Automatic Authentication of Handwritten Documents via Low Density Pixel Measurements

We introduce an effective approach for automatic offline au- thentication of handwritten samples where the forgeries are skillfully done, i.e., the true and forgery sample appearances are almost alike. Subtle details of temporal information used in online verification are not available offline and are also hard to recover robustly. Thus the spatial dynamic information like the pen-tip pressure characteristics are considered, emphasizing on the extraction of low density pixels. The points result from the ballistic rhythm of a genuine signature which a forgery, however skillful that may be, always lacks. Ten effective features, including these low density points and den- sity ratio, are proposed to make the distinction between a true and a forgery sample. An adaptive decision criteria is also derived for better verification judgements.

Validation of Reverse Engineered Web Application Models

Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.

Optimal Conditions for Carotenoid Production and Antioxidation Characteristics by Rhodotorula rubra

This study aims to screen out and to optimize the major nutrients for maximum carotenoid production and antioxidation characteristics by Rhodotorula rubra. It was found that supplementary of 10 g/l glucose as carbon source, 1 g/l ammonium sulfate as nitrogen source and 1 g/l yeast extract as growth factor in the medium provided the better yield of carotenoid content of 30.39 μg/g cell dry weight the amount of antioxidation of Rhodotorula rubra by DPPH, ABTS and MDA method were 1.463%, 34.21% and 34.09 μmol/l, respectively.

Finite Element Investigation of Transmission Conditions for Non-Monotonic Temperature Interphases

Imperfect transmission conditions modeling a thin reactive 2D interphases layer between two dissimilar bonded strips have been extracted. In this paper, the soundness of these transmission conditions for heat conduction problems are examined by the finite element method for a strong temperature-dependent source or sink and non-monotonic temperature distributions around the faces..

Redundancy in Steel Frames with Masonry Infill Walls

Structural redundancy is an interesting point in seismic design of structures. Initially, the structural redundancy is described as indeterminate degree of a system. Although many definitions are presented for redundancy in structures, recently the definition of structural redundancy has been related to the configuration of structural system and the number of lateral load transferring directions in the structure. The steel frames with infill walls are general systems in the constructing of usual residential buildings in some countries. It is obviously declared that the performance of structures will be affected by adding masonry infill walls. In order to investigate the effect of infill walls on the redundancy of the steel frame which constructed with masonry walls, the components of redundancy including redundancy variation index, redundancy strength index and redundancy response modification factor were extracted for the frames with masonry infills. Several steel frames with typical storey number and various numbers of bays were designed and considered. The redundancy of frames with and without infill walls was evaluated by proposed method. The results showed the presence of infill causes increase of redundancy.

A Feature-based Invariant Watermarking Scheme Using Zernike Moments

In this paper, a novel feature-based image watermarking scheme is proposed. Zernike moments which have invariance properties are adopted in the scheme. In the proposed scheme, feature points are first extracted from host image and several circular patches centered on these points are generated. The patches are used as carriers of watermark information because they can be regenerated to locate watermark embedding positions even when watermarked images are severely distorted. Zernike transform is then applied to the patches to calculate local Zernike moments. Dither modulation is adopted to quantize the magnitudes of the Zernike moments followed by false alarm analysis. Experimental results show that quality degradation of watermarked image is visually transparent. The proposed scheme is very robust against image processing operations and geometric attacks.

Towards Automatic Recognition and Grading of Ganoderma Infection Pattern Using Fuzzy Systems

This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.

Artificial Neural Networks Application to Improve Shunt Active Power Filter

Active Power Filters (APFs) are today the most widely used systems to eliminate harmonics compensate power factor and correct unbalanced problems in industrial power plants. We propose to improve the performances of conventional APFs by using artificial neural networks (ANNs) for harmonics estimation. This new method combines both the strategies for extracting the three-phase reference currents for active power filters and DC link voltage control method. The ANNs learning capabilities to adaptively choose the power system parameters for both to compute the reference currents and to recharge the capacitor value requested by VDC voltage in order to ensure suitable transit of powers to supply the inverter. To investigate the performance of this identification method, the study has been accomplished using simulation with the MATLAB Simulink Power System Toolbox. The simulation study results of the new (SAPF) identification technique compared to other similar methods are found quite satisfactory by assuring good filtering characteristics and high system stability.

