Search results for: Synthetic data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7566

Search results for: Synthetic data

7536 In Vitro Study of Coded Transmission in Synthetic Aperture Ultrasound Imaging Systems

Authors: Ihor Trots, Yuriy Tasinkevych, Andrzej Nowicki, Marcin Lewandowski

Abstract:

In the paper the study of synthetic transmit aperture method applying the Golay coded transmission for medical ultrasound imaging is presented. Longer coded excitation allows to increase the total energy of the transmitted signal without increasing the peak pressure. Moreover signal-to-noise ratio and penetration depth are improved while maintaining high ultrasound image resolution. In the work the 128-element linear transducer array with 0.3 mm inter-element spacing excited by one cycle and the 8 and 16- bit Golay coded sequences at nominal frequency 4 MHz was used. To generate a spherical wave covering the full image region a single element transmission aperture was used and all the elements received the echo signals. The comparison of 2D ultrasound images of the tissue mimicking phantom and in vitro measurements of the beef liver is presented to illustrate the benefits of the coded transmission. The results were obtained using the synthetic aperture algorithm with transmit and receive signals correction based on a single element directivity function.

Keywords: Golay coded sequences, radiation pattern, signal processing, synthetic aperture, ultrasound imaging.

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7535 Error Effects on SAR Image Resolution using Range Doppler Imaging Algorithm

Authors: Su Su Yi Mon, Fang Jiancheng

Abstract:

Synthetic Aperture Radar (SAR) is an imaging radar form by taking full advantage of the relative movement of the antenna with respect to the target. Through the simultaneous processing of the radar reflections over the movement of the antenna via the Range Doppler Algorithm (RDA), the superior resolution of a theoretical wider antenna, termed synthetic aperture, is obtained. Therefore, SAR can achieve high resolution two dimensional imagery of the ground surface. In addition, two filtering steps in range and azimuth direction provide accurate enough result. This paper develops a simulation in which realistic SAR images can be generated. Also, the effect of velocity errors in the resulting image has also been investigated. Taking some velocity errors into account, the simulation results on the image resolution would be presented. Most of the times, algorithms need to be adjusted for particular datasets, or particular applications.

Keywords: Synthetic Aperture Radar (SAR), Range Doppler Algorithm (RDA), Image Resolution.

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7534 Dynamic Response of Wind Turbines to Theoretical 3D Seismic Motions Taking into Account the Rotational Component

Authors: L. Hermanns, M.A. Santoyo, L. E. Quirós, J. Vega, J. M. Gaspar-Escribano, B. Benito

Abstract:

We study the dynamic response of a wind turbine structure subjected to theoretical seismic motions, taking into account the rotational component of ground shaking. Models are generated for a shallow moderate crustal earthquake in the Madrid Region (Spain). Synthetic translational and rotational time histories are computed using the Discrete Wavenumber Method, assuming a point source and a horizontal layered earth structure. These are used to analyze the dynamic response of a wind turbine, represented by a simple finite element model. Von Mises stress values at different heights of the tower are used to study the dynamical structural response to a set of synthetic ground motion time histories

Keywords: Synthetic seismograms, rotations, wind turbine, dynamic structural response

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7533 Ablation, Mechanical and Thermal Properties of Fiber/Phenolic Matrix Composites

Authors: N. Winya, S. Chankapoe, C. Kiriratnikom

Abstract:

In this study, an ablation, mechanical and thermal properties of a rocket motor insulation from phenolic/ fiber matrix composites forming a laminate with different fiber between fiberglass and locally available synthetic fibers. The phenolic/ fiber matrix composites was mechanics and thermal properties by means of tensile strength, ablation, TGA and DSC. The design of thermal insulation involves several factors.Determined the mechanical properties according to MIL-I-24768: Density >1.3 g/cm3, Tensile strength >103 MPa and Ablation <0.14 mm/s to optimization formulation of phenolic binder, fiber glass reinforcement and other ingredients were conducted after that the insulation prototype was formed and cured. It was found that the density of phenolic/fiberglass composites and phenolic/ synthetic fiber composite was 1.66 and 1.41 g/cm3 respectively. The ablative of phenolic/fiberglass composites and phenolic/ synthetic fiber composite was 0.13 and 0.06 mm/s respectively.

