Search results for: Content based image retrieval

Authors: S. Sookpeng, C. J. Martin, D. J. Gentle

Abstract:

Automatic tube current modulation (ATCM) systems are available for all CT manufacturers and are used for the majority of patients. Understanding how the systems work and their influence on patient dose and image quality is important for CT users, in order to gain the most effective use of the systems. In the present study, a new phantom was used for evaluating dose distribution and image quality under the ATCM operation for the Toshiba Aquilion 64 CT scanner using different ATCM options and a fixed mAs technique. A routine chest, abdomen and pelvis (CAP) protocol was selected for study and Gafchromic film was used to measure entrance surface dose (ESD), peripheral dose and central axis dose in the phantom. The results show the dose reductions achievable with various ATCM options, in relation with the target noise. The doses and image noise distribution were more uniform when the ATCM system was implemented compared with the fixed mAs technique. The lower limit set for the tube current will affect the modulations especially for the lower dose option. This limit prevented the tube current being reduced further and therefore the lower dose ATCM setting resembled a fixed mAs technique. Selection of a lower tube current limit is likely to reduce doses for smaller patients in scans of chest and neck regions.

Keywords: Computed Tomography (CT), Automatic Tube Current Modulation (ATCM), Automatic Exposure Control (AEC).

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Authors: Ahmed Badawi

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This paper proposes a method for speckle reduction in medical ultrasound imaging while preserving the edges with the added advantages of adaptive noise filtering and speed. A nonlinear image diffusion method that incorporates local image parameter, namely, scatterer density in addition to gradient, to weight the nonlinear diffusion process, is proposed. The method was tested for the isotropic case with a contrast detail phantom and varieties of clinical ultrasound images, and then compared to linear and some other diffusion enhancement methods. Different diffusion parameters were tested and tuned to best reduce speckle noise and preserve edges. The method showed superior performance measured both quantitatively and qualitatively when incorporating scatterer density into the diffusivity function. The proposed filter can be used as a preprocessing step for ultrasound image enhancement before applying automatic segmentation, automatic volumetric calculations, or 3D ultrasound volume rendering.

Keywords: Ultrasound imaging, Nonlinear isotropic diffusion, Speckle noise, Scattering.

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Authors: Sharan Badiger, Prema T. Akkasaligar

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Medical imaging technology has experienced a dramatic change in the last few years. Medical imaging refers to the techniques and processes used to create images of the human body (or parts thereof) for various clinical purposes such as medical procedures and diagnosis or medical science including the study of normal anatomy and function. With the growth of computers and image technology, medical imaging has greatly influenced the medical field. The diagnosis of a health problem is now highly dependent on the quality and the credibility of the image analysis. This paper deals with the various aspects and types of medical imaging.

Keywords: Computed Tomography, Echocardiography, Medical Imaging, Magnetic Resonance, Ultrasound Imaging.

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Authors: Chit Su Htwe, Win Htay

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The iris recognition technology is the most accurate, fast and less invasive one compared to other biometric techniques using for example fingerprints, face, retina, hand geometry, voice or signature patterns. The system developed in this study has the potential to play a key role in areas of high-risk security and can enable organizations with means allowing only to the authorized personnel a fast and secure way to gain access to such areas. The paper aim is to perform the iris region detection and iris inner and outer boundaries localization. The system was implemented on windows platform using Visual C# programming language. It is easy and efficient tool for image processing to get great performance accuracy. In particular, the system includes two main parts. The first is to preprocess the iris images by using Canny edge detection methods, segments the iris region from the rest of the image and determine the location of the iris boundaries by applying Hough transform. The proposed system tested on 756 iris images from 60 eyes of CASIA iris database images.

Keywords: Canny, C#, hough transform, image preprocessing.

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Authors: G. Nur

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Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristics, etc) due to the complex nature of the 3D video. Therefore, effective factors on this experience should be utilized while assessing it. In this paper, structural information of the depth map sequences of the 3D video is considered as content related factor effective on the depth perception assessment. Cartoon-like filter is utilized to abstract the significant depth levels in the depth map sequences to determine the structural information. Moreover, subjective experiments are conducted using 3D videos associated with cartoon-like depth map sequences to investigate the effectiveness of ambient illumination condition, which is a contextual factor, on depth perception. Using the knowledge gained through this study, 3D video experience metrics can be developed to deliver better service to the 3D video service users. 