A Metametadata Architecture forPedagogic Data Description

This paper focuses on a novel method for semantic searching and retrieval of information about learning materials. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. A novel metametadata taxonomy has been developed which provides the basis for a semantic search engine to extract, match and map queries to retrieve relevant results. The use of ontological views is a foundation for viewing the pedagogical content of metadata extracted from learning objects by using the pedagogical attributes from the metametadata taxonomy. Using the ontological approach and metametadata (based on the metametadata taxonomy) we present a novel semantic searching mechanism.These three strands – the taxonomy, the ontological views, and the search algorithm – are incorporated into a novel architecture (OMESCOD) which has been implemented.

A Serial Hierarchical Support Vector Machine and 2D Feature Sets Act for Brain DTI Segmentation

Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.

Salient Points Reduction for Content-Based Image Retrieval

Salient points are frequently used to represent local properties of the image in content-based image retrieval. In this paper, we present a reduction algorithm that extracts the local most salient points such that they not only give a satisfying representation of an image, but also make the image retrieval process efficiently. This algorithm recursively reduces the continuous point set by their corresponding saliency values under a top-down approach. The resulting salient points are evaluated with an image retrieval system using Hausdoff distance. In this experiment, it shows that our method is robust and the extracted salient points provide better retrieval performance comparing with other point detectors.

Effect of White Kwao Extract (Pueraria mirifica) on in vitro Development and Implantation Rate of Mouse Embryo

The White Kwao (Pueraria mirifica), a potent phytoestrogenic medicinal plant, has long been use in Thailand as a traditional folkmedicine. However, no scientific information of the direct effect of White Kwao on the development of mammalian embryo was available. Therefore, the purpose of this study was to investigate the effect of White Kwao extract on the in vitro development and implantation rate of mouse embryos. This study was designed into two experiments. In the first experiment, the two-cell stage mouse embryos were collected from the oviduct of superovulated mature female mice, and randomly cultured in three different media, the M16, M16 supplemented with 0.52μg esthinylestradiol-17β, and M16 supplemented with 10 mg/ml White Kwao extract. The culture was incubated in CO2 incubator at 37 oC . After the embryos were cultivated, the developments of embryos were observed every 24 hours for 5 days. The development rate of embryos from the two-cell stage to blastocyst stage in the media was with White Kwao was significantly higher (p

Effects of Late Sowing on Quality of Coriander (Coriandrum sativum L.)

Coriander is an annual and herbaceous plant, belong to the apiaceae family. This plant is cultivated world widely. It is well known for having medicinal properties. The aim of this experiment was to study seed quality of species grown in Kermanshah conditions. The experiment was carried out in research farm, Campus of Agriculture and Natural Resources, Razi University, Kermanshah, Iran. Coriander (local type) was grown in late spring May (5th and 20th) and Jun (4th and 19th), and plant density (10, 30, 50 and 70 plants m-2) in 2009. The experimental plots were laid out in a factorial according to a randomized complete block design with three replications. The fruits were harvest between 83.5 – 106.5 days after sowing. The essential oil and oil content was extracted by Clevenger and Soxhlet apparatuses, respectively. Results showed that delay at planting date increased the oil content. Also, with the increase at plant density was decreased oil content and essential oil.

LSGENSYS - An Integrated System for Pattern Recognition and Summarisation

This paper presents a new system developed in Java® for pattern recognition and pattern summarisation in multi-band (RGB) satellite images. The system design is described in some detail. Results of testing the system to analyse and summarise patterns in SPOT MS images and LANDSAT images are also discussed.