Keywords: Phenolic Resin, Ablation, Rocket Motor, Insulation

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7532 The Effect of Ethylene Glycol to Soy Polyurethane Foam Classifications

Authors: Flora Elvistia Firdaus

Abstract:

Soy polyol obtained from hydroxylation of soy epoxide with ethylene glycol were prepared as pre-polyurethane. The two step process method were applied in the polyurethane synthesis. The blending of soy polyol with synthetic polyol then simultaneously carried out to TDI (2,4): MDI (4,4-) (80:20), blowing agent, and surfactant. Ethylene glycol were not taking part in the polyurethane synthesis. The inclusion of ethylene glycol were used as a control. Characterization of polyurethane foam through impact resillience, indentation deflection, and density can visualize the polyurethane classifications.

Keywords: Ethylene glycol, polyurethane foam, soy polyol, synthetic polyol

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7531 Selective Separation of Lead and Mercury Ions from Synthetic Produced Water via a Hollow Fiber Supported Liquid Membrane

Authors: S. Suren, U. Pancharoen

Abstract:

A double module hollow fiber supported liquid membrane (HFSLM) was applied to selectively separate lead and mercury ions from dilute synthetic produced water. The experiments were investigated on several variables: types of extractants (D2EHPA, Cyanex 471, Aliquat 336, and TOA), concentration of the selected extractant and operating time. The results clearly showed that the double module HFSLM could selectively separate Pb(II) and Hg(II) in feed solution at a very low concentration to less than the regulatory discharge limit of 0.2 and 0.005 mg/L issued by the Ministry of Industry and the Ministry of Natural Resource Environment, Thailand. The highest extractions of lead and mercury ions from synthetic produced water were 96% and 100% using 0.03 M D2EHPA and 0.06 M Aliquat 336 as the extractant for the first and second modules.

Keywords: Hollow fiber, Lead ions, Liquid membrane, Mercury ions, Selective separation

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7530 Laser Ultrasonic Imaging Based on Synthetic Aperture Focusing Technique Algorithm

Authors: Sundara Subramanian Karuppasamy, Che Hua Yang

Abstract:

In this work, the laser ultrasound technique has been used for analyzing and imaging the inner defects in metal blocks. To detect the defects in blocks, traditionally the researchers used piezoelectric transducers for the generation and reception of ultrasonic signals. These transducers can be configured into the sparse and phased array. But these two configurations have their drawbacks including the requirement of many transducers, time-consuming calculations, limited bandwidth, and provide confined image resolution. Here, we focus on the non-contact method for generating and receiving the ultrasound to examine the inner defects in aluminum blocks. A Q-switched pulsed laser has been used for the generation and the reception is done by using Laser Doppler Vibrometer (LDV). Based on the Doppler effect, LDV provides a rapid and high spatial resolution way for sensing ultrasonic waves. From the LDV, a series of scanning points are selected which serves as the phased array elements. The side-drilled hole of 10 mm diameter with a depth of 25 mm has been introduced and the defect is interrogated by the linear array of scanning points obtained from the LDV. With the aid of the Synthetic Aperture Focusing Technique (SAFT) algorithm, based on the time-shifting principle the inspected images are generated from the A-scan data acquired from the 1-D linear phased array elements. Thus the defect can be precisely detected with good resolution.

Keywords: Laser ultrasonics, linear phased array, nondestructive testing, synthetic aperture focusing technique, ultrasonic imaging.

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7529 Retrospective Synthetic Focusing with Correlation Weighting for Very High Frame Rate Ultrasound

Authors: Chang-Lin Hu, Yao-You Cheng, Meng-Lin Li

Abstract:

The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.

Keywords: retrospective synthetic focusing, high frame rate, correlation weighting.

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7528 Processes Simulation Study of Coal to Methanol Based on Gasification Technology

Authors: Po-Chuang Chen, Hsiu-Mei Chiu, Yau-Pin Chyou, Chiou-Shia Yu

Abstract:

This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.

Keywords: Gasification, Methanol, LPMEOH, System-levelsimulation.

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7527 MIBiClus: Mutual Information based Biclustering Algorithm

Authors: Neelima Gupta, Seema Aggarwal

Abstract:

Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.

Keywords: Biclustering, mutual information.

