Functional properties of a protein product from Caryodendron orinocense (Barinas nut)

The functional properties of Caryodendron orinocense protein product were investigated and compared with those of soybean (Glycina maxima). The product protein content was 24.47 g/100 g (Nx6.25). Solubility increased at both sides of the isoelectric point (pH 4.0) and with increased NaCl concentration up to 0.5M. Compared with soybean flour (50% protein), the protein product exhibited higher water and oil absorption, but lower emulsifying activity, emulsion stability, foaming capacity, and foam stability, the last one increase at higher pH. Emulsifying activity, foaming capacity, and foam stability were ionic strength dependent. C. orinocense protein product increased its emulsifying activity steadily from 0.05M to 0.75M NaCl, while it remained almost constant for soybean flour. Foaming capacity increased drastically at pH 10. The minimum time and concentration to form a gel was 20% in 4 min and 10% in 8 min for the Caryodendron protein product and soybean flour, respectively. The bulk density was 0.5056+/-0.0041 g/mL.     

HumanTop: a multi-object tracking tabletop

In this paper, a computer vision based interactive multi-touch tabletop system called HumanTop is introduced. HumanTop implements a stereo camera vision subsystem which allows not only an accurate fingertip tracking algorithm but also a precise touch-over-the-working surface detection method. Based on a pair of visible spectra cameras, a novel synchronization circuit makes the camera caption and the image projection independent from each other, providing the minimum basis for the development of computer vision analysis based on visible spectrum cameras without any interference coming from the projector. The assembly of both cameras and the synchronization circuit is not only capable of performing an ad-hoc version of a depth camera, but it also introduces the recognition and tracking of textured planar objects, even when contents are projected over them. On the other hand HumanTop supports the tracking of sheets of paper and ID-code markers. This set of features makes the HumanTop a comprehensive, intuitive and versatile augmented tabletop that provides multitouch interaction with projective augmented reality on any flat surface. As an example to exploit all the capabilities of HumanTop, an educational application has been developed using an augmented book as a launcher to different didactic contents. A pilot study in which 28 fifth graders participated is presented. Results about efficiency, usability/satisfaction and motivation are provided. These results suggest that HumanTop is an interesting platform for the development of educational contents.     

A genetic algorithm for job-shop scheduling with operators enhanced by weak Lamarckian evolution and search space narrowing

The job-shop scheduling problem with operators is a very interesting problem that generalizes the classic job-shop problem in such a way that an operation must be algorithm to solve this problem considering makespan minimization. The genetic algorithm uses permutations with repetition to encode chromosomes and a schedule generation scheme, termed OG&T, as decoding algorithm. This combination guaranties that at least one of the chromosomes represents and optimal schedule and, at the samhat machines and operators are idle while an operation is available to be processed. To improve the quality of the schedules for large instances, we use Lamarckian evolution and modify the OG&T algorithm to further reduce the idle time of the machines and operators, in this case at the risk of leaving all optimal schedules out of the search space. We conducted a large experimental study showing that these improvements allow the genetic algorithm to reach high quality solutions in very short time, and so it is quite competitive with the current state-of-the-art methods.     

Invariant‐set‐based fault diagnosis in Lure systems

In this paper, we present an invariant‐set‐based method for actuator and sensor fault detection and isolation in Lure systems. The Lure plant is controlled by an observer‐based feedback tracking controller, designed for the nominal (fault‐free) system. Suitable residual signals are constructed from measurable system outputs and estimates associated with the nominal observer. Faults are diagnosed by online contrasting the residual signal trajectories against sets of values that the residuals are shown to attain under healthy or faulty operation. These values are obtained via set‐invariance analysis of the system closed‐loop trajectories. Copyright © 2013 John Wiley & Sons, Ltd.     

Standard goal programming with fuzzy hierarchies: a sequential approach

This paper proposes a pragmatic model for multi-objective decision-making processes involving clusters of objectives which have a decisional meaning for the decision maker (DM). We provide the DMs with a comfortable tool that allows them to express their preferences both by comparing criteria of the same cluster and via the comparison between the different clusters. In standard goal programming the importance of the goals is modeled by the introduction of preferential weights or/and the incorporation of pre-emptive priorities. However, in many cases the DM is not able to establish a precise preference structure. Even in the case of precise weights the solution does not match necessarily the relative weights or, in the case of precise pre-emptive priority, the result could be very restrictive. In order to overcome these drawbacks, in this paper the normalized unwanted deviations are interpreted in terms of achievement degrees of the goals and fuzzy relations are used to model the relative importance of the goals. Thus, we show how several methodologies from the fuzzy goal programming literature can be tailored for solving standard GP problems. We apply this new modeling to problems where there is a “natural” clustering between goals of the same class. We address this situation by solving two phases; in the first one each class is handled separately taking into account the hierarchy of their goals and, in the second phase, we integrate the results of the first phase and the imprecise hierarchy of the different classes. We formulate a new goal programming model called as sequential goal programming with fuzzy hierarchy model. Because many real situations involve decision making in this environment, our proposal can be a useful tool of broad application. A numerical example illustrates the methodology.     

Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems

Recently, multi-objective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds of algorithms can obtain a set of solutions with different trade-offs. This contribution analyzes different application alternatives in order to attain the desired accuracy/interpr-etability balance by maintaining the improved accuracy that a tuning of membership functions could give but trying to obtain more compact models. In this way, we propose the use of multi-objective evolutionary algorithms as a tool to get almost one improved solution with respect to a classic single objective approach (a solution that could dominate the one obtained by such algorithm in terms of the system error and number of rules). To do that, this work presents and analyzes the application of six different multi-objective evolutionary algorithms to obtain simpler and still accurate linguistic fuzzy models by performing rule selection and a tuning of the membership functions. The results on two different scenarios show that the use of expert knowledge in the algorithm design process significantly improves the search ability of these algorithms and that they are able to improve both objectives together, obtaining more accurate and at the same time simpler models with respect to the single objective based approach.

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Malicious uses of blockchains by malware: from the analysis to Smart-Zephyrus

The permanent availability and relative obscurity of blockchains is the perfect ground for using them for malicious purposes. However, the use of blockchains by malwares has not been characterized yet. This paper analyses the current state of the art in this area. One of the lessons learned is that covert communications for malware have received little attention. To foster further defence-oriented research, a novel mechanism (dubbed Smart-Zephyrus) is built leveraging smart contracts written in Solidity. Our results show that it is possible to hide 4 Kb of secret in 41 s. While being expensive (around USD 1.82 per bit), the provided stealthiness might be worth the price for attackers.

     

Optimization of biochemical systems through mathematical programming: Methods and applications

In this work we present a general (mono and multiobjective) optimization framework for the technological improvement of biochemical systems. The starting point of the method is a mathematical model in ordinary differential equations (ODEs) of the investigated system, based on qualitative biological knowledge and quantitative experimental data. In the method we take advantage of the special structural features of a family of ODEs called power-law models to reduce the computational complexity of the optimization program. In this way, the genetic manipulation of a biochemical system to meet a certain biotechnological goal can be expressed as an optimization program with some desired properties such as linearity or convexity.The general method of optimization is presented and discussed in its linear and geometric programming versions. We furthermore illustrate the use of the method by several real case studies. We conclude that the technological improvement of microorganisms can be afforded using the combination of mathematical modelling and optimization. The systematic nature of this approach facilitates the redesign of biochemical systems and makes this a predictive exercise rather than a trial-and-error procedure.