Strict interpretations of deterministic pushdown acceptors

Three results are established. The first is that every nondeterministic strict interpretation of a deterministic pushdown acceptor (dpda) has an equivalent, deterministic, strict interpretation. The second is that ifM ₁ andM ₂ are two compatible strict interpretations of the dpdaM, then there exist deterministic strict interpretationsM andM such thatL(M ) =L(M ₁)L(M ₂) andL(M ) =L(M ₁)L(M ₂). The third states that there is no dpda whose strict interpretations yield all the deterministic context-free languages.This author was supported in part by the National Science Foundation under Grant MCS-77-22323.     

Pruning 2-Connected Graphs

Given an undirected graph G with edge costs and a specified set of terminals, let the density of any subgraph be the ratio of its cost to the number of terminals it contains. If G is 2-connected, does it contain smaller 2-connected subgraphs of density comparable to that of?G? We answer this question in the affirmative by giving an algorithm to pruneG and find such subgraphs of any desired size, incurring only a logarithmic factor increase in density (plus a small additive term). We apply our pruning techniques to give algorithms for two NP-Hard problems on finding large 2-vertex-connected subgraphs of low cost; no previous approximation algorithm was known for either problem. In the k-2VC problem, we are given an undirected graph G with edge costs and an integer k; the goal is to find a minimum-cost 2-vertex-connected subgraph of G containing at least k vertices. In the Budget-2VC problem, we are given a graph G with edge costs, and a budget B; the goal is to find a 2-vertex-connected subgraph H of G with total edge cost at most B that maximizes the number of vertices in H. We describe an O(log?nlog?k) approximation for the k-2VC problem, and a bicriteria approximation for the Budget-2VC problem that gives an $O(\frac{1}{\epsilon}\log^{2} n)$ approximation, while violating the budget by a factor of at most 2+ε.     

Use of distributed data sources in facility location

Facility location decisions are usually determined by cost and coverage related factors although empirical studies show that such factors as infrastructure, labor conditions and competition also play an important role in practice. The objective of this paper is to develop a multi-objective facility location model accounting for a wide range of factors affecting decision-making. The proposed model selects potential facilities from a set of pre-defined alternative locations according to the number of customers, the number of competitors and real-estate cost criteria. However, that requires large amount of both spatial and non-spatial input data, which could be acquired from distributed data sources over the Internet. Therefore, a computational approach for processing input data and representation of modeling results is elaborated. It is capable of accessing and processing data from heterogeneous spatial and non-spatial data sources. Application of the elaborated data gathering approach and facility location model is demonstrated using an example of fast food restaurants location problem.     

Algorithms for computing diffuse reflection paths in polygons

Let s be a point source of light inside a polygon P of n vertices. A polygonal path from s to some point t inside P is called a diffuse reflection path if the turning points of the path lie on edges of?P. A?diffuse reflection path is said to be optimal if it has the minimum number of reflections on the path. The problem of computing a diffuse reflection path from s to t inside P has not been considered explicitly in the past. We present three different algorithms for this problem which produce suboptimal paths. For constructing such a path, the first algorithm uses a greedy method, the second algorithm uses a transformation of a minimum link path, and the third algorithm uses the edge–edge visibility graph of?P. The first two algorithms are for polygons without holes, and they run in O(n+klogn) time, where k denotes the number of reflections in the constructed path. The third algorithm is for polygons with or without holes, and it runs in O(n ²) time. The number of reflections in the path produced by this third algorithm can be at most three times that of an optimal diffuse reflection path. Though the combinatorial approach used in the third algorithm gives a better bound on the number of reflections on the path, the first and the second algorithms stand on the merit of their elegant geometric approaches based on local geometric information.     

Process diagnostics using trace alignment: Opportunities, issues, and challenges

Business processes leave trails in a variety of data sources (e.g., audit trails, databases, and transaction logs). Hence, every process instance can be described by a trace, i.e., a sequence of events. Process mining techniques are able to extract knowledge from such traces and provide a welcome extension to the repertoire of business process analysis techniques. Recently, process mining techniques have been adopted in various commercial BPM systems (e.g., BPM|one, Futura Reflect, ARIS PPM, Fujitsu Interstage, Businesscape, Iontas PDF, and QPR PA). Unfortunately, traditional process discovery algorithms have problems dealing with less structured processes. The resulting models are difficult to comprehend or even misleading. Therefore, we propose a new approach based on trace alignment. The goal is to align traces in such a way that event logs can be explored easily. Trace alignment can be used to explore the process in the early stages of analysis and to answer specific questions in later stages of analysis. Hence, it complements existing process mining techniques focusing on discovery and conformance checking. The proposed techniques have been implemented as plugins in the ProM framework. We report the results of trace alignment on one synthetic and two real-life event logs, and show that trace alignment has significant promise in process diagnostic efforts.     

