Search results for: particle encoding scheme

Authors: Peter J. Riley

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Introductory courses in High Energy Physics (HEP) can be extended with the Tri-Preon (TP) model to both supplements and challenge the Standard Model (SM) theory. TP supplements by simplifying the tracking of Conserved Quantum Numbers at an interaction vertex, e.g., the lepton number can be seen as a di-preon current. TP challenges by proposing extended particle families to three generations of particle triplets for leptons, quarks, and weak bosons. There are extensive examples discussed at an introductory level in six arXiv publications, including supersymmetry, hyper color, and the Higgs. Interesting exercises include pion decay, kaon-antikaon mixing, neutrino oscillations, and K+ decay to muons. It is a revealing exercise for students to weigh the pros and cons of parallel theories at an early stage in their HEP journey.

Keywords: HEP, particle physics, standard model, Tri-Preon model

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Authors: Sofia Ayouche, Rachid Ellaia, Rajae Aboulaich

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Today, insurers may use the yield curve as an indicator evaluation of the profit or the performance of their portfolios; therefore, they modeled it by one class of model that has the ability to fit and forecast the future term structure of interest rates. This class of model is the Nelson-Siegel-Svensson model. Unfortunately, many authors have reported a lot of difficulties when they want to calibrate the model because the optimization problem is not convex and has multiple local optima. In this context, we implement a hybrid Particle Swarm optimization and Nelder Mead algorithm in order to minimize by least squares method, the difference between the zero-coupon curve and the NSS curve.

Keywords: optimization, zero-coupon curve, Nelson-Siegel-Svensson, particle swarm optimization, Nelder-Mead algorithm

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Authors: Mohan Ramasundaram, Amutha Prabakar Muniyandi

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Remote user authentication is one of the important tasks for any kind of remote server applications. Several remote authentication schemes are proposed by the researcher for Telecare Medicine Information System (TMIS). Most of the existing techniques have limitations, vulnerable to various kind attacks, lack of functionalities, information leakage, no perfect forward security and ineffectiveness. Authentication is a process of user verification mechanism for allows him to access the resources of a server. Nowadays, most of the remote authentication protocols are using two-factor authentications. We have made a survey of several remote authentication schemes using three factors and this survey shows that the most of the schemes are inefficient and subject to several attacks. We observed from the experimental evaluation; the proposed scheme is very secure against various known attacks that include replay attack, man-in-the-middle attack. Furthermore, the analysis based on the communication cost and computational cost estimation of the proposed scheme with related schemes shows that our proposed scheme is efficient.

Keywords: Telecare Medicine Information System, elliptic curve cryptography, three-factor, biometric, random oracle

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Authors: Himanshu Singh, Rishi Kant, Shantanu Bhattacharya

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This paper adopts a top-down approach for mathematical modeling to predict the size reduction from micro to nano-scale through persistent etching. The process is simulated using a finite difference approach. Previously, various researchers have simulated the etching process for 1-D and 2-D substrates. It consists of two processes: 1) Convection-Diffusion in the etchant domain; 2) Chemical reaction at the surface of the particle. Since the process requires analysis along moving boundary, partial differential equations involved cannot be solved using conventional methods. In 1-D, this problem is very similar to Stefan's problem of moving ice-water boundary. A fixed grid method using finite volume method is very popular for modelling of etching on a one and two dimensional substrate. Other popular approaches include moving grid method and level set method. In this method, finite difference method was used to discretize the spherical diffusion equation. Due to symmetrical distribution of etchant, the angular terms in the equation can be neglected. Concentration is assumed to be constant at the outer boundary. At the particle boundary, the concentration of the etchant is assumed to be zero since the rate of reaction is much faster than rate of diffusion. The rate of reaction is proportional to the velocity of the moving boundary of the particle. Modelling of the above reaction was carried out using Matlab. The initial particle size was taken to be 50 microns. The density, molecular weight and diffusion coefficient of the substrate were taken as 2.1 gm/cm3, 60 and 10-5 cm2/s respectively. The etch-rate was found to decline initially and it gradually became constant at 0.02µ/s (1.2µ/min). The concentration profile was plotted along with space at different time intervals. Initially, a sudden drop is observed at the particle boundary due to high-etch rate. This change becomes more gradual with time due to declination of etch rate.

