A multi-objective evolutionary algorithm for an effective tuning of?fuzzy logic controllers in?heating, ventilating and air conditioning systems

This paper focuses on the use of multi-objective evolutionary algorithms to develop smartly tuned fuzzy logic controllers dedicated to the control of heating, ventilating and air conditioning systems, energy performance, stability and indoor comfort requirements. This problem presents some specific restrictions that make it very particular and complex because of the large time requirements needed to consider multiple criteria (which enlarge the solution search space) and the long computation time models required in each evaluation.     

Assessing the SALSA architecture for developing agent-based ambient computing applications

We have proposed the use of autonomous agents for coping with some of the challenges of creating ambient computing systems. The motivation of this research is that ambient computing environments are characterized by the distribution, reactivity, collaboration and adaptation of their artifacts, which are also characteristics attributed to software agents. To assist developers in creating the software entities of an ambient computing environment, the Simple Agent Library for Smart Ambients (SALSA) was created. The SALSA middleware and architecture enables the creation of autonomous agents reactive to the context of the ambient computing environment. SALSA agents can represent users, resources, or wrap complex system functionality of the environment. The aim of this paper is to provide evidence that SALSA facilitates the implementation of ambient computing services through autonomous agents. Unfortunately, the literature on Ubicomp development frameworks has, aside from a few exceptions, not reported experimental evaluation of their usability. The evaluations of Ubicomp development platforms have not addressed this issue since their evaluations have been mostly focused on performance and to prove feasibility. We present the results of an empirical evaluation conducted to assess the use of SALSA. This study included in-lab programming experiments and design exercises to evaluate the programming facilities provided by SALSA agents. Even though for some of the evaluation participants the use of autonomous agents as an abstraction for the development of ubiquitous computing systems was not innate, the evaluation results demonstrate that the execution model of SALSA and its facilities to implement Ubicomp systems are comprehensible.     

GaAsSb/InAlAs PA DHBTs Grown by Production MBE

The epi material growth of GaAsSb based DHBTs with InAlAs emitters are investigated using a 4 × 100mm multi-wafer production Riber 49 MBE reactor fully equipped with real-time in-situ sensors including an absorption band edge spectroscope and an optical-based flux monitor. The state-of-the-art hole mobilities are obtained from 100nm thick carbon-doped GaAsSb. A Sb composition variation of less than ± 0.1 atomic percent across a 4 × 100mm platen configuration has been achieved. The large area InAlAs/GaAsSb/InP DHBT device demonstrates excellent DC characteristics,such as BVCEO＞6V and a DC current gain of 45 at 1kA/cm2 for an emitter size of 50μm × 50μm. The devices have a 40nm thick GaAsSb base with p-doping of 4. 5 × 1019cm-3 . Devices with an emitter size of 4μm × 30μm have a current gain variation less than 2% across the fully processed 100mm wafer. ft and fmax are over 50GHz,with a power efficiency of 50% ,which are comparable to standard power GaAs HBT results. These results demonstrate the potential application of GaAsSb/InP DHBT for power amplifiers and the feasibility of multi-wafer MBE for mass production of GaAsSb-based HBTs.     

Finding multiple solutions in job shop scheduling by niching genetic algorithms

The interest in multimodal optimization methods is increasing in the last years. The objective is to find multiple solutions that allow the expert to choose the solution that better adapts to the actual conditions. Niching methods extend genetic algorithms to domains that require the identification of multiple solutions. There are different niching genetic algorithms: sharing, clearing, crowding and sequential, etc. The aim of this study is to study the applicability and the behavior of several niching genetic algorithms in solving job shop scheduling problems, by establishing a criterion in the use of different methods according to the needs of the expert. We will experiment with different instances of this problem, analyzing the behavior of the algorithms from the efficacy and diversity points of view.     

Induced ordered weighted geometric operators and their use in the aggregation of multiplicative preference relations

In this article, we introduce the induced ordered weighted geometric (IOWG) operator and its properties. This is a more general type of OWG operator, which is based on the induced ordered weighted averaging (IOWA) operator. We provide some IOWG operators to aggregate multiplicative preference relations in group decision‐making (GDM) problems. In particular, we present the importance IOWG (I‐IOWG) operator, which induces the ordering of the argument values based on the importance of the information sources; the consistency IOWG (C‐IOWG) operator, which induces the ordering of the argument values based on the consistency of the information sources; and the preference IOWG (P‐IOWG) operator, which induces the ordering of the argument values based on the relative preference values associated with each one of them. We also provide a procedure to deal with “ties” regarding the ordering induced by the application of one of these IOWG operators. This procedure consists of a sequential application of the aforementioned IOWG operators. Finally, we analyze the reciprocity and consistency properties of the collective multiplicative preference relations obtained using IOWG operators. © 2004 Wiley Periodicals, Inc.     

