On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets

When performing a classification task, we may find some data-sets with a different class distribution among their patterns. This problem is known as classification with imbalanced data-sets and it appears in many real application areas. For this reason, it has recently become a relevant topic in the area of Machine Learning.The aim of this work is to improve the behaviour of fuzzy rule based classification systems (FRBCSs) in the framework of imbalanced data-sets by means of a tuning step. Specifically, we adapt the 2-tuples based genetic tuning approach to classification problems showing the good synergy between this method and some FRBCSs.Our empirical results show that the 2-tuples based genetic tuning increases the performance of FRBCSs in all types of imbalanced data. Furthermore, when the initial Rule Base, built by a fuzzy rule learning methodology, obtains a good behaviour in terms of accuracy, we achieve a higher improvement in performance for the whole model when applying the genetic 2-tuples post-processing step. This enhancement is also obtained in the case of cooperation with a preprocessing stage, proving the necessity of rebalancing the training set before the learning phase when dealing with imbalanced data.     

Effect of physical vapor deposition metallic thin films on micro injection molded weld line mechanical properties

Micro injection molded polymeric parts coated with functional thin films/layers show off the promising applications in microsystems area. But the unfavorable and unavoidable defect of weld line in micro injection molding part leads to detrimental mechanical and surface properties. The possibility of the functional thin film for enhancing micro injection molded weld lines was investigated. Two typical coating materials (aluminum and titanium) with various film thicknesses (400, 600, 800 nm) were deposited on one side of the micro injection molded weld line tensile sample via physical vapor deposition (PVD) method. The coated micro weld line samples were characterized by tensile tests. The results show that PVD films of aluminum and titanium can reinforce the strength and stiffness of micro injection molded weld line, even at thin thickness levels. But when the film thickness is increasing, the weaker adhesion between metallic films and polymers decreased the PVD films’ enhancing performance for micro weld line mechanical properties due to the degradation of polymers related to longer time exposure under high temperature.     

Model Checking Games for the Quantitative μ-Calculus

We investigate quantitative extensions of modal logic and the modal μ-calculus, and study the question whether the tight connection between logic and games can be lifted from the qualitative logics to their quantitative counterparts. It turns out that, if the quantitative μ-calculus is defined in an appropriate way respecting the duality properties between the logical operators, then its model checking problem can indeed be characterised by a quantitative variant of parity games. However, these quantitative games have quite different properties than their classical counterparts, in particular they are, in general, not positionally determined. The correspondence between the logic and the games goes both ways: the value of a formula on a quantitative transition system coincides with the value of the associated quantitative game, and conversely, the values of quantitative parity games are definable in the quantitative μ-calculus.     

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

Nowadays, the patients and physicians use the health-related websites as an important information source and, therefore, it is critical the quality evaluation of health- related websites. The quality assessment of health-related websites becomes especially relevant because their use imply the existence of a wide range of threats which can affect people’s health. Additionally, website quality evaluation can also contribute to maximize the exploitation of invested resources by organizations in the development of user-perceived quality websites. But there is not yet a clear and unambiguous definition of the concept of website quality and the debate about quality evaluation on the Web remains open. In this paper, we present a qualitative and user-oriented methodology for assessing quality of health-related websites based on a 2-tuple fuzzy linguistic approach. To identify the quality criteria set, a qualitative research has been carried out using the focus groups technique. The measurement method generates linguistic quality assessments considering the visitors’ judgements with respect to those quality criteria. The combination of the linguistic judgements is implemented without a loss of information by applying a 2-tuple linguistic weighted average operator. This methodology means an improvement on quality evaluation of health websites through the commitment to put users first.     

MPC for battery/fuel cell hybrid vehicles including fuel cell dynamics and battery performance improvement

In this paper, the performance and durability of hybrid PEM fuel cell vehicles are investigated. To that end, a hybrid predictive controller is proposed to improve battery performance and to avoid fuel cell and battery degradation. Such controller deals with this complex control problem by handling binary and continuous variables, piecewise affine models and constraints. Moreover, the control strategy is to track motor power demand and keep batteries close to a desired battery state of charge which is appropriately chosen to minimize hydrogen consumption. It is important to highlight the consideration of constraints which are directly related to the goals of this paper, such as minimum fuel cell power threshold and time limitation between fuel cell startups and shutdowns. Furthermore, different models have been elaborated and particularized for a vehicle prototype. These models include few innovations such as a reference governor which smooths fuel cell power demand during sharp power profiles, forcing batteries to supply such peaks and resulting a longer fuel cell lifetime. Battery thermal dynamics are also taken into account in these models in order to analyze the effect of battery temperature on its degradation. Finally, this paper studies the feasibility of the real implementation, presenting an explicit formulation as a solution to reduce execution time. This explicit controller exhibits the same performance as the hybrid predictive controller does with a reduced computational effort. All the results have been validated in several simulations.     

