Optimized algorithms for predictive range and KNN queries on moving objects

There have been many studies on management of moving objects recently. Most of them try to optimize the performance of predictive window queries. However, not much attention is paid to two other important query types: the predictive range query and the predictive k nearest neighbor query. In this article, we focus on these two types of queries. The novelty of our work mainly lies in the introduction of the Transformed Minkowski Sum, which can be used to determine whether a moving bounding rectangle intersects a moving circular query region. This enables us to use the traditional tree traversal algorithms to perform range and kNN searches. We theoretically show that our algorithms based on the Transformed Minkowski Sum are optimal in terms of the number of tree node accesses. We also experimentally verify the effectiveness of our technique and show that our algorithms outperform alternative approaches.     

Understanding provenance black boxes

Current provenance stores associated with workflow management systems (WfMSs) capture enough coarse-grained information to describe which datasets were used and which processes were run. While this information is enough to rebuild a workflow run, it is not enough to facilitate user understanding. Because the data is manipulated via a series of black boxes, it is often impossible for a human to understand what happened to the data. In this work, we highlight the missing information that can assist user understanding. Unfortunately, provenance information is already very complex and difficult for a user to comprehend, which can be exacerbated by adding the extra information needed for deeper blackbox understanding. In order to alleviate this, we develop a model of provenance answers that follow a “roll up”, “drill down” strategy. We evaluate these techniques to determine if users have better understanding of provenance information. We show how this information can be captured by workflow management systems, and that the structures and information needed for this model are a negligible addition to standard provenance stores. Finally, we implement these techniques in a real provenance system, and evaluate implementation feasibility.     

XML schema refinement through redundancy detection and normalization

As XML becomes increasingly popular, XML schema design has become an increasingly important issue. One of the central objectives of good schema design is to avoid data redundancies: redundantly stored information can lead not just only to a higher data storage cost but also to increased costs for data transfer and data manipulation. Furthermore, such data redundancies can lead to potential update anomalies, rendering the database inconsistent. One strategy to avoid data redundancies is to design redundancy-free schema from the start on the basis of known functional dependencies. We observe that XML databases are often “casually designed” and XML FDs may not be determined in advance. Under such circumstances, discovering XML data redundancies from the data itself becomes necessary and is an integral part of the schema refinement (or re-design) process. We present the design and implementation of the first system, DiscoverXFD, for efficient discovery of XML data redundancies. It employs a novel XML data structure and introduces a new class of partition-based algorithms. The XML data redundancies are defined on the basis of a new notion of XML functional dependency (XML FD) that (1) extends previous notions by incorporating set elements into the XML FD specification, and (2) maintains tuple-based semantics through the novel concept of Generalized Tree Tuple (GTT). Using this comprehensive XML FD notion, we introduce a new normal form (GTT-XNF) for XML documents, and provide comprehensive comparisons with previous studies. Given the set of data redundancies (in the form of redundancy-indicating XML FDs) discovered by DiscoverXFD, we describe a normalization algorithm for converting any original XML schema into one in GTT-XNF.     

Algorithms for searching massive graphs

Given a large graph, stored on disk, there is often a need to perform a search over this graph. Such a need could arise, for example, in the search component of a data-intensive expert system or to solve path problems in deductive database systems. In this paper, we present a novel data structuring technique and show how a branch-and-bound search algorithm can use this data structuring to prune the search space. Simulation results confirm that, using these techniques, a search can be expedited significantly without incurring a large storage penalty. As a side benefit, it is possible to organize the search to obtain successive approximations to the desired solution with considerable reduction in the total search     

ICP dry etching of ZnO and effects of hydrogen

Two different plasma chemistries for etching ZnO were examined. Both Cl₂/Ar and CH₄/H₂/Ar produced etch rates which increased linearly with rf power, reaching values of 1200 Å/min for Cl₂/Ar and 3000 Å/min for CH₄/H₂/Ar. The evolution of surface morphology, surface composition, and PL intensity as a function of energy during etching were monitored. The effect of H in ZnO was studied using direct implantation at doses of 10¹⁵–10¹⁶ cm⁻², followed by annealing at 500–700 °C. The hydrogen shows significant outdiffusion at 500 °C and is below the detection limits of SIMS after 700 °C anneals. SEM of the etched features showed anisotropic sidewalls, indicative of an ion-driven etch mechanism.     

