Search results for: density approximation

Authors: Ekta Singh, M. P. Singh

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The habitat where the present study has been carried out is productive in relation to nutrient quality and they may perform several useful functions, but are also threatened for their existence. Hence, the proposed work, will add much new information about biodiversity of macrophytes in drains and their embankment. All the species were identified with their different stages of growth which encountered on the three selected sites (I, II and III). The number of species occurring at each site is grouped seasonally, i.e. summer, rainy and winter season and the species were further recorded for the study of phytosociology. Phytosociological characters such as frequency, density and abundance were influenced by the climatic, anthropogenic and biotic stresses prevailing at the three study sites. All the species present at the study sites have shown maximum values of frequency, density and abundance in rainy season in comparison to that of summer and winter seasons.

Keywords: Abundance, Biodiversity, Density, Frequency, Macrophytes, Phytosociology.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop, Pairote Sattayatham

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Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte Carlo method in the approximation step. The data reduction has been performed horizontally and vertically through our EMR sampling method. The proposed method is analyzed by a series of experiments. We apply our algorithm on clustering and classification tasks to evaluate the utility of our approach.

Keywords: Data Stream, Monte Carlo, Sampling, DensityEstimation.

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Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

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Indonesia, as an archipelagic nation, has a very long coastline with significant potential for marine resources, including mangrove ecosystems. The Lapindo mudflow disaster in Sidoarjo, East Java, resulted in mudflow being discharged into the sea through the Brantas and Porong rivers. The mud material transported by the river flow is feared to be dangerous because it contains harmful substances such as heavy metals. This study aims to map the mangrove ecosystem in terms of its density and assess the impact of the Lapindo mud disaster on the mangrove ecosystem, along with efforts to sustain its continuity. The mapping of the coastal mangrove conditions in Sidoarjo was carried out using remote sensing products, specifically Landsat 7 ETM+ images, taken during dry months in 2002, 2006, 2009, and 2014. The density of mangroves was determined using NDVI, which utilizes band 3 (the red channel) and band 4 (the near IR channel). Image processing to generate NDVI was performed using ENVI 5.1 software. The NDVI results were used to assess mangrove density on a scale from 0 to 1. The growth of mangrove ecosystems, both in terms of area and density, showed a significant increase from year to year. The development of mangrove ecosystems was influenced by the deposition of Lapindo mud in the estuaries of the Porong and Brantas rivers, where the silt provided a suitable medium for the growth of the mangrove ecosystem, leading to an increase in its density. The rise in density was supported by public awareness to mitigate heavy metal contamination, allowing for mangrove breeding near the affected areas.

Keywords: Archipelagic nation, Mangrove, Lapindo mudflow disaster, NDVI.

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Authors: N. H. Adenan, M. S. M. Noorani

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River flow prediction is an essential tool to ensure proper management of water resources and the optimal distribution of water to consumers. This study presents an analysis and prediction by using nonlinear prediction method with monthly river flow data for Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The reconstruction of phase space involves the reconstruction of one-dimension (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. The revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) was employed to compare prediction performance for the nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show that the prediction results using the nonlinear prediction method are better than ARIMA and SVM. Therefore, the results of this study could be used to develop an efficient water management system to optimize the allocation of water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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Authors: Abdusalam Gsiea, Ramadan Al-habashi, Mohamed Atumi, Khaled Atmimi

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We present a theoretical investigation on the structural, electronic properties and vibrational mode of nitrogen impurities in ZnO. The atomic structures, formation and transition energies and vibrational modes of (NO3)i interstitial or NO4 substituting on an oxygen site ZnO were computed using ab initio total energy methods. Based on Local density functional theory, our calculations are in agreement with one interpretation of bound-excition photoluminescence for N-doped ZnO. First-principles calculations show that (NO3)i defects interstitial or NO4 substituting on an Oxygen site in ZnO are important suitable impurity for p-type doping in ZnO. However, many experimental efforts have not resulted in reproducible p-type material with N2 and N2O doping. by means of first-principle pseudo-potential calculation we find that the use of NO or NO2 with O gas might help the experimental research to resolve the challenge of achieving p-type ZnO.

Keywords: Density functional theory, nitrogen, p-type, ZnO.

