Search results for: medical MR images

Authors: S. Shefali, S. M. Deshpande, S. G. Tamhankar

Abstract:

Now a days, a significant part of commercial and governmental organisations like museums, cultural organizations, libraries, commercial enterprises, etc. invest intensively in new technologies for image digitization, digital libraries, image archiving and retrieval. Hence image authorization, authentication and security has become prime need. In this paper, we present a semi-fragile watermarking scheme for color images. The method converts the host image into YIQ color space followed by application of orthogonal dual domains of DCT and DWT transforms. The DCT helps to separate relevant from irrelevant image content to generate silent image features. DWT has excellent spatial localisation to help aid in spatial tamper characterisation. Thus image adaptive watermark is generated based of image features which allows the sharp detection of microscopic changes to locate modifications in the image. Further, the scheme utilises the multipurpose watermark consisting of soft authenticator watermark and chrominance watermark. Which has been proved fragile to some predefined processing like intentinal fabrication of the image or forgery and robust to other incidental attacks caused in the communication channel.

Keywords: Cryptography, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Watermarking.

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Authors: Mert Bal, Hayri Sever, Oya Kalıpsız

Abstract:

Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.

Keywords: Formal Concept Analysis, Rough Set Theory, Granular Computing, Medical Decision Support System.

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Authors: Sushil Kumar Saraswat, K. K. Pant

Abstract:

Co metal supported on SiO2 and Al2O3 catalysts with a metal loading varied from 30 of 70 wt.% were evaluated for decomposition of methane to COx free hydrogen and carbon nanomaterials. The catalytic runs were carried out from 550-800oC under atmospheric pressure using fixed bed vertical flow reactor. The fresh and spent catalysts were characterized by BET surface area analyzer, XRD, SEM, TEM and TG analysis. The data showed that 50% Co/Al2O3 catalyst exhibited remarkable higher activity at 800oC with respect to H2 production compared to rest of the catalysts. However, the catalytic activity and durability was greatly declined at higher temperature. The main reason for the catalytic inhibition of Co containing SiO2 catalysts is the higher reduction temperature of Co2SiO4. TEM images illustrate that the carbon materials with various morphologies, carbon nanofibers (CNFs), helical-shaped CNFs and branched CNFs depending on the catalyst composition and reaction temperature were obtained.

Keywords: Carbon nanotubes, Cobalt, Hydrogen Production, Methane decomposition.

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Authors: W. Koranuntachai, T. Chantrasmi, U. Nontakaew

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Medical latex gloves are made from the latex compound in production lines. Latex dipping is considered one of the most important processes that directly affect the final product quality. In a continuous production line, a chain conveyor carries the formers through the process and partially submerges them into an open channel flow in a latex dipping tank. In general, the conveyor speed is determined by the desired production capacity, and the latex-dipping tank can then be designed accordingly. It is important to understand the flow behavior in the dipping tank in order to achieve high quality in the process. In this work, Computational Fluid Dynamics (CFD) was used to simulate the flow past an array of formers in a simplified latex dipping process. The computational results showed both the flow structure and the vortex generation between two formers. The maximum shear stress over the surface of the formers was used as the quality metric of the latex-dipping process when adjusting operation parameters.

Keywords: medical latex gloves, latex dipping, dipping tank, computational fluid dynamics

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Authors: Mohamed K. Watfa

Abstract:

Like any sentient organism, a smart environment relies first and foremost on sensory data captured from the real world. The sensory data come from sensor nodes of different modalities deployed on different locations forming a Wireless Sensor Network (WSN). Embedding smart sensors in humans has been a research challenge due to the limitations imposed by these sensors from computational capabilities to limited power. In this paper, we first propose a practical WSN application that will enable blind people to see what their neighboring partners can see. The challenge is that the actual mapping between the input images to brain pattern is too complex and not well understood. We also study the connectivity problem in 3D/2D wireless sensor networks and propose distributed efficient algorithms to accomplish the required connectivity of the system. We provide a new connectivity algorithm CDCA to connect disconnected parts of a network using cooperative diversity. Through simulations, we analyze the connectivity gains and energy savings provided by this novel form of cooperative diversity in WSNs.

Keywords: Wireless Sensor Networks, Pervasive Computing, Eye Vision Application, 3D Connectivity, Clusters, Energy Efficient, Cooperative diversity.