A systems approach to rural housing

An attempt is made in this paper to arrive at a methodology for generating building technologies appropriate to rural housing. An evaluation of traditional/ ‘ modern ’ technologies currently in use reveals the need for alternatives. The lacunae in the presently available technologies also lead to a definition of rural housing needs. It is emphasised that contending technologies must establish a ‘ goodness of fit ’ between the house form and the pattern of needs. A systems viewpoint which looks at thedynamic process of building construction and thestatic structure of the building is then suggested as a means to match the technologies to the needs. The process viewpoint emphasises the role of building materials production and transportation in achieving desired building performances. A couple of examples of technological alternatives like the compacted soil block and the polythene-stabilised soil roof covering are then discussed. The static structural system viewpoint is then studied to arrive at methodologies of cost reduction. An illustrative analysis is carried out using the dynamic programming technique, to arrive at combinations of alternatives for the building components which lead to cost reduction. Some of the technological options are then evaluated against the need patterns. Finally, a guideline for developments in building technology is suggested.     

Synthesis of Nanocrystalline α-Alumina Powder Using Triethanolamine

Nanocrystalline α-Al₂O₃ powders have been prepared by pyrolysis of a complex compound of aluminum with triethanolamine (TEA). The soluble metal-ion–TEA complex forms the precursor material on complete dehydration of the complex of aluminum-TEA. The single-phase α-Al₂O₃ powder has resulted after heat treatment at 1025°C. The precursors and the heat-treated final powders have been characterized by X-ray diffractometry, thermogravimetric and differential thermal analysis, and transmission electron microscopy (TEM). The average particle sizes as measured from X-ray line broadening and TEM are ∼25 nm. The powder has crystallite sizes of the same order indicates the poor agglomeration of crystallites.     

DPM dissipation experiment at MST’s experimental mine and comparison with CFD simulation

Diesel Particulate Matter (DPM) is regulated in the U.S. for both underground coal and metal/nonmetal mines. Today, many underground mines still face difficulty in compliance with DPM regulations. The DPM research carried out in Missouri University of Science and Technology (MST) is to use computational fluid dynamics (CFD) to study the DPM distribution in commonly used face areas. The result is expected to be used for selection of DPM reduction strategies and better working practices, which can help the underground mines to meet regulation limits and improve the working environment for the miners. An experiment was conducted at MST’s Experimental Mine to validate CFD simulation. DPM was collected at four locations downstream of a stationary diesel engine. The experiment data were then compared with the CFD simulation results. The comparison shows that CFD simulation can forecast the location of DPM concentration with practical accuracy (less than 0.15 m). CFD can be used to further study DPM distribution in commonly used working faces and give guidance to DPM reduction.     

Processable aromatic polyesters based on bisphenol derived from cashew nut shell liquid: synthesis and characterization

The miscibility of chitosan/poly(ethylene oxide) (CS/PEO) blends was investigated by a combination of experiment and molecular simulation. Results from X-ray diffraction (WAXD) and thermal analysis (DSC) suggest that the maximum miscibility was seen at the PEO weight fraction (w _PEO) =0.2; the optimum stoichiometric ratio for CS and PEO functional groups. The change in vibrational frequencies from infrared spectra was attributed to the specific interaction between PEO ether oxygen with the amino and hydroxyl groups of CS. Radial distribution functions (RDF) from MD simulation suggest that all CS functional groups (NH₂, C3-OH, and C6-OH) can interact with PEO ether groups for which NH₂ has the highest activity. For CS hydroxyl groups, a more significant contribution of C6-OH rather than C3-OH groups that interact with PEO ether oxygen was observed. The interaction parameter (χ) determined from MD simulation was in good agreement with that of the DSC experiment (χ_CS-PEO?=?-0.21). Based on a comparison between χ and χ _critical , CS/PEO blend was predicted to be miscible for w _PEO <0.58 with a maximum at w _PEO =0.2. In addition, the order parameter from the mesoscale simulation was employed to monitor the phase separation in these blends. From MesoDyn simulation, the miscibility was decreased with increasing PEO content, and miscible CS/PEO blends were obtained only with w _PEO <0.58, in good agreement with MD simulation and experiment.