The Effect of Complementary Irrigation in Different Growth Stages on Yield, Qualitative and Quantitative Indices of the Two Wheat (Triticum aestivum L.) Cultivars in Mazandaran

In most wheat growing moderate regions and especially in the north of Iran climate, is affected grain filling by several physical and abiotic stresses. In this region, grain filling often occurs when temperatures are increasing and moisture supply is decreasing. The experiment was designed in RCBD with split plot arrangements with four replications. Four irrigation treatments included (I0) no irrigation (check); (I1) one irrigation (50 mm) at heading stage; (I2) two irrigation (100 mm) at heading and anthesis stage; and (I3) three irrigation (150 mm) at heading, anthesis and early grain filling growth stage, two wheat cultivars (Milan and Shanghai) were cultured in the experiment. Totally raining was 453 mm during the growth season. The result indicated that biological yield, grain yield and harvest index were significantly affected by irrigation levels. I3 treatment produced more tillers number in m2, fertile tillers number in m2, harvest index and biological yield. Milan produced more tillers number in m2, fertile tillers in m2, while Shanghai produced heavier tillers and grain 1000 weight. Plant height was significant in wheat varieties while were not statistically significant in irrigation levels. Milan produced more grain yield, harvest index and biological yield. Grain yield shown that I1, I2, and I3 produced increasing of 5228 (21%), 5460 (27%) and 5670 (29%) kg ha-1, respectively. There was an interaction of irrigation and cultivar on grain yields. In the absence of the irrigation reduced grain 1000 weight from 45 to 40 g. No irrigation reduced soil moisture extraction during the grain filling stage. Current assimilation as a source of carbon for grain filling depends on the light intercepting viable green surfaces of the plant after anthesis that due to natural senescence and the effect of various stresses. At the same time the demand by the growing grain is increasing. It is concluded from research work that wheat crop irrigated Milan cultivar could increase the grain yield in comparison with Shanghai cultivar. Although, the grain yield of Shanghai under irrigation was slightly lower than Milan. This grain yield also was related to weather condition, sowing date, plant density and location conditions and management of fertilizers, because there was not significant difference in biological and straw yield. The best result was produced by I1 treatment. I2 and I3 treatments were not significantly difference with I1 treatment. Grain yield of I1 indicated that wheat is under soil moisture deficiency. Therefore, I1 irrigation was better than I0.

Analysis of DNA Microarray Data using Association Rules: A Selective Study

DNA microarrays allow the measurement of expression levels for a large number of genes, perhaps all genes of an organism, within a number of different experimental samples. It is very much important to extract biologically meaningful information from this huge amount of expression data to know the current state of the cell because most cellular processes are regulated by changes in gene expression. Association rule mining techniques are helpful to find association relationship between genes. Numerous association rule mining algorithms have been developed to analyze and associate this huge amount of gene expression data. This paper focuses on some of the popular association rule mining algorithms developed to analyze gene expression data.

Classification of Radio Communication Signals using Fuzzy Logic

Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.

Information Extraction from Unstructured and Ungrammatical Data Sources for Semantic Annotation

The internet has become an attractive avenue for global e-business, e-learning, knowledge sharing, etc. Due to continuous increase in the volume of web content, it is not practically possible for a user to extract information by browsing and integrating data from a huge amount of web sources retrieved by the existing search engines. The semantic web technology enables advancement in information extraction by providing a suite of tools to integrate data from different sources. To take full advantage of semantic web, it is necessary to annotate existing web pages into semantic web pages. This research develops a tool, named OWIE (Ontology-based Web Information Extraction), for semantic web annotation using domain specific ontologies. The tool automatically extracts information from html pages with the help of pre-defined ontologies and gives them semantic representation. Two case studies have been conducted to analyze the accuracy of OWIE.

3D Face Recognition Using Modified PCA Methods

In this paper we present an approach for 3D face recognition based on extracting principal components of range images by utilizing modified PCA methods namely 2DPCA and bidirectional 2DPCA also known as (2D) 2 PCA.A preprocessing stage was implemented on the images to smooth them using median and Gaussian filtering. In the normalization stage we locate the nose tip to lay it at the center of images then crop each image to a standard size of 100*100. In the face recognition stage we extract the principal component of each image using both 2DPCA and (2D) 2 PCA. Finally, we use Euclidean distance to measure the minimum distance between a given test image to the training images in the database. We also compare the result of using both methods. The best result achieved by experiments on a public face database shows that 83.3 percent is the rate of face recognition for a random facial expression.

Fast Facial Feature Extraction and Matching with Artificial Face Models

Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.