Search results for: Great Deluge Algorithm.

Authors: Petru Manescu, Joseph Azencot, Michael Beuve, Hamid Ladjal, Jacques Saade, Jean-Michel Morreau, Philippe Giraud, Behzad Shariat

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Organ motion, especially respiratory motion, is a technical challenge to radiation therapy planning and dosimetry. This motion induces displacements and deformation of the organ tissues within the irradiated region which need to be taken into account when simulating dose distribution during treatment. Finite element modeling (FEM) can provide a great insight into the mechanical behavior of the organs, since they are based on the biomechanical material properties, complex geometry of organs, and anatomical boundary conditions. In this paper we present an original approach that offers the possibility to combine image-based biomechanical models with particle transport simulations. We propose a new method to map material density information issued from CT images to deformable tetrahedral meshes. Based on the principle of mass conservation our method can correlate density variation of organ tissues with geometrical deformations during the different phases of the respiratory cycle. The first results are particularly encouraging, as local error quantification of density mapping on organ geometry and density variation with organ motion are performed to evaluate and validate our approach.

Keywords: Biomechanical simulation, dose distribution, image guided radiation therapy, organ motion, tetrahedral mesh, 4D-CT.

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each region of interest (ROI), 6 distinct sets of texture features are extracted such as: first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. When analyzing more phases, we show that the injection of liquid cause changes to the high relevant features in each region. Our results demonstrate that for detecting HCC tumor phase 3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between pathology and healthy classes, according to our method, relates to first order histogram parameters with accuracy of 85% in phase 1, 95% in phase 2, and 95% in phase 3.

Keywords: Feature selection, Multi-phasic liver images, Neural network, Texture analysis.

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: Accelerate MRI scans, image reconstruction, pyramid network, deep learning.

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Authors: Kiran Ijaz, Umar Manzoor, Arshad Ali Shahid

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In this paper we present an extension to Vision Based LRTA* (VLRTA*) known as Vision Based Moving Target Search (VMTS) for capturing unknown moving target in unknown territory with randomly generated obstacles. Target position is unknown to the agents and they cannot predict its position using any probability method. Agents have omni directional vision but can see in one direction at some point in time. Agent-s vision will be blocked by the obstacles in the search space so agent can not see through the obstacles. Proposed algorithm is evaluated on large number of scenarios. Scenarios include grids of sizes from 10x10 to 100x100. Grids had obstacles randomly placed, occupying 0% to 50%, in increments of 10%, of the search space. Experiments used 2 to 9 agents for each randomly generated maze with same obstacle ratio. Observed results suggests that VMTS is effective in locate target time, solution quality and virtual target. In addition, VMTS becomes more efficient if the number of agents is increased with proportion to obstacle ratio.

Keywords: Vision, MTS, Unknown Target, Coordination, VMTS, Multi-Agent.

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Authors: Sameru Sharma, Sanjay Sharma, Derick Engles

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Multiple-input multiple-output (MIMO) systems are widely in use to improve quality, reliability of wireless transmission and increase the spectral efficiency. However in MIMO systems, multiple copies of data are received after experiencing various channel effects. The limitations on account of complexity due to number of antennas in case of conventional decoding techniques have been looked into. Accordingly we propose a modified sphere decoder (MSD-1) algorithm with lower complexity and give rise to system with high spectral efficiency. With the aim to increase signal diversity we apply rotated quadrature amplitude modulation (QAM) constellation in multi dimensional space. Finally, we propose a new architecture involving space time trellis code (STTC) concatenated with space time block code (STBC) using MSD-1 at the receiver for improving system performance. The system gains have been verified with channel state information (CSI) errors.

Keywords: Channel State Information , Diversity, Multi-Antenna, Rotated Constellation, Space Time Codes.

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Authors: Chiharu Okuma, Jun Murakami, Naoki Yamamoto

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In digital signal processing it is important to approximate multi-dimensional data by the method called rank reduction, in which we reduce the rank of multi-dimensional data from higher to lower. For 2-dimennsional data, singular value decomposition (SVD) is one of the most known rank reduction techniques. Additional, outer product expansion expanded from SVD was proposed and implemented for multi-dimensional data, which has been widely applied to image processing and pattern recognition. However, the multi-dimensional outer product expansion has behavior of great computation complex and has not orthogonally between the expansion terms. Therefore we have proposed an alterative method, Third-order Orthogonal Tensor Product Expansion short for 3-OTPE. 3-OTPE uses the power method instead of nonlinear optimization method for decreasing at computing time. At the same time the group of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is also developed with SVD extensions for multi-dimensional data. 3-OTPE and HOSVD are similarly on the rank reduction of multi-dimensional data. Using these two methods we can obtain computation results respectively, some ones are the same while some ones are slight different. In this paper, we compare 3-OTPE to HOSVD in accuracy of calculation and computing time of resolution, and clarify the difference between these two methods.

