Qualitative representation of spatial knowledge in two-dimensional space

Various relation-based systems, concerned with the qualitative representation and processing of spatial knowledge, have been developed in numerous application domains. In this article, we identify the common concepts underlying qualitative spatial knowledge representation, we compare the representational properties of the different systems, and we outline the computational tasks involved in relation-based spatial information processing. We also describesymbolic spatial indexes, relation-based structures that combine several ideas in spatial knowledge representation. A symbolic spatial index is an array that preserves only a set of spatial relations among distinct objects in an image, called the modeling space; the index array discards information, such as shape and size of objects, and irrelevant spatial relations. The construction of a symbolic spatial index from an input image can be thought of as a transformation that keeps only a set of representative points needed to define the relations of the modeling space. By keeping the relative arrangements of the representative points in symbolic spatial indexes and discarding all other points, we maintain enough information to answer queries regarding the spatial relations of the modeling space without the need to access the initial image or an object database. Symbolic spatial indexes can be used to solve problems involving route planning, composition of spatial relations, and update operations.     

Direction relations and two-dimensional range queries: optimisation techniques

This paper defines direction relations (e.g., north, northeast) between two-dimensional objects and shows how they can be efficiently retrieved using B-, KDB- and R- tree-based data structures. Essentially, our work studies optimisation techniques for 2D range queries that arise during the processing of direction relations. We test the efficiency of alternative indexing methods through extensive experimentation and present analytical models that estimate their performance. The analytical estimates are shown to be very close to the actual results and can be used by spatial query optimizers in order to predict the retrieval cost. In addition, we implement modifications of the existing structures that yield better performance for certain queries. We conclude the paper by discussing the most suitable method depending on the type of the range and the properties of the data.     

Continuous authentication on relational streams

According to the database outsourcing model, a data owner delegates database functionality to a third-party service provider, which answers queries received from clients. Authenticated query processing enables the clients to verify the correctness of query results. Despite the abundance of methods for authenticated processing in conventional databases, there is limited work on outsourced data streams. Stream environments pose new challenges such as the need for fast structure updating, support for continuous query processing and authentication, and provision for temporal completeness. Specifically, in addition to the correctness of individual results, the client must be able to verify that there are no missing results in between data updates. This paper presents a comprehensive set of methods covering relational streams. We first describe REF, a technique that achieves correctness and temporal completeness but incurs false transmissions, i.e., the provider has to inform the clients whenever there is a data update, even if their results are not affected. Then, we propose CADS, which minimizes the processing and transmission overhead through an elaborate indexing scheme and a virtual caching mechanism. In addition, we present an analytical study to determine the optimal indexing granularity, and extend CADS for the case that the data distribution changes over time. Finally, we evaluate the effectiveness of our techniques through extensive experiments.     

Aggregate nearest neighbor queries in road networks

Aggregate nearest neighbor queries return the object that minimizes an aggregate distance function with respect to a set of query points. Consider, for example, several users at specific locations (query points) that want to find the restaurant (data point), which leads to the minimum sum of distances that they have to travel in order to meet. We study the processing of such queries for the case where the position and accessibility of spatial objects are constrained by spatial (e.g., road) networks. We consider alternative aggregate functions and techniques that utilize Euclidean distance bounds, spatial access methods, and/or network distance materialization structures. Our algorithms are experimentally evaluated with synthetic and real data. The results show that their relative performance depends on the problem characteristics.     

A threshold-based algorithm for continuous monitoring of k nearest neighbors

Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naive solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm for the continuous monitoring of nearest neighbors that minimizes the communication overhead between the server and the data objects. The proposed method can be used with multiple, static, or moving queries, for any distance definition, and does not require additional knowledge (e.g., velocity vectors) besides object locations.     

Reverse nearest neighbors in large graphs

A reverse nearest neighbor (RNN) query returns the data objects that have a query point as their nearest neighbor (NN). Although such queries have been studied quite extensively in Euclidean spaces, there is no previous work in the context of large graphs. In this paper, we provide a fundamental lemma, which can be used to prune the search space while traversing the graph in search for RNN. Based on it, we develop two RNN methods; an eager algorithm that attempts to prune network nodes as soon as they are visited and a lazy technique that prunes the search space when a data point is discovered. We study retrieval of an arbitrary number k of reverse nearest neighbors, investigate the benefits of materialization, cover several query types, and deal with cases where the queries and the data objects reside on nodes or edges of the graph. The proposed techniques are evaluated in various practical scenarios involving spatial maps, computer networks, and the DBLP coauthorship graph.     

Analysing the operation of the basic pass transistor structure

Pass transistor logic has become important for the design of low‐power high‐performance digital circuits due to the smaller node capacitances and reduced transistors count it offers. However, the acceptance and application of this logic depends on the availability of supporting automation tools, e.g. timing simulators, that can accurately analyse the performance of large circuits at a speed, significantly faster than that of SPICE based tools. In this paper, a simple and robust modelling technique for the basic pass transistor structure is presented, which offers the possibility of fast timing analysis for circuits that employ pass transistors as controlled switches. The proposed methodology takes advantage of the physical mechanisms in the pass transistor operation. The obtained accuracy compared to SPICE simulation results is sufficient for a wide range of input and circuit parameters. Copyright © 2006 John Wiley & Sons, Ltd.     

An expert system for fault repairing and maintenance of electricmachines

The authors describe a rule-based expert system for troubleshooting and repairing of electrical machines. Empirical rules are used to help the user to find and repair any known fault for any electrical machine. An interactive methodology is implemented for fast and safe data interchange between computer and user, using tree menus. The expert system, which has been developed and tested at the National Technical University of Athens, can be used by industries and universities for engineering and educational purposes     

Hydrogen carriers: Production,transmission, decomposition,and storage

Recognizing the potential role of liquid hydrogen carriers in overcoming the inherent limitations in transporting and storing gaseous and liquid hydrogen, a complete production and use scenario is postulated and analyzed for perspective one-way and two-way carriers. The carriers, methanol, ammonia and toluene/MCH (methylcyclohexane), are produced at commercially viable scales in a central location, transmitted by rail or pipelines for 2000 miles, and decomposed near city gates to generate fuel-cell quality hydrogen for distribution to refueling stations. In terms of the levelized cost of H₂ distributed to the stations, methanol is less expensive to produce ($1.22/kg-H₂) than MCH ($1.35/kg-H₂) or ammonia ($2.20/kg-H₂). Levelized train transmission cost is smaller for methanol ($0.63/kg-H₂) than ammonia ($1.29/kg-H₂) or toluene/MCH system ($2.07/kg-H₂). Levelized decomposition cost is smaller for ammonia ($0.30–1.06/kg-H₂) than MCH ($0.54–1.22/kg-H₂) or methanol ($0.43–1.12/kg-H₂). Over the complete range of demand investigated, 10–350 tpd-H₂, the levelized cost of H₂ distributed to stations is aligned as methanol « ammonia ~ MCH. With pipelines at much larger scale, 6000 tpd-H₂, the levelized cost decreases by ~1 $/kg-H₂ for ammonia and MCH and much less for methanol. Methanol is a particularly attractive low-risk carrier in the transition phase with lower than 50-tpd H₂ demand.