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7526 Self-Healing Performance of Heavyweight Concrete with Steam Curing

Authors: Hideki Igawa, Yoshinori Kitsutaka, Takashi Yokomuro, Hideo Eguchi

Abstract:

In this study, the crack self-healing performance of the heavyweight concrete used in the walls of containers and structures designed to shield radioactive materials was investigated. A steam curing temperature that preserves self-healing properties and demolding strength was identified. The presented simultaneously mixing method using the expanding material and the fly ash in the process of admixture can maximize the self-curing performance. Also adding synthetic fibers in the heavyweight concrete improved the self-healing performance.

Keywords: Expanding material, heavyweight concrete, self-healing performance, synthetic fiber.

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7525 Unsupervised Outlier Detection in Streaming Data Using Weighted Clustering

Authors: Yogita, Durga Toshniwal

Abstract:

Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.

Keywords: Concept Evolution, Irrelevant Attributes, Streaming Data, Unsupervised Outlier Detection.

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7524 Mean Shift-based Preprocessing Methodology for Improved 3D Buildings Reconstruction

Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

Abstract:

In this work, we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift.

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7523 Synthesis and Characterization of ZnO and Fe3O4 Nanocrystals from Oleat-based Organometallic Compounds

Authors: PoiSim Khiew, WeeSiong Chiu, ThianKhoonTan, Shahidan Radiman, Roslan Abd-Shukor, Muhammad Azmi Abd-Hamid, ChinHua Chia

Abstract:

Magnetic and semiconductor nanomaterials exhibit novel magnetic and optical properties owing to their unique size and shape-dependent effects. With shrinking the size down to nanoscale region, various anomalous properties that normally not present in bulk start to dominate. Ability in harnessing of these anomalous properties for the design of various advance electronic devices is strictly dependent on synthetic strategies. Hence, current research has focused on developing a rational synthetic control to produce high quality nanocrystals by using organometallic approach to tune both size and shape of the nanomaterials. In order to elucidate the growth mechanism, transmission electron microscopy was employed as a powerful tool in performing real time-resolved morphologies and structural characterization of magnetic (Fe3O4) and semiconductor (ZnO) nanocrystals. The current synthetic approach is found able to produce nanostructures with well-defined shapes. We have found that oleic acid is an effective capping ligand in preparing oxide-based nanostructures without any agglomerations, even at high temperature. The oleate-based precursors and capping ligands are fatty acid compounds, which are respectively originated from natural palm oil with low toxicity. In comparison with other synthetic approaches in producing nanostructures, current synthetic method offers an effective route to produce oxide-based nanomaterials with well-defined shapes and good monodispersity. The nanocystals are well-separated with each other without any stacking effect. In addition, the as-synthesized nanopellets are stable in terms of chemically and physically if compared to those nanomaterials that are previous reported. Further development and extension of current synthetic strategy are being pursued to combine both of these materials into nanocomposite form that will be used as “smart magnetic nanophotocatalyst" for industry waste water treatment.

Keywords: Metal oxide nanomaterials, Nanophotocatalyst, Organometallic synthesis, Morphology Control

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7522 Content Based Sampling over Transactional Data Streams

Authors: Mansour Tarafdar, Mohammad Saniee Abade

Abstract:

This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.

Keywords: Sampling, data streams, closed frequent item set mining.

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7521 Cash Flow Optimization on Synthetic CDOs

Authors: Timothée Bligny, Clément Codron, Antoine Estruch, Nicolas Girodet, Clément Ginet

Abstract:

Collateralized Debt Obligations are not as widely used nowadays as they were before 2007 Subprime crisis. Nonetheless there remains an enthralling challenge to optimize cash flows associated with synthetic CDOs. A Gaussian-based model is used here in which default correlation and unconditional probabilities of default are highlighted. Then numerous simulations are performed based on this model for different scenarios in order to evaluate the associated cash flows given a specific number of defaults at different periods of time. Cash flows are not solely calculated on a single bought or sold tranche but rather on a combination of bought and sold tranches. With some assumptions, the simplex algorithm gives a way to find the maximum cash flow according to correlation of defaults and maturities. The used Gaussian model is not realistic in crisis situations. Besides present system does not handle buying or selling a portion of a tranche but only the whole tranche. However the work provides the investor with relevant elements on how to know what and when to buy and sell.

Keywords: Synthetic Collateralized Debt Obligation (CDO), Credit Default Swap (CDS), Cash Flow Optimization, Probability of Default, Default Correlation, Strategies, Simulation, Simplex.

