Search results for: off-line g-ray spectroscopy

Authors: Hanan Alenezi

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Membrane performance depends on the kind of solvent used in preparation. A membrane made by Polyetherimide (PEI) was evaluated for gas separation using X-Ray Diffraction (XRD), Scanning electron microscope (SEM), and Energy Dispersive X-Ray Spectroscopy (EDS). The purity and the thickness are detected to evaluate the membrane in order to optimize PEI membrane preparation.

Keywords: Energy Dispersive X-Ray Spectroscopy, EDS, membrane, Polyetherimide, PEI, Scanning electron microscope, SEM, Solvent, X-Ray Diffraction, XRD.

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Authors: Mehmet Tahir Sandıkkaya, Bülent Örencik

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Many electronic voting systems, classified mainly as homomorphic cryptography based, mix-net based and blind signature based, appear after the eighties when zero knowledge proofs were introduced. The common ground for all these three systems is that none of them works without real time cryptologic calculations that should be held on a server. As far as known, the agent-based approach has not been used in a secure electronic voting system. In this study, an agent-based electronic voting schema, which does not contain real time calculations on the server side, is proposed. Conventional cryptologic methods are used in the proposed schema and some of the requirements of an electronic voting system are constructed within the schema. The schema seems quite secure if the used cryptologic methods and agents are secure. In this paper, proposed schema will be explained and compared with already known electronic voting systems.

Keywords: Electronic voting, E-voting, Mobile softwareagents, Offline electronic voting.

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: Impersonation, image registration, incrimination, object detection, threshold evaluation.

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Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani

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We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.

Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.

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Authors: A. Baloğlu, A. Çınar

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Different tools and technologies were implemented for Crisis Response and Management (CRM) which is generally using available network infrastructure for information exchange. Depending on type of disaster or crisis, network infrastructure could be affected and it could not be able to provide reliable connectivity. Thus any tool or technology that depends on the connectivity could not be able to fulfill its functionalities. As a solution, a new message exchange framework has been developed. Framework provides offline/online information exchange platform for CRM Information Systems (CRMIS) and it uses XML compression and packet prioritization algorithms and is based on open source web technologies. By introducing offline capabilities to the web technologies, framework will be able to perform message exchange on unreliable networks. The experiments done on the simulation environment provide promising results on low bandwidth networks (56kbps and 28.8 kbps) with up to 50% packet loss and the solution is to successfully transfer all the information on these low quality networks where the traditional 2 and 3 tier applications failed.

Keywords: Crisis Response and Management, XML Messaging, Web Services, XML compression, Mining.

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Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma, Hirendra Das

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Signature represents an individual characteristic of a person which can be used for his / her validation. For such application proper modeling is essential. Here we propose an offline signature recognition and verification scheme which is based on extraction of several features including one hybrid set from the input signature and compare them with the already trained forms. Feature points are classified using statistical parameters like mean and variance. The scanned signature is normalized in slant using a very simple algorithm with an intention to make the system robust which is found to be very helpful. The slant correction is further aided by the use of an Artificial Neural Network (ANN). The suggested scheme discriminates between originals and forged signatures from simple and random forgeries. The primary objective is to reduce the two crucial parameters-False Acceptance Rate (FAR) and False Rejection Rate (FRR) with lesser training time with an intension to make the system dynamic using a cluster of ANNs forming a multiple classifier system.

Keywords: offline, algorithm, FAR, FRR, ANN.

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Authors: A. Deręgowska, J. Depciuch, R. Wojnarowska, J. Polit, D. Broda, H. Nechai, M. Gonchar, and E. Sheregii

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16-Mercaptohexadecanoic acid (MHDA) and tripeptide glutathione conjugated with gold nanoparticles (Au-NPs) are characterized by Fourier Transform InfaRared (FTIR) spectroscopy combined with Surface-enhanced Raman scattering (SERS) spectroscopy. Surface Plasmon Resonance (SPR) technique based on FTIR spectroscopy has become an important tool in biophysics, which is perspective for the study of organic compounds. FTIR-spectra of MHDA shows the line at 2500 cm-1 attributed to thiol group which is modified by presence of Au-NPs, suggesting the formation of bond between thiol group and gold. We also can observe the peaks originate from characteristic chemical group. A Raman spectrum of the same sample is also promising. Our preliminary experiments confirm that SERS-effect takes place for MHDA connected with Au-NPs and enable us to detected small number (less than 106 cm-2) of MHDA molecules. Combination of spectroscopy methods: FTIR and SERS – enable to study optical properties of Au- NPs and immobilized bio-molecules in context of a bio-nano-sensors.

