Robust control method for the inverted pendulum system with structured uncertainty caused by measurement error

In this article, we propose a design method for an inverted pendulum system with a structured uncertainty. We consider that such an uncertainty is caused by a measurement error in the rotation angle of the pendulum and effects on the system structure that cannot be included in the nominal elements. For the uncertain system obtained, we apply an integral tracking control and the guaranteed cost control to design a robust, stable, tracking control system. Finally, we show the effectiveness of our method through a numerical example.     

Vehicle inductive signatures recognition using a Madaline neural network

In this paper, we report results obtained with a Madaline neural network trained to classify inductive signatures of two vehicles classes: trucks with one rear axle and trucks with double rear axle. In order to train the Madaline, the inductive signatures were pre-processed and both classes, named C2 and C3, were subdivided into four subclasses. Thus, the initial classification task was split into four smaller tasks (theoretically) easier to be performed. The heuristic adopted in the training attempts to minimize the effects of the input space non-linearity on the classifier performance by uncoupling the learning of the classes and, for this, we induce output Adalines to specialize in learning one of the classes. The percentages of correct classifications presented concern patterns which were not submitted to the neural network in the training process, and, therefore, they indicate the neural network generalization ability. The results are good and stimulate the maintenance of this research on the use of Madaline networks in vehicle classification tasks using not linearly separable inductive signatures.     

Scale free interval graphs

Scale free graphs have attracted attention by their non-uniform structure that can be used as a model for various social and physical networks. In this paper, we propose a natural and simple random model for generating scale free interval graphs. The model generates a set of intervals randomly under a certain distribution, which defines a random interval graph. The main advantage of the model is its simpleness. The structure/properties of generated graphs are analyzable by relatively simple probabilistic and/or combinatorial arguments, which is different from many other models. Based on such arguments, we show for our random interval graph that its degree distribution follows a power law, and that it has a large average clustering coefficient.     

Interactive learning and management of visual information via human-like software robot

To achieve smooth real-world interaction between people and computers, we developed a system that displays a three-dimensional computer-graphic human-like image from the waist up (anthropomorphic software robot: hereinafter “robot”) on the display, that interactively sees and hears, and that has fine and detailed control functions such as facial expressions, line of sight, and pointing at targets with its finger. The robot visually searches and identifies persons and objects in real space that it has learned in advance (registered space, which was our office in this case), manages the history information of the places and times it found objects and/or persons, and tells the user, indicating their three-dimensional positions with line of sight and its finger. It interactively learns new objects and persons with line of with their names and owners. By using this function, the robot can engage in simple dialogue (do a task) with the user. Osamu Hasegawa, Ph.D.: He received the B.E. and M.E. degrees from the Science University of Tokyo, in 1988, 1990 respectively. He received Ph.D. degree from the University of Tokyo, in 1993. Currently, he is a senior research scientist at the Electrotechnical Laboratory (ETL), Tsukuba, Japan. His research interests include Computer Vision and Multi-modal Human Interface. Dr. Hasegawa is a member of the AAAI, the Institute of Electronics, Information and Communication Engineers, Japan (IEICE), Information Processing Society of Japan and others. Katsuhiko Sakaue, Ph.D.: He received the B.E., M.E., and Ph.D. degrees all in electronic engineering from the University of Tokyo, in 1976, 1978 and 1981, respectively. In 1981, he joined the Electrotechnical Laboratory, Ministry of International Trade and Industry, and engaged in researches in image processing and computer vision. He received the Encouragement Prize in 1979 from IEICE, and the Paper Award in 1985 from Information Processing Society of Japan. He is a member of IEICE, IEEE, IPSJ, ITE. Satoru Hayamizu, Ph.D.: He is a leader of Interactive Intermodal Integration Lab. at Electrotechnical Laboratory. He received the B.E., M.E., Ph.D. degrees from Tokyo University. Since 1981, he has been working on speech recognition, spoken dialogue, and communication with artifacts. From 1989 to 1990, he was a visiting scholar in Carnegie Mellon University and in 1994 a visiting scientist in LIMSI/CNRS.     

An application of the 2-nitrobenzenesulfenyl method to proteomic profiling of human colorectal carcinoma: A novel approach for biomarker discovery

In the development of novel biomarkers, the proteomic approach is advantageous because using it the cancer-associated proteins can be directly identified. We previously developed a 2-nitrobenzenesulfenyl (NBS) method to improve quantitative proteome analysis. Here, we applied this method to proteomic profiling of colorectal carcinoma (CRC) to identify novel proteins with altered expression in CRC. Each pair of tumor and normal tissue specimens from 12 CRC patients was analyzed, and approximately 5000 NBS-labeled paired peaks were quantified. Peaks with altered signal intensities (>1.5-fold) and occurring frequently in the samples (>70%) were selected, and 128 proteins were identified by MS/MS analyses as differentially expressed proteins in CRC tissues. Many proteins were newly revealed to be CRC related; 30 were reported in earlier studies of CRC. Six proteins that were up-regulated in CRC (ZYX, RAN, RCN1, AHCY, LGALS1, and VIM) were further characterized and validated by Western blot and immunohistochemistry. All six were found to be CRC-localized, either in cancer cells or in stroma cells near the cancer cells. These results indicate that the proteins identified in this study are novel candidates for CRC markers, and that the NBS method is useful in proteome mining to discover novel biomarkers.     

