Image Compression and Video Segmentation Using Hierarchical Self-Organization

Both image compression based on color quantization and image segmentation are two typical tasks in the field of image processing. Several techniques based on splitting algorithms or cluster analyses have been proposed in the literature. Self-organizing maps have been also applied to these problems, although with some limitations due to the fixed network architecture and the lack of representation in hierarchical relations among data. In this paper, both problems are addressed using growing hierarchical self-organizing models. An advantage of these models is due to the hierarchical architecture, which is more flexible in the adaptation process to input data, reflecting inherent hierarchical relations among data. Comparative results are provided for image compression and image segmentation. Experimental results show that the proposed approach is promising for image processing, and the powerful of the hierarchical information provided by the proposed model.     

Variable Structure Control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven infront of disturbances and noise effects.     

Brain reading using full brain support vector machines for object recognition: there is no "face" identification area

Over the past decade, object recognition work has confounded voxel response detection with potential voxel class identification. Consequently, the claim that there are areas of the brain that are necessary and sufficient for object identification cannot be resolved with existing associative methods (e.g., the general linear model) that are dominant in brain imaging methods. In order to explore this controversy we trained full brain (40,000 voxels) single TR (repetition time) classifiers on data from 10 subjects in two different recognition tasks on the most controversial classes of stimuli (house and face) and show 97.4% median out-of-sample (unseen TRs) generalization. This performance allowed us to reliably and uniquely assay the classifier's voxel diagnosticity in all individual subjects' brains. In this two-class case, there may be specific areas diagnostic for house stimuli (e.g., LO) or for face stimuli (e.g., STS); however, in contrast to the detection results common in this literature, neither the fusiform face area nor parahippocampal place area is shown to be uniquely diagnostic for faces or places, respectively.     

A backstepping controller for path‐tracking of an underactuated autonomous airship

In this paper we propose a nonlinear control approach for the path‐tracking of an autonomous underactuated airship. A backstepping controller is designed from the airship nonlinear dynamic model including wind disturbances, and further enhanced to consider actuators saturation. Control implementation issues related to airship underactuation are also addressed, namely control allocation and an attitude reference shaping to obtain a faster error correction with smoother input requests. The results obtained demonstrate the capacity of an underactuated unmanned airship to execute a realistic mission including vertical take‐off and landing, stabilization and path‐tracking, in the presence of wind disturbances, with a single robust control law. Copyright © 2008 John Wiley & Sons, Ltd.     

Synthesis of symmetric and asymmetric singly terminated elliptic ladder filters for multiplexing applications

An extension of the Cauer ladder development for synthesizing singly terminated filters with symmetric and asymmetric responses is presented. Basically, a driving‐point immittance including reactive constant elements is carried out in such a way that provides the transmission zeros. The reactive constant elements are introduced into the synthesis for two reasons. The first is to consider the possibility of the asymmetric position of transmission zeros in the real frequency axis. The second one is to obtain canonical forms, i.e. networks with the minimum number of elements in the case of symmetrical responses. To validate the proposed method, a filter with asymmetrical response has been synthesized, comparing different topologies for its use in multiplexers. This fact is illustrated with a Ku‐band elliptic response diplexer designed in H‐plane rectangular waveguide. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

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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The Green language type system

A programming language that considers basic values and classes as objects brings more opportunities of code reuse and it is easier to use than a language that does not support this feature. However, popular statically typed object-oriented languages do not consider classes as first-class objects because this concept is difficult to integrate with static type checking. They also do not consider basic values as objects for sake of efficiency. This article presents the Green language type system which supports classes as classless objects and offers a mechanism to treat basic values as objects. The result is a reasonably simple type system which is statically typed and easy to implement. It simplifies several other language mechanisms and prevents any infinite regression of metaclasses.     

The application of inductively coupled plasma mass spectrometry in clinical pharmacological oncology research

Metal-based anticancer agents are frequently used in the treatment of a wide variety of cancer types. The monitoring of these anticancer agents in biological samples is important to understand their pharmacokinetics, pharmacodynamics, and metabolism. In addition, determination of metals originating from anticancer agents is relevant to assess occupational exposure of health care personnel working with these drugs. The high sensitivity of inductively coupled plasma mass spectrometry (ICP-MS) has resulted in an increased popularity of this technique for the analysis of metal-based anticancer drugs. In addition to the quantitative analysis of the metal of interest in a sample, ICP-MS can be used as an ultrasensitive metal selective detector in combination with speciation techniques such as liquid chromatography. In the current review we provide a systematic survey of publications describing the analysis of platinum- and ruthenium-containing anticancer agents using ICP-MS, focused on the determination of total metal concentrations and on the speciation of metal compounds in biological fluids, DNA- and protein-adducts, and environmental samples. We conclude that ICP-MS is a powerful tool for the quantitative analysis of metal-based anticancer agents from multiple sample sources.     

On the interpretation of the forbidden spots observed in the electron diffraction patterns of flat Au triangular nanoparticles

In many cases nanostructures present forbidden spots in their electron diffraction patterns when they are observed by transmission electron microscopy (TEM). To interpret their TEM and high resolution transmission electron microscopy (HRTEM) images properly, an understanding of the origin of these spots is necessary. In this work we comment on the origin of the forbidden spots observed in the [111] and [112] electron diffraction patterns of flat gold triangular nanoparticles. The forbidden spots were successfully indexed as corresponding to the first laue Zone (FOLZ) and the HRTEM images presented a contrast produced by the interference of the zero-order Laue zone (ZOLZ) and FOLZ spots. We discuss the use of the forbidden spots in the study of the structure of nanoparticles and show that they are related to the shape and incompleteness of layers in the very thin particles.