Keywords: Glutathione; gold nanoparticles, Fourier transform infrared spectroscopy, MHDA, surface-enhanced Raman scattering.

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Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

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In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are class balancing, data shuffling, and standardization, were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the sequential model and ReLU activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: Spectroscopy, soluble solid content, pineapple, neural network.

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Authors: Nazli Darkhal

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The use of gems and ornaments has been common in Iran since the beginning of history. The prosperity of the country, the wealth, and the interest of the people of this land in a luxurious and glorious life, combined with beauty, have always attracted the attention of Iranian people to gems and jewelry. Iranians are famous in the world for having a long history of collecting and recognizing precious stones. In this case, we can use the unique treasure of national jewelry. Raman spectroscopy method is one of the oscillating spectroscopy methods that is classified in the group of nondestructive study methods, and like other methods, in addition to several advantages, it also has disadvantages and problems. Micro Raman spectroscopy is one of the different types of Raman spectroscopy in which an optical microscope is combined with a Raman device to provide more capabilities and advantages than its original method. In this way, with the help of Raman spectroscopy and a light microscope, while observing more details from different parts of the historical sample, natural or artificial pigments can be identified in a small part of it. The EDX (Energy Dispersive X ray) electron microscope also functions as the basis for the interaction of the electron beam with the matter. The beams emitted from this interaction can be used to examine samples. In this article, in addition to introducing the micro-Raman spectroscopy method, studies have been conducted on the structure of three samples of existing stones in the historic citadel of Bam. Using this method of study on precious and semi-precious stones, in addition to requiring a short time, can provide us with complete information about the structure and theme of these samples. The results of experiments and gemology of the stones showed that the selected beads are agate and jasper, and they can be placed in the chalcedony group.

Keywords: Bam citadel, precious stones, semi-precious stones, Raman spectroscopy, scanning electron microscope.

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Authors: Kamaldeep Joshi, Rajkumar Yadav, Ashok Kumar Yadav

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Digital Watermarking is a procedure to prevent the unauthorized access and modification of personal data. It assures that the communication between two parties remains secure and their communication should be undetected. This paper investigates the consequence of the watermark strength of the grayscale image using a Discrete Wavelet Transformation (DWT) additive technique. In this method, the gray scale host image is divided into four sub bands: LL (Low-Low), HL (High-Low), LH (Low-High), HH (High-High) and the watermark is inserted in an LL sub band using DWT technique. As the image is divided into four sub bands, a watermark of equal size of the LL sub band has been inserted and the results are discussed. LL represents the average component of the host image which contains the maximum information of the image. Two kinds of experiments are performed. In the first, the same watermark is embedded in different images and in the later on the strength of the watermark varies by a factor of s i.e. (s=10, 20, 30, 40, 50) and it is inserted in the same image.

Keywords: Watermarking, discrete wavelet transform, scaling factor, steganography.

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Authors: Hiren Mewada, Suprava Patnaik

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Object identification and segmentation application requires extraction of object in foreground from the background. In this paper the Bhattacharya distance based probabilistic approach is utilized with an active contour model (ACM) to segment an object from the background. In the proposed approach, the Bhattacharya histogram is calculated on non-linear structure tensor space. Based on the histogram, new formulation of active contour model is proposed to segment images. The results are tested on both color and gray images from the Berkeley image database. The experimental results show that the proposed model is applicable to both color and gray images as well as both texture images and natural images. Again in comparing to the Bhattacharya based ACM in ICA space, the proposed model is able to segment multiple object too.

Keywords: Active Contour, Bhattacharya Histogram, Structure tensor, Image segmentation.

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Authors: D. Karthikeyan, G. Balakrishnan

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Human faces, as important visual signals, express a significant amount of nonverbal info for usage in human-to-human communication. Age, specifically, is more significant among these properties. Human age estimation using facial image analysis as an automated method which has numerous potential real‐world applications. In this paper, an automated age estimation framework is presented. Support Vector Regression (SVR) strategy is utilized to investigate age prediction. This paper depicts a feature extraction taking into account Gray Level Co-occurrence Matrix (GLCM), which can be utilized for robust face recognition framework. It applies GLCM operation to remove the face's features images and Active Appearance Models (AAMs) to assess the human age based on image. A fused feature technique and SVR with GA optimization are proposed to lessen the error in age estimation.

Keywords: Support vector regression, feature extraction, gray level co-occurrence matrix, active appearance models.