Keywords: particle size reduction, micromixer, FDM modelling, wet etching

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Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

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The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

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Authors: S. Akinde, Jubril Olatunbosun

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In recent years, most of the urban centers in Nigeria are fast experiencing housing problems such as unaffordable housing and environmental challenges, all of which determine the nature of housing quality. The population continues to increase and the demand for quality housing increases probably at the same rate. Several kinds of houses serve various purposes; the objectives of the low cost housing schemes as the name suggests is to make houses quality to both the middle and lower classes of people in Lagos. A casual look into the study area of Iba Low Cost Housing Estate and the Unity Low Cost Housing Estate, Ojo and Alimosho respectively in Lagos State have shown a huge demands for houses. The study area boasts of a large population all engaged in various commercial activities with income at various levels. It would be fair to say that these people are mainly of the middle class and lower class. This means the low cost housing scheme truly serves these purposes. A Low Cost Housing Scheme of Iba which is publicly owned and Low Cost Housing Scheme of Unity Estate (UE) is privately owned.  

Keywords: housing, residential quality, low cost housing scheme, public, private estates

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Authors: M. A. Adejumobi, J. O. Ojediran

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The aim of irrigation is to recharge the available water in the soil. Quality of irrigation water is essential for the yield and quality of crops produced, maintenance of soil productivity and protection of the environment. The analysis of irrigation water arises as a need to know the impact of irrigation water on the yield of crops, the effect, and the necessary control measures to rectify the effect of this for optimum production and yield of crops. This study was conducted to assess the quality of irrigation water with its performance on crop planted, in Josepdam irrigation scheme Bacita, Nigeria. Field visits were undertaken to identify and locate water supply sources and collect water samples from these sources; X1 Drain, Oshin, River Niger loop and Ndafa. Laboratory experiments were then undertaken to determine the quality of raw water from these sources. The analysis was carried for various parameters namely; physical and chemical analyses after water samples have been taken from four sources. The samples were tested in laboratory. Results showed that the raw water sources shows no salinity tendencies with SAR values less than 1me/l and Ecvaules at Zero while the pH were within the recommended range by FAO, there are increase in potassium and sulphate content contamination in three of the location. From this, it is recommended that there should be proper monitoring of the scheme by conducting analysis of water and soil in the environment, preferable test should be carried out at least one year to cover the impact of seasonal variations and to determine the physical and chemical analysis of the water used for irrigation at the scheme.

Keywords: irrigation, salinity, raw water quality, scheme

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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Authors: Ruo-Qian Wang

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Open-source CFD has become increasingly popular and promising. The recent progress in multiphase flow enables new CFD applications, which provides an economic and flexible research tool for complex flow problems. Our numerical study using four-way coupling Euler-Lagrangian Large-Eddy Simulations to resolve particle cloud dynamics with OpenFOAM and CFDEM will be introduced: The fractioned Navier-Stokes equations are numerically solved for fluid phase motion, solid phase motion is addressed by Lagrangian tracking for every single particle, and total momentum is conserved by fluid-solid inter-phase coupling. The grid convergence test was performed, which proves the current resolution of the mesh is appropriate. Then, we validated the code by comparing numerical results with experiments in terms of particle cloud settlement and growth. A good comparison was obtained showing reliability of the present numerical schemes. The time and height at phase separations were defined and analyzed for a variety of initial release conditions. Empirical formulas were drawn to fit the results.

Keywords: four-way coupling, dredging, land reclamation, multiphase flows, oil spill

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Authors: Mohammad Arif Khan

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This paper analyzes and presents the development of Artificial Neural Network based controller of space vector modulation (ANN-SVPWM) for a seven-phase voltage source inverter. At first, the conventional method of producing sinusoidal output voltage by utilizing six active and one zero space vectors are used to synthesize the input reference, is elaborated and then new PWM scheme called Artificial Neural Network Based PWM is presented. The ANN based controller has the advantage of the very fast implementation and analyzing the algorithms and avoids the direct computation of trigonometric and non-linear functions. The ANN controller uses the individual training strategy with the fixed weight and supervised models. A computer simulation program has been developed using Matlab/Simulink together with the neural network toolbox for training the ANN-controller. A comparison of the proposed scheme with the conventional scheme is presented based on various performance indices. Extensive Simulation results are provided to validate the findings.