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Authors: Mona Elsalamawy, Ashraf Ragab Mohamed, Abdellatif Elsayed Abosen

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This paper aims to evaluate the effectiveness of different crystalline coating materials concerning of chloride ions penetration. The concrete ages at the coating installation and its moisture conditions were addressed; where, these two factors may play a dominant role for the effectiveness of the used materials. Rapid chloride ions penetration test (RCPT) was conducted at different ages and moisture conditions according to the relevant standard. In addition, the contaminated area and the penetration depth of the chloride ions were investigated immediately after the RCPT test using chemical identifier, 0.1 M silver nitrate AgNO₃ solution. Results have shown that, the very low chloride ions penetrability, for the studied crystallization materials, were investigated only with the old age concrete (G1). The significant reduction in chloride ions’ penetrability was illustrated after 7 days of installing the crystalline coating layers. Using imageJ is more reliable to describe the contaminated area of chloride ions, where the distribution of aggregate and heterogeneous of cement mortar was considered in the images analysis.

Keywords: Chloride permeability, contaminated area, crystalline waterproofing materials, RCPT, XRD.

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Authors: Chakkrit Snae, Michael Brueckner

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In this paper the authors present the framework of a system for assisting users through counseling on personal health, the Personal Health Assistance Service Expert System (PHASES). Personal health assistance systems need Personal Health Records (PHR), which support wellness activities, improve the understanding of personal health issues, enable access to data from providers of health services, strengthen health promotion, and in the end improve the health of the population. This is especially important in societies where the health costs increase at a higher rate than the overall economy. The most important elements of a healthy lifestyle are related to food (such as balanced nutrition and diets), activities for body fitness (such as walking, sports, fitness programs), and other medical treatments (such as massage, prescriptions of drugs). The PHASES framework uses an ontology of food, which includes nutritional facts, an expert system keeping track of personal health data that are matched with medical treatments, and a comprehensive data transfer between patients and the system.

Keywords: Personal health assistance service, expert system, ontologies, knowledge management, information technology.

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Authors: Arturo Aquino, Manuel Emilio Gegundez, Jose Manuel Bravo, Diego Marin

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Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.

Keywords: Retinal vessel segmentation, quality assessment, performanceevaluation, similarity function.

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Authors: Mohammad Akbarpour Sekeh, Mohd. Aizaini Maarof, Mohd. Foad Rohani, Malihe Motiei

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Duplicated region detection is a technical method to expose copy-paste forgeries on digital images. Copy-paste is one of the common types of forgeries to clone portion of an image in order to conceal or duplicate special object. In this type of forgery detection, extracting robust block feature and also high time complexity of matching step are two main open problems. This paper concentrates on computational time and proposes a local block matching algorithm based on block clustering to enhance time complexity. Time complexity of the proposed algorithm is formulated and effects of two parameter, block size and number of cluster, on efficiency of this algorithm are considered. The experimental results and mathematical analysis demonstrate this algorithm is more costeffective than lexicographically algorithms in time complexity issue when the image is complex.

Keywords: Copy-paste forgery detection, Duplicated region, Timecomplexity, Local block matching, Sequential block clustering.

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: Video surveillance, disentanglement, face detection.

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Authors: F.Alilat, S.Loumi, H.Merrad, B.Sansal

Abstract:

In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.

Keywords: Neural Networks, fuzzy ART, fuzzy ARTMAP, Remote sensing, multispectral Classification.

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Authors: Yanwen Li, Shuguo Xie

Abstract:

In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: Gradient image, segmentation and extract, mean-shift algorithm, dictionary learning.

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Authors: Sreejith Jayachandran, Mojtaba Ghodsi, Morteza Mohammadzaheri

Abstract:

The modern busy world is running behind new embedded technologies based on computers and software meanwhile some people are unable to monitor their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. In this research, we present a device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. The various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data are collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud and stores it there; the processed digital data are then instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors, and other health staff can collect these data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate these data for awareness of the patient's current health status. Moreover, the system is connected to a GPS module. In emergencies, the concerned team can be positioning the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the Remote Health Monitoring System (RHMS) is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system 11×10×10 cm3 with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured for 100 GBP (British Pound Sterling), and can facilitate the communication between patients and health systems, but also it can be employed for numerous other uses including communication sectors in the aerospace and transportation systems.

Keywords: Embedded Technology, Telemonitoring system, Microcontroller, Arduino UNO, Cloud storage, GPS, RHMS, Remote Health Monitoring System, Alert system.