Keywords: 3D Video, Ambient Illumination, Cartoon Effect, Depth Perception.

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Authors: Guanqiao Wang, Hongyang Yu

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There is a lot of repetitive work in the traditional construction industry. These repetitive tasks can significantly improve production efficiency by replacing manual tasks with robots. Therefore, robots appear more and more frequently in the construction industry. Navigation and positioning is a very important task for construction robots, and the requirements for accuracy of positioning are very high. Traditional indoor robots mainly use radio frequency or vision methods for positioning. Compared with ordinary robots, the indoor plastering robot needs to be positioned closer to the wall for wall plastering, so the requirements for construction positioning accuracy are higher, and the traditional navigation positioning method has a large error, which will cause the robot to move. Without the exact position, the wall cannot be plastered or the error of plastering the wall is large. A positioning method is proposed, which is assisted by line lasers and uses image processing-based positioning to perform more accurate positioning on the traditional positioning work. In actual work, filter, edge detection, Hough transform and other operations are performed on the images captured by the camera. Each time the position of the laser line is found, it is compared with the standard value, and the position of the robot is moved or rotated to complete the positioning work. The experimental results show that the actual positioning error is reduced to less than 0.5 mm by this accurate positioning method.

Keywords: Indoor plastering robot, navigation, precise positioning, line laser, image processing.

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Authors: Laila Y. Fannas, Ahmed Y. Ben Sasi

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This research presents a handwritten signature recognition based on angle feature vector using Artificial Neural Network (ANN). Each signature image will be represented by an Angle vector. The feature vector will constitute the input to the ANN. The collection of signature images will be divided into two sets. One set will be used for training the ANN in a supervised fashion. The other set which is never seen by the ANN will be used for testing. After training, the ANN will be tested for recognition of the signature. When the signature is classified correctly, it is considered correct recognition otherwise it is a failure.

Keywords: Signature Recognition, Artificial Neural Network, Angle Features.

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Authors: Khairul Nizam Tahar, Anuar Ahmad

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This paper has introduced a slope photogrammetric mapping using unmanned aerial vehicle. There are two units of UAV has been used in this study; namely; fixed wing and multi-rotor. Both UAVs were used to capture images at the study area. A consumer digital camera was mounted vertically at the bottom of UAV and captured the images at an altitude. The objectives of this study are to obtain three dimensional coordinates of slope area and to determine the accuracy of photogrammetric product produced from both UAVs. Several control points and checkpoints were established Real Time Kinematic Global Positioning System (RTK-GPS) in the study area. All acquired images from both UAVs went through all photogrammetric processes such as interior orientation, exterior orientation, aerial triangulation and bundle adjustment using photogrammetric software. Two primary results were produced in this study; namely; digital elevation model and digital orthophoto. Based on results, UAV system can be used to mapping slope area especially for limited budget and time constraints project.

Keywords: Slope mapping, 3D, DEM, UAV, Photogrammetry, image processing.

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Authors: E. Keramaris

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In this study, laboratory experiments in open channel flows over a sand bed were conducted. A porous bed (sand bed) with porosity of ε=0.70 and porous thickness of s΄=3 cm was tested. Vertical distributions of velocity were evaluated by using a two-dimensional (2D) Particle Image Velocimetry (PIV). Velocity profiles are measured above the impermeable bed and above the sand bed for the same different total water heights (h= 6, 8, 10 and 12 cm) and for the same slope S=1.5. Measurements of mean velocity indicate the effects of the bed material used (sand bed) on the flow characteristics (Velocity distribution and Reynolds number) in comparison with those above the impermeable bed.

Keywords: Particle image velocimetry, sand bed, velocity distribution, Reynolds number.