A survey: Ant Colony Optimization based recent research and implementation on several engineering domain

Ant Colony Optimization (ACO) is a Swarm Intelligence technique which inspired from the foraging behaviour of real ant colonies. The ants deposit pheromone on the ground in order to mark the route for identification of their routes from the nest to food that should be followed by other members of the colony. This ACO exploits an optimization mechanism for solving discrete optimization problems in various engineering domain. From the early nineties, when the first Ant Colony Optimization algorithm was proposed, ACO attracted the attention of increasing numbers of researchers and many successful applications are now available. Moreover, a substantial corpus of theoretical results is becoming available that provides useful guidelines to researchers and practitioners in further applications of ACO. This paper review varies recent research and implementation of ACO, and proposed a modified ACO model which is applied for network routing problem and compared with existing traditional routing algorithms.     

Synthesis of Nanocrystalline Lanthanum Strontium Manganite Powder by the Urea–Formaldehyde Polymer Gel Combustion Route

Nanocrystalline lanthanum strontium manganite (LSM) powder has been synthesized by combustion of a transparent gel obtained by the polymerization of methylol urea and urea in a solution containing La³⁺, Sr²⁺, and Mn²⁺ (LSM ions). Chemistry of the transparent urea–formaldehyde (UF) polymer gel formation and structure of the gel have been proposed such that the LSM ions act in between the growing UF polymer chains by interacting through NH, OH, and CO groups by co-ordination and prevent polymer self-assembly through inter-chain hydrogen bonding as evidenced from infrared spectrum. Thermally stable structures formed by the decomposition of UF polymer below 300°C undergo combustion in the presence of nitrate oxidant in a temperature range from 350°–450°C. A perovskite LSM phase has been formed by self-sustained combustion of the dried gel initiated with little kerosene. The powder obtained after deagglomeration and calcination at 600°C for 2 h has a D ₅₀ value of 0.19 μm, and the particles are aggregates of crystallites 10–25 nm in size.     

Choroidal neovascular membrane in Best's vitelliform macular dystrophy

The right eye of a 9-year-old white boy with Best's vitelliform macular dystrophy had an intact egg-yolk lesion and a retinal pigment epithelial defect superiorly, suggesting an early pseudohypopyon stage. The disruptive phase of the left eye showed subretinal hemorrhages, a "signet ring," and a subretinal neovascular membrane.     

Nano and micro structural studies of thin films of ZnO

Zinc oxide thin films grown by sol–gel and RF sputtering methods have been characterized. The characterization techniques used involve ellipsometry, optical absorption, scanning tunneling microscopy, scanning and transmission electron microscopy. The films grown by sol–gel spin method which followed zinc acetate route exhibited a smoother texture than the films, which were deposited by using zinc nitrate route. The later type of films showed a dendritic character. Nano-structured fine grains of size ranging from 20 to 60 nm were observed with zinc nitrate precursor film. Individual grains show a sharp contrast with different facets and boundaries. Crystal planes and lattice parameters calculated by electron diffraction and X-ray diffraction are quite close and in agreement with the reported values in literature. Scanning tunneling microscopy has been used for measuring the average roughness of the surface and estimating the lattice constants. The STM studies of RF sputtered films, although showing a ZnO structure, exhibited a disturbed lattice. This was presumably due to the fact that after deposition the films were not annealed. Nanographs of 2D and 3D view of atomic positions of ZnO have been presented by using scanning tunneling microscopy.     

Corrosion behavior of carbon steel rock bolt in simulated Yucca Mountain ground waters

Medium carbon steel (AISI 1040) was one of the candidate materials for rock bolts to reinforce the borehole liners and emplacement drifts of the high-level nuclear waste repository in Yucca Mountain. The corrosion performance of this structural steel was investigated by techniques such as linear polarization, electrochemical impedance spectroscopy (EIS), and laboratory immersion tests in simulated ground waters. The corrosion rates of the steel were measured for the temperatures in the range from 25 °C to 85 °C, for the ionic concentrations of 1 time (1×), 10 times (10×), and a hundred times (100×) ground water concentration. The steel corroded uniformly at penetration rates of 35 to 200 μm/year in the deaerated waters, and at 200 to 1000 μm/year in the aerated waters. Increasing temperatures in the deaerated waters increased the corrosion rate of the steel. However, increasing ionic concentrations influenced the corrosion rate only slightly. In the aerated 1×and 10×waters, increasing temperatures increased the rates of the steel significantly. In the aerated 100×waters, the corrosion rate increased from 25 °C to 45 °C and decreased at higher temperatures (65 °C and up) due to the formation of oxide/hydroxide films and salt scales on the surface of the steel specimen. The steel suffered pitting corrosion in the both deaerated and aerated hot ground water environments after anodic polarization. This article is based on a presentation made in the symposium “Effect of Processing on Materials Properties for Nuclear Waste Disposition,” November 10–11, 2003, at the TMS Fall meeting in Chicago, Illinois, under the joint auspices of the. TMS Corrosion and Environmental Effects and Nuclear Materials Committees.