy dielectric liquids is described. This method provides additional information about the shape of the pulse, which is not usually given by the conventional methods.<>     

Synthesis and Performance Properties of Cationic Fabric Softeners Derived from Different Fatty Acids and 1(2-Hydroxyethylpiperazine)

Quaternary ammonium salts (otherwise known as “quats”) commonly form the foundation of formulations in the antimicrobial industry. Many studies have been conducted on the biological activity of surfactants derived from fatty acids viz. lauric acid, myristic acid, stearic acid and palmitic acid and palm fatty acid with polyamine, i.e. 1(2-hydroxyethylpiperazine). The present paper investigates the synthesis and surface-active properties of esteramide quats derived from the esterification of the above-mentioned fatty acids and 1(2-hydroxyethylpiperazine) followed by quaternization using dimethyl sulphate (DMS). These derivatives were fully characterized by using Fourier transform infrared spectroscopy, 1H nuclear magnetic resonance (NMR) spectroscopy, and 13C-NMR spectroscopy. In addition to the cationic content, surface tension, CMC (critical micelle concentration), fabric softening, rewettability, emulsification and dispersing power were determined as their surface-active properties.