Spatiotemporal conversion of auditory information for cochleotopic mapping

Auditory communication signals such as monkey calls are complex FM vocal sounds and in general induce action potentials in different timing in the primary auditory cortex. Delay line scheme is one of the effective ways for detecting such neuronal timing. However, the scheme is not straightforwardly applicable if the time intervals of signals are beyond the latency time of delay lines. In fact, monkey calls are often expressed in longer time intervals (hundreds of milliseconds to seconds) and are beyond the latency times observed in the brain (less than several hundreds of milliseconds). Here, we propose a cochleotopic map similar to that in vision known as a retinotopic map. We show that information about monkey calls could be mapped on a cochleotopic cortical network as spatiotemporal firing patterns of neurons, which can then be decomposed into simple (linearly sweeping) FM components and integrated into unified percepts by higher cortical networks. We suggest that the spatiotemporal conversion of auditory information may be essential for developing the cochleotopic map, which could serve as the foundation for later processing, or monkey call identification by higher cortical areas.     

Superconductivity in dilute Cu-Nb-Sn alloys containing Nb3Sn precipitates

The dilute Cu-Nb-Sn alloys containing small amounts of Nb and Sn less than 1 at % exhibited superconductivity after quenching from the liquid state and ageing. The best superconducting properties ( andJ _c=130 A cm^–2) in a Cu-0.30 at % Nb 0.15 at % Sn alloy were obtained when the sample was aged at 550° C for 384 h. This sample exhibited a structure of fine Nb₃Sn precipitates of 200 to 500Å diameter distributed homogeneously in the Cu matrix, and therefore it was concluded that superconductivity in these alloys resulted from the proximity effect of Nb₃Sn particles. In spite of the similar structure obtained by ageing at 800° C, the Cu-Nb-Sn alloys showed inferior superconducting properties compared to the Cu-0.4 at % Nb alloy and this would be explained qualitatively by the difference in the mean free path in the two alloys.     

Interdiffusion in Co-Mn alloys

Interdiffusion coefficient in cobalt-manganese alloys has been determined by Matano's method in the temperature range between 1133 and 1423 K on (pure Co)-(Co-30.28 at. pct Mn alloy) and (pure Co)-(Co-51.76 at. pct Mn alloy) couples. This, ∼D, has been found to increase with the increase of manganese content. However, the activation energy (∼Q) and frequency factor ( ₀) show a maximum at about 10 at. pct Mn. The concentration dependence of and has been discussed taking into account the thermodynamic properties of the alloy. The difference in between the ferro- and paramagnetic phases in Co-5 at. pct Mn alloy has been found to be 24 kJ/mol, which is larger, than that for the diffusion of Mn⁵⁴ in this alloy. Further it has been found that the Kirkendall marker moves toward manganese-rich side, showing that manganese atoms diffuse faster than cobalt atoms. From the marker shift, the intrinsic diffusion coefficients,D _Co andD _Mn, at 33 at. pct Mn have been determined as follows:D _Co=0.22×10⁻⁴ exp(−263 kJ mol⁻¹/RT) m²/s, andD _Mn=0.98×10⁻⁴ exp(−229 kJ mol⁻¹/RT) m²/s.     

On intractability of the classUP

The classUP [V] is the class of sets accepted by polynomial-time nondeterministic Turing machines which have at most one accepting path for every input. The complexity of this class closely relates to that of computing inverses ofone-way functions, where a one-way function is a one-to-one, length-increasing, and polynomial-time computable function whose inverse cannot be computed within polynomial time. It is known [GS], [K] that there exists a one-way function if and only ifP UP. In this paper the intractability of sets inUP is investigated in terms of polynomial-time reducibility to a sparse set. It is shown thatUP has a set that is _m ^P -reducible to no sparse set ifP UP. We interpret this structural property in the relation with approximation algorithms: it is shown that ifP UP, thenUP has a set with no 1-APT approximation and, furthermore,UP has a set that is not _m ^P -reducible to any set with a 1-APT approximation. The implication of this result in the study of one-way functions is also discussed. In order to prove the main theorem, we introduce a variation of tree-pruning methods.This paper was written while the author visited the Department of Mathematics, University of California, Santa Barbara. This research was supported in part by the National Science Foundation under Grant CCR-8611980.     

An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.