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.     

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.     

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 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     

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     

A study on the degree of deliberation and meditation of cyber poll respondents for nuclear-related decision making

Public participation is essential in each step of the nuclear-related decision-making process. Recently, the electronic systems using the Internet have become quite popular, and have emerged as a good medium for communicating with the public. In this study, a comprehensive utilization of electronic public participation was used to analyze public opinion on a given nuclear-related decision-making process. The degree of deliberation and meditation of the public participating in an electronic poll survey was evaluated, and the decision-making factors representing the personal characteristics of the poll respondents such as age, income, education, residence, degree of knowledge and concern were carefully incorporated when preparing the poll-survey questionnaire for its evaluation. Fuzzy analysis was used to assess and aggregate the responses to each decision-making factor. As a case study, this procedure was used to analyzing public opinion on the location of a low-level radioactive waste disposal facility on the campus of Seoul National University. The results show that there is a tendency of respondents who are on the negative side of the argument to be more deliberate and meditative in their decision-making process than those on the positive side. Knowledge and residence were found to be important decision-making factors.     

BioFET sensor for detection of albumin in urine

Characterisation of a BioFET for detection of albumin in a mixture of human urine is presented. To avoid electrolyte effect of the urine, it was measured in PBS (phosphate buffer saline) at a fixed pH after albumin binding. The drain current was modulated by the albumin bound to the anti-albumin immobilised on the gate surface of the BioFET. The current variation ratio was likely to be proportional to the concentration of the albumin in the range 50-250 mg/1. The results show the feasibility of the BioFET as a urinary albumin sensor.