Iterative Fuzzy Clustering Algorithm With Supervision to Construct Probabilistic Fuzzy Rule Base From Numerical Data

To deal with data patterns with linguistic ambiguity and with probabilistic uncertainty in a single framework, we construct an interpretable probabilistic fuzzy rule-based system that requires less human intervention and less prior knowledge than other state of the art methods. Specifically, we present a new iterative fuzzy clustering algorithm that incorporates a supervisory scheme into an unsupervised fuzzy clustering process. The learning process starts in a fully unsupervised manner using fuzzy c-means (FCM) clustering algorithm and a cluster validity criterion, and then gradually constructs meaningful fuzzy partitions over the input space. The corresponding fuzzy rules with probabilities are obtained through an iterative learning process of selecting clusters with supervisory guidance based on the notions of cluster-pureness and class-separability. The proposed algorithm is tested first with synthetic data sets and benchmark data sets from the UCI Repository of Machine Learning Database and then, with real facial expression data and TV viewing data.     

Characteristics of ACPDP test panels with aluminum fence electrode formed via anodic bonding with soda‐lime glass

Abstract— In an attempt to reduce materials and processing costs of ACPDPs, aluminum fence electrodes were prepared on soda‐lime glass substrates by chemically etching aluminum foil bonded directly onto the substrate via an anodic‐bonding process. Several different fence‐electrode patterns were designed and coated either with a glass dielectric layer or with an anodic aluminum oxide layer. Firing voltages, operation margin, luminance, and luminous efficiency of such test panels were evaluated. The results indicated that the performance of test panels with aluminum fence electrodes is comparable with conventional test panels with ITO/Ag electrodes, demonstrating the possibility of a dramatic reduction in the costs of ACPDPs.     

Decentralized Iterative Learning Control to Large-Scale Industrial Processes for Nonrepetitive Trajectory Tracking

In the procedure of steady-state hierarchical optimization with feedback for a large-scale industrial process, it is usual that a sequence of step set-point changes is carried out and used by the decision-making units while searching the eventual optimum. In this case, the real process experiences a form of disturbances around its operating set-point. In order to improve the dynamic performance of transient responses for such a large-scale system driven by the set-point changes, an open-loop proportional integral derivative-type iterative learning control (ILC) strategy is explored in this paper by considering the different magnitudes of the controller's step set-point change sequence. Utilizing the Hausdorff-Young inequality of convolution integral, the convergence of the algorithm is derived in the sense of Lebesgue-P norm. Furthermore, the extended higher order ILC rule is developed, and the convergence is analyzed. Simulation results illustrate that the proposed ILC strategies can remarkably improve the dynamic performance such as decreasing the overshoot, accelerating the transient response, shortening the settling time, etc.     

HERMES: embedded file system design for A/V application

Embedded systems such as PVR, set-top box, HDTV put unique demand on I/O subsystem design. Underlying software, particularly file system, needs to be elaborately designed so that it can meet tight constraints of consumer electronics platform: performance, price, reliability, and etc. In this work, we develop state-of-art file system elaborately tailored for A/V workload. There are two design objectives in our file system: performance and support for logical level abstraction. For performance, we develop a number of novel features: extent based allocation, single level file structure with block index augmentation scheme, aggressive free block allocation to minimize disk fragmentation, elaborate file system meta data layout, separation of name space data and file data and etc. HERMES enables the user to view file as a collection of semantic units (frame or audio samples). HERMES file system encompasses most of state-of-the-art file system technologies published in preceding works. Via extensive physical experiment, we verify that HERMES file system successfully addresses the original issues: good scalability, predictable I/O latency (minimizing variability in I/O latency), efficient disk head movement and etc. This is the result of harmonious effort of large I/O size, aggressive free block allocation algorithm, data block placement strategy, file organization, layout of HERMES file system and etc. The result of performance experiments indicate that HERMES file system prototype successfully meets the file system constraints for high volume and high bandwidth multimedia application. HERMES file system exhibits superior performance to EXT2 file system (Linux) and XFS file system (SGI).

Dynamic Path Management with Resilience Constraints under Multiple Link Failures in MPLS/GMPLS Networks

Most previous research on MPLS/GMPLS recovery management has focused on efficient routing or signaling methods from single failures. However, multiple simultaneous failures may occur in large-scale complex virtual paths of MPLS/GMPLS networks. In this paper, we present a dynamic MPLS/GMPLS path management strategy in which the path recovery mechanism can rapidly find an optimal backup path which satisfies the resilience constraints under multiple link failure occurrences. We derived the conditions to test the existence of resilience-guaranteed backup path, and developed a decomposition theorem and backup path construction algorithm for the fast restoration of resilience-guaranteed backup paths, for the primary path with an arbitrary configuration. Finally, simulation results are presented to evaluate the performance of the proposed approach.     