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Authors: Arafet Bouaicha, Hatem Allegui, Amar Rouane, El-Hassane Aglzim, Abdelkader Mami

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In order to further understand the behavior of PEM fuel cell and optimize their performance, it is necessary to perform measurements in real time. The internal impedance measurement by electrochemical impedance spectroscopy (EIS) is of great importance. In this work, we present the impedance measurement method of a PEM fuel cell by electrochemical impedance spectroscopy method and the realization steps of electronic load for this measuring technique implementation. The theoretical results are obtained from the simulation of software PSPICE® and experimental tests are carried out using the Ballard Nexa™ PEM fuel cell system.

Keywords: Electronic load, MOS transistor, PEM fuel cell, Impedance measurement, Electrochemical Impedance Spectroscopy (EIS).

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Authors: Hamed Masoumi, Seyed Mohsen Safavi, Zahra Khani

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In this paper, an automated system is presented for identification and separation of plastic resins based on near infrared (NIR) reflectance spectroscopy. For identification and separation among resins, a "Two-Filter" identification method is proposed that is capable to distinguish among polyethylene terephthalate (PET), high density polyethylene (HDPE), polyvinyl chloride (PVC), polypropylene (PP) and polystyrene (PS). Through surveying effects of parameters such as surface contamination, sample thickness, label and cap existence, it was obvious that the "Two-Filter" method has a high efficiency in identification of resins. It is shown that accurate identification and separation of five major resins can be obtained through calculating the relative reflectance at two wavelengths in the NIR region.

Keywords: Identification, Near Infrared, Plastic, Separation, Spectroscopy

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Authors: Abraham Varghese, Kannan Balakrishnan, Reji R. Varghese, Joseph S. Paul

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Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.

Keywords: Local Binary pattern (LBP), Modified Local Binary pattern (MOD-LBP), T1 and T2 weighted images, Moment features.

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Authors: S. K. Aruna, S. Chitra

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This research paper presents a framework for classifying Magnetic Resonance Imaging (MRI) images for Dementia. Dementia, an age-related cognitive decline is indicated by degeneration of cortical and sub-cortical structures. Characterizing morphological changes helps understand disease development and contributes to early prediction and prevention of the disease. Modelling, that captures the brain’s structural variability and which is valid in disease classification and interpretation is very challenging. Features are extracted using Gabor filter with 0, 30, 60, 90 orientations and Gray Level Co-occurrence Matrix (GLCM). It is proposed to normalize and fuse the features. Independent Component Analysis (ICA) selects features. Support Vector Machine (SVM) classifier with different kernels is evaluated, for efficiency to classify dementia. This study evaluates the presented framework using MRI images from OASIS dataset for identifying dementia. Results showed that the proposed feature fusion classifier achieves higher classification accuracy.

Keywords: Magnetic resonance imaging, dementia, Gabor filter, gray level co-occurrence matrix, support vector machine.

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Authors: David Prochazka, Ľudmila Ballová, Karel Novotný, Jan Novotný, Radomír Malina, Petr Babula, Vojtěch Adam, René Kizek, Klára Procházková, Jozef Kaiser

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Here we report on the utilization of Laser-Induced Breakdown Spectroscopy (LIBS) for determination of Quantum Dots (QDs) in liquid solution. The process of optimization of experimental conditions from choosing the carrier medium to application of colloid QDs is described. The main goal was to get the best possible signal to noise ratio. The results obtained from the measurements confirmed the capability of LIBS technique for qualitative and afterwards quantitative determination of QDs in liquid solution.

Keywords: Laser-Induced Breakdown Spectroscopy, liquid analysis, nanocrystals, nanotechnology, Quantum dots.

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Authors: T. Abdallah, K. Easawi, A. Khalid, S. Negm, H. Talaat

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Nanocrystals (NC) alloyed composite CdSxSe1-x(x=0 to 1) have been prepared using the chemical solution deposition technique. The energy band gap of these alloyed nanocrystals of approximately the same size, have been determined by scanning tunneling spectroscopy (STS) technique at room temperature. The values of the energy band gap obtained directly using STS are compared to those measured by optical spectroscopy. Increasing the molar fraction ratio x from 0 to 1 causes clearly observed increase in the band gap of the alloyed composite nanocrystal. Vegard-s law was applied to calculate the parameters of the effective mass approximation (EMA) model and the dimension obtained were compared to the values measured by STM. The good agreement of the calculated and measured values is a direct result of applying Vegard's law in the nanocomposites.

Keywords: Alloy semiconductor nanocrystals, STM.