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Authors: Rita Riekstina-Dolge, Zanda Kruma, Daina Karklina, Fredijs Dimins

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Apple juice is the main raw material for cider production. In this study apple juices obtained from 14 dessert and crab variety apples grown in Latvia were investigated. For all samples soluble solids, titratable acidity, pH and sugar content were determined. Crab apples produce more dry matter, total sugar and acid content compared to the dessert apples but it depends on the apple variety. Total sugar content of crab apple juices was 1.3 to 1.8 times larger than in dessert apple juices. Titratable acidity of dessert apple juices is in the range of 4.1g L^-1 to 10.83g L^-1 and in crab apple juices titratable acidity is from 7.87g L^-1 to 19.6g L^-1. Fructose was detected as the main sugar whereas glucose level varied depending on the variety. The highest titratable acidity and content of sugars was detected in ‘Cornelia’ apples juice.

Keywords: Apple juice, hierarchical cluster analysis, sugars, titratable acidity.

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Authors: Radek Malinský, Ivan Jelínek

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Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend.

Keywords: Blog, Sentiment Analysis, Web 2.0, Webometrics

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Authors: Vita Strazdina, Aleksandrs Jemeljanovs, Vita Sterna

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A game animals – elk (Alces alces), deer (Cervus elaphus), roe deer (Capreolus capreolus) or wild boar (Sus scrofa scrofa) - every autumn and winter period provide an excellent investment, diversification of many consumer meals. In last years consumption and assortiment of game meat products significantly increase. Investigations about biochemical composition of game meat are not very much. The meat of wild animals is more favourable for human health because it has lower saturated fatty acids content, but higher content of protein. Therefore the aim of investigations was to compare biochemical composition of ungulates obtained in Latvia.Investigations were carried out in wild animals different regions of Latvia. In the studied samples protein, intramuscular fat, fatty acids and cholesterol were determined. The biochemical analysis of 54 samples were done. Results of analysis showed that protein content 22.36 – 22.92% of all types of meat samples is not different statistically, significantly lower fat content 1.33 ± 0.88% had elk meat samples and 1.59 ± 0.59% roe deer samples. Content of cholesterol was various 64.41 – 95.07% in the ruminant meat samples of different species. From the dietetic point of view the best composition of fatty acids has meat samples of roe deer.

Keywords: dietic product, game meat, intramuscular fat

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Authors: Sundararajan Sangeetha, Joseph Jesu Christopher, Swaminathan Ramakrishnan

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In this work, the primary compressive strength components of human femur trabecular bone are qualitatively assessed using image processing and wavelet analysis. The Primary Compressive (PC) component in planar radiographic femur trabecular images (N=50) is delineated by semi-automatic image processing procedure. Auto threshold binarization algorithm is employed to recognize the presence of mineralization in the digitized images. The qualitative parameters such as apparent mineralization and total area associated with the PC region are derived for normal and abnormal images.The two-dimensional discrete wavelet transforms are utilized to obtain appropriate features that quantify texture changes in medical images .The normal and abnormal samples of the human femur are comprehensively analyzed using Harr wavelet.The six statistical parameters such as mean, median, mode, standard deviation, mean absolute deviation and median absolute deviation are derived at level 4 decomposition for both approximation and horizontal wavelet coefficients. The correlation coefficient of various wavelet derived parameters with normal and abnormal for both approximated and horizontal coefficients are estimated. It is seen that in almost all cases the abnormal show higher degree of correlation than normals. Further the parameters derived from approximation coefficient show more correlation than those derived from the horizontal coefficients. The parameters mean and median computed at the output of level 4 Harr wavelet channel was found to be a useful predictor to delineate the normal and the abnormal groups.

Keywords: Image processing, planar radiographs, trabecular bone and wavelet analysis.

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Authors: Yue Du, Sahan C. B. Herath, Qing-Guo Wang, Harry Asada, Peter C. Y. Chen

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Mechanical interaction between endothelial cells (ECs) and the extracellular matrix (or collagen gel) is known to influence the sprouting response of endothelial cells during angiogenesis. This influence is believed to impact on the capability of endothelial cells to sense soluble chemical cues. Quantitative analysis of endothelial-cell-mediated displacement of the collagen gel provides a means to explore this mechanical interaction. Existing analysis in this context is generally limited to 2D settings. In this paper, we investigate the mechanical interaction between endothelial cells and the extracellular matrix in terms of the endothelial-cellmediated displacement of the collagen gel in both 2D and 3D. Digital image correlation and Digital volume correlation are applied on confocal reflectance image stacks to analyze cell-mediated displacement of the gel. The skeleton of the sprout is extracted from phase contrast images and superimposed on the displacement field to further investigate the link between the development of the sprout and the displacement of the gel.

