Mode Matching Analysis of a Tapered Coaxial Tip in a Parallel-Plate Waveguide

A tapered coaxial tip in a parallel plate waveguide is investigated. A boundary-value problem of electromagnetic scattering from a tapered coaxial monopole is solved rigorously based on the Fourier transform, eigenfunction expansion, and mode matching. Scattering parameters are represented in a series and computed to understand the behavior of the scattering in terms of the coaxial tip geometry.     

A robust algorithm for text region detection in natural scene images

In this paper, a new method for detecting text regions in natural scene images is presented. The proposed algorithm is based on the segmentation of objects in a scene, followed by the identification of text objects by a support vector machine (SVM). First, to segment objects in the scene, the input image is separated into chromatic and achromatic regions according to the distribution of red, green and blue (RGB) elements, and different clustering algorithms are applied. Second, each object is transformed into the wavelet domain for multi-resolution analysis, and moment features of the wavelet coefficients are used in the SVM for the classification of text objects. The proposed approach provides robustness to non-uniform illumination by using different clustering algorithms according to the characteristics of the colour components in the segmentation. Also, moment features, used for classification, are invariant to the size, direction, shape and other properties of texts. Experimental results demonstrate the effectiveness of this approach.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

Simultaneous degradation of nitroaromatic compounds TNT,RDX, atrazine,and simazine by Pseudomonas putida HK‐6 in bench‐scale bioreactors

BACKGROUND: Environmental contamination by nitroaromatic compounds such as 2,4,6‐trinitrotoluene (TNT), hexahydro‐1,3,5‐trinitro‐1,3,5‐s‐triazine (RDX), atrazine, and/or simazine (TRAS) generated as waste from military and agricultural activities is a serious worldwide problem. Microbiological treatment of these compounds is an attractive method because many explosives and herbicides are biodegradable and the process can be made cost‐effective. We explored the feasibility of using cultures of Pseudomonas putida HK‐6 for simultaneous degradation of TRAS with the aim of microbial application in wastewater treatment in bench‐scale bioreactors. RESULTS: Experiments were conducted to study the effects of supplemental carbons, nitrogens, and Tween‐80 on the degradation of Ps. putida HK‐6 in media containing TRAS as target substrate(s). The most effective TRAS degradation was shown in the presence of molasses. Addition of nitrogen sources produced a delayed effect for the target substrate(s). Tween‐80 enhanced the degradation of target substrate(s). Simultaneous degradation of these compounds proceeded to completion within the given period. CONCLUSIONS: Ps. putida HK‐6 was capable of growth with TRAS, and the effects of supplements on TRAS degradation and simultaneous TRAS degradation were evaluated in bench‐scale bioreactors. The results of this study have practical applications in the processes of industrial waste stream treatment where the disposal of TRAS may be problematic. Copyright © 2008 Society of Chemical Industry     

Online and Offline Rotary Regression Analysis of Torque Estimator for Switched Reluctance Motor Drives

A new torque estimator for switched reluctance motor (SRM) drives based on 2-D rotary regression analysis is presented in this paper. The proposed torque estimator is composed of a bicubic regressive polynomial as a function of rotor position and input current. The regressive coefficients can be computed offline or online from the torque characteristics acquired either experimentally or from numerical computation. Furthermore, a torque estimation method by taking mutual coupling into consideration is proposed. It can be seen that the estimated and experimentally obtained self-coupling and mutual-coupling torque characteristics are in good agreement with each other. In addition, the dynamic torque waveforms with and without the mutual coupling, estimated by the proposed estimator, are found to be virtually the same as those obtained from the bicubic spline interpolation for SRM drives with single-pulse voltage, hysteresis current chopping, as well as with voltage pulse width modulation control. The success of all the case studies being reported is a good validation of the usefulness and accuracy of the proposed real-time torque estimator that, as described in this paper, can be used to quickly estimate the instantaneous output torque of SRM drives.     

