Integrating Constraints and Concurrent Objects in Musical Applications: A Calculus and its Visual Language

We propose PiCO, a calculus integrating concurrent objects and constraints, as a base for music composition tools. In contrast with calculi such as NiehrenMueller:Free, milner.parrow.ea:calculus-mobile or TyCO vasconcelos:typed-concurrent, both constraints and objects are primitive notions in PiCO. In PiCO a base object model is extended with constraints by orthogonally adding the notion of constraint system found in the -calculus OzCalculus. Concurrent processes make use of a constraint store to synchronize communications either via the ask and tell operations of the constraint model or the standard message-passing mechanism of the object model. A message delegation mechanism built into the calculus allows encoding of general forms of inheritance. This paper includes encodings in PiCO of the concepts of class and sub-class. These allow us to represent complex partially defined objects such as musical structures in a compact way. We illustrate the transparent interaction of constraints and objects by a musical example involving harmonic and temporal relations. The relationship between Cordial, a visual language for music composition applications, and its underlying model PiCO is described.     

The multi-L-REP decomposition and its application to a point-in-polygon inclusion test

This paper presents a scheme for decomposing polygons called multi-L-REP. The scheme can be considered as a generalization of the L-REP decomposition, which associates the edges of a polygon with a set of layered triangles. In the multi-L-REP these layered triangles are grouped into regions of a plane division. The paper also shows some alternative algorithms for its construction, and one of its applications: the point-in polygon inclusion test. Finally, a special case of multi-L-REP that has several interesting properties and shows a very fast point-in-polygon inclusion test is presented.     

Blockchain and artificial intelligence for network security

Annals of Telecommunications -     

Least cost distance analysis for spatial interpolation

Spatial interpolation allows creation of continuous raster surfaces from a subsample of point-based measurements. Most interpolation approaches use Euclidean distance measurements between data points to generate predictions of values at unknown locations. However, there are many spatially distributed data sets that are not properly represented by Euclidean distances and require distance measures which represent their complex geographic connectivity. The problem of defining non-Euclidean distances between data points has been solved using the network-based solutions, but such techniques have historically relied on a network of connected line segments to determine point-to-point distances. While these vector-based solutions are computationally efficient, they cannot model more complex 2- and 3-dimensional systems of connectivity. Here, we use least-cost-path analyses to define distances between sampled points; a solution that allows for arbitrarily complex systems of connectivity to be interpolated. We used least-cost path distances in conjunction with the inverse distance weighting interpolation for a proof-of-concept interpolation of water temperature data in a complex deltaic river system. We compare our technique to Euclidean distance interpolation, and demonstrate that our technique, which follows connectivity rules, yields are more realistic interpolation of water temperature.     

On the performance of the approximate parametrization algorithm for curves

In Pérez-Díaz et al. (2009) [5], the authors present an algorithm to parametrize approximately ?-rational curves, and they show that the Hausdorff distance, w.r.t. the Euclidean distance, between the input and output curves is finite. In this paper, we analyze this distance for a family of curves randomly generated and we empirically find a reasonable upper bound of the Hausdorff distance between each input and output curve of the family.     

EFFECT of pH and ENZYMATIC TREATMENT ON MICROFILTRATION and ULTRAFILTRATION of TANGERINE JUICE

Tangerine (Citrus reticulata blanco) juice clarification by crossflow microfiltration and ultrafiltration using polysulphone flat sheet membranes with nominal molecular weight cut off of 25,000, 50,000, 100,000 and 0.1 μm, 0.2 μm pore sizes was studied. the juice was pretreated by polygalacturonase and pH adjustment. the treated juice was clarified with a laboratory scale filtration unit with effective filtration area of 14 cm². Filtration conditions were transmembrane pressure of 93 to 194 kPa, crossflow velocity of 0.96 to 3.5 m/s and 25°C. Membrane performance was evaluated in terms of volume flux and clarity (% transmittance) of the permeate. Pretreatment of the juice by polygalacturonase and adjustment to pH 2 with HCl resulted in a clearer supernatant than enzyme treatment alone. Maximum flux was obtained with the 0.1 μm microfiltration membrane. Flux increased with transmembrane pressure and crossflow velocity. Flux at 194 kPa and 3.5 m/s was 69 L per square meter per hour. Permeate clarity was better at higher transmembrane pressure and lower velocity, due to the effect of the polarized/fouling layer of solute on the membrane surface, which acted as a secondary “dynamic” filter.