APPLIED COMPUTATIONAL INTELLIGENCE FOR FINANCE AND ECONOMICS

This article introduces some relevant research works on computational intelligence applied to finance and economics. The objective is to offer an appropriate context and a starting point for those who are new to computational intelligence in finance and economics and to give an overview of the most recent works. A classification with five different main areas is presented. Those areas are related with different applications of the most modern computational intelligence techniques showing a new perspective for approaching finance and economics problems. Each research area is described with several works and applications. Finally, a review of the research works selected for this special issue is given.     

EFFECTS OF A RATIONING RULE ON THE AUSUBEL AUCTION: A GENETIC ALGORITHM IMPLEMENTATION

The increasing use of auctions as a selling mechanism has led to a growing interest in the subject. Thus both auction theory and experimental examinations of these theories are being developed. A recent method used for carrying out examinations on auctions has been the design of computational simulations. The aim of this article is to develop a genetic algorithm to find automatically a bidder optimal strategy while the other players are always bidding sincerely. To this end a specific dynamic multiunit auction has been selected: the Ausubel auction, with private values, dropout information, and with several rationing rules implemented. The method provides the bidding strategy (defined as the action to be taken under different auction conditions) that maximizes the bidder's payoff. The algorithm is tested under several experimental environments that differ in the elasticity of their demand curves, number of bidders and quantity of lots auctioned. The results suggest that the approach leads to strategies that outperform sincere bidding when rationing is needed.     

On the capabilities of IEEE 802.11e for multimedia communications over heterogeneous 802.11/802.11e WLANs

Multimedia communications over WLAN is widely acknowledged as one of the key, emerging applications for wireless LANs. As with any multi-service network, there is the need to provision the WLANs with the QoS mechanisms capable of guaranteeing the requirements of various services. The upcoming IEEE 802.11e (EDCA) standard is a proposal defining the mechanisms for wireless LANs aiming to provide QoS support to time-sensitive applications such as voice and video communications. Due to the fact that the IEEE 802.11e interface cards will take over the WLAN market, replacing the use of legacy IEEE 802.11 interface cards in most WLAN applications, an important number of networking scenarios will consist of a hybrid configuration comprising legacy IEEE 802.11-based stations and IEEE 802.11e-based stations. For this reason, in this paper we carry out a performance analysis on the effectiveness of the IEEE 802.11e (EDCA) upcoming standard when supporting different services, such as, voice, video, best-effort, background and in the presence of traffic generated by legacy 802.11 (DCF) based stations.     

Coherent Ion Plasma Oscillations in a DC Corona Discharge in Rarefied Air

Stable, nearly sinusoidal, phase-coherent ion plasma oscillations have been consistently observed superimposed on the dc levels of positive coaxial corona discharges at air pressures of the order of a few torr. The frequency of these oscillations, typically several hundred kilohertz, has been found to be a function of air density and dependent on the presence and concentration of gaseous trace contaminants. Various characteristics of these oscillations, a simplified theoretical model, and possible applications are discussed.     

Global and local distance-based generalized linear models

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models first to the generalized linear model framework. Then, a nonparametric version of these models is proposed by means of local fitting. Distances between individuals are the only predictor information needed to fit these models. Therefore, they are applicable, among others, to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. An implementation is provided by the R package dbstats, which also implements other distance-based prediction methods. Supplementary material for this article is available online, which reproduces all the results of this article.     

Simulation of transport and extravasation of nanoparticles in tumors which exhibit enhanced permeability and retention effect

