Search results for: Case-based reasoning; Breast cancer diagnosis; Genetic algorithm; Wrapper feature selection

Authors: Abbas Ali Mahmood Karwi

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Accurate timing alignment and stability is important to maximize the true counts and minimize the random counts in positron emission tomography So signals output from detectors must be centering with the two isotopes to pre-operation and fed signals into four units of pulse-processing units, each unit can accept up to eight inputs. The dual source computed tomography consist two units on the left for 15 detector signals of Cs-137 isotope and two units on the right are for 15 detectors signals of Co-60 isotope. The gamma spectrum consisting of either single or multiple photo peaks. This allows for the use of energy discrimination electronic hardware associated with the data acquisition system to acquire photon counts data with a specific energy, even if poor energy resolution detectors are used. This also helps to avoid counting of the Compton scatter counts especially if a single discrete gamma photo peak is emitted by the source as in the case of Cs-137. In this study the polyenergetic version of the alternating minimization algorithm is applied to the dual energy gamma computed tomography problem.

Keywords: Alignment, Spectrum, Laser, Detectors, Image

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Authors: R. Walha, F. Drira, H. El-Abed, A. M. Alimi

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The Automatic Speech Recognition (ASR) applied to Arabic language is a challenging task. This is mainly related to the language specificities which make the researchers facing multiple difficulties such as the insufficient linguistic resources and the very limited number of available transcribed Arabic speech corpora. In this paper, we are interested in the development of a HMM-based ASR system for Standard Arabic (SA) language. Our fundamental research goal is to select the most appropriate acoustic parameters describing each audio frame, acoustic models and speech recognition unit. To achieve this purpose, we analyze the effect of varying frame windowing (size and period), acoustic parameter number resulting from features extraction methods traditionally used in ASR, speech recognition unit, Gaussian number per HMM state and number of embedded re-estimations of the Baum-Welch Algorithm. To evaluate the proposed ASR system, a multi-speaker SA connected-digits corpus is collected, transcribed and used throughout all experiments. A further evaluation is conducted on a speaker-independent continue SA speech corpus. The phonemes recognition rate is 94.02% which is relatively high when comparing it with another ASR system evaluated on the same corpus.

Keywords: ASR, HMM, acoustical analysis, acoustic modeling, Standard Arabic language

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Authors: K. Vinoth Kumar, M.P. Selvan

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This paper presents a simple approach for load flow analysis of a radial distribution network. The proposed approach utilizes forward and backward sweep algorithm based on Kirchoff-s current law (KCL) and Kirchoff-s voltage law (KVL) for evaluating the node voltages iteratively. In this approach, computation of branch current depends only on the current injected at the neighbouring node and the current in the adjacent branch. This approach starts from the end nodes of sub lateral line, lateral line and main line and moves towards the root node during branch current computation. The node voltage evaluation begins from the root node and moves towards the nodes located at the far end of the main, lateral and sub lateral lines. The proposed approach has been tested using four radial distribution systems of different size and configuration and found to be computationally efficient.

Keywords: constant current load, constant impedance load, constant power load, forward–backward sweep, load flow analysis, radial distribution system.

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Authors: Prashant P. Bedekar, Sudhir R. Bhide, Vijay S. Kale

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Overcurrent (OC) relays are the major protection devices in a distribution system. The operating time of the OC relays are to be coordinated properly to avoid the mal-operation of the backup relays. The OC relay time coordination in ring fed distribution networks is a highly constrained optimization problem which can be stated as a linear programming problem (LPP). The purpose is to find an optimum relay setting to minimize the time of operation of relays and at the same time, to keep the relays properly coordinated to avoid the mal-operation of relays. This paper presents two phase simplex method for optimum time coordination of OC relays. The method is based on the simplex algorithm which is used to find optimum solution of LPP. The method introduces artificial variables to get an initial basic feasible solution (IBFS). Artificial variables are removed using iterative process of first phase which minimizes the auxiliary objective function. The second phase minimizes the original objective function and gives the optimum time coordination of OC relays.

Keywords: Constrained optimization, LPP, Overcurrent relaycoordination, Two-phase simplex method.

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Authors: P. Vijaya Laxmi, V. Goswami, V. Suchitra

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This paper presents a finite buffer renewal input single working vacation and vacation interruption queue with state dependent services and state dependent vacations, which has a wide range of applications in several areas including manufacturing, wireless communication systems. Service times during busy period, vacation period and vacation times are exponentially distributed and are state dependent. As a result of the finite waiting space, state dependent services and state dependent vacation policies, the analysis of these queueing models needs special attention. We provide a recursive method using the supplementary variable technique to compute the stationary queue length distributions at pre-arrival and arbitrary epochs. An efficient computational algorithm of the model is presented which is fast and accurate and easy to implement. Various performance measures have been discussed. Finally, some special cases and numerical results have been depicted in the form of tables and graphs. 

Keywords: State Dependent Service, Vacation Interruption, Supplementary Variable, Single Working Vacation, Blocking Probability.