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Authors: R. Sabre

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This work focuses on the symmetric alpha stable process with continuous time frequently used in modeling the signal with indefinitely growing variance, often observed with an unknown additive error. The objective of this paper is to estimate this error from discrete observations of the signal. For that, we propose a method based on the smoothing of the observations via Jackson polynomial kernel and taking into account the width of the interval where the spectral density is non-zero. This technique allows avoiding the “Aliasing phenomenon” encountered when the estimation is made from the discrete observations of a process with continuous time. We have studied the convergence rate of the estimator and have shown that the convergence rate improves in the case where the spectral density is zero at the origin. Thus, we set up an estimator of the additive error that can be subtracted for approaching the original signal without error.

Keywords: Spectral density, stable processes, aliasing, p-adic.

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Authors: Pavlo Selyshchev

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Irradiated material is a typical example of a complex system with nonlinear coupling between its elements. During irradiation the radiation damage is developed and this development has bifurcations and qualitatively different kinds of behavior. The accumulation of primary defects in irradiated crystals is considered in frame work of nonlinear evolution of complex system. The thermo-concentration nonlinear feedback is carried out as a mechanism of self-oscillation development. It is shown that there are two ways of the defect density evolution under stationary irradiation. The first is the accumulation of defects; defect density monotonically grows and tends to its stationary state for some system parameters. Another way that takes place for opportune parameters is the development of self-oscillations of the defect density. The stationary state, its stability and type are found. The bifurcation values of parameters (environment temperature, defect generation rate, etc.) are obtained. The frequency of the selfoscillation and the conditions of their development is found and rated. It is shown that defect density, heat fluxes and temperature during self-oscillations can reach much higher values than the expected steady-state values. It can lead to a change of typical operation and an accident, e.g. for nuclear equipment.

Keywords: Irradiation, Primary Defects, Solids, Self-oscillation.

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Authors: Mohammad-Eghbal Ghobadi, Mokhtar Ghobadi

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Coriander is an annual and herbaceous plant, belong to the apiaceae family. This plant is cultivated world widely. It is well known for having medicinal properties. The aim of this experiment was to study seed quality of species grown in Kermanshah conditions. The experiment was carried out in research farm, Campus of Agriculture and Natural Resources, Razi University, Kermanshah, Iran. Coriander (local type) was grown in late spring May (5th and 20th) and Jun (4th and 19th), and plant density (10, 30, 50 and 70 plants m-2) in 2009. The experimental plots were laid out in a factorial according to a randomized complete block design with three replications. The fruits were harvest between 83.5 – 106.5 days after sowing. The essential oil and oil content was extracted by Clevenger and Soxhlet apparatuses, respectively. Results showed that delay at planting date increased the oil content. Also, with the increase at plant density was decreased oil content and essential oil.

Keywords: coriander, late sowing, plant density, oil content, essential oil

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Authors: A. Jamekhorshid, G. Karimi, I. Noshadi, A. Jahangiri

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Non-uniform current distribution in polymer electrolyte membrane fuel cells results in local over-heating, accelerated ageing, and lower power output than expected. This issue is very critical when fuel cell experiences water flooding. In this work, the performance of a PEM fuel cell is investigated under cathode flooding conditions. Two-dimensional partially flooded GDL models based on the conservation laws and electrochemical relations are proposed to study local current density distributions along flow fields over a wide range of cell operating conditions. The model results show a direct association between cathode inlet humidity increases and that of average current density but the system becomes more sensitive to flooding. The anode inlet relative humidity shows a similar effect. Operating the cell at higher temperatures would lead to higher average current densities and the chance of system being flooded is reduced. In addition, higher cathode stoichiometries prevent system flooding but the average current density remains almost constant. The higher anode stoichiometry leads to higher average current density and higher sensitivity to cathode flooding.

Keywords: Current distribution, Flooding, Hydrogen energysystem, PEM fuel cell.

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Authors: Yeşim Tosun, Remzi Şahin

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This paper presents results of compressive strength, capillary water absorption, and density tests conducted on concrete containing recycled aggregate (RCA) which is obtained from structural waste generated by the construction industry in Turkey. In the experiments, 0%, 15%, 30%, 45% and 60% of the normal (natural) coarse aggregate was replaced by the recycled aggregate. Maximum aggregate particle sizes were selected as 16 mm, 22,4 mm and 31,5 mm; and 0,06%, 0,13% and 0,20% of air-entraining agent (AEA) were used in mixtures. Fly ash and superplasticizer were used as a mineral and chemical admixture, respectively. The same type (CEM I 42.5) and constant dosage of cement were used in the study. Water/cement ratio was kept constant as 0.53 for all mixture. It was concluded that capillary water absorption, compressive strength, and density of concrete decreased with increasing RCA ratio. Increasing in maximum aggregate particle size and amount of AEA also affect the properties of concrete significantly.

