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.     

A Nonvolatile Organic Memory Device Using ITO Surfaces Modified by Ag‐Nanodots

We report on a single‐layer organic memory device made of poly(N‐vinylcarbazole) embedded between an Al electrode and ITO modified with Ag nanodots (Ag‐NDs). Devices exhibit high ON/OFF switching ratios of 10⁴. This level of performance could be achieved by modifying the ITO electrodes with some Ag‐NDs that act as trapping sites, reducing the current in the OFF state. Temperature dependence of the electrical characteristics suggest that the current of the low‐resistance state can be attributed to Schottky charge tunnelling through low‐resistance pathways of Al particles in the polymer layer and that the high‐resistance state can be controlled by charge trapping by the Al particles and Ag‐NDs.     

Synthesis of Mg-α-sialon from the mixture of silicon, aluminum and magnesia powders in a flowing nitrogen atmosphere

Synthesis of Mg-α-Sialon has been investigated by the mixture of silicon, aluminum and magnesia powders in a flowing nitrogen atmosphere in the range of 1300–1600 °C, when Mg-α-Sialon is designed with a chemical formulation of Mg _x Si_12−3x Al_3x O _x N_16−x in present work. The results showed that Mg-α-sialon initially occurred at 1400 °C and basically increased with elevated temperatures. For the samples of x = 0.6, 0.8 and 1.0 the products mainly consisted of Mg-α-Sialon with small amounts of Si, AlN and 21R AlN-polytypoid phases at 1600° C. However, in final products of x = 1.2, 1.4 and 1.6 only a little of Mg-α-Sialon formed and a great amount of Si remained in these samples at all the fired temperatures. Fortunately, the content of Mg-α-Sialon in these samples were obviously increased by adding a small amount of α-Si₃N₄ as seeds before nitridation.     

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.     

A slotted post-wall waveguide array with interdigital structure for 45/spl deg/ linear and dual polarization

This work proposes a dual-polarized planar antenna; two post-wall slotted waveguide arrays with orthogonal 45/spl deg/ linearly-polarized waves interdigitally share the aperture on a single layer substrate. Uniform excitation of the two-dimensional slot array is confirmed by experiment in the 25 GHz band. The isolation between two slot arrays is also investigated in terms of the relative displacement along the radiation waveguide axis in the interdigital structure. The isolation is 33.0 dB when the relative shift of slot position between the two arrays is -0.5/spl lambda//sub g/, while it is only 12.8 dB when there is no shift. The cross-polarization level in the far field is -25.2 dB for a -0.5/spl lambda//sub g/ shift, which is almost equal to that of the isolated single polarization array. It is degraded down to -9.6 dB when there is no shift.     

Highly ordered microstructures of poly(styrene-b-isoprene) block copolymers induced by solution meniscus

Microstructures of hundreds of micron thick poly(styrene-block-isoprene) copolymer films solution-cast in a cylindrical tube with the solvent evaporation controlled were investigated by transmission electron microscope (TEM), small angle X-ray scattering (SAXS) and optical microscope (OM). In a block copolymer with cylindrical polyisoprene microdomains, the orientation of the cylinders was varied along radial direction of the cylindrical tube. Highly aligned hexagonal arrays of in-plane polyisoprene cylinders were formed with their cylindrical axis parallel to the circumference of the tube in the regimes close to the wall edge. In contrast randomly ordered microdomains were observed at the center of the tube. We have also found that the orientation depends on the solvent evaporation rate and an intermediate rate (∼2.3 nL/s) provides the best orientation. In the case of a block copolymer with a bicontinuous double gyroid structure, we obtained a globally ordered microstructure where [111] crystallographic direction was parallel to the circumference of the tube. For both block copolymers, the area of highly ordered arrays of nanoscopic domains is over 1 mm². Development of the orientation was explained by coupling two orthogonal fields: (1) The flow of a solution induced by strong capillary force at a meniscus between the cylindrical tube wall and the block copolymer solution and (2) the solvent evaporation.