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7520 Sophorolipids Production by Candida Bombicola using Synthetic Dairy Wastewater

Authors: A. Daverey, K. Pakshirajan, P. Sangeetha

Abstract:

Sophorolipids (SLs) production by the yeast Candida bombicola was studied in batch shake flasks using synthetic dairy wastewaters (SDWW) with or without any added external carbon and nitrogen sources. A maximum SLs production of 38.76 g/l was observed with the SDWW supplemented with low cost substrate of sugarcane molasses at 50 g/l and soybean oil at 50 g/l. When the SDWW was supplemented with more costly glucose, yeast extract, urea and soybean oil, the production, however, got lowered to only 29.49 g/l, but with a maximum biomass production of 17.38 g/l together with a complete utilization of the carbon sources.

Keywords: Candida bombicola, dairy wastewater, fat and oil, sophorolipids.

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7519 Compressive Properties of a Synthetic Bone Substitute for Vertebral Cancellous Bone

Authors: H. N. Mehmanparast, J.M. Mac-Thiong., Y. Petit

Abstract:

Transpedicular screw fixation in spinal fractures, degenerative changes, or deformities is a well-established procedure. However, important rate of fixation failure due to screw bending, loosening, or pullout are still reported particularly in weak bone stock in osteoporosis. To overcome the problem, mechanism of failure has to be fully investigated in vitro. Post-mortem human subjects are less accessible and animal cadavers comprise limitations due to different geometry and mechanical properties. Therefore, the development of a synthetic model mimicking the realistic human vertebra is highly demanded. A bone surrogate, composed of Polyurethane (PU) foam analogous to cancellous bone porous structure, was tested for 3 different densities in this study. The mechanical properties were investigated under uniaxial compression test by minimizing the end artifacts on specimens. The results indicated that PU foam of 0.32 g.cm-3 density has comparable mechanical properties to human cancellous bone in terms of young-s modulus and yield strength. Therefore, the obtained information can be considered as primary step for developing a realistic cancellous bone of human vertebral body. Further evaluations are also recommended for other density groups.

Keywords: Cancellous bone, Pedicle screw, Polyurethane foam, Synthetic bone

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7518 Synthetic Aperture Radar Remote Sensing Classification Using the Bag of Visual Words Model to Land Cover Studies

Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

Abstract:

Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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7517 Effects of Ultrasonic Treatment on Germination of Synthetic Sunflower Seeds

Authors: Thitiporn Machikowa, Thanawit Kulrattanarak, Sodchol Wonprasaid

Abstract:

One problem of synthetic sunflower cultivation is an erratic germination of the seeds. To improve the germination, presowing seed treatment with an ultrasound was tested. All treatments were carried out at 40 kHz frequency with the intensities of 40, 60, 80 and 100% of the ultrasonic generator total power (250 W) for the durations of 5, 10, 15 and 20 minutes. Data on seed germination percentage, seed vigor index (SVI), root and shoot lengths of seedlings were collected. The results showed that germination, SVI, root and shoot lengths of ultrasonic treated seedlings were different from the control, depending on intensity of the ultrasound. The effects of ultrasonic treatment were significant on germination, resulting in a maximum increase of 43% at 40 and 60% intensities compared to that of the control seeds. In addition, seedlings of these 2 treatments had higher SVI and longer root and shoot lengths than that of the control seedlings. All treatment durations resulted in higher germination and SVI, longer root and higher shoot lenghts of seedlings than the control. Among the duration treatments, only SVI and seedling root length were significantly different.

Keywords: Ultrasonic, germination, root length, shoot length, Helianthus annuus L.

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7516 Manifold Analysis by Topologically Constrained Isometric Embedding

Authors: Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel

Abstract:

We present a new algorithm for nonlinear dimensionality reduction that consistently uses global information, and that enables understanding the intrinsic geometry of non-convex manifolds. Compared to methods that consider only local information, our method appears to be more robust to noise. Unlike most methods that incorporate global information, the proposed approach automatically handles non-convexity of the data manifold. We demonstrate the performance of our algorithm and compare it to state-of-the-art methods on synthetic as well as real data.

Keywords: Dimensionality reduction, manifold learning, multidimensional scaling, geodesic distance, boundary detection.