Keywords: Angiogenesis, digital image correlation, digital volume correlation, interaction between ECs and ECM.

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Authors: Siddhartha Bhattacharyya, Paramartha Dutta, Ujjwal Maulik, Prashanta Kumar Nandi

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A multilayer self organizing neural neural network (MLSONN) architecture for binary object extraction, guided by a beta activation function and characterized by backpropagation of errors estimated from the linear indices of fuzziness of the network output states, is discussed. Since the MLSONN architecture is designed to operate in a single point fixed/uniform thresholding scenario, it does not take into cognizance the heterogeneity of image information in the extraction process. The performance of the MLSONN architecture with representative values of the threshold parameters of the beta activation function employed is also studied. A three layer bidirectional self organizing neural network (BDSONN) architecture comprising fully connected neurons, for the extraction of objects from a noisy background and capable of incorporating the underlying image context heterogeneity through variable and adaptive thresholding, is proposed in this article. The input layer of the network architecture represents the fuzzy membership information of the image scene to be extracted. The second layer (the intermediate layer) and the final layer (the output layer) of the network architecture deal with the self supervised object extraction task by bi-directional propagation of the network states. Each layer except the output layer is connected to the next layer following a neighborhood based topology. The output layer neurons are in turn, connected to the intermediate layer following similar topology, thus forming a counter-propagating architecture with the intermediate layer. The novelty of the proposed architecture is that the assignment/updating of the inter-layer connection weights are done using the relative fuzzy membership values at the constituent neurons in the different network layers. Another interesting feature of the network lies in the fact that the processing capabilities of the intermediate and the output layer neurons are guided by a beta activation function, which uses image context sensitive adaptive thresholding arising out of the fuzzy cardinality estimates of the different network neighborhood fuzzy subsets, rather than resorting to fixed and single point thresholding. An application of the proposed architecture for object extraction is demonstrated using a synthetic and a real life image. The extraction efficiency of the proposed network architecture is evaluated by a proposed system transfer index characteristic of the network.

Keywords: Beta activation function, fuzzy cardinality, multilayer self organizing neural network, object extraction,

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Authors: Manjunath Aradhya V N, Hemantha Kumar G, Shivakumara P

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Document image processing has become an increasingly important technology in the automation of office documentation tasks. During document scanning, skew is inevitably introduced into the incoming document image. Since the algorithm for layout analysis and character recognition are generally very sensitive to the page skew. Hence, skew detection and correction in document images are the critical steps before layout analysis. In this paper, a novel skew detection method is presented for binary document images. The method considered the some selected characters of the text which may be subjected to thinning and Hough transform to estimate skew angle accurately. Several experiments have been conducted on various types of documents such as documents containing English Documents, Journals, Text-Book, Different Languages and Document with different fonts, Documents with different resolutions, to reveal the robustness of the proposed method. The experimental results revealed that the proposed method is accurate compared to the results of well-known existing methods.

Keywords: Optical Character Recognition, Skew angle, Thinning, Hough transform, Document processing

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Authors: I. V. Kuzminov

Abstract:

According to its content, the proposed article is a collection of articles with comments and additions. All articles, in one way or another, have a connection with the Second Law of Thermodynamics. The content of the articles is given in a concise form. The articles were published in different journals at different times. Main topics are presented: gravity, biography of the Earth, physics of global warming-cooling cycles, multiverse. The articles are based on the laws of classical physics. Along the way, it should be noted that the Second Law of Thermodynamics can be formulated as the Law of Matter Cooling. As it cools down, the processes of condensation, separation, and changes in the aggregate states of matter occur. In accordance with these changes, a picture of the world is being formed. Also, the main driving force of these processes is the inverse temperature dependence of the forces of gravity. As matter cools, the forces of gravity increase. The actions of these phenomena in the compartment form a picture of the world.