A Regression Approach to Music Emotion Recognition

Content-based retrieval has emerged in the face of content explosion as a promising approach to information access. In this paper, we focus on the challenging issue of recognizing the emotion content of music signals, or music emotion recognition (MER). Specifically, we formulate MER as a regression problem to predict the arousal and valence values (AV values) of each music sample directly. Associated with the AV values, each music sample becomes a point in the arousal-valence plane, so the users can efficiently retrieve the music sample by specifying a desired point in the emotion plane. Because no categorical taxonomy is used, the regression approach is free of the ambiguity inherent to conventional categorical approaches. To improve the performance, we apply principal component analysis to reduce the correlation between arousal and valence, and RReliefF to select important features. An extensive performance study is conducted to evaluate the accuracy of the regression approach for predicting AV values. The best performance evaluated in terms of the R ² statistics reaches 58.3% for arousal and 28.1% for valence by employing support vector machine as the regressor. We also apply the regression approach to detect the emotion variation within a music selection and find the prediction accuracy superior to existing works. A group-wise MER scheme is also developed to address the subjectivity issue of emotion perception.     

Secretome analysis of novel IgE-binding proteins from Penicillium citrinum

The Penicillium genus of fungi is a frequently reported cause of allergic reactions. However, only a limited number of allergens have been reported. In Penicillium spp., many allergens show higher IgE-binding activity in culture filtrate extracts than in cellular extracts. In order to investigate the IgE-reactive profile of mold-sensitized patients, secreted IgE-reactive proteins from Penicillium citrinum were identified by 2-DE, serum immunoblotting, and nanoLC-MS/MS. Among the IgE-reactive spots, one known allergen, Pen c 13, and four novel allergens were identified. The cDNAs coding for Pen c 32 and Pen c 30 were cloned using designed primers based on nanoLC-MS/MS analysis. The amino acid sequences of Pen c 32 and Pen c 30 were, respectively, found to have extensive similarity with those of pectate lyases and catalases from various fungi. Native Pen c 30 was shown to have catalase activity and to bind to serum IgE from 48% of mold-allergic patients and induced immediate type skin reactions in a sensitized patient. Here, we present a proteome approach which resulted in the identification of four novel secreted allergens. These novel allergens might be useful in allergy diagnosis and in the treatment of mold-allergic disorders.     

A methodology for measuring in situ lattice strain of bulk polycrystalline material under cyclic load

The material response of polycrystalline materials under cyclic loading is not fully understood. Even during uniaxial loading, individual grains embedded within the polycrystalline material can experience complicated strain histories. By quantifying the deformation state at the crystal level, we can begin to understand the conditions that lead to fatigue failure. An in situ powder diffraction method was developed and employed at the Cornell High Energy Synchrotron Source to measure the aggregate crystal response at various points in a material's life using synchrotron x ray. A set of experiments was conducted using a load frame capable of exerting cyclic uniaxial loads on a specimen. A high speed x-ray shutter was developed to synchronize the x-ray beam and the loading cycle. Using the high speed shutter, the evolution of the lattice strains for the families of crystallographic planes was measured while the aggregate was under cyclic uniaxial loading, thus monitoring a live evolution of lattice strain in a cyclically loaded specimen. The methodology is demonstrated using uniaxial cyclic specimens machined from oxygen free conductivity (OFHC) copper sheet.     

Magnetic compound refractive lens for focusing and polarizing cold neutron beams

Biconcave cylindrical lenses are used to focus beams of x rays or neutrons using the refractive properties of matter. In the case of neutrons, the refractive properties of magnetic induction can similarly focus and simultaneously polarize the neutron beam without the concomitant attenuation of matter. This concept of a magnetic refractive lens was tested using a compound lens consisting of 99 pairs of cylindrical permanent magnets. The assembly successfully focused the intensity of a white beam of cold neutrons of one spin state at the detector, while defocusing the other. This experiment confirmed that a lens of this nature may boost the intensity locally by almost an order of magnitude and create a polarized beam. An estimate of the performance of a more practically dimensioned device suitable for incorporation in reflectometers and slit-geometry small angle scattering instruments is given.     

Evaluation of the critical stroke of an earthworm-like robot for capsule endoscopes

Recently, the capsule endoscope has been highlighted for the patient's convenience and the possibility of application in the small intestine. However, the capsule endoscope has some limitations in obtaining an image of the digestive organ because its movement depends only on the peristaltic motion. In order to solve these problems, it is necessary to determine the locomotive mechanism of the capsule endoscope. Therefore, the present authors have already proposed an earthworm-like robot, which has a locomotive mechanism. However, this mechanism should be designed so that the earthworm-like robot has a larger stroke than the critical stroke required to perform motion inside the small intestine. In this study, therefore, not only is the modelling of the locomotive process based on a biomechanical study presented but also the movement of the earthworm-like robot in the small intestine is simulated. Through the simulation process, the variation in the critical stroke with regard to the elastic modulus of the mesentery is investigated. Finally, from an in vitro test of the proposed robot, it is found that the experimental result is very similar to that of the simulation. Consequently, the present work will provide guidelines for designing an earthworm-like robot for diagnosis of the small intestine.