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Authors: M. Gooroochurn, M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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A registration framework for image-guided robotic surgery is proposed for three emergency neurosurgical procedures, namely Intracranial Pressure (ICP) Monitoring, External Ventricular Drainage (EVD) and evacuation of a Chronic Subdural Haematoma (CSDH). The registration paradigm uses CT and white light as modalities. This paper presents two simulation studies for a preliminary evaluation of the registration protocol: (1) The loci of the Target Registration Error (TRE) in the patient-s axial, coronal and sagittal views were simulated based on a Fiducial Localisation Error (FLE) of 5 mm and (2) Simulation of the actual framework using projected views from a surface rendered CT model to represent white light images of the patient. Craniofacial features were employed as the registration basis to map the CT space onto the simulated intraoperative space. Photogrammetry experiments on an artificial skull were also performed to benchmark the results obtained from the second simulation. The results of both simulations show that the proposed protocol can provide a 5mm accuracy for these neurosurgical procedures.

Keywords: Image-guided Surgery, Multimodality Registration, Photogrammetry, Preoperative to Intraoperative Registration.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

Abstract:

In this paper, we propose a novel fast search algorithm for short MPEG video clips from video database. This algorithm is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Instead of fully decompressed video frames, partially decoded data, namely DC images are utilized. Combined with active search [4], a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by 6 hours of video to search for given 200 MPEG video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and Equal Error Rate (ERR) of 3 % is achieved, which is more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, adjacent pixel intensity difference quantization (APIDQ), DC image, histogram feature.

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Authors: Amr Almaddah, Sadi Vural, Yasushi Mae, Kenichi Ohara, Tatsuo Arai

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In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the training bootstrap by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe lighting conditions with significant improvements on the face recognition rates.

Keywords: Face synthesis and recognition, Face illumination recovery, 2D spherical spaces, Vision for graphics.

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Authors: K. Jyothi, T. S. Mohamed Saleem, L. Vineela, C. Gopinath, K. B. Yadavender Reddy

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Objective: Acute coronary syndrome is a clinical condition encompassing ST segments elevation myocardial infraction, Non ST segment is elevation myocardial infraction and un stable angina is characterized by ruptured coronary plaque, stress and myocardial injury. Angina pectoris is a pressure like pain in the chest that is induced by exertion or stress and relived with in the minute after cessation of effort or using sublingual nitroglycerin. The present research was undertaken to study the drug utilization pattern of antiplatelet drugs for the ischemic heart disease in a tertiary care hospital. Method: The present study is retrospective drug utilization study and study period is 6months. The data is collected from the discharge case sheet of general medicine department from medical department Rajiv Gandhi institute of medical sciences, Kadapa. The tentative sample size fixed was 250 patients. Out of 250 cases 19 cases was excluded because of unrelated data. Results: A total of 250 prescriptions were collected for the study according to the inclusion criteria 233 prescriptions were diagnosed with ischemic heart disease 17 prescriptions were excluded due to unrelated information. out of 233 prescriptions 128 are male (54.9%) and 105 patients are were female (45%). According to the gender distribution, the prevalence of ischemic heart disease in males are 90 (70.31%) and females are 39 (37.1%). In the same way the prevalence of ischemic heart disease along with cerebrovascular disease in males are 39 (29.6%) and females are 66 (62.6%). Conclusion: We found that 94.8% of drug utilization of antiplatelet drugs was achieved in the Rajiv Gandhi institute of medical sciences, Kadapa from 2011-2012.

Keywords: Angina pectoris, aspirin, clopidogrel, myocardial infarction.

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Authors: Gee-Sern Jison Hsu

Abstract:

A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.

Keywords: Face recognition, open-set identification, hidden Markov model, support vector machines.

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Authors: Mazliham Mohd Su'ud, Pierre Loonis, Idris Abu Seman

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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.

Keywords: Fuzzy Inference Systems, Tomography analysis, Modelizationof expert's information, Ganoderma Infection pattern recognition

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Authors: J. George, M. Al Mutairi, W. Aljuryyad, A. Alhussanan, A. Alkashan, T. Aldoghiri, Z. Alamari, A. Albakr

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Introduction: Students make plans for their career and are keen in exploring options of employment in those carriers. They make their employment choice based on their desires and preferences. This study aims to identify if students of King Saud Bin Abdulaziz for Health Sciences, College of Applied Medical Sciences after obtaining appropriate education prefer to work as clinicians, university faculty, or full-time researchers. There are limited studies in Saudi Arabia exploring the university student’s employment choices and preferences. This study would help employers to build the required job positions and prevent misleading employers from opening undesired positions in the job market. Methodology: The study included 394 students from third and fourth years both male and female among the eighth programs of college of applied medical sciences, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh campus. A prospective quantitative cross-sectional study was conducted; data were collected by distributing a seven item questionnaire and analyzed using SPSS. Results: Among the participants, 358 (90.9%) of them chose one of the three listed career choices, 263 (66.8%) decided to work as hospital staff after their education, 75 students (19.0%) chose to work as a faculty member in a university after obtaining appropriate degree, 20 students (5.1%) preferred to work as full-time researcher after obtaining appropriate degree, the remaining 36 students (9.1%) had different career goals, such as obtaining a master degree after graduating, to obtain a bachelor of medicine and bachelor in surgery degree, and working in the private sector. The most recurrent reason behind the participants' choice was "career goal", where 276 (70.1%) chose it as a reason. Conclusion: The findings of the study showed that most student’s preferred to work in hospitals as clinicians, followed by choice of working as a faculty in a university, the least choice was to be working as full-time researchers.