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7515 An ensemble of Weighted Support Vector Machines for Ordinal Regression

Authors: Willem Waegeman, Luc Boullart

Abstract:

Instead of traditional (nominal) classification we investigate the subject of ordinal classification or ranking. An enhanced method based on an ensemble of Support Vector Machines (SVM-s) is proposed. Each binary classifier is trained with specific weights for each object in the training data set. Experiments on benchmark datasets and synthetic data indicate that the performance of our approach is comparable to state of the art kernel methods for ordinal regression. The ensemble method, which is straightforward to implement, provides a very good sensitivity-specificity trade-off for the highest and lowest rank.

Keywords: Ordinal regression, support vector machines, ensemblelearning.

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7514 Mathematical Model of Depletion of Forestry Resource: Effect of Synthetic Based Industries

Authors: Manisha Chaudhary, Joydip Dhar, Govind Prasad Sahu

Abstract:

A mathematical model is proposed considering the forest biomass density B(t), density of wood based industries W(t) and density of synthetic industries S(t). It is assumed that the forest biomass grows logistically in the absence of wood based industries, but depletion of forestry biomass is due to presence of wood based industries. The growth of wood based industries depends on B(t), while S(t) grows at a constant rate, independent of B(t). Further there is a competition between W(t) and S(t) according to market demand. The proposed model has four ecologically feasible steady states, namely, E1: forest biomass free and wood industries free equilibrium; E2: wood industries free equilibrium and two coexisting equilibria E∗1 , E∗2 . Behavior of the system near all feasible equilibria is analyzed using the stability theory of differential equations. In the proposed model, the natural depletion rate h1 is a crucial parameter and system exhibits Hopf-bifurcation about the non-trivial equilibrium with respect to h1. The analytical results are verified using numerical simulation.

Keywords: A mathematical model, Competition between wood based and synthetic industries, Hopf-bifurcation, Stability analysis.

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7513 Contour Estimation in Synthetic and Real Weld Defect Images based on Maximum Likelihood

Authors: M. Tridi, N. Nacereddine, N. Oucief

Abstract:

This paper describes a novel method for automatic estimation of the contours of weld defect in radiography images. Generally, the contour detection is the first operation which we apply in the visual recognition system. Our approach can be described as a region based maximum likelihood formulation of parametric deformable contours. This formulation provides robustness against the poor image quality, and allows simultaneous estimation of the contour parameters together with other parameters of the model. Implementation is performed by a deterministic iterative algorithm with minimal user intervention. Results testify for the very good performance of the approach especially in synthetic weld defect images.

Keywords: Contour, gaussian, likelihood, rayleigh.

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7512 Equilibrium, Kinetic and Thermodynamic Studies of the Biosorption of Textile Dye (Yellow Bemacid) onto Brahea edulis

Authors: G. Henini, Y. Laidani, F. Souahi, A. Labbaci, S. Hanini

Abstract:

Environmental contamination is a major problem being faced by the society today. Industrial, agricultural, and domestic wastes, due to the rapid development in the technology, are discharged in the several receivers. Generally, this discharge is directed to the nearest water sources such as rivers, lakes, and seas. While the rates of development and waste production are not likely to diminish, efforts to control and dispose of wastes are appropriately rising. Wastewaters from textile industries represent a serious problem all over the world. They contain different types of synthetic dyes which are known to be a major source of environmental pollution in terms of both the volume of dye discharged and the effluent composition. From an environmental point of view, the removal of synthetic dyes is of great concern. Among several chemical and physical methods, adsorption is a promising technique due to the ease of use and low cost compared to other applications in the process of discoloration, especially if the adsorbent is inexpensive and readily available. The focus of the present study was to assess the potentiality of Brahea edulis (BE) for the removal of synthetic dye Yellow bemacid (YB) from aqueous solutions. The results obtained here may transfer to other dyes with a similar chemical structure. Biosorption studies were carried out under various parameters such as mass adsorbent particle, pH, contact time, initial dye concentration, and temperature. The biosorption kinetic data of the material (BE) was tested by the pseudo first-order and the pseudo-second-order kinetic models. Thermodynamic parameters including the Gibbs free energy ΔG, enthalpy ΔH, and entropy ΔS have revealed that the adsorption of YB on the BE is feasible, spontaneous, and endothermic. The equilibrium data were analyzed by using Langmuir, Freundlich, Elovich, and Temkin isotherm models. The experimental results show that the percentage of biosorption increases with an increase in the biosorbent mass (0.25 g: 12 mg/g; 1.5 g: 47.44 mg/g). The maximum biosorption occurred at around pH value of 2 for the YB. The equilibrium uptake was increased with an increase in the initial dye concentration in solution (Co = 120 mg/l; q = 35.97 mg/g). Biosorption kinetic data were properly fitted with the pseudo-second-order kinetic model. The best fit was obtained by the Langmuir model with high correlation coefficient (R2 > 0.998) and a maximum monolayer adsorption capacity of 35.97 mg/g for YB.