Keywords: space vector PWM, total harmonic distortion, seven-phase, voltage source inverter, multi-phase, artificial neural network

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Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

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Proxy signature scheme permits an original signer to delegate his/her signing capability to a proxy signer, and then the proxy signer generates a signing message on behalf of the original signer. The two parties must be able to authenticate one another and agree on a secret encryption key, in order to communicate securely over an unreliable public network. Authenticated key agreement protocols have an important role in building secure communications network between the two parties. In this paper, we present a secure proxy signature scheme over an efficient and secure authenticated key agreement protocol based on the discrete logarithm problem.

Keywords: proxy signature, warrant partial delegation, key agreement, discrete logarithm

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Authors: Muhammad Zaheer Babar, Amer Kashif, Muhammad Rizwan Javed

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Nowadays distributed generation integration is best way to overcome the increasing load demand. Optimal allocation of distributed generation plays a vital role in reducing system losses and improves voltage profile. In this paper, a Meta heuristic technique is proposed for allocation of DG in order to reduce power losses and improve voltage profile. The proposed technique is based on Multi Objective Particle Swarm optimization. Fewer control parameters are needed in this algorithm. Modification is made in search space of PSO. The effectiveness of proposed technique is tested on IEEE 33 bus test system. Single DG as well as multiple DG scenario is adopted for proposed method. Proposed method is more effective as compared to other Meta heuristic techniques and gives better results regarding system losses and voltage profile.

Keywords: Distributed generation (DG), Multi Objective Particle Swarm Optimization (MOPSO), particle swarm optimization (PSO), IEEE standard Test System

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Authors: Navneet Kaur, S. D. Tiwari

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Magnetic nanoparticles possess fascinating properties which make their behavior unique in comparison to corresponding bulk materials. Superparamagnetism is one such interesting phenomenon exhibited only by small particles of magnetic materials. In this state, the thermal energy of particles become more than their magnetic anisotropy energy, and so particle magnetic moment vectors fluctuate between states of minimum energy. This situation is similar to paramagnetism of non-interacting ions and termed as superparamagnetism. The magnetization of such systems has been described by Langevin function. But, the estimated fit parameters, in this case, are found to be unphysical. It is due to non-consideration of particle size distribution. In this work, analysis of magnetization data on NiO nanoparticles is presented considering the effect of particle size distribution. Nanoparticles of NiO of two different sizes are prepared by heating freshly synthesized Ni(OH)₂ at different temperatures. Room temperature X-ray diffraction patterns confirm the formation of single phase of NiO. The diffraction lines are seen to be quite broad indicating the nanocrystalline nature of the samples. The average crystallite size are estimated to be about 6 and 8 nm. The samples are also characterized by transmission electron microscope. Magnetization of both sample is measured as function of temperature and applied magnetic field. Zero field cooled and field cooled magnetization are measured as a function of temperature to determine the bifurcation temperature. The magnetization is also measured at several temperatures in superparamagnetic region. The data are fitted to an appropriate expression considering a distribution in particle size following a least square fit procedure. The computer codes are written in PYTHON. The presented analysis is found to be very useful for estimating the particle size distribution present in the samples. The estimated distributions are compared with those determined from transmission electron micrographs.

Keywords: anisotropy, magnetization, nanoparticles, superparamagnetism

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Authors: Qijiao He

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MicroElectrical-Mechanical System (MEMS) is one of the most rapidly developing frontier research field both in theory study and applied technology. Micro-channel is a very important link component of MEMS. With the research and development of MEMS, the size of the micro-devices and the micro-channels becomes further smaller. Compared with the macroscale flow, the flow characteristics of gas in the micro-channel have changed, and the rarefaction effect appears obviously. However, for the rarefied gas and microscale flow, Navier-Stokes-Fourier (NSF) equations are no longer appropriate due to the breakup of the continuum hypothesis. A Nonlinear Coupled Constitutive Model (NCCM) has been derived from the Boltzmann equation to describe the characteristics of both continuum and rarefied gas flows. We apply the present scheme to simulate continuum and rarefied gas flows in a micro-channel structure. And for comparison, we apply other widely used methods which based on particle simulation or direct solution of distribution function, such as Direct simulation of Monte Carlo (DSMC), Unified Gas-Kinetic Scheme (UGKS) and Lattice Boltzmann Method (LBM), to simulate the flows. The results show that the present solution is in better agreement with the experimental data and the DSMC, UGKS and LBM results than the NSF results in rarefied cases but is in good agreement with the NSF results in continuum cases. And some characteristics of both continuum and rarefied gas flows are observed and analyzed.

