Effects of oxygen on anionic butadiene telomerization in hydrocarbon solvents

During the development of an anionic butadiene telomerization process consisting of two stages, initiator preparation and telomerization, in a hydrocarbon solvent which contained a chain-transfer agent, we found that a small amount of oxygen accidentally introduced caused an unusually large decrease in the telomer viscosity. Based on the degree of such decrease due to the addition of oxygen at the two stages and based on the rather modest reactivity of oxygen with organosodium compounds, we concluded that free oxygen was catalytically involved in the telomerization process. The results of kinetic and transmetalation studies indicated that only the chain-transfer reaction was accelerated catalytically by free oxygen.     

The desorbing action of polyvinylpyrrolidone

Work has been carried out to obtain an understanding of the interaction between a cationic (basic) dye and polyvinylpyrrolidone, using visible absorption spectroscopy and viscometry. Changes in the enthalpy, entropy and number of binding sites on the polymer have been calculated.     

Fabrication and evaluation of aluminum nitride based MEMS piezoelectric vibration sensors for large-amplitude vibration applications

Microsystem Technologies - In this work, we designed a novel structure to produce vibration sensors with a linear voltage output that are suitable for large-amplitude vibration applications....     

A random-forests-based classifier using class association rules and its application to an intrusion detection system

With the rapid developments of network technology, devices connected to the network in a variety of fields have increased, and then, network security has become more important. Rule-based classification for intrusion detection is useful, because it is not only easily understood by humans, but also accurate for the classification of new patterns. Genetic network programming (GNP) is one of the rule-mining techniques as well as the evolutionary-optimization techniques. It can extract rules efficiently even from an enormous database, but still needs more accuracy and stability for practical use. This paper describes a classification system with random forests, employing weighted majority vote in the classification to enhance its performance. For the performance evaluation, NSL-KDD (Network Security Laboratory-Knowledge Discovery and Data Mining) data set is used and the proposed method is compared with the conventional methods, including other machine-learning techniques (Random forests, SVM, J4.8) in terms of the accuracy and false positive rate.     

On Self-Learning Systems

Abstract

The fundamental problem on self-learning is discussed. The characteristics and the capability of two representative organizers obtained by the Karhunen-Loève system and the stochastic approximation method are described and their relationship with Bayes' solution is discussed.

The organization obtainable by the KL system is realized by calculating the difference of the features between the categories and by classifying the system so as to maximize this difference. This procedure is shown to be optimal. Further, the sufficient condition for this procedure to be the Bayes' solution is derived.

For the organization attainable by the stochastic approximation method, two functional to be evaluated are introduced and the system is organized so as to minimize these functionals. The necessary and the sufficient conditions for these procedures to be Bayes' solution are obtained for the mixture of normal distributions with identical covariance matrices.

The several simulations on a digital computer are performed for both cases. The results of these simulations indicate the validity of our learning systems.     

Midpoint-validation algorithm for support vector machine classification

In this article, we propose a midpoint-validation algorithm for a support vector machine which improves the generalization of the support vector machine so that the midpoint-validation error is minimized. We compared its performance with other techniques for support vector machines, and also tested our proposed method on fifth benchmark problems. The results obtained from the simulation shows the effectiveness of the proposed method.     

A method to improve the stability of adaptive steering driver-vehicle systems

If the behavior of a combined vehicle tracks the behavior of an ideal vehicle model, the good handling performance can be maintained with large variations in the dynamics of the combined vehicles. Based on this notion, we have developed an adaptive steering controller which achieves good tracking performance. However, we designed an ideal vehicle model without considering variations in the abilities of the driver. If an adequate ideal vehicle model can be designed which can adapt to variations in the abilities of the drivers, a better handling performance of an adaptive combined driver-vehicle system can be realized. In this article, attention is focused on the lane change maneuver and the cornering maneuver, and we propose a new scheme to design an ideal vehicle model which can adapt to variations in the abilities of the driver. Finally, by carrying out numerical simulations, it is shown that the ideal vehicle model which was designed is very effective.     

Insight into unusual impurity absorbability of GeO(2) in GeO(2)∕Ge stacks

Adsorbed species and its diffusion behaviors in GeO(2)∕Ge stacks, which are future alternative metal-oxide-semiconductor (MOS) materials, have been investigated using various physical analyses. We clarified that GeO(2) rapidly absorbs moisture in air just after its exposure. After the absorbed moisture in GeO(2) reaches a certain limit, the GeO(2) starts to absorb some organic molecules, which is accompanied by a structural change in GeO(2) to form a partial carbonate or hydroxide. We also found that the hydrogen distribution in GeO(2) shows intrinsic characteristics, indicative of different diffusion behaviors at the surface and at the GeO(2)∕Ge interface. Because the impurity absorbability of GeO(2) has a great influence on the electrical properties in Ge-MOS devices, these results provide valuable information in realizing high quality GeO(2)∕Ge stacks for the actual use of Ge-MOS technologies.