Complementary effects of solid lubricants in the automotive brake lining

An experimental investigation was carried out to examine the tribological behavior of NAO (non-asbestos organic) type brake linings containing different volume ratios of graphite and antimony trisulfide (Sb₂S₃). A scale dynamometer was used for friction tests and particular emphases were given to the effect of applied pressure, sliding speed, and temperature on the coefficient of friction according to the relative amounts of the two solid lubricants. Results showed that the brake linings with both solid lubricants exhibited better friction stability and less speed sensitivity than the friction materials containing a single solid lubricant. In particular, the brake lining containing higher concentrations of graphite showed better fade resistance than others during high-temperature friction test.     

Recrystallization of phenylbutazone using supercritical fluid antisolvent process

Phenylbutazone was recrystallized from its solutions by using a supercritical fluid antisolvent process. It was dissolved in acetone and supercritical carbon dioxide was injected into the solution, thereby inducing supersaturation and particle formation. Variation in the physical properties of the recrystallized phenylbutazone was investigated as a function of the crystallizing temperature and the carbon dioxide injection rate. The recrystallized particles showed cleaner surfaces and more ordered morphology compared to the particles obtained by other methods such as solvent evaporation. X-ray diffraction patterns indicated that the crystallinity of the particles had been modified upon the recrystallization. Differential scanning calorimetry measurement revealed that the crystallizing temperature influenced the thermal stability of the resulting crystals. Larger crystals were produced when the carbon dioxide injection rate was reduced.     

Learning user preferences of route choice behaviour for adaptive route guidance

As the use of navigation systems becomes more widespread, the demand for advanced functions of navigation systems also increases. In the light of user satisfaction, personalisation of route guidance by incorporating user preferences is one of the most desired features. A user model applied to personalised route guidance is presented. The user model adaptively updates route selection rules when it discovers the predicted choice differs from the actual choice of the driver. This study employs a decision tree learning algorithm, the C4.5 algorithm, which has advantages over other data mining methods in terms of its comprehensible model structure. Simulation experiments with a real-world network were conducted to analyse the applicability of the model to adaptive route guidance and the accuracy of its prediction     

The evolving patterns of inter-industrial knowledge structure: Case of Korean manufacturing in the 1980s

The notion of knowledge-based economy premises that technological knowledge be created, accumulated and disseminated through the interactive learning among principal actors in the national system. This paper analyzes, from a dynamic perspective, the structure of inter-industrial technological knowledge. Both human-driven disembodied channel and capital-driven embodied channel are investigated based on network analysis. The set of empirical data covers the Korean manufacturing sector during the 1980s. Overall, density of network tends to be increasing over time, implying that knowledge network becomes expanded and intensified. A number of distinctive features are identified between knowledge types and industrial categories. The findings in turn render important policy implications that should be addressed when developing technology policy. Clearly, the policy framework needs to be industry-specific and country-specific in accordance with the development stage and industrial structure of reference time. This revised version was published online in August 2006 with corrections to the Cover Date.     

Using classification techniques for informal requirements in the requirements analysis-supporting system

In order to efficiently develop large-scale and complicated software, it is important for system engineers to correctly understand users’ requirements. Most requirements in large-scale projects are collected from various stakeholders located in various regions, and they are generally written in natural language. Therefore, the initial collected requirements must be classified into various topics prior to analysis phases in order to be usable as input in several requirements analysis methods. If this classification process is manually done by analysts, it becomes a time-consuming task. To solve this problem, we propose a new bootstrapping method which can automatically classify requirements sentences into each topic category using only topic words as the representative of the analysts’ views. The proposed method is verified through experiments using two requirements data sets: one written in English and the other in Korean. The significant performances were achieved in the experiments: the 84.28 and 87.91 F1 scores for the English and Korean data sets, respectively. As a result, the proposed method can provide an effective function for an Internet-based requirements analysis-supporting system so as to efficiently gather and analyze requirements from various and distributed stakeholders by using the Internet.