Bayesian networks for enhancement of requirements engineering: a literature review

Requirements analysis is the software engineering stage that is closest to the users’ world. It also involves tasks that are knowledge intensive. Thus, the use of Bayesian networks (BNs) to model this knowledge would be a valuable aid. These probabilistic models could manage the imprecision and ambiguities usually present in requirements engineering (RE). In this work, we conduct a literature review focusing on where and how BNs are applied on subareas of RE in order to identify which gaps remain uncovered and which methods might engineers employ to incorporate this intelligent technique into their own requirements processes. The scarcity of identified studies (there are only 20) suggests that not all RE areas have been properly investigated in the literature. The evidence available for adopting BNs into RE is sufficiently mature yet the methods applied are not easily translatable to other topics. Nonetheless, there are enough studies supporting the applicability of synergistic cooperation between RE and BNs. This work provides a background for understanding the current state of research encompassing RE and BNs. Functional, non-functional and -ilities requirements artifacts are enhanced by the use of BNs. These models were obtained by interacting with experts or by learning from databases. The most common criticism from the point of view of BN experts is that the models lack validation, whereas requirements engineers point to the lack of a clear application method for BNs and the lack of tools for incorporating them as built-in help functions.     

LPS: A Language Prototyping System Using Modular Monadic Semantics

This paper describes LPS, a Language Prototyping System that facilitates the modular development of interpreters from semantic building blocks. The system is based on the integration of ideas from Modular Monadic Semantics and Generic Programming.To define a new programming language, the abstract syntax is described as the fixpoint of non-recursive pattern functors. For each functor an algebra is defined whose carrier is the computational monad obtained from the application of several monad transformers to a base monad. The interpreter is automatically generated by a catamorphism or, in some special cases, a monadic catamorphism.The system has been implemented as a domain-specific language embedded in Haskell and we have also implemented an interactive framework for language testing.     

Robot arm reaching through neural inversions and reinforcement learning

We present a neural method that computes the inverse kinematics of any kind of robot manipulators, both redundant and non-redundant. Inverse kinematics solutions are obtained through the inversion of a neural network that has been previously trained to approximate the manipulator forward kinematics. The inversion provides difference vectors in the joint space from difference vectors in the workspace. Our differential inverse kinematics (DIV) approach can be viewed as a neural network implementation of the Jacobian transpose method for arm kinematic control that does not require previous knowledge of the arm forward kinematics. Redundancy can be exploited to obtain a special inverse kinematic solution that meets a particular constraint (e.g. joint limit avoidance) by inverting an additional neural network The usefulness of our DIV approach is further illustrated with sensor-based multilink manipulators that learn collision-free reaching motions in unknown environments. For this task, the neural controller has two modules: a reinforcement-based action generator (AG) and a DIV module that computes goal vectors in the joint space. The actions given by the AG are interpreted with regard to those goal vectors.     

Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter

The time aggregation properties of the Hodrick-Prescott (HP) filter, which decomposes a time series into trend and cycle, are analyzed for the case of annual, quarterly, and monthly data. Aggregation of the disaggregate components cannot be obtained as the exact result from direct application of an HP filter to the aggregate series. Employing several criteria, HP decompositions for different levels of aggregation that provide similar results can be found. The aggregation is guided by the principle that the period associated with the frequency for which the filter gain is should not be altered. This criterion is intuitive and easy to apply. It is shown that it is approximated, to the first order, by an already proposed empirical rule and that alternative, more complex criteria yield similar results. Moreover, the values of the smoothing parameter of the HP filter that provide results which are approximately consistent under aggregation are considerably robust with respect to the ARIMA model of the series. Aggregation is found to perform better for the case of temporal aggregation than for systematic sampling. The desirability of exact aggregation consistency is investigated. A clarification concerning the supposed spuriousness of the cycles obtained by the HP filter is discussed.     

In situ autolysis of mouse brain: ultrastructure of mitochondria and the function of oxidative phosphorylation and mitochondrial DNA

The effect of in situ autolysis on cerebral mitochondrial structure and function has been investigated. Mice (n = 9) were sacrificed and stored for up to 24 h under unfavorable post-mortem conditions at 25 degrees C. At different time intervals groups of three animals were submitted to post-mortem dissection and tissue from different regions of the brain was used for the preparation of "free" and synaptosomal mitochondria. On electron microscopic examination, the post-mortem period had no significant influence on mitochondrial morphology and enzymatic activities of complexes I-V of the mitochondrial oxidative phosphorylation system were still present in all the mitochondrial preparations from different regions of the brain, albeit at a reduced levels. Degradation of mitochondrial DNA was virtually absent from mitochondrial preparations during the 24-h period of autolysis, as shown by the presence of intact DNA by Southern blot and PCR analysis. Based on these results, alterations in mitochondrial DNA and deficiencies of mitochondrial respiratory complexes I-V can be recognized in cerebral tissue even after 24 h of unfavorable post-mortem storage conditions.