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Authors: Satish Kolli, Adriana Ferancova, David Porter, Jukka Kömi

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Electrochemical impedance spectroscopy (EIS) has been used to detect sensitization in austenitic stainless steels that are heat treated in the temperature regime 600-820 °C to produce different degrees of sensitization in the material. The tests were conducted at five different DC potentials in the transpassive region. The quantitative determination of degree of sensitization has been done using double loop electrochemical potentiokinetic reactivation tests (DL-EPR). The correlation between EIS Nyquist diagrams and DL-EPR degree of sensitization values has been studied. The EIS technique can be used as a qualitative tool in determining the intergranular corrosion in austenitic stainless steels that are heat treated at a given temperature.

Keywords: Electrochemical impedance spectroscopy, intergranular corrosion, sensitization, stainless steel.

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Authors: Tasnuva Tamanna, Aimin Yu

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Application of nanoscience in biomedical field has come across as a new era. This study involves the synthesis of nano drug carrier with antibiotic loading. Based on the founding that polydopamine (PDA) nanoparticles could be formed via self-polymerization of dopamine at alkaline pH, one-step synthesis of rifampicin coupled polydopamine (PDA-R) nanoparticles was achieved by adding rifampicin into the dopamine solution. The successful yield of PDA nanoparticles with or without the presence of rifampicin during the polymerization process was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy. Drug loading was monitored by UV-vis spectroscopy and the loading efficiency of rifampicin was calculated to be 76%. Such highly capacious nano-reservoir was found very stable with little drug leakage at pH 3.

Keywords: Drug loading, nanoparticles, polydopamine, rifampicin.

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Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: Color moments, visual thing recognition system, SIFT, color SIFT.

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Authors: K. Rugele, M. Gavare, M. Grube, K. Tihomirova, E. Skripsts, S. Larsson, J. Rubulis

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The consumption of lactose in acid cheese whey anaerobic fermentation process under fed-batch conditions was studied. During fermentation for 100 hours the biogas production (CO2 and CH4) was analyzed online. Among the standard analyses FT-IR spectroscopy was used to follow the consumption of lactose by bacteria. The absorption bands at 990, 894 and 787 cm-1 in the 2nd derivative spectra were shown to be characteristic for lactose and were used to follow the lactose conversion. It was shown that acid cheese whey lactose was converted by bacteria in first 7 hours. In the spectra of 17, 18 and 95 hour fermentation samples lactose was not identified and these results correlated with the HPLC data.

Keywords: Acid whey, anaerobic digestion, biogas, FT-IR spectroscopy, lactose consumption.

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Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, feature extraction, offline signature verification, VOTING-based classifier

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Authors: V. P. Muhamed Shajudheen, K. Viswanathan, K. Anitha Rani, A. Uma Maheswari, S. Saravana Kumar

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In this paper, a simple chemical precipitation route for the preparation of titanium dioxide nanoparticles, synthesized by using titanium tetra isopropoxide as a precursor and polyvinyl pyrrolidone (PVP) as a capping agent, is reported. The Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA) of the samples were recorded and the phase transformation temperature of titanium hydroxide, Ti(OH)₄ to titanium oxide, TiO₂ was investigated. The as-prepared Ti(OH)₄ precipitate was annealed at 800°C to obtain TiO₂ nanoparticles. The thermal, structural, morphological and textural characterizations of the TiO₂ nanoparticle samples were carried out by different techniques such as DSC-TGA, X-Ray Diffraction (XRD), Fourier Transform Infra-Red spectroscopy (FTIR), Micro Raman spectroscopy, UV-Visible absorption spectroscopy (UV-Vis), Photoluminescence spectroscopy (PL) and Field Effect Scanning Electron Microscopy (FESEM) techniques. The as-prepared precipitate was characterized using DSC-TGA and confirmed the mass loss of around 30%. XRD results exhibited no diffraction peaks attributable to anatase phase, for the reaction products, after the solvent removal. The results indicate that the product is purely rutile. The vibrational frequencies of two main absorption bands of prepared samples are discussed from the results of the FTIR analysis. The formation of nanosphere of diameter of the order of 10 nm, has been confirmed by FESEM. The optical band gap was found by using UV-Visible spectrum. From photoluminescence spectra, a strong emission was observed. The obtained results suggest that this method provides a simple, efficient and versatile technique for preparing TiO₂ nanoparticles and it has the potential to be applied to other systems for photocatalytic activity.

Keywords: TiO2 nanoparticles, chemical precipitation route, phase transition, Fourier Transform Infra-Red spectroscopy, micro Raman spectroscopy, UV-Visible absorption spectroscopy, Photoluminescence spectroscopy, Field Effect Scanning Electron Microscopy.