Keywords: Adsorption, Brahea edulis, isotherm, yellow bemacid.

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7511 A Hybrid DEA Model for the Measurement of the Enviromental Performance

Authors: A. Hadi-Vencheh, N. Shayesteh Moghadam

Abstract:

Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Since some of the environmental performance indicators cannot be controlled by companies managers, it is necessary to develop the model in a way that it could be applied when discretionary and/or non-discretionary factors were involved. In this paper, we present a semi-radial DEA approach to measuring environmental performance, which consists of non-discretionary factors. The model, then, has been applied on a real case.

Keywords: Environmental performance, efficiency, non-discretionary variables, data envelopment analysis.

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7510 Removal of Heavy Metals from Wastewater by Adsorption and Membrane Processes: a Comparative Study

Authors: Nermen N. Maximous, George F. Nakhla, W. K. Wan

Abstract:

This research aimed at investigating the Cr (III), Cd (II) and Pb (II) removal efficiencies by using the newly synthesized metal oxides/ polyethersulfone (PES), Al2O3/PES and ZrO2/PES, membranes from synthetic wastewater and exploring fouling mechanisms. A Comparative study between the removal efficiencies of Cr (III), Cd (II) and Pb (II) from synthetic and natural wastewater by using adsorption onto agricultural by products and the newly synthesized Al2O3/PES and ZrO2/PES membranes was conducted to assess the advantages and limitations of using the metal oxides/PES membranes for heavy metals removal. The results showed that about 99 % and 88 % removal efficiencies were achieved by the tested membranes for Pb (II) and Cr (III), respectively.

Keywords: Adsorption, metals removal, ultrafiltrationmembranes, wastewater

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7509 Fundamental Theory of the Evolution Force: Gene Engineering utilizing Synthetic Evolution Artificial Intelligence

Authors: L. K. Davis

Abstract:

The effects of the evolution force are observable in nature at all structural levels ranging from small molecular systems to conversely enormous biospheric systems. However, the evolution force and work associated with formation of biological structures has yet to be described mathematically or theoretically. In addressing the conundrum, we consider evolution from a unique perspective and in doing so we introduce the “Fundamental Theory of the Evolution Force: FTEF”. We utilized synthetic evolution artificial intelligence (SYN-AI) to identify genomic building blocks and to engineer 14-3-3 ζ docking proteins by transforming gene sequences into time-based DNA codes derived from protein hierarchical structural levels. The aforementioned served as templates for random DNA hybridizations and genetic assembly. The application of hierarchical DNA codes allowed us to fast forward evolution, while dampening the effect of point mutations. Natural selection was performed at each hierarchical structural level and mutations screened using Blosum 80 mutation frequency-based algorithms. Notably, SYN-AI engineered a set of three architecturally conserved docking proteins that retained motion and vibrational dynamics of native Bos taurus 14-3-3 ζ.

Keywords: 14-3-3 docking genes, synthetic protein design, time based DNA codes, writing DNA code from scratch.

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7508 An Efficient Classification Method for Inverse Synthetic Aperture Radar Images

Authors: Sang-Hong Park

Abstract:

This paper proposes an efficient method to classify inverse synthetic aperture (ISAR) images. Because ISAR images can be translated and rotated in the 2-dimensional image place, invariance to the two factors is indispensable for successful classification. The proposed method achieves invariance to translation and rotation of ISAR images using a combination of two-dimensional Fourier transform, polar mapping and correlation-based alignment of the image. Classification is conducted using a simple matching score classifier. In simulations using the real ISAR images of five scaled models measured in a compact range, the proposed method yields classification ratios higher than 97 %.

Keywords: Radar, ISAR, radar target classification, radar imaging.

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7507 A Survey in Techniques for Imbalanced Intrusion Detection System Datasets

Authors: Najmeh Abedzadeh, Matthew Jacobs

Abstract:

An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, intrusion detection system, imbalanced datasets, sampling algorithms, big data.

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