Succession of hide–seek and pursuit–evasion at heterogeneous locations

Many interactions between searching agents and their elusive targets are composed of a succession of steps, whether in the context of immune systems, predation or counterterrorism. In the simplest case, a two-step process starts with a search-and-hide phase, also called a hide-and-seek phase, followed by a round of pursuit–escape. Our aim is to link these two processes, usually analysed separately and with different models, in a single game theory context. We define a matrix game in which a searcher looks at a fixed number of discrete locations only once each searching for a hider, which can escape with varying probabilities according to its location. The value of the game is the overall probability of capture after k looks. The optimal search and hide strategies are described. If a searcher looks only once into any of the locations, an optimal hider chooses it''s hiding place so as to make all locations equally attractive. This optimal strategy remains true as long as the number of looks is below an easily calculated threshold; however, above this threshold, the optimal position for the hider is where it has the highest probability of escaping once spotted.     

Role of dixantogen in froth flotation

Mechanism of dixantogen action in froth flotation is discussed. It is shown that this reagent eliminates kinetic constraints during formation of a flotation complex, rather than improves hydrophobicity of a mineral surface.     

On the recovery of the time average of continuous and discrete time functions from their Laplace and z‐transforms

The determination of the time averages of continuous functions or discrete time sequences is important for various problems in physics and engineering, and the generalized final‐value theorems of the Laplace and z‐transforms, relevant to functions and sequences not having a limit at infinity, but having a well‐defined average, can be very helpful in this determination. In the present contribution, we complete the proofs of these theorems and extend them to more general time functions and sequences. Besides formal proofs, some simple examples and heuristic and pedagogical comments on the physical nature of the limiting processes defining the averaging are given. Copyright © 2012 John Wiley & Sons, Ltd.     

OPM/Web – Object-Process Methodology for Developing Web Applications

Web applications can be classified as hybrids between hypermedia and information systems. They have a relatively simple distributed architecture from the user viewpoint, but a complex dynamic architecture from the designer viewpoint. They need to respond to operation by an unlimited number of heterogeneously skilled users, address security and privacy concerns, access heterogeneous, up-to-date information sources, and exhibit dynamic behaviors that involve such processes as code transferring. Common system development methods can model some of these aspects, but none of them is sufficient to specify the large spectrum of Web application concepts and requirements. This paper introduces OPM/Web, an extension to the Object-Process Methodology (OPM) that satisfies the functional, structural and behavioral Web-based information system requirements. The main extensions of OPM/Web are adding properties of links to express requirements, such as those related to encryption; extending the zooming and unfolding facilities to increase modularity; cleanly separating declarations and instances of code to model code transferring; and adding global data integrity and control constraints to express dependence or temporal relations among (physically) separate modules. We present a case study that helps evaluate OPM/Web and compare it to an extension of the Unified Modeling Language (UML) for the Web application domain.     

Fuzzy and probability vectors as elements of a vector space

The problem of defining vector space operations on fuzzy and probability vectors is discussed. It is shown that such a definition is equivalent to choosing a 1-1 and onto mapping from the unit interval into the real axis. Although such a mapping cannot be continuous, it is suggested that under certain approximations a continuous mapping can be chosen. A characterization of some useful mappings with applications to image processing is also given.     

A Mechanized Proof Environment for the Convenient Computations Proof Method

A mechanized verification environment made up of theories over the deductive mechanized theorem prover PVS is presented, which allows taking advantage of the convenient computations method. This method reduces the conceptual difficulty of proving a given property for all the possible computations of a system by separating two different concerns: (1) proving that special convenient computations satisfy the property, and (2) proving that every computation is related to a convenient one by a relation which preserves the property. The approach is especially appropriate for applications in which the first concern is trivial once the second has been shown, e.g., where the specification itself is that every computation reduces to a convenient one. Two examples are the serializability of transactions in distributed databases, and sequential consistency of distributed shared memories. To reduce the repetition of effort, a clear separation is made between infrastructural theories to be supplied as a proof environment PVS library to users, and the specification and proof of particular examples. The provided infrastructure formally defines the method in its most general way. It also defines a computation model and a reduction relation—the equivalence of computations that differ only in the order of finitely many independent operations. One way to prove that this relation holds between every computation and some convenient one involves the definition of a measure function from computations into a well-founded set. Two possible default measures, which can be applied in many cases, are also defined in the infrastructure, along with useful lemmas that assist in their usage. We show how the proof environment can be used, by a step-by-step explanation of an application example.