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Authors: V. Sudha, D. Sriram Kumar

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Orthogonal Frequency Division Multiplexing (OFDM) has been used in many advanced wireless communication systems due to its high spectral efficiency and robustness to frequency selective fading channels. However, the major concern with OFDM system is the high peak-to-average power ratio (PAPR) of the transmitted signal. Some of the popular techniques used for PAPR reduction in OFDM system are conventional partial transmit sequences (CPTS) and clipping. In this paper, a parallel combination/hybrid scheme of PAPR reduction using clipping and CPTS algorithms is proposed. The proposed method intelligently applies both the algorithms in order to reduce both PAPR as well as computational complexity. The proposed scheme slightly degrades bit error rate (BER) performance due to clipping operation and it can be reduced by selecting an appropriate value of the clipping ratio (CR). The simulation results show that the proposed algorithm achieves significant PAPR reduction with much reduced computational complexity.

Keywords: CCDF, OFDM, PAPR, PTS.

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Authors: Eva Nedeliakova, Jaroslav Masek, Juraj Camaj

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This article describes the results of research focused on quality of railway freight transport services. Improvement of these services has a crucial importance in customer considering on the future use of railway transport. Processes filling the customer demands and output quality assessment were defined as a part of the research. In this contribution is introduced the map of quality planning and the algorithm of applied methodology. It characterizes a model which takes into account characters of transportation with linking a perception services quality in ordinary and extraordinary operation. Despite the fact that rail freight transport has its solid position in the transport market, lots of carriers worldwide have been experiencing a stagnation for a couple of years. Therefore, specific results of the research have a significant importance and belong to numerous initiatives aimed to develop and support railway transport not only by creating a single railway area or reducing noise but also by promoting railway services. This contribution is focused also on the application of dynamic quality models which represent an innovative method of evaluation quality services. Through this conception, time factor, expected, and perceived quality in each moment of the transportation process can be taken into account.

Keywords: Quality, railway, transport, service.

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya, M. Sharmila

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An extensive amount of work has been done in data clustering research under the unsupervised learning technique in Data Mining during the past two decades. Moreover, several approaches and methods have been emerged focusing on clustering diverse data types, features of cluster models and similarity rates of clusters. However, none of the single clustering algorithm exemplifies its best nature in extracting efficient clusters. Consequently, in order to rectify this issue, a new challenging technique called Cluster Ensemble method was bloomed. This new approach tends to be the alternative method for the cluster analysis problem. The main objective of the Cluster Ensemble is to aggregate the diverse clustering solutions in such a way to attain accuracy and also to improve the eminence the individual clustering algorithms. Due to the massive and rapid development of new methods in the globe of data mining, it is highly mandatory to scrutinize a vital analysis of existing techniques and the future novelty. This paper shows the comparative analysis of different cluster ensemble methods along with their methodologies and salient features. Henceforth this unambiguous analysis will be very useful for the society of clustering experts and also helps in deciding the most appropriate one to resolve the problem in hand.

Keywords: Clustering, Cluster Ensemble Methods, Coassociation matrix, Consensus Function, Median Partition.

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Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

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Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

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Authors: Andre Slonopas, Warren Thompson, Zona Kostic

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Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicates via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.

Keywords: Moving Target Defense, cybersecurity, network security, hopping randomization, software defined network, network security theory.

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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: 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: Lynette Sheridan Burns, Benjamin J. Matthews

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The context of post-industrial journalism is one in which the material circumstances of mechanical publication have been displaced by digital technologies, increasing the distance between the orthodoxy of the newsroom and the culture of journalistic writing. Content is, with growing frequency, created for delivery via the internet, publication on web-based ‘platforms’ and consumption on screen media. In this environment, the question is not ‘who is a journalist?’ but ‘what is journalism?’ today. The changes bring into sharp relief new distinctions between journalistic work and journalistic labor, providing a key insight into the current transition between the industrial journalism of the 20^th century, and the post-industrial journalism of the present. In the 20^th century, the work of journalists and journalistic labor went hand-in-hand as most journalists were employees of news organizations, whilst in the 21^st century evidence of a decoupling of ‘acts of journalism’ (work) and journalistic employment (labor) is beginning to appear. This 'decoupling' of the work and labor that underpins journalism practice is far reaching in its implications, not least for institutional structures. Under these conditions we are witnessing the emergence of expanded ‘entrepreneurial’ journalism, based on smaller, more independent and agile - if less stable - enterprise constructs that are a feature of creative industries. Entrepreneurial journalism is realized in a range of organizational forms from social enterprise, through to profit driven start-ups and hybrids of the two. In all instances, however, the primary motif of the organization is an ideological definition of journalism. An example is the Scoop Foundation for Public Interest Journalism in New Zealand, which owns and operates Scoop Publishing Limited, a not for profit company and social enterprise that publishes an independent news site that claims to have over 500,000 monthly users. Our paper demonstrates that this journalistic work meets the ideological definition of journalism; conducted within the creative industries using an innovative organizational structure that offers a new, viable post-industrial future for journalism.

Keywords: Creative industries, digital communication, journalism, post-industrial.

