Sliding mode-like fuzzy logic control with self-tuning the deadzone parameters

In this paper, a fuzzy logic controller (FLC) is designed based on the similarity between the FLC and the sliding mode control (SMC). The proposed scheme provides the sliding mode-like FLC with fast self-tuning the dead-zone parameters (boundary layer thickness) under parameter variations of the controlled system. To show the validity and the effectiveness of the proposed control method, simulations are performed for the position control of a rotary inverted pendulum     

Suboptimal filter for continuous‐time linear systems with unknown parameters

The filtering problem for continuous‐time linear systems with unknown parameters is considered. A new suboptimal filter is herein proposed. It is based on the optimal mean‐square linear combination of the local Kalman filters. In contrast to the optimal weights, the suboptimal weights do not depend on current observations; thus, the proposed filter can easily be implemented in real‐time. Examples demonstrate high accuracy and efficiency of the suboptimal filter. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Self-absorption correction for solid-state photoluminescence quantum yields obtained from integrating sphere measurements

A new method is presented for analyzing the effects of self-absorption on photoluminescence integrating sphere quantum yield measurements. Both the observed quantum yield and luminescence spectrum are used to determine the self-absorption probability, taking into account both the initial emission and subsequent absorption and reemission processes. The analysis is experimentally validated using the model system of the laser dye perylene red dispersed in a polymer film. This approach represents an improvement over previous methods that tend to overestimate the true quantum yield, especially in cases with high sample absorbance or quantum yield values.     

Capturing and reusing knowledge in engineering change management: A case of automobile development

The development of complex products, such as automobiles, involves engineering changes that frequently require redesigning or altering the products. Although it has been found that efficient management of knowledge and collaboration in engineering changes is crucial for the success of new product development, extant systems for engineering changes focus mainly on storing documents related to the engineering changes or simply automating the approval processes, while the knowledge that is generated from collaboration and decision-making processes may not be captured and managed easily. This consequently limits the use of the systems by the participants in engineering change processes. This paper describes a model for knowledge management and collaboration in engineering change processes, and based on the model, builds a prototype system that demonstrates the model’s strengths. We studied a major Korean automobile company to analyze the automobile industry’s unique requirements regarding engineering changes. We also developed domain ontologies from the case to facilitate knowledge sharing in the design process. For achieving efficient retrieval and reuse of past engineering changes, we used a case-based reasoning (CBR) with a concept-based similarity measure.

Dielectric function and electrical resistivity of liquid carbon determined by femtosecond spectroscopy

Femtosecond pump-probe reflectance of graphite and diamond targets following intense laser irradiation is used to measure the optical properties of the pressurized liquid carbon phase while it retains an optically sharp surface before expanding hydrodynamically as a hot plasma. These measurements allow the historically elusive liquid phase of carbon to be characterized optically for the first time. A Drude dielectric model of the reflectance spectrum 1 ps after excitation just above the melting threshold reveals a poorly conducting liquid metal with a dc resistivity 625±75 · cm. The optically determined resistivity decreases with increasing sample excitation. The initial stages of hydrodynamic surface expansion of Al, W, and C targets are also quantitatively characterized by time-resolved reflectance, revealing the expansion speed as well as further dielectric properties of the high-temperature-pressure phase.Paper presented at the Third Workshop on Subsecond Thermophysics, September 17–18, 1992, Graz, Austria.     

Simultaneous optimization of artificial neural networks for financial forecasting

Artificial neural networks (ANNs) have been popularly applied for stock market prediction, since they offer superlative learning ability. However, they often result in inconsistent and unpredictable performance in the prediction of noisy financial data due to the problems of determining factors involved in design. Prior studies have suggested genetic algorithm (GA) to mitigate the problems, but most of them are designed to optimize only one or two architectural factors of ANN. With this background, the paper presents a global optimization approach of ANN to predict the stock price index. In this study, GA optimizes multiple architectural factors and feature transformations of ANN to relieve the limitations of the conventional backpropagation algorithm synergistically. Experiments show our proposed model outperforms conventional approaches in the prediction of the stock price index.     

Air conditioner operation behaviour based on students' skin temperature in a classroom

A total of 25 college students participated in a study to determine when they would use an air conditioner during a lecture in a university classroom. The ambient temperature and relative humidity were measured 75 cm above the floor every minute. Skin temperatures were measured every minute at seven points, according to the recommendation of Hardy and Dubois. The average clothing insulation value (CLO) of subjects was 0.53 ± 0.07 CLO. The mean air velocity in the classroom was 0.13 ± 0.028 m/s. When the subjects turned the air conditioner both on and off, the average ambient temperatures, relative humidity and mean skin temperatures were 27.4 and 23.7 °C (p = 0.000), 40.9 and 40.0% (p = 0.528) and 32.7 and 32.2 °C (p = 0.024), respectively. When the status of the air conditioner was changed, the differences of skin temperatures in core body parts (head, abdomen and thigh) were not statistically significant. However, in the extremities (mid-lower arm, hand, shin and instep), the differences were statistically significant. Subjects preferred a fluctuating environment to a constant temperature condition. We found that a changing environment does not affect classroom study.     

Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting

This study considers real estate appraisal forecasting problem. While there is a great deal of literature about use of artificial intelligence and multiple linear regression for the problem, there has been always controversy about which one performs better. Noting that this controversy is due to difficulty finding proper predictor variables in real estate appraisal, we propose a modified version of ridge regression, i.e., ridge regression coupled with genetic algorithm (GA-Ridge). In order to examine the performance of the proposed method, experimental study is done for Korean real estate market, which verifies that GA-Ridge is effective in forecasting real estate appraisal. This study addresses two critical issues regarding the use of ridge regression, i.e., when to use it and how to improve it.     

Dynamic deformation behavior of ultrafine-grained low-carbon steels fabricated by equal-channel angular pressing

The dynamic deformation behavior of ultrafine-grained low-carbon steels fabricated by equal-channel angular pressing (ECAP) was investigated in this study. Dynamic torsional tests, using a torsional Kolsky bar, were conducted on four steel specimens, two of which were annealed at 480 °C after ECAP, and then the test data were compared in terms of microstructures, tensile properties, and adiabatic shear-band formation. The equal-channel angular pressed specimen consisted of very fine, equiaxed grains of 0.2 to 0.3 μm in size, which were slightly coarsened after annealing. The dynamic torsional test results indicated that maximum shear stress decreased with increasing annealing time, whereas fracture shear strain increased. Some adiabatic shear bands were observed at the gage center of the dynamically deformed torsional specimen. Their width was smaller in the equal-channel angular pressed specimen than in the 1-hour-annealed specimen, but they were not found in the 24-hour-annealed specimen. Ultrafine, equiaxed grains of 0.05 to 0.2 μm in size were formed inside the adiabatic shear band, and their boundaries had characteristics of high-angle grain boundaries. These phenomena were explained by dynamic recrystallization due to a highly localized plastic strain and temperature rise during dynamic deformation.