Keywords: continuum and rarefied gas flows, discontinuous Galerkin method, generalized hydrodynamic equations, numerical simulation

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Authors: Myungkyu Park, Minkun Kim, Sunghoon Kim, Samgon Ryu

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Recently, research for reactive fabrics which have the characteristics of CWA (Chemical Warfare Agent) decomposition is being performed actively. The performance level of decomposition for CWA decomposition in various environmental condition is one of the critical factors in applicability as protective materials for NBC (Nuclear, Biological, and Chemical) protective clothing. In this study, results of performance test for CWA decomposition by reactive fabric made of electrospinning web and reactive particle are presented. Currently, the MOF (metal organic framework) type of UiO-66-NH₂ is frequently being studied as material for decomposing CWA especially blister agent HD [Bis(2-chloroethyl) sulfide]. When we test decomposition rate with electrospinning web made of PVB (Polyvinyl Butiral) polymer and UiO-66-NH₂ particle, we can get very high protective performance than the case other particles are applied. Furthermore, if the repellant surface fabric is added on reactive material as the component of protective fabric, the performance of layer by layered reactive fabric could be approached to the level of current NBC protective fabric for HD decomposition rate. Reactive fabric we used in this study is manufactured by electrospinning process of polymer which contains the reactive particle of UiO-66-NH₂, and we performed crystalizing process once again on that polymer fiber web in solvent systems as a second step for manufacturing reactive fabric. Three kinds of polymer materials are used in this process, but PVB was most suitable as an electrospinning fiber polymer considering the shape of product. The density of particle on fiber web and HD decomposition rate is enhanced by secondary crystallization compared with the results which are not processed. The amount of HD penetration by 24hr AVLAG (Aerosol Vapor Liquid Assessment Group) swatch test through the reactive fabrics with secondary crystallization and without crystallization is 24 and 146μg/cm² respectively. Even though all of the reactive fiber webs for this test are combined with repellant surface layer at outer side of swatch, the effects of secondary crystallization of particle for the reactive fiber web are remarkable.

Keywords: CWA, Chemical Warfare Agent, gas decomposition, particle growth, protective clothing, reactive fabric, swatch test

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Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

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The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic

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Authors: Hiroshi Yamaguchi, Phillip C. Y. Sheu, Ryo Fujita, Shigeo Tsujii

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In this paper, the secure BioSemantic Scheme is presented to bridge biological/biomedical research problems and computational solutions via semantic computing. Due to the diversity of problems in various research fields, the semantic capability description language (SCDL) plays and important role as a common language and generic form for problem formalization. SCDL is expected the essential for future semantic and logical computing in Biosemantic field. We show several example to Biomedical problems in this paper. Moreover, in the coming age of cloud computing, the security problem is considered to be crucial issue and we presented a practical scheme to cope with this problem.

Keywords: biomedical applications, private information retrieval (PIR), semantic capability description language (SCDL), semantic computing

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Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

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The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Joseph Marfo Boaheng, Daniel Ansong, Eugenia Amporfo

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Health Insurance is proposed to provide financial protection against catastrophic health care cost arising from disease. Ghana has had a National Health Insurance Scheme (NHIS) since 2003 with the current enrolment/retention rate of 36%. The main goal of the scheme is to provide equity in the health sector as well as ensuring affordable health care for the poor. However, the current payment system is not flexible to attract significant proportion of the poor informal sector onto the scheme. Looking at the extensive use of mobiles in the Ghana where about 29,220,602.00 registered mobile phone lines are actively in used as of June 2014, paying health insurance premium through mobile phone could be feasible to attract larger proportion of the informal sector onto the scheme. Methodology: The quantitative cross-sectional survey was used to solicit the required information from 877 respondents living in Kumasi, the second capital city of Ghana. The magnitude of the effect of Pro-rata system (flexible payment terms) on NHIS enrollment rate was estimated with binary logistic regression model. Results: The odds for an individual to enroll onto NHIS with mobile phone increases about 2 times more when payment of insurance premium is on pro-rata basis ie. flexible payment terms (p=0.008, CI=1.212-3.565). Conclusion: The study advocates the National Health Insurance Authority consider this alternative payment system that has the potential of attracting a greater proportion of the informal sector to be enrolled or retained onto the scheme.