Keywords: Capillary water absorption, compressive strength, density, recycled concrete aggregates.

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Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

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This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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Authors: Arturo Aquino, Manuel Emilio Gegundez, Diego Marin

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In this paper, a new automated methodology to detect the optic disc (OD) automatically in retinal images from patients with risk of being affected by Diabetic Retinopathy (DR) and Macular Edema (ME) is presented. The detection procedure comprises two independent methodologies. On one hand, a location methodology obtains a pixel that belongs to the OD using image contrast analysis and structure filtering techniques and, on the other hand, a boundary segmentation methodology estimates a circular approximation of the OD boundary by applying mathematical morphology, edge detection techniques and the Circular Hough Transform. The methodologies were tested on a set of 1200 images composed of 229 retinographies from patients affected by DR with risk of ME, 431 with DR and no risk of ME and 540 images of healthy retinas. The location methodology obtained 98.83% success rate, whereas the OD boundary segmentation methodology obtained good circular OD boundary approximation in 94.58% of cases. The average computational time measured over the total set was 1.67 seconds for OD location and 5.78 seconds for OD boundary segmentation.

Keywords: Diabetic retinopathy, macular edema, optic disc, automated detection, automated segmentation.

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Authors: Li Long, Thomas Ortlepp

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A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor and sensor layout shape factor. Based on the properties of electrons, phonons, grain boundaries and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of Boltzmann transport equation. The model includes the effects of grain structure, grain boundary trap properties and doping concentration. The layer structure factor of sensor is analyzed with respect to infrared absorption coefficient. The effect of layout design is characterized with the shape factor, which is calculated for different sensor designs. Double layer polycrystalline silicon thermopile infrared sensors on suspended support membrane have been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed with measurement results.

Keywords: Polycrystalline silicon film, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor.

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Authors: Manoochehr Gholipoor

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The response of growth and yield of rainfed-chickpea to population density should be evaluated based on long-term experiments to include the climate variability. This is achievable just by simulation. In this simulation study, this evaluation was done by running the CYRUS model for long-term daily weather data of five locations in Iran. The tested population densities were 7 to 59 (with interval of 2) stands per square meter. Various functions, including quadratic, segmented, beta, broken linear, and dent-like functions, were tested. Considering root mean square of deviations and linear regression statistics [intercept (a), slope (b), and correlation coefficient (r)] for predicted versus observed variables, the quadratic and broken linear functions appeared to be appropriate for describing the changes in biomass and grain yield, and in harvest index, respectively. Results indicated that in all locations, grain yield tends to show increasing trend with crowding the population, but subsequently decreases. This was also true for biomass in five locations. The harvest index appeared to have plateau state across low population densities, but decreasing trend with more increasing density. The turning point (optimum population density) for grain yield was 30.68 stands per square meter in Isfahan, 30.54 in Shiraz, 31.47 in Kermanshah, 34.85 in Tabriz, and 32.00 in Mashhad. The optimum population density for biomass ranged from 24.6 (in Tabriz) to 35.3 stands per square meter (Mashhad). For harvest index it varied between 35.87 and 40.12 stands per square meter.

Keywords: Rainfed-chickpea, biomass, harvest index, grain yield, simulation.

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Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs – Sigmoid, ReLU, and Tanh – have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment on multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLU-ReLU) combination. Our results show that on using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: Activation Function, Universal Approximation function, Neural Networks, convergence.

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Authors: Baghdasaryan Marinka

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Monitoring the distribution of electric power consumption in the technological process of ore grinding is conducted. As a result, the impacts of the mill filling rate, the productivity of the ore supply, the volumetric density of the grinding balls, the specific density of the ground ore, and the relative speed of the mill rotation on the specific consumption of electric power have been studied. The power and technological factors affecting the reactive power generated by the synchronous motors, operating within the technological scheme are studied. A block diagram for evaluating the power consumption modes of the technological process is presented, which includes the analysis of the technological scheme, the determination of the place and volumetric density of the ore-grinding mill, the evaluation of the technological and power factors affecting the energy saving process, as well as the assessment of the electric power standards.

