Search results for: soft particle.

Authors: Pardeep Singh, Sanjay Sharma

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With increasing data in medical databases, medical data retrieval is growing in popularity. Some of this analysis including inducing propositional rules from databases using many soft techniques, and then using these rules in an expert system. Diagnostic rules and information on features are extracted from clinical databases on diseases of congenital anomaly. This paper explain the latest soft computing techniques and some of the adaptive techniques encompasses an extensive group of methods that have been applied in the medical domain and that are used for the discovery of data dependencies, importance of features, patterns in sample data, and feature space dimensionality reduction. These approaches pave the way for new and interesting avenues of research in medical imaging and represent an important challenge for researchers.

Keywords: CBIR, GA, Rough sets, CBMIR, SVM.

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Authors: E. Petrakis, V. Karmali, K. Komnitsas

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In this study grinding experiments were performed in a laboratory ball mill using Polish ferronickel slag in order to study the effect of the particle size on alkali activation and the properties of the produced alkali activated materials (AAMs). In this regard, the particle size distribution and the specific surface area of the grinding products in relation to grinding time were assessed. The experimental results show that products with high compressive strength, e.g. higher than 60 MPa, can be produced when the slag median size decreased from 39.9 μm to 11.9 μm. Also, finer fractions are characterized by higher reactivity and result in the production of AAMs with lower porosity and better mechanical properties.

Keywords: Alkali activated materials, compressive strength, particle size distribution, slag.

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Authors: Ahmed Mahmoudi, Imen Mejri, Mohamed A. Abbassi, Ahmed Omri

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A new algorithm based on the lattice Boltzmann method (LBM) is proposed as a potential solver for one-dimensional heat and mass transfer for isothermal carbonization of wood particles. To check the validity of this algorithm, the LBM results have been compared with the published data and a good agreement is obtained. Then, the model is used to study the effect of reactor temperature and particle size on the evolution of the local temperature and mass loss inside the wood particle.

Keywords: Lattice Boltzmann Method, pyrolysis, conduction, carbonization.

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Authors: Nnamdi I. Nwulu, Shola G. Oroja

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It has become crucial over the years for nations to improve their credit scoring methods and techniques in light of the increasing volatility of the global economy. Statistical methods or tools have been the favoured means for this; however artificial intelligence or soft computing based techniques are becoming increasingly preferred due to their proficient and precise nature and relative simplicity. This work presents a comparison between Support Vector Machines and Artificial Neural Networks two popular soft computing models when applied to credit scoring. Amidst the different criteria-s that can be used for comparisons; accuracy, computational complexity and processing times are the selected criteria used to evaluate both models. Furthermore the German credit scoring dataset which is a real world dataset is used to train and test both developed models. Experimental results obtained from our study suggest that although both soft computing models could be used with a high degree of accuracy, Artificial Neural Networks deliver better results than Support Vector Machines.

Keywords: Artificial Neural Networks, Credit Scoring, SoftComputing Models, Support Vector Machines.

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Authors: M. H. Narasingha, K. Pana-Suppamassadu, P. Narataruksa

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The separation efficiency of a hydrocyclone has extensively been considered on the rigid particle assumption. A collection of experimental studies have demonstrated their discrepancies from the modeling and simulation results. These discrepancies caused by the actual particle elasticity have generally led to a larger amount of energy consumption in the separation process. In this paper, the influence of particle elasticity on the separation efficiency of a hydrocyclone system was investigated through the Finite Element (FE) simulations using crude oil droplets as the elastic particles. A Reitema-s design hydrocyclone with a diameter of 8 mm was employed to investigate the separation mechanism of the crude oil droplets from water. The cut-size diameter eter of the crude oil was 10 - Ðçm in order to fit with the operating range of the adopted hydrocylone model. Typical parameters influencing the performance of hydrocyclone were varied with the feed pressure in the range of 0.3 - 0.6 MPa and feed concentration between 0.05 – 0.1 w%. In the simulation, the Finite Element scheme was applied to investigate the particle-flow interaction occurred in the crude oil system during the process. The interaction of a single oil droplet at the size of 10 - Ðçm to the flow field was observed. The feed concentration fell in the dilute flow regime so the particle-particle interaction was ignored in the study. The results exhibited the higher power requirement for the separation of the elastic particulate system when compared with the rigid particulate system.

Keywords: Hydrocyclone, separation efficiency, strain energy density, strain rate.