Keywords: Singular value decomposition (SVD), higher-order SVD (HOSVD), higher-order tensor, outer product expansion, power method.

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Authors: Nader Gharibnavaz, Hossein Yazdi

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If organizations like Mellat Bank want to identify its customer market completely to reach its specified goals, it can segment the market to offer the product package to the right segment. Our objective is to offer a segmentation model for Iran banking market in Mellat bank view. The methodology of this project is combined by “segmentation on the basis of four part-quality variables" and “segmentation on the basis of different in means". Required data are gathered from E-Systems and researcher personal observation. Finally, the research offers the organization that at first step form a four dimensional matrix with 756 segments using four variables named value-based, behavioral, activity style, and activity level, and at the second step calculate the means of profit for every cell of matrix in two distinguished work level (levels α1:normal condition and α2: high pressure condition) and compare the segments by checking two conditions that are 1- homogeneity every segment with its sub segment and 2- heterogeneity with other segments, and so it can do the necessary segmentation process. After all, the last offer (more explained by an operational example and feedback algorithm) is to test and update the model because of dynamic environment, technology, and banking system.

Keywords: market segmentation model, banking system, Mellat bank

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Authors: Ferhat Kadioglu, Hasan Puskul

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A composite material with carbon fiber and polymer matrix has been used as adherent for manufacturing adhesive joints. In order to evaluate different fiber orientations on joint performance, the adherents with the 0°, ±15°, ±30°, ±45° fiber orientations were used in the single lap joint configuration. The joints with an overlap length of 25 mm were prepared according to the ASTM 1002 specifications and subjected to tensile loadings. The structural adhesive used was a two-part epoxy to be cured at 70°C for an hour. First, mechanical behaviors of the adherents were measured using three point bending test. In the test, considerations were given to stress to failure and elastic modulus. The results were compared with theoretical ones using rule of mixture. Then, the joints were manufactured in a specially prepared jig, after a proper surface preparation. Experimental results showed that the fiber orientations of the adherents affected the joint performance considerably; the joints with ±45° adherents experienced the worst shear strength, half of those with 0° adherents, and in general, there was a great relationship between the fiber orientations and failure mechanisms. Delamination problems were observed for many joints, which were thought to be due to peel effects at the ends of the overlap. It was proved that the surface preparation applied to the adherent surface was adequate. For further explanation of the results, a numerical work should be carried out using a possible non-linear analysis.

Keywords: Composite materials, adhesive bonding, bonding strength, lap joint, tensile strength.

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: Ring recognition, edge detection, X-ray computed tomography, dendrochronology.

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Authors: S. Montenegro, W. Hu

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The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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Authors: Nevena Stolba, A Min Tjoa

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Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.

Keywords: data mining, data warehousing, decision-support systems, evidence-based medicine.

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Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

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Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: Indoor localization, waterfall, digital forensics, tracking and cloud.

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Authors: Amir Gandomkar, Tahereh Soltani Gord faramarzi, Parisa Safaripour Chafi, Abdol-Reza Amani

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Temperature, humidity and precipitation in an area, are parameters proved influential in the climate of that area, and one should recognize them so that he can determine the climate of that area. Climate changes are of primary importance in climatology, and in recent years, have been of great concern to researchers and even politicians and organizations, for they can play an important role in social, political and economic activities. Even though the real cause of climate changes or their stability is not yet fully recognized, they are a matter of concern to researchers and their importance for countries has prompted them to investigate climate changes in different levels, especially in regional, national and continental level. This issue has less been investigated in our country. However, in recent years, there have been some researches and conferences on climate changes. This study is also in line with such researches and tries to investigate and analyze the trends of climate changes (temperature and precipitation) in Sefid-roud (the name of a river) basin. Three parameters of mean annual precipitation, temperature, and maximum and minimum temperatures in 36 synoptic and climatology stations in a statistical period of 49 years (1956-2005) in the stations of Sefid-roud basin were analyzed by Mann-Kendall test. The results obtained by data analysis show that climate changes are short term and have a trend. The analysis of mean temperature revealed that changes have a significantly rising trend, besides the precipitation has a significantly falling trend.