Keywords: Electric power standard, factor, ore grinding, power consumption, reactive power, technological.

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: Polyethylene, polymerization, density, melt index, neural network.

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Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

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Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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Authors: Ahmed Badawi, J. Michael Johnson, Mohamed Mahfouz

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This paper proposes new enhancement models to the methods of nonlinear anisotropic diffusion to greatly reduce speckle and preserve image features in medical ultrasound images. By incorporating local physical characteristics of the image, in this case scatterer density, in addition to the gradient, into existing tensorbased image diffusion methods, we were able to greatly improve the performance of the existing filtering methods, namely edge enhancing (EE) and coherence enhancing (CE) diffusion. The new enhancement methods were tested using various ultrasound images, including phantom and some clinical images, to determine the amount of speckle reduction, edge, and coherence enhancements. Scatterer density weighted nonlinear anisotropic diffusion (SDWNAD) for ultrasound images consistently outperformed its traditional tensor-based counterparts that use gradient only to weight the diffusivity function. SDWNAD is shown to greatly reduce speckle noise while preserving image features as edges, orientation coherence, and scatterer density. SDWNAD superior performances over nonlinear coherent diffusion (NCD), speckle reducing anisotropic diffusion (SRAD), adaptive weighted median filter (AWMF), wavelet shrinkage (WS), and wavelet shrinkage with contrast enhancement (WSCE), make these methods ideal preprocessing steps for automatic segmentation in ultrasound imaging.

Keywords: Nonlinear anisotropic diffusion, ultrasound imaging, speckle reduction, scatterer density estimation, edge based enhancement, coherence enhancement.

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Authors: S. Malathi, P. Seenuvasakumaran

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Nanomaterials ferrites have applications in making permanent magnets, high density information devices, color imaging etc. In the present examination, lithium ferrite is synthesized by sol-gel process. The x-ray diffraction (XRD) result shows that the structure of lithium ferrite is monoclinic structure. The average particle size 22 nm is calculated by Scherer formula. The lattice parameters and dislocation density (δ) are calculated from XRD data. Strain (ε) values are evaluated from Williamson – hall plot. The FT-IR study reveals the formation of ferrites showing the significant absorption bands. The VU-VIS spectroscopic data is used to calculate direct and indirect optical band gap (Eg) of 1.57eV and 1.01eV respectively for lithium ferrite by using Tauc plot at the edge of the absorption band. The energy dispersive x-ray analysis spectra showed that the expected elements exist in the material. The magnetic behaviour of the materials studied using vibrating sample magnetometer (VSM).

Keywords: Sol-gel, dislocation density, energy band gap, VSM.

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Authors: J. M. Owoyemi, O. S. Ogunrinde

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The suitability of Newsprint and Kraft papers for the production of cement bonded ceiling board was investigated. Sample boards were produced from newsprint paper (100%), mixture of newsprint and Kraft paper (50:50) and Kraft paper (100%) at 1:1, 2:1 and 3:1 cement/paper mixing ratio respectively with 3% additive concentration of calcium chloride (CaCl₂). Density, flexural and thickness swelling properties of the boards were investigated. The effects of paper type and mixing ratio on the physical and mechanical properties were also examined. The bending properties of the board which include Modulus of Elasticity (MOE) and Modulus of Rupture (MOR) increased linearly with increase in density. Modulus of rupture of boards increased as the density and mixing ratio increased. The thickness swelling property for the two paper types decreased as the board density and mixing ratio increased. Boards made from Kraft paper recorded higher strength values than the ones made from recycled newsprint paper while the mixture of kraft and newsprint papers had the best surface finish. The result of the study will help in managing the large quality of waste from paper converting/carton industry and that the ceiling boards produced could be installed with clout nails or used with suspended ceiling fittings.

Keywords: Cement, Kraft paper, Mixing ratio, Newsprint.