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Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz

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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.

Keywords: Component, robotic, automated, production, offline programming, CAD.

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Authors: Masayoshi Matsui, Akiko Nakahara, Akiko Takatsu, Kenji Kato, Naoki Matsuda

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The state and stability of hemoglobin adsorbed on the glass surface was investigated using slab optical waveguide (SOWG) spectroscopy. The peak position of the absorption band of hemoglobin adsorbed on the glass surface was same as that of the hemoglobin in solution. This result suggests that no significant denaturation occurred by adsorption. The adsorption of hemoglobin is relatively strong that the hemoglobin molecules even remained adsorbed after rinsing the cell with buffer solution. The peak shift caused by the reduction of adsorbed hemoglobin was also observed.

Keywords: hemoglobin, reduction, slab optical waveguide spectroscopy, solid/liquid interface.

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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Authors: A. Ben Abdallah, H. Essabbah, M. H. Bedoui

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The myocardial sintigraphy is an imaging modality which provides functional informations. Whereas, coronarography modality gives useful informations about coronary arteries anatomy. In case of coronary artery disease (CAD), the coronarography can not determine precisely which moderate lesions (artery reduction between 50% and 70%), known as the “gray zone", are haemodynamicaly significant. In this paper, we aim to define the relationship between the location and the degree of the stenosis in coronary arteries and the observed perfusion on the myocardial scintigraphy. This allows us to model the impact evolution of these stenoses in order to justify a coronarography or to avoid it for patients suspected being in the gray zone. Our approach is decomposed in two steps. The first step consists in modelling a coronary artery bed and stenoses of different location and degree. The second step consists in modelling the left ventricle at stress and at rest using the sphercical harmonics model and myocardial scintigraphic data. We use the spherical harmonics descriptors to analyse left ventricle model deformation between stress and rest which permits us to conclude if ever an ischemia exists and to quantify it.

Keywords: Spherical harmonics model, vascular bed, 3D reconstruction, left ventricle, myocardial scintigraphy.

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Authors: Yasser M. Moustafa, Rania E. Morsi, Mohammed Fathy

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Multiwall carbon nanotubes, prepared by chemical vapor deposition, have an average diameter of 60-100 nm as shown by High Resolution Transmittance Electron Microscope, HR-TEM. The Multiwall carbon nanotubes (MWCNTs) were further characterized using X-ray Diffraction and Raman Spectroscopy. Mercury uptake capacity of MWCNTs was studied using batch adsorption method at different concentration ranges up to 150 ppm. Mercury concentration (before and after the treatment) was measured using cold vapor atomic absorption spectroscopy. The effect of time, concentration, pH and adsorbent dose were studied. MWCNT were found to perform complete absorption in the sub-ppm concentrations (parts per billion levels) while for high concentrations, the adsorption efficiency was 92% at the optimum conditions; 0.1 g of the adsorbent at 150 ppm mercury (II) solution. The adsorption of mercury on MWCNTs was found to follow the Freundlich adsorption isotherm and the pseudo-second order kinetic model.

Keywords: Cold Vapor Atomic Absorption Spectroscopy, Hydride System, Mercury Removing, Multi Wall Carbon Nanotubes.

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Authors: Ashok V. Borhade, Sanjay G. Wakchaure

Abstract:

Pure phase gallosilicate nitrite sodalite has been synthesized in a single step by low temperature (373 oK) hydrothermal technique. The product obtained was characterized using a combination of techniques including X-ray powder diffraction, IR, Raman spectroscopy, SEM, MAS NMR spectroscopy as well as thermogravimetry. Sodalite with an ideal composition was obtained after synthesis at 3730K and seven days duration using alkaline medium. The structural features of the Na8[GaSiO4]6(NO2)2 sodalite were investigated by IR, MAS NMR spectroscopy of 29Si and 23Na nuclei and by Reitveld refinement of X-ray powder diffraction data. The crystal structure of this sodalite has been refined in the space group P 4 3n; with a cell parameter 8.98386Å, V= 726.9 Å, (Rwp= 0.077 and Rp=0.0537) and Si-O-Ga angle is found to be 132.920 . MAS NMR study confirms complete ordering of Si and Ga in the gallosilicate framework. The surface area of single entity with stoichiometry Na8[GaSiO4]6(NO2)2 was found to be 8.083 x10-15 cm2/g.

Keywords: Gallosilicate, hydrothermal, nitrite, Reitveldrefinement.

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