Keywords: Trend, Climate changes, Sefid-roud, Mann-Kendall

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Authors: Ramaswamy Palaniappan

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In this paper, several improvements are proposed to previous work of automated classification of alcoholics and nonalcoholics. In the previous paper, multiplayer-perceptron neural network classifying energy of gamma band Visual Evoked Potential (VEP) signals gave the best classification performance using 800 VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the dataset is extended to include 3560 VEP signals from 102 subjects: 62 alcoholics and 40 non-alcoholics. Three modifications are introduced to improve the classification performance: i) increasing the gamma band spectral range by increasing the pass-band width of the used filter ii) the use of Multiple Signal Classification algorithm to obtain the power of the dominant frequency in gamma band VEP signals as features and iii) the use of the simple but effective knearest neighbour classifier. To validate that these two modifications do give improved performance, a 10-fold cross validation classification (CVC) scheme is used. Repeat experiments of the previously used methodology for the extended dataset are performed here and improvement from 94.49% to 98.71% in maximum averaged CVC accuracy is obtained using the modifications. This latest results show that VEP based classification of alcoholics is worth exploring further for system development.

Keywords: Alcoholic, Multilayer-perceptron, Nearest neighbour, Gamma band, MUSIC, Visual evoked potential.

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Authors: Alexander Y. Vaninsky

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This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.

Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.

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Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee

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In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.

Keywords: Text detection, edge profile, signboard image, fuzzy clustering.

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Authors: Hesham A. Ali, Mofreh M. Salem, Ahmed A. Hamza

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Recently, there have been considerable efforts towards the convergence between P2P and Grid computing in order to reach a solution that takes the best of both worlds by exploiting the advantages that each offers. Augmenting the peer-to-peer model to the services of the Grid promises to eliminate bottlenecks and ensure greater scalability, availability, and fault-tolerance. The Grid Information Service (GIS) directly influences quality of service for grid platforms. Most of the proposed solutions for decentralizing the GIS are based on completely flat overlays. The main contributions for this paper are: the investigation of a novel resource discovery framework for Grid implementations based on a hierarchy of structured peer-to-peer overlay networks, and introducing a discovery algorithm utilizing the proposed framework. Validation of the framework-s performance is done via simulation. Experimental results show that the proposed organization has the advantage of being scalable while providing fault-isolation, effective bandwidth utilization, and hierarchical access control. In addition, it will lead to a reliable, guaranteed sub-linear search which returns results within a bounded interval of time and with a smaller amount of generated traffic within each domain.

Keywords: Grid computing, grid information service, P2P, resource discovery.

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Authors: Pin-Hsu Kao, Wen-Shou Tseng, Hung-Ming Tai, Yuan-Ming Chang, Jenh-Yih Juang

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We report a lithography-free approach to fabricate the biomimetics, quasi-beehive Si nanostructures (QBSNs), on Si-substrates. The self-assembled SiGe nanoislands via the strain induced surface roughening (Asaro-Tiller-Grinfeld instability) during in-situ annealing play a key role as patterned sacrifice regions for subsequent reactive ion etching (RIE) process performed for fabricating quasi-beehive nanostructures on Si-substrates. As the measurements of field emission, the bare QBSNs show poor field emission performance, resulted from the existence of the native oxide layer which forms an insurmountable barrier for electron emission. In order to dramatically improve the field emission characteristics, the platinum nanopillars (Pt-NPs) were deposited on QBSNs to form Pt-NPs/QBSNs heterostructures. The turn-on field of Pt-NPs/QBSNs is as low as 2.29 V/μm (corresponding current density of 1 μA/cm2), and the field enhancement factor (β-value) is significantly increased to 6067. More importantly, the uniform and continuous electrons excite light emission, due to the surrounding filed emitters from Pt-NPs/QBSNs, can be easily obtained. This approach does not require an expensive photolithographic process and possesses great potential for applications.

Keywords: Biomimetics, quasi-beehive Si, SiGe nanoislands, platinum nanopillars, field emission.

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Authors: Min Sang Lee, Hee Jae Shin, In Pyo Cha, Sun Ho Ko, Hyun Kyung Yoon, Hong Gun Kim, Lee Ku Kwac

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The prepreg process among the CFRP (Carbon Fiber Reinforced Plastic) forming methods is the short term of ‘Pre-impregnation’, which is widely used for aerospace composites that require a high quality property such as a fiber-reinforced woven fabric, in which an epoxy hardening resin is impregnated the reality. However, that this process requires continuous researches and developments for its commercialization because the delamination characteristically develops between the layers when a great weight is loaded from outside to supplement such demerit, three lamination methods among the prepreg lamination methods of CFRP were designed to minimize the delamination between the layers due to external impacts. Further, the newly designed methods and the existing lamination methods were analyzed through a mechanical characteristic test, Interlaminar Shear Strength test. The Interlaminar Shear Strength test result confirmed that the newly proposed three lamination methods, i.e. the Roll, Half and Zigzag laminations, presented more excellent strengths compared to the conventional Ply lamination. The interlaminar shear strength in the roll method with relatively dense fiber distribution was approximately 1.75% higher than that in the existing ply lamination method, and in the half method, it was approximately 0.78% higher.