Keywords: Gravitational forces, cooling of matter, second law of thermodynamics, planetary model of the atom.

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Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

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Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

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This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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Authors: Alaa H. J. Al-Rkaby, A. Chegenizadeh, H. R. Nikraz

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Anisotropy is one of the major aspects that affect soil behavior, and extensive efforts have investigated its effect on the mechanical properties of soil. However, very little attention has been given to the combined effect of anisotropy and fine contents. Therefore, in this paper, the anisotropic strength of sand containing different fine content (F) of 5%, 10%, 15%, and 20%, was investigated using hollow cylinder tests under different principal stress directions of α = 0° and α = 90°. For a given principal stress direction (α), it was found that increasing fine content resulted in decreasing deviator stress (q). Moreover, results revealed that all fine contents showed anisotropic strength where there is a clear difference between the strength under 0° and the strength under 90°. This anisotropy was greatest under F = 5% while it decreased with increasing fine contents, particularly at F = 10%. Mixtures with low fine content show low contractive behavior and tended to show more dilation. Moreover, all sand-clay mixtures exhibited less dilation and more compression at α = 90° compared with that at α = 0°.

Keywords: Anisotropy, principal stress direction, fine content, hollow cylinder sample.

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Authors: Kuo-Cheng Liu

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Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.

Keywords: Just-noticeable distortion (JND), discrete cosine transform (DCT), JPEG.

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Authors: Saeid Saryazdi, Hossein Nezamabadi-pour

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A new blind gray-level watermarking scheme is described. In the proposed method, the host image is first divided into 4*4 non-overlapping blocks. For each block, two first AC coefficients of its Hadamard transform are then estimated using DC coefficients of its neighbor blocks. A gray-level watermark is then added into estimated values. Since embedding watermark does not change the DC coefficients, watermark extracting could be done by estimating AC coefficients and comparing them with their actual values. Several experiments are made and results suggest the robustness of the proposed algorithm.

Keywords: Digital Watermarking, Image watermarking, Information Hiden, Steganography.

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Authors: Mohammed Salahat, Steve Wade

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This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: SSM, UML, domain-driven design, soft domain-driven design, naked objects, soft language, information retrieval, multimethodology.

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Authors: Nieto B. W, Luna A. C, Ramos R. J.

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This paper describes an experience of research, development and innovation applied in Industrial Naval at (Science and Technology Corporation for the Development of Shipbuilding Industry, Naval in Colombia (COTECMAR) particularly through processes of research, innovation and technological development, based on theoretical models related to organizational knowledge management, technology management and management of human talent and integration of technology platforms. It seeks ways to facilitate the initial establishment of environments rich in information, knowledge and content-supported collaborative strategies on dynamic processes missionary, seeking further development in the context of research, development and innovation of the Naval Engineering in Colombia, making it a distinct basis for the generation of knowledge assets from COTECMAR. The integration of information and communication technologies, supported on emerging technologies (mobile technologies, wireless, digital content via PDA, and content delivery services on the Web 2.0 and Web 3.0) as a view of the strategic thrusts in any organization facilitates the redefinition of processes for managing information and knowledge, enabling the redesign of workflows, the adaptation of new forms of organization - preferably in networking and support the creation of symbolic-inside-knowledge promotes the development of new skills, knowledge and attitudes of the knowledge worker

Keywords: Management Knowledge, Information andCommunication Technologies, Knowledge Worker.

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Authors: Nour Aljafari, Mariam, S. Maani, Serter Atabay, Tarig Ali, Said Daker, Lara Daher, Hamad Bukhammas, Mohammed Abou Shakra

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This paper aims at determining the soil characteristics that influence the irrigation process of green landscapes and deciding on the optimum amount of water needed for irrigation. The laboratory experiments were conducted using the constant head methodology to determine the soil infiltration rates. The steady state infiltration rate was reached after 10 minutes of infiltration at a rate of 200 mm/hr. The effects of different water heads on infiltration rates were also investigated, and the head of 11 cm was found to be the optimum head for the test. The experimental results showed consistent infiltration results for the range between 11 cm and 15 cm. The study also involved finding the initial moisture content, which ranged between 5% and 25%, and finding the organic content, which occupied 1% to 2% of the soil. These results will be later utilized, using the water balance approach, to estimate the optimum amount of water needed for irrigation for changing weather conditions.