Keywords: College of Applied Medical Sciences, employment ambitions, graduating students, King Saud bin Abdulaziz University for Health Sciences.

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Authors: Sajid Abbas, Joon Pyo Hong, Jung-Ryun Lee, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: Computed tomography, Computed laminography, Compressive sending, Low-dose.

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Authors: N.S. Pradhan, S.K. Dubey, A. D.Yadav, Arvind Singh, D.C. Kothari

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Un-doped GaN film of thickness 1.90 mm, grown on sapphire substrate were uniformly implanted with 325 keV Mn+ ions for various fluences varying from 1.75 x 1015 - 2.0 x 1016 ions cm-2 at 3500 C substrate temperature. The structural, morphological and magnetic properties of Mn ion implanted gallium nitride samples were studied using XRD, AFM and SQUID techniques. XRD of the sample implanted with various ion fluences showed the presence of different magnetic phases of Ga3Mn, Ga0.6Mn0.4 and Mn4N. However, the compositions of these phases were found to be depended on the ion fluence. AFM images of non-implanted sample showed micrograph with rms surface roughness 2.17 nm. Whereas samples implanted with the various fluences showed the presence of nano clusters on the surface of GaN. The shape, size and density of the clusters were found to vary with respect to ion fluence. Magnetic moment versus applied field curves of the samples implanted with various fluences exhibit the hysteresis loops. The Curie temperature estimated from zero field cooled and field cooled curves for the samples implanted with the fluence of 1.75 x 1015, 1.5 x 1016 and 2.0 x 1016 ions cm-2 was found to be 309 K, 342 K and 350 K respectively.

Keywords: GaN, Ion implantation, XRD, AFM, SQUID

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Authors: B. Akhmetov, A. Doszhanova, A. Ivanov, T. Kartbayev, A. Malygin

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The article examines the methods of protection of citizens' personal data on the Internet using biometric identity authentication technology. It`s celebrated their potential danger due to the threat of loss of base biometric templates. To eliminate the threat of compromised biometric templates is proposed to use neural networks large and extra-large sizes, which will on the one hand securely (Highly reliable) to authenticate a person by his biometrics, and on the other hand make biometrics a person is not available for observation and understanding. This article also describes in detail the transformation of personal biometric data access code. It`s formed the requirements for biometrics converter code for his work with the images of "Insider," "Stranger", all the "Strangers". It`s analyzed the effect of the dimension of neural networks on the quality of converters mystery of biometrics in access code.

Keywords: Biometric security technologies, Conversion of personal biometric data access code, Electronic signature, Large neural networks, quality of converters "Biometrics - the code", the Egovernment.

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Authors: Ahmad R. Naghsh-Nilchi, Mohammad Roshanzamir

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One of the popular methods for recognition of facial expressions such as happiness, sadness and surprise is based on deformation of facial features. Motion vectors which show these deformations can be specified by the optical flow. In this method, for detecting emotions, the resulted set of motion vectors are compared with standard deformation template that caused by facial expressions. In this paper, a new method is introduced to compute the quantity of likeness in order to make decision based on the importance of obtained vectors from an optical flow approach. For finding the vectors, one of the efficient optical flow method developed by Gautama and VanHulle[17] is used. The suggested method has been examined over Cohn-Kanade AU-Coded Facial Expression Database, one of the most comprehensive collections of test images available. The experimental results show that our method could correctly recognize the facial expressions in 94% of case studies. The results also show that only a few number of image frames (three frames) are sufficient to detect facial expressions with rate of success of about 83.3%. This is a significant improvement over the available methods.

Keywords: Facial expression, Facial features, Optical flow, Motion vectors.