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Authors: Marc Landry, Azeddine Kaddouri, Yassine Bouslimani, Mohsen Ghribi

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In this paper, a new alignment method based on the particle swarm optimization (PSO) technique is presented. The PSO algorithm is used for locating the optimal coupling position with the highest optical power with three-degrees of freedom alignment. This algorithm gives an interesting results without a need to go thru the complex mathematical modeling of the alignment system. The proposed algorithm is validated considering practical tests considering the alignment of two Single Mode Fibers (SMF) and the alignment of SMF and PCF fibers.

Keywords: Particle-swarm optimization, optical fiber, automatic alignment.

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Authors: Jana Puchyova

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In recent years a number of applications with multirobot systems (MRS) is growing in various areas. But their design is in practice often difficult and algorithms are proposed for the theoretical background and do not consider errors and noise in real conditions, so they are not usable in real environment. These errors are visible also in task of target localization enough, when robots try to find and estimate the position of the target by the sensors. Localization of target is possible also with one robot but as it was examined target finding and localization with group of mobile robots can estimate the target position more accurately and faster. The accuracy of target position estimation is made by cooperation of MRS and particle filtering. Advantage of usage the MRS with particle filtering was tested on task of fixed target localization by group of mobile robots.

Keywords: Multi-robot system, particle filter, position estimation, target localization.

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Authors: Hidehiko Okada

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The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.

Keywords: Evolutionary algorithms, swarm intelligence, particle swarm optimization, neural network, interval arithmetic.

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Authors: Alireza Sadrmomtaz

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Positron emission particle tracking (PEPT) is a technique in which a single radioactive tracer particle can be accurately tracked as it moves. A limitation of PET is that in order to reconstruct a tomographic image it is necessary to acquire a large volume of data (millions of events), so it is difficult to study rapidly changing systems. By considering this fact, PEPT is a very fast process compared with PET. In PEPT detecting both photons defines a line and the annihilation is assumed to have occurred somewhere along this line. The location of the tracer can be determined to within a few mm from coincident detection of a small number of pairs of back-to-back gamma rays and using triangulation. This can be achieved many times per second and the track of a moving particle can be reliably followed. This technique was invented at the University of Birmingham [1]. The attempt in PEPT is not to form an image of the tracer particle but simply to determine its location with time. If this tracer is followed for a long enough period within a closed, circulating system it explores all possible types of motion. The application of PEPT to industrial process systems carried out at the University of Birmingham is categorized in two subjects: the behaviour of granular materials and viscous fluids. Granular materials are processed in industry for example in the manufacture of pharmaceuticals, ceramics, food, polymers and PEPT has been used in a number of ways to study the behaviour of these systems [2]. PEPT allows the possibility of tracking a single particle within the bed [3]. Also PEPT has been used for studying systems such as: fluid flow, viscous fluids in mixers [4], using a neutrally-buoyant tracer particle [5].

Keywords: PET, BGO, Particle Tracking, ECAT 931, List mode, PEPT.

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: Biomass concentration, Extended Kalman Filter, Particle Filter, State estimation, Specific growth rate.

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Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in a pipe bends caused by particles is a major concern in the oil and gas fields and might cause breakdown to production equipment. This work investigates the effect of sand particle transport in an elbow using computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model is employed to calculate the air/solid particle flow in the elbow. Generic erosion model in Ansys fluent and three particle rebound models are used to predict the erosion rate on the 90° elbows. The model result is compared with experimental data from the open literature validating the CFD-based predictions which reveals that due to the sand particles impinging on the wall of the elbow at high velocity, a point on the pipe elbow were observed to have started turning red due to velocity increase and the maximum erosion locations occur at 48°.

Keywords: Erosion, prediction, elbow, computational fluid dynamics, CFD.

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Authors: Samindi Samarakoon, Ørjan Sletbakk Vie, Remi Kleiven Fjelldal

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White concrete facade elements are widely used in construction industry. It is challenging to achieve the desired workability in casting of white concrete elements. Particle Matrix model was used for proportioning the self-compacting white concrete (SCWC) to control segregation and bleeding and to improve workability. The paper presents how to reach the target slump flow while controlling bleeding and segregation in SCWC. The amount of aggregates, binders and mixing water, as well as type and dosage of superplasticizer (SP) to be used are the major factors influencing the properties of SCWC. Slump flow and compressive strength tests were carried out to examine the performance of SCWC, and the results indicate that the particle matrix model could produce successfully SCWC controlling segregation and bleeding.

Keywords: Mix design, particle, matrix model, white concrete.

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Authors: R. Alias, A. Kasa, M. R. Taha

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The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200 and 300 kPa. The results show that the peak and residual shear strength increases as particle size increases.

Keywords: Particle size, shear strength, granular material, direct shear test.

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Authors: Buntara Sthenly Gan, Naohiro Kawada

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A simple and easy algorithm is presented for a fast calculation of kernel functions which required in fluid simulations using the