Ball Milling of Amaranth Starch-Enriched Fraction. Changes on Particle Size,Starch Crystallinity,and Functionality as a Function of Milling Energy

Starch-enriched fractions of amaranth grain were obtained from planetary ball milling and subsequently studied for particle size reduction, hydration properties, and crystallinity loss. Wide-angle X-ray scattering (WAXS) was used to evaluate the crystalline of starch-enriched fractions, using an iterative smoothing algorithm to estimate amorphous background scattering. This methodology was then used to determine initial crystallinity and monitor crystallinity loss during this process. The attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) showed that ball-milling treatment significantly decreased (p?<?0.05) the intensity ratios of the bands at 1,039 and 1,014 cm^?1 corresponding to the crystalline/amorphous part of starch structure. Starch crystallinity degree decreased by ball milling due to starch amorphization during this process. An excellent correlation was found between crystallinity degree obtained by WAXS and ATR-FTIR data for the whole ball-milled-analyzed samples. The energy required for size reduction was satisfactorily explained using a generalized grinding equation. A decrease of span and median diameter (D ₅₀) indicated sample homogenization during ball milling. Water absorption index and water solubility increased with crystallinity loss during process. The flour produced at the higher milling energy (6.52 kJ/g), with a mean size of 68?±?1 μm, showed a low crystallinity degree (<5 %), and high water absorption and solubility indexes in comparison to the starch-enriched fraction sample. Particle activation provided by ball-milling process can offer chances for starch application such as sorbent agent in food or pharmaceutical industries.     

Data‐driven bounded‐error fault detection

In this paper, a new data‐driven fault‐detection method is proposed. This method is based on a new nonparametric system identification approach, which constitutes the principal contribution to this work. The fault‐detection method is a parametric model‐free approach that can be applied to nonlinear systems that work at various operating points. Not only can the fault‐detection process be applied to the steady state of each operating point, but it can also be applied to the transient state resulting from a change in the operating point. In order to detect faults, the proposed method uses an interval predictor based on bounded‐error techniques. The utilization of techniques based on bounded error enables system uncertainties to be included in an explicit way. This in turn leads to the possibility of obtaining interval predictions of the behaviour of the system, which include information on the reliability of the prediction itself. In order to show the effectiveness of the fault‐detection method, two examples are presented: in the form of a simulated process (counter‐flow shell‐and‐tube heat‐exchanger system) and an example of a real application (two‐tanks system). A comparison with two fault‐detection methods has also been included. Copyright © 2013 John Wiley & Sons, Ltd.     

Water Distribution System Computer‐Aided Design by Agent Swarm Optimization

Optimal design of water distribution systems (WDSs), including the sizing of components, quality control, reliability, renewal, and rehabilitation strategies, etc., is a complex problem in water engineering that requires robust methods of optimization. Classical methods of optimization are not well suited for analyzing highly dimensional, multimodal, nonlinear problems, especially given inaccurate, noisy, discrete, and complex data. Agent Swarm Optimization (ASO) is a novel paradigm that exploits swarm intelligence and borrows some ideas from multiagent‐based systems. It is aimed at supporting decision‐making processes by solving multiobjective optimization problems. ASO offers robustness through a framework where various population‐based algorithms coexist. The ASO framework is described and used to solve the optimal design of WDS. The approach allows engineers to work in parallel with the computational algorithms to force the recruitment of new searching elements, thus contributing to the solution process with expert‐based proposals.     

Ethylene production,respiration and gas exchange modelling in modified atmosphere packaging for banana fruits

A mathematical model was developed from experimental measurements to describe the evolution of the O₂, CO₂ and ethylene in a modified atmosphere packaging system for Cavendish bananas. The respiration and ethylene production in the fruits were experimentally obtained from a closed system method and then represented by Michaelis–Menten equations of enzyme kinetics. The gas transfer through the packaging was described by a Fick's diffusion equation, and the temperature dependence was represented based on the Arrhenius law. The model was validated by packaging the fruit in perforated bags of polypropylene and low density polyethylene at 12 °C for a period of 8 days. With the developed model it was possible to satisfactorily describe the experimental evolution of the gas content in the headspace of the packages, obtaining coefficients of determination (R²) of 0.93 for the O₂ levels, 0.90–0.91 for the CO₂ levels, and 0.89–0.93 for the ethylene levels.