Keywords: Infiltration rate, moisture content, grass type, organic content.

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Authors: Arash Poordana, Reza Ziaie Moayed

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Calcareous sands are found most commonly in areas adjacent to crude oil and gas, and particularly around water. These types of soil have high compressibility due to high inter-granular porosity, irregularity, fragility, and especially crushing. Also, based on experience, it has been shown that the behavior of these types of soil is not similar to silica sand in loading. Since the destructive effects of cement on the environment are obvious, other alternatives such as bentonite are popular to be used. Bentonite has always been used commercially in civil engineering projects and according to its low hydraulic conductivity, it is used for landfills, cut-off walls, and nuclear wastelands. In the present study, unconfined compression tests in five ageing periods (1, 3, 7, 14, and 28 days) after mixing different percentages of bentonite (5%, 7.5% and 10%) with Bushehr calcareous sand were performed. The relative density considered for the specimens is 50%. Optimum water content was then added to each specimen accordingly (19%, 18.5%, and 17.5%). The sample preparation method was wet tamping and the specimens were compacted in five layers. It can be concluded from the results that as the bentonite content increases, the unconfined compression strength of the soil increases. Based on the obtained results, 3-day and 7-day ageing periods showed 30% and 50% increase in the shear strength of soil, respectively.

Keywords: Unconfined compression test, bentonite, bushehr calcareous sand.

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Authors: P. Rattanapoltee, P. Kaewkannetra

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According to biodiesel from microalgae is an attractive fuel for several reasons such as renewable, biodegradable and environmental friendly. Thus, this study, green microalgae Scenedesmus acutus PPNK1 isolated from natural water, was selected based on high growth rates, easy cultivation and high lipid content. The Nile red fluorescence method has been successfully applied to the determination of lipids in S. acutus PPNK1. The combination of the method to the lipid composition in algal cells showed the yellow fluorescence under fluorescent microscope. Interestingly, maximum cell numbers and biomass concentration were obtained at 5.44´10⁷ cells/mL and 1.60 g/L when it was cultivated in BG-11 medium while in case of BG-11 with nitrogen deprivation (N 0.25 g/L), accumulated lipid content in cells (44.67%) was achieved that was higher than that found in case of BG-11 medium at about 2 times (22.63%).

Keywords: Biodiesel, Lipid, Microalgae, Nile red.

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Authors: Dingding Chen, Kazuo Arakawa, Masakazu Uchino, Changheng Xu

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Vacuum assisted resin transfer moulding (VARTM) is a promising manufacture process for making large and complex fiber reinforced composite structures. However, the complexity of the flow of the resin in the infusion stage usually leads to nonuniform property distribution of the produced composite part. In order to control the flow of the resin, the situation of flow should be mastered. For the safety of the usage of the produced composite in practice, the understanding of the property distribution is essential. In this paper, we did some trials on monitoring the resin infusion stage and evaluation for the fiber volume fraction distribution of the VARTM produced composite using the digital image correlation methods. The results showthat3D-DIC is valid on monitoring the resin infusion stage and it is possible to use 2D-DIC to estimate the distribution of the fiber volume fraction on a FRP plate.

Keywords: Digital image correlation, VARTM, FRP, fiber volume fraction.

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Authors: Ahmad T. Al-Taani, Abdullah M. AL-Issa

Abstract:

In this work we propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by dividing the cover into blocks of equal sizes and then embeds the message in the edge of the block depending on the number of ones in left four bits of the pixel. The proposed approach is tested on a database consists of 100 different images. Experimental results, compared with other methods, showed that the proposed approach hide more large information and gave a good visual quality stego-image that can be seen by human eyes.

Keywords: Data Embedding, Cryptography, Watermarking, Steganography, Least Significant Bit, Information Hiding.

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

Abstract:

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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