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Authors: R. Dangtungee, A. Rattanapan, S. Siengchin

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Waste silicon carbide (waste SiC) filled high-density polyethylene (HDPE) with and without surface modifiers were studied. Two types of surface modifiers namely; high-density polyethylene-grafted-maleic anhydride (HDPE-g-MA) and 3-aminopropyltriethoxysilane have been used in this study. The composites were produced using a two roll mill, extruder and shaped in a hydraulic compression molding machine. The mechanical properties of polymer composites such as flexural strength and modulus, impact strength, tensile strength, stiffness and hardness were investigated over a range of compositions. It was found that, flexural strength and modulus, tensile modulus and hardness increased, whereas impact strength and tensile strength decreased with the increasing in filler contents, compared to the neat HDPE. At similar filler content, the effect of both surface modifiers increased flexural modulus, impact strength, tensile strength and stiffness but reduced the flexural strength. Morphological investigation using SEM revealed that the improvement in mechanical properties was due to enhancement of the interfacial adhesion between waste SiC and HDPE.

Keywords: High-density polyethylene, HDPE-g-MA, mechanical properties, morphological properties, silicon carbide, waste silicon carbide.

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studied with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studies with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Flora E. Firdaus

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Polyurethane foam (PUF) is formed by a chemical reaction of polyol and isocyanate. The aim is to understand the impact of Silicone on synthesizing polyurethane in differentiate volume of molding. The method used was one step process, which is simultaneously caried out a blending polyol (petroleum polyol and soybean polyol), a TDI (2,4):MDI (4,4-) (80:20), a distilled water, and a silicone. The properties of the material were measured via a number of parameters, which are polymer density, compressive strength, and cellular structures. It is found that density of polyurethane using silicone with volume of molding either 250 ml or 500 ml is lower than without using silicone.

Keywords: soybean, petro, silicone, polyurethane

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Authors: Ihsan Al-Abboodi, Tahsin Toma-Sabbagh

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Laboratory tests have been carried out to investigate the response of 2x2 pile group subjected to triangular soil movement. The pile group was instrumented with displacement and tilting devices at the pile cap and strain gauges on two piles of the group. In this paper, results from four model tests were presented to study the effects of axial loads and soil density on the lateral behavior of piles. The responses in terms of bending moment, shear force, soil pressure, deflection, and rotation of piles were compared. Test results indicate that increasing the soil strength could increase the measured moment, shear, soil pressure, and pile deformations. Most importantly, adding loads to the pile cap induces additional moment to the head of front-pile row unlike the back-pile row which was influenced insignificantly.

Keywords: Pile group, passive piles, lateral soil movement, soil density, axial loads.

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Authors: S.Solaymani, T.Ghodselahi, N.B.Nezafat, H.Zahrabi, A.Gelali

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The morphological parameter of a thin film surface can be characterized by power spectral density (PSD) functions which provides a better description to the topography than the RMS roughness and imparts several useful information of the surface including fractal and superstructure contributions. Through the present study Nanoparticle copper/carbon composite films were prepared by co-deposition of RF-Sputtering and RF-PECVD method from acetylene gas and copper target. Surface morphology of thin films is characterized by using atomic force microscopy (AFM). The Carbon content of our films was obtained by Rutherford Back Scattering (RBS) and it varied from .4% to 78%. The power values of power spectral density (PSD) for the AFM data were determined by the fast Fourier transform (FFT) algorithms. We investigate the effect of carbon on the roughness of thin films surface. Using such information, roughness contributions of the surface have been successfully extracted.

Keywords: Atomic force microscopy, Fast Fourier transform, Power spectral density, RBS.

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Authors: Aritra Acharyya, Moumita Mukherjee, J. P. Banerjee

Abstract:

A generalized method for small-signal simulation of avalanche noise in Mixed Tunneling Avalanche Transit Time (MITATT) device is presented in this paper where the effect of series resistance is taken into account. The method is applied to a millimeter-wave Double Drift Region (DDR) MITATT device based on Silicon to obtain noise spectral density and noise measure as a function of frequency for different values of series resistance. It is found that noise measure of the device at the operating frequency (122 GHz) with input power density of 1010 Watt/m2 is about 35 dB for hypothetical parasitic series resistance of zero ohm (estimated junction temperature = 500 K). Results show that the noise measure increases as the value of parasitic resistance increases.

Keywords: Noise Analysis, Silicon MITATT, Admittancecharacteristics, Noise spectral density.

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Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

Abstract:

Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity, and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method.

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Authors: J. P. Dubois, H. M. Chiu

Abstract:

In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Keywords: ATM, multiplexing, queueing, telemedicine, VBR.

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