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Authors: Yung-Gi Wu

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With the growing of computer and network, digital data can be spread to anywhere in the world quickly. In addition, digital data can also be copied or tampered easily so that the security issue becomes an important topic in the protection of digital data. Digital watermark is a method to protect the ownership of digital data. Embedding the watermark will influence the quality certainly. In this paper, Vector Quantization (VQ) is used to embed the watermark into the image to fulfill the goal of data hiding. This kind of watermarking is invisible which means that the users will not conscious the existing of embedded watermark even though the embedded image has tiny difference compared to the original image. Meanwhile, VQ needs a lot of computation burden so that we adopt a fast VQ encoding scheme by partial distortion searching (PDS) and mean approximation scheme to speed up the data hiding process. The watermarks we hide to the image could be gray, bi-level and color images. Texts are also can be regarded as watermark to embed. In order to test the robustness of the system, we adopt Photoshop to fulfill sharpen, cropping and altering to check if the extracted watermark is still recognizable. Experimental results demonstrate that the proposed system can resist the above three kinds of tampering in general cases.

Keywords: Data hiding, vector quantization, watermark.

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Authors: Abdessamad Essaouabi, Ibnelhaj Elhassane

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Efficient storage, transmission and use of video information are key requirements in many multimedia applications currently being addressed by MPEG-4. To fulfill these requirements, a new approach for representing video information which relies on an object-based representation, has been adopted. Therefore, objectbased watermarking schemes are needed for copyright protection. This paper proposes a novel blind object watermarking scheme for images and video using the in place lifting shape adaptive-discrete wavelet transform (SA-DWT). In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, etc.

Keywords: Watermark, visual model, robustness, in place lifting shape adaptive-discrete wavelet transform.

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

Abstract:

Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: Assembly, assistive technologies, augmented reality, manufacturing, visualization.

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Authors: Sanjay Kanade, Danielle Camara, Dijana Petrovska-Delacretaz, Bernadette Dorizzi

Abstract:

In this paper, a two factor scheme is proposed to generate cryptographic keys directly from biometric data, which unlike passwords, are strongly bound to the user. Hash value of the reference iris code is used as a cryptographic key and its length depends only on the hash function, being independent of any other parameter. The entropy of such keys is 94 bits, which is much higher than any other comparable system. The most important and distinct feature of this scheme is that it regenerates the reference iris code by providing a genuine iris sample and the correct user password. Since iris codes obtained from two images of the same eye are not exactly the same, error correcting codes (Hadamard code and Reed-Solomon code) are used to deal with the variability. The scheme proposed here can be used to provide keys for a cryptographic system and/or for user authentication. The performance of this system is evaluated on two publicly available databases for iris biometrics namely CBS and ICE databases. The operating point of the system (values of False Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set by properly selecting the error correction capacity (ts) of the Reed- Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096% and FRR is 0.76%.

Keywords:

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Authors: Zhang Bian, Zhao Jijun

Abstract:

The urban layout of Xi’an city (the capital Chang’an in the Tang dynasty) was shaped by feudal etiquette, but this dominant factor was replaced by modern city planning during the period of the Republic of China. This makes Xi’an a representative case to explore the transformation process of Chinese cities in the early 20^th century. By analyzing the contrast and connection between the historical texts of city planning and the realistic construction activities recorded by the maps and images, this paper reviews the transformation process of the urban space of Xi’an in the early 20^th century and divides it into four phases according to important events that significantly impacted planning and construction activities. Based on this, the entire transformation of Xi’an’s city planning and practices can be characterized by three aspects: 1) the dominant force of the city plan and construction changed with the establishment of modern city administrations; 2) the layout of the city was continuously broadened to meet the demand of modern economy and city life; and, 3) the ritual space was transformed into practical space for commercial and recreational activities.

Keywords: City space, early 20th century, transformation, Xi’an city.

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Authors: Yu-Xiang Zhao, Chien-Hsing Chou, Mu-Chun Su, Yi-Zeng Hsieh

Abstract:

The purpose of this study is to design a portable virtual piano. By utilizing optical fiber gloves and the virtual piano software designed by this study, the user can play the piano anywhere at any time. This virtual piano consists of three major parts: finger tapping identification, hand movement and positioning identification, and MIDI software sound effect simulation. To play the virtual piano, the user wears optical fiber gloves and simulates piano key tapping motions. The finger bending information detected by the optical fiber gloves can tell when piano key tapping motions are made. Images captured by a video camera are analyzed, hand locations and moving directions are positioned, and the corresponding scales are found. The system integrates finger tapping identification with information about hand placement in relation to corresponding piano key positions, and generates MIDI piano sound effects based on this data. This experiment shows that the proposed method achieves an accuracy rate of 95% for determining when a piano key is tapped.

Keywords: virtual piano, portable, identification, optical fibergloves.

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