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     

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.     

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.     

A time-domain approach to transmission network equivalents viaProny analysis for electromagnetic transients analysis

This paper presents a method of obtaining transmission network equivalents from the network's response to a pulse excitation signal. The proposed method is based on modal decomposition representation for the large-scale interconnected system. In this framework we use Prony analysis to identify the network function of the system and to decompose the large system into a parallel combination of simple first-order systems. As a result the network function of the transmission network can be identified easily, and a Thevenin-type of discrete-time filter model can be generated. It can reproduce the driving-point impedance characteristic of the network. Furthermore, the proposed model can be implemented into the EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement     

Reliability and performance analysis of time – space – time switching networks with multiple separated space switches

Since electronic switching systems usually require very strict reliability requirements as well as good performance objectives, we need to jointly analyse the performance and reliability of switching systems. In this paper, we compare conventional time–space–time switches with single space switches with those with multiple separated space switches, from the viewpoints of reliability and performance. We consider time–space–time switching networks which consist of N incoming time switches, i.e. one NxN space switch, two (N/2)x(N/2) space switches, and four (N/4)x(N/4) space switches. We introduce a Markov reliability model to study the effect of failures and analyse the reliability and performance of three different types of switching networks in terms of average blocking probability and the mean time to unreliable operation, as we vary the offered traffic. As a result, T–S–T switching networks with multiple separated space switches exhibit better performance and reliability than those with single space switches.     

Self-aligned offset gated poly-Si TFTs with a floating sub-gate

We have fabricated a self-aligned offset-gated poly-Si thin film transistor (TFT) by employing a novel photoresist reflow process. The gate structure of the new device is consisted of two unique patterns: A main-gate and a sub-gate. The new fabrication method extends the gate-oxide over the offset region. With the assistance of the sub-gate and reflowed photoresist a self-aligned offset region is successfully obtained due to the offset oxide acting as an implantation mask. The poly-Si TFT with symmetrical offsets is easily fabricated and the new method does not require any additional offset mask step. Compared with the misaligned offset gated poly-Si TFTs, excellent symmetric electrical characteristics are obtained     

Modified atmosphere packaging of a mixed prepared vegetable salad dish

The aim of this study was to design a modified atmosphere package for a mixed vegetable salad consisting of 75 g of cut carrot, 55 g of cut cucumber, 20 g of sliced garlic and 50 g of whole green pepper. Respiration data of all the components were combined with film permeability data to predict package atmospheres and design optimal packages for experimental testing for improved shelf-life of the produce. The optimal package avoided minimum O₂ and maximum CO₂ tolerance limits, and chilling injury temperatures for any component. A pouch form package made of 27 mm low density polyethylene developed a modified atmosphere of 2.0–2.1% O₂ and 5.5–5.7% CO₂, which was beneficial for all components and provided better quality retention than other test packages.     

A neural network-based power system stabilizer using power flowcharacteristics

A neural network-based power system stabilizer (neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The use of power flow dynamics provides a PSS for a wide range of operation with reduced size neural networks. The neuro-PSS consists of two neural networks: neuro-identifier and neuro-controller. The low-frequency oscillation is modeled by the neuro-identifier using the power flow dynamics, then a generalized backpropagation-through-time (GBTT) algorithm is developed to train the neuro-controller. The simulation results show that the neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS     

Formation of C4 species in the deactivation of a Pd/SiO2 catalyst during the selective hydrogenation of acetylene

The deactivation characteristics of Pd/SiO₂ in the selective hydrogenation of acetylene were correlated with changes in the amount of the C4 species produced. The amounts of butenes produced changed in parallel with the catalyst activity, indicating that the rate limiting step for butene production was the same as that for acetylene hydrogenation. On the other hand, the amount of 1,3-butadiene produced changed, showing a maximum with catalyst deactivation because 1,3-butadiene is an intermediate in the sequential reaction process which involves both the production and consumption of 1,3-butadiene. This was verified by a simultaneous TG/reaction experiment showing that 1,3-butadiene was a precursor of green oil. The catalyst showed a self-regenerative behavior in its activity and the amounts of C4 species produced during the early stage of deactivation because two opposite factors, which contributed to either the lowering or the promotion of activity, were involved in the process. A specific type of polymer species, produced during the initial period of deactivation, is proposed to be responsible for the promotion of catalyst activity.