Determining the factors that influence the delivery of sub-micron particles to tumors and understanding the relative importance of each of these factors is fundamental to the optimization of the particle delivery process. In this paper, a model that combines random walk with the pressure driven movement of nanoparticles in a tumor vasculature is presented. Nanoparticle movement in a cylindrical tube with dimensions similar to the tumor's blood capillary with a single pore is simulated. Nanoparticle velocities are calculated as a pressure driven flow over imposed to Brownian motion. The number and percentage of nanoparticles leaving the blood vessel through a single pore is obtained as a function of pore size, nanoparticle size and concentration, interstitial pressure, and blood pressure. The model presented here is able to determine the importance of these controllable parameters and thus it can be used to understand the process and predict the best conditions for nanoparticle-based treatment. The results indicate that the nanoparticle delivery gradually increases with pore size and decreases with nanoparticle size for tumors with high interstitial fluid pressure (in this work we found this behavior for head and neck carcinoma and for metastatic melanoma with interstitial pressures of 18 mmHg and 19 mmHg, respectively). For tumors with lower interstitial fluid pressure (rectal carcinoma with 15.3 mmHg) however, delivery is observed to have little sensitivity to particle size for almost the entire nanoparticle size range. Though an increase in nanoparticle concentration increases the number of nanoparticles being delivered, the efficiency of the delivery (percentage of nanoparticles delivered) is found to remain closely unaffected.     

Using the primal-dual interior point algorithm within the branch-price-and-cut method

Branch-price-and-cut has proven to be a powerful method for solving integer programming problems. It combines decomposition techniques with the generation of both columns and valid inequalities and relies on strong bounds to guide the search in the branch-and-bound tree. In this paper, we present how to improve the performance of a branch-price-and-cut method by using the primal-dual interior point algorithm. We discuss in detail how to deal with the challenges of using the interior point algorithm with the core components of the branch-price-and-cut method. The effort to overcome the difficulties pays off in a number of advantageous features offered by the new approach. We present the computational results of solving well-known instances of the vehicle routing problem with time windows, a challenging integer programming problem. The results indicate that the proposed approach delivers the best overall performance when compared with a similar branch-price-and-cut method which is based on the simplex algorithm.     

TWO GRAMMATICAL INFERENCE APPLICATIONS IN MUSIC PROCESSING

This article reviews our work in the field of music processing (MP) using grammatical inference (GI), where regular grammars are used for modeling musical style. These models can be used to generate automatic composition (AC) and classify music by style (musical style identification) with their resulting applications. The latter, for instance, would improve content-based retrieval in multimedia databases, joining indexing by musical style to other suitable indexes. In this work, several GI techniques are used to learn from examples of melodies, stochastic grammars for different musical styles. Then, each of the learned grammars is used to generate new melodies (composition) or to classify test melodies (style identification). Our studies in this field show the need of proper music coding schemes, so different coding schemes are presented and compared. Results from our previous studies have been improved, achieving in style identification a classification error rate that ranges from 0.5 to 1.7%, depending on the corpus used.     

A multicore solution to Block–Toeplitz linear systems of equations

There exist algorithms, also called “fast” algorithms, which exploit the special structure of Toeplitz matrices so that, e.g., allow to solve a linear system of equations in O(n ²) flops. However, some implementations of classical algorithms that do not use this structure (O(n ³) flops) highly reduce the time to solution when several cores are available. That is why it is necessary to work on “fast” algorithms so that they do not lose track of the benefits of new hardware/software. In this work, we propose a new approach to the Generalized Schur Algorithm, a very known algorithm for the solution of Toeplitz systems, to work on a Block–Toeplitz matrix. Our algorithm is based on matrix–matrix multiplications, thus allowing to exploit an efficient implementation of this operation if it exists. Our algorithm also makes use of the thread level parallelism featured by multicores to decrease execution time.     

How mobile phones perform in collaborative augmented reality (CAR) applications

This paper presents the experimental analysis of mobile phones for Augmented Reality marker tracking, a core task that any CAR application must include. The results show that the most time consuming stage is the marker detection stage, followed by the image acquisition stage. Moreover, the rendering stage is decoupled on some devices, depending on the operative system used. This decoupling process allows avoiding low refresh rates, facilitating the collaborative work. However, the use of multicore devices does not significantly improve the performance provided by CAR applications. Finally, the results show that unless a poor network bandwidth makes the network to become the system bottleneck, the performance of CAR applications based on mobile phones will be limited by the detection stage. These results can be used as the basis for an efficient design of CAR systems and applications based on mobile phones.