Keywords: enrollment, health insurance, mobile phone, pro-rata

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Authors: I. O. Oladele, J. A. Omotoyinbo, A. M. Okoro, A. G. Okikiola, J. L. Olajide

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This work was carried out to investigate comparatively the effects of modified and unmodified cow bone particles on the mechanical properties of polyester matrix composites in order to investigate the suitability of the materials as biomaterial. Cow bones were procured from an abattoir, sun dried for 4 weeks and crushed. The crushed bones were divided into two, where one part was turned to ash while the other part was pulverized with laboratory ball mill before the two grades were sieved using 75 µm sieve size. Bone ash and bone particle reinforced tensile and flexural composite samples were developed from pre-determined proportions of 2, 4, 6, and 8 %. The samples after curing were stripped from the moulds and were allowed to further cure for 3 weeks before tensile and flexural tests were performed on them. The tensile test result showed that, 8 wt % bone particle reinforced polyester composites has higher tensile properties except for modulus of elasticity where 8 wt % bone ash particle reinforced composites has higher value while for flexural test, bone ash particle reinforced composites demonstrate the best flexural properties. The results show that these materials are structurally compatible.

Keywords: biomedical, composites, cow bone, mechanical properties, polyester, reinforcement

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Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li

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Transports of solid particles through the drill pipe, drill string-hole annulus and hydraulically generated fractures are important dynamic processes encountered in oil and gas well drilling and completion operations. Different from particle transport in infinite space, the transports of cuttings, proppants and formation sand are hindered by a finite boundary. Therefore, an accurate description of the particle transport behavior under the bounded wall conditions encountered in drilling and hydraulic fracturing operations is needed to improve drilling safety and efficiency. In this study, the particle settling experiments were carried out to investigate the particle settling behavior in the pipe, annulus and between the parallel plates filled with power-law fluids. Experimental conditions simulated the particle Reynolds number ranges of 0.01-123.87, the dimensionless diameter ranges of 0.20-0.80 and the fluid flow behavior index ranges of 0.48-0.69. Firstly, the wall effect of the annulus is revealed by analyzing the settling process of the particles in the annular geometry with variable inner pipe diameter. Then, the geometric continuity among the pipe, annulus and parallel plates was determined by introducing the ratio of inner diameter to an outer diameter of the annulus. Further, a unified dimensionless diameter was defined to confirm the relationship between the three different geometry in terms of the wall effect. In addition, a dimensionless term independent from the settling velocity was introduced to establish a unified explicit settling velocity model applicable to pipes, annulus and fractures with a mean relative error of 8.71%. An example case study was provided to demonstrate the application of the unified model for predicting particle settling velocity. This paper is the first study of annulus wall effects based on the geometric continuity concept and the unified model presented here will provide theoretical guidance for improved hydraulic design of cuttings transport, proppant placement and sand management operations.

Keywords: wall effect, particle settling velocity, cuttings transport, proppant transport in fracture

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Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

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In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

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Authors: Salman Piri

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In this study, a two-dimensional lattice Boltzmann method (LBM) was considered for the numerical simulation of fluid flow in a channel. Also, the Lagrangian method was used for particle tracking in one-way coupling. Three hundred spherical particles with specific diameters were released in the channel entry and an elliptical object was placed in the channel for flow obstruction. The effect of gravity, the drag force, the Saffman lift and the Brownian forces were evaluated in the particle motion trajectories. Also, the effect of the geometrical parameter, ellipse aspect ratio, and the flow characteristic or Reynolds number was surveyed for the transport and deposition of particles. Moreover, the influence of particle diameter between 0.01 and 10 µm was investigated. Results indicated that in small Reynolds, more inertial and gravitational trapping occurred on the obstacle surface for particles with larger diameters. Whereas, for nano-particles, influenced by Brownian diffusion and vortices behind the obstacle, the inertial and gravitational mechanisms were insignificant and diffusion was the dominant deposition mechanism. In addition, in Reynolds numbers larger than 400, there was no significant difference between the deposition of finer and larger particles. Also, in higher aspect ratios of the ellipse, more inertial trapping occurred for particles of larger diameter (10 micrometers), while in lower cases, interception and gravitational mechanisms were dominant.