Keywords: Carbon Fiber Reinforced Plastic (CFRP), Pre-Impregnation, Laminating Method, Interlaminar Shear Strength (ILSS).

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Authors: Gökhan Polat, Dicle Kocaoğlu Yılmazer, Muhlis Nezihi Sarıdede

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Iron oxides are the main input to produce iron in integrated iron and steel plants. During production of iron from iron oxides, some wastes with high iron content occur. These main wastes can be classified as basic oxygen furnace (BOF) sludge, flue dust and rolling scale. Recycling of these wastes has a great importance for both environmental effects and reduction of production costs. In this study, recycling experiments were performed on basic oxygen furnace sludge, flue dust and rolling scale which contain 53.8%, 54.3% and 70.2% iron respectively. These wastes were mixed together with coke as reducer and these mixtures are pressed to obtain cylindrical briquettes. These briquettes were pressed under various compacting forces from 1 ton to 6 tons. Also, both stoichiometric and twice the stoichiometric cokes were added to investigate effect of coke amount on reduction properties of the waste mixtures. Then, these briquettes were reduced at 1000°C and 1100°C during 30, 60, 90, 120 and 150 min in a muffle furnace. According to the results of reduction experiments, the effect of compacting force, temperature and time on reduction ratio of the wastes were determined. It is found that 1 ton compacting force, 150 min reduction time and 1100°C are the optimum conditions to obtain reduction ratio higher than 75%.

Keywords: Iron oxide wastes, reduction, coke, recycling.

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Authors: A. Muthuramalingam, S. Himavathi

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Harmonic pollution and low power factor in power systems caused by power converters have been of great concern. To overcome these problems several converter topologies using advanced semiconductor devices and control schemes have been proposed. This investigation is to identify a low cost, small size, efficient and reliable ac to dc converter to meet the input performance index of UPS. The performance of single phase and three phase ac to dc converter along with various control techniques are studied and compared. The half bridge converter topology with linear current control is identified as most suitable. It is simple, energy efficient because of single switch power loss and transformer-less operation of UPS. The results are validated practically using a prototype built using IGBT and analog controller. The performance for both single and three-phase system is verified. Digital implementation of closed loop control achieves higher reliability. Its cost largely depends on chosen bit precision. The minimal bit precision for optimum converter performance is identified as 16-bit with fixed-point operation. From the investigation and practical implementation it is concluded that half bridge ac – dc converter along with digital linear controller meets the performance index of UPS for single and three phase systems.

Keywords: PFC, energy efficient, half bridge, ac-dc converter, boost topology, linear current control, digital bit precision.

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Authors: Parvinder Singh Sandhu, Dalwinder Singh Salaria, Hardeep Singh

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Software Reusability is primary attribute of software quality. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. In this paper, we have devised the framework of metrics that uses McCabe-s Cyclometric Complexity Measure for Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling Metric values of the software component as input attributes and calculated reusability of the software component. Here, comparative analysis of the fuzzy, Neuro-fuzzy and Fuzzy-GA approaches is performed to evaluate the reusability of software components and Fuzzy-GA results outperform the other used approaches. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: Software Reusability, Software Metrics, Neural Networks, Genetic Algorithm, Fuzzy Logic.

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: Comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control.

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Authors: C. Edwards, P. Parker

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Flight school members are facing a major disruption in the technologies available for them to fly as electric planes enter the aviation industry. The year 2020 marked a new era in aviation with the first type certification of an electric plane. The Pipistrel Velis Electro is a two-seat electric aircraft (e-plane) designed for flight training. Electric flight training has the potential to deeply reduce emissions, noise, and cost of pilot training. Though these are all attractive features, understanding must be developed on the perceptions of the essential actor of the technology, the pilot. This study asks student pilots, flight instructors, flight center managers, and other members of flight schools about their perceptions of e-planes. The questions were divided into three categories: safety and trust of the technology, expected costs in comparison to conventional planes, and interest in the technology, including their desire to fly electric planes. Participants were recruited from flight schools using a protocol approved by the Office of Research Ethics. None of these flight schools have an e-plane in their fleet so these views are based on perceptions rather than direct experience. The results revealed perceptions that were strongly positive with many qualitative comments indicating great excitement about the potential of the new electric aviation technology. Some concerns were raised regarding battery endurance limits. Overall, the flight school community is clearly in favor of introducing electric propulsion technology and reducing the environmental impacts of their industry.

Keywords: electric planes, flight training, green aircraft, student pilots, sustainable aviation

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Authors: Sami Baraketi, Jean-Marie Garcia, Olivier Brun

Abstract:

Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: O. Rahli, N. Mimouni, R. Bennacer, K. Bouhadef

Abstract:

This numerical study investigates the travelling wave’s appearance and the behavior of Poiseuille-Rayleigh-Benard (PRB) flow induced in 3D thermosolutale mixed convection (TSMC) in horizontal rectangular channels. The governing equations are discretized by using a control volume method with third order Quick scheme in approximating the advection terms. Simpler algorithm is used to handle coupling between the momentum and continuity equations. To avoid the excessively high computer time, full approximation storage (FAS) with full multigrid (FMG) method is used to solve the problem. For a broad range of dimensionless controlling parameters, the contribution of this work is to analyzing the flow regimes of the steady longitudinal thermoconvective rolls (noted R//) for both thermal and mass transfer (TSMC). The transition from the opposed volume forces to cooperating ones, considerably affects the birth and the development of the longitudinal rolls. The heat and mass transfers distribution are also examined.

Keywords: Heat and mass transfer, mixed convection, Poiseuille-Rayleigh-Benard flow, rectangular duct.

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Authors: M. Arulvizhi

Abstract:

In Multiuser MIMO communication systems, interuser interference has a strong impact on the transmitted signals. Precoding technique schemes are employed for multiuser broadcast channels to suppress an interuser interference. Different Linear and nonlinear precoding schemes are there. For the massive system dimension, it is difficult to design an appropriate precoding algorithm with low computational complexity and good error rate performance at the same time over fading channels. This paper describes the error rate performance of precoding schemes over fading channels with the assumption of perfect channel state information at the transmitter. To estimate the bit error rate performance, different propagation environments namely, Rayleigh, Rician and Nakagami fading channels have been offered. This paper presents the error rate performance comparison of these fading channels based on precoding methods like Channel Inversion and Dirty paper coding for multiuser broadcasting system. MATLAB simulation has been used. It is observed that multiuser system achieves better error rate performance by Dirty paper coding over Rayleigh fading channel.

Keywords: Multiuser MIMO, channel inversion precoding, dirty paper coding, fading channels, BER.

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Authors: Ali N. Suri, Ahmad A. Al-Makhlufi

Abstract:

In this paper the problem of buckling of plates on foundation of finite length and with different side support is studied.

The Finite Strip Method is used as tool for the analysis. This method uses finite strip elastic, foundation, and geometric matrices to build the assembly matrices for the whole structure, then after introducing boundary conditions at supports, the resulting reduced matrices is transformed into a standard Eigenvalue-Eigenvector problem. The solution of this problem will enable the determination of the buckling load, the associated buckling modes and the buckling wave length.

To carry out the buckling analysis starting from the elastic, foundation, and geometric stiffness matrices for each strip a computer program FORTRAN list is developed.

Since stiffness matrices are function of wave length of buckling, the computer program used an iteration procedure to find the critical buckling stress for each value of foundation modulus and for each boundary condition.

The results showed the use of elastic medium to support plates subject to axial load increase a great deal the buckling load, the results found are very close with those obtained by other analytical methods and experimental work.

The results also showed that foundation compensates the effect of the weakness of some types of constraint of side support and maximum benefit found for plate with one side simply supported the other free.

Keywords: Buckling, Finite Strip, Different Sides Support, Plates on Foundation.

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Authors: Kentaro Miyoko, Yoshihiko Mori, Yugo Ikeda, Yoshihiro Nishino, Yong-Bok Choi, Hiromi Okada

Abstract:

Optical burst switching (OBS) has been proposed to realize the next generation Internet based on the wavelength division multiplexing (WDM) network technologies. In the OBS, the burst contention is one of the major problems. The deflection routing has been designed for resolving the problem. However, the deflection routing becomes difficult to prevent from the burst contentions as the network load becomes high. In this paper, we introduce a flow rate control methods to reduce burst contentions. We propose new flow rate control methods based on the leaky bucket algorithm and deflection routing, i.e. separate leaky bucket deflection method, and dynamic leaky bucket deflection method. In proposed methods, edge nodes which generate data bursts carry out the flow rate control protocols. In order to verify the effectiveness of the flow rate control in OBS networks, we show that the proposed methods improve the network utilization and reduce the burst loss probability through computer simulations.

Keywords: Optical burst switching, OBS, flow rate control.

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