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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: 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: 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: Muhamad Sani Buang, Shahrul Azam Abdullah, Juri Saedon

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There is not much effective guideline on development of design parameters selection on spring back for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for spring back in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in Uchannel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24 ). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on spring back of flange angle (β2 ) and wall opening angle (β1 ), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the spring back behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for spring back was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values.  

Keywords: Advance high strength steel, U-channel process, Springback, Design of Experiment, Optimization, Response Surface Methodology (RSM).

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Authors: Guadalupe Pérez, Jorge Islas, Mirna Guevara, Raúl Suárez

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Jatropha curcas is a perennial oleaginous plant that is currently considered an energy crop with high potential as an environmentally sustainable biofuel. During the last decades, research in biofuels has grown in tropical and subtropical regions in Latin America. However, as far we know, there are no reports on the growth and yield patterns of Jatropha curcas under the specific agro climatic scenarios of the State of Morelos, Mexico. This study presents the results of 52 months monitoring of 10 toxic and non-toxic ecotypes of Jatropha curcas (E1M, E2M, E3M, E4M, E5M, E6O, E7O, E8O, E9C, E10C) in an experimental plantation with minimum watering and fertilization resources. The main objective is to identify the ecotypes with the highest potential as biodiesel raw material in the select region, by developing experimental information. Specifically, we monitored biophysical and growth parameters, including plant survival and seed production (at the end of month 52), to study the performance of each ecotype and to establish differences among the variables of morphological growth, net seed oil content, and toxicity. To analyze the morphological growth, a statistical approach to the biophysical parameters was used; the net seed oil content -80 to 192 kg/ha- was estimated with the first harvest; and the toxicity was evaluated by examining the phorbol ester concentration (µg/L) in the oil extracted from the seeds. The comparison and selection of ecotypes was performed through a methodology developed based on the normalization of results. We identified four outstanding ecotypes (E1M, E2M, E3M, and E4M) that can be used to establish Jatropha curcas as energy crops in the state of Morelos for feasible agro-industrial production of biodiesel and other products related to the use of biomass.

Keywords: Biodiesel production, Jatropha curcas, morphologic growth, toxic and non-toxic ecotypes, seed oil content.

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Authors: Ramaswamy Palaniappan

Abstract:

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: S. Piramu Kailasam

Abstract:

This study is expected to compress true color image with compression algorithms in color spaces to provide high compression rates. The need of high compression ratio is to improve storage space. Alternative aim is to rank compression algorithms in a suitable color space. The dataset is sequence of true color images with size 128 x 128. HAAR Wavelet is one of the famous wavelet transforms, has great potential and maintains image quality of color images. HAAR wavelet Transform using Set Partitioning in Hierarchical Trees (SPIHT) algorithm with different color spaces framework is applied to compress sequence of images with angles. Embedded Zerotrees of Wavelet (EZW) is a powerful standard method to sequence data. Hence the proposed compression frame work of HAAR wavelet, xyz color space, morphological gradient and applied image with EZW compression, obtained improvement to other methods, in terms of Compression Ratio, Mean Square Error, Peak Signal Noise Ratio and Bits Per Pixel quality measures.

Keywords: Color Spaces, HAAR Wavelet, Morphological Gradient, Embedded Zerotrees Wavelet Compression.

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Authors: Alexander Y. Vaninsky

Abstract:

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: O. Abramova, L. Abukova, A. Goreva, G. Isaeva

Abstract:

The present work was made for the purpose of evaluating the interstitial water’s role in the mobilization of metal elements of clay deposits and occurrences in sedimentary formation in the hydro-geological basins. The experiments were performed by using a special facility, which allows adjusting the pressure, temperature, and the frequency of the acoustic vibrations. The dates for study were samples of the oil shales (Baltic career, O₂kk) and clay rocks, mainly montmorillonite composition (Borehole SG-12000, the depth of selection 1000–3600 m, the Azov-Kuban trough, N₁). After interstitial water squeezing from the rock samples, decrease in the original content of the rock forming components including trace metals V, Cr, Co, Ni, Cu, Zn, Zr, Mo, Pb, W, Ti, and others was recorded. The experiments made it possible to evaluate the ore elements output and organic matters with the interstitial waters. Calculations have shown that, in standard conditions, from each ton of the oil shales, 5-6 kg of ore elements and 9-10 kg of organic matter can be escaped. A quantity of matter, migrating from clays in the process of solidification, is changed depending on the lithogenesis stage: more recent unrealized deposits lose more ore and organic materials than the clay rocks, selected from depth over 3000 m. Each ton of clays in the depth interval 1000-1500 m is able to generate 3-5 kg of the ore elements and 6-8 kg of the organic matters. The interstitial waters are a freight forwarder over transferring these matters in the reservoir beds. It was concluded that the interstitial waters which escaped from the study samples are solutions with abnormal high concentrations of the metals and organic matters. In the discharge zones of the sediment basins, such fluids can create paragenetic associations of the sedimentary-catagenetic ore and hydrocarbon mineral resources accumulations.

Keywords: Hydrocarbons, ore genesis, paragenesis, interstitial waters.

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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

Abstract:

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

Abstract:

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

Abstract:

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: 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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