Keywords: ellipse aspect elito, particle tracking diffusion, lattice boltzman method, larangain particle tracking

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Authors: Rabih Ghostine, Craig Kapfer, Viswanathan Kannan, Ibrahim Hoteit

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Urban flooding resulting from a sudden release of water due to dam-break or excessive rainfall is a serious threatening environment hazard, which causes loss of human life and large economic losses. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision, and rescue plans. This work reports on the numerical modelling of flash flood propagation in urban areas after an excessive rainfall event or dam-break. A two-dimensional (2D) depth-averaged shallow water model is used with a refined unstructured grid of triangles for representing the urban area topography. The 2D shallow water equations are solved using a second-order well-balanced discontinuous Galerkin scheme. Theoretical test case and three flood events are described to demonstrate the potential benefits of the scheme: (i) wetting and drying in a parabolic basin (ii) flash flood over a physical model of the urbanized Toce River valley in Italy; (iii) wave propagation on the Reyran river valley in consequence of the Malpasset dam-break in 1959 (France); and (iv) dam-break flood in October 1982 at the town of Sumacarcel (Spain). The capability of the scheme is also verified against alternative models. Computational results compare well with recorded data and show that the scheme is at least as efficient as comparable second-order finite volume schemes, with notable efficiency speedup due to parallelization.

Keywords: dam-break, discontinuous Galerkin scheme, flood modeling, shallow water equations

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Authors: I Gede Puja Astawa, Yoedy Moegiharto, Ahmad Zainudin, Imam Dui Agus Salim, Nur Annisa Anggraeni

Abstract:

Performance of Orthogonal Frequency Division Multiplexing (OFDM) system can be improved by adding channel coding (error correction code) to detect and correct the errors that occur during data transmission. One can use the convolution code. This paper presents performance of OFDM using Space Time Block Codes (STBC) diversity technique use QAM modulation with code rate 1/2. The evaluation is done by analyzing the value of Bit Error Rate (BER) vs. Energy per Bit to Noise Power Spectral Density Ratio (Eb/No). This scheme is conducted 256 sub-carrier which transmits Rayleigh multipath channel in OFDM system. To achieve a BER of 10-3 is required 30 dB SNR in SISO-OFDM scheme. For 2x2 MIMO-OFDM scheme requires 10 dB to achieve a BER of 10-3. For 4x4 MIMO-OFDM scheme requires 5 dB while adding convolution in a 4x4 MIMO-OFDM can improve performance up to 0 dB to achieve the same BER. This proves the existence of saving power by 3 dB of 4x4 MIMO-OFDM system without coding, power saving 7 dB of 2x2 MIMO-OFDM system without coding and significant power savings from SISO-OFDM system.

Keywords: convolution code, OFDM, MIMO, QAM, BER

Procedia PDF Downloads 364

Authors: Rajesh Bera, Durbadal Mandal, Rajib Kar, Sakti P. Ghoshal

Abstract:

This paper describes optimal thinning of an Elliptical Cylindrical Array (ECA) of uniformly excited isotropic antennas which can generate directive beam with minimum relative Side Lobe Level (SLL). The Particle Swarm Optimization (PSO) method, which represents a new approach for optimization problems in electromagnetic, is used in the optimization process. The PSO is used to determine the optimal set of ‘ON-OFF’ elements that provides a radiation pattern with maximum SLL reduction. Optimization is done without prefixing the value of First Null Beam Width (FNBW). The variation of SLL with element spacing of thinned array is also reported. Simulation results show that the number of array elements can be reduced by more than 50% of the total number of elements in the array with a simultaneous reduction in SLL to less than -27dB.

Keywords: thinned array, Particle Swarm Optimization, Elliptical Cylindrical Array, Side Lobe Label.

Procedia PDF Downloads 414

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

Abstract:

This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 127

Authors: Abdelraheem M. Aly, Minh Tuan Nguyen, Sang-Wook Lee

Abstract:

The incompressible smoothed particle hydrodynamics (ISPH) is used to simulate impact free surface flows. In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. The current ISPH method is applied to simulate dam break flow over an inclined plane with different inclination angles. The effects of inclination angle in the velocity of wave front and pressure distribution is discussed. The impact of circular cylinder over water in tank has also been simulated using ISPH method. The computed pressures on the solid boundaries is studied and compared with the experimental results.

Keywords: incompressible smoothed particle hydrodynamics, free surface flow, inclined plane, water entry impact

Procedia PDF Downloads 373

Authors: Kapse Swapnil, K. Shankar

Abstract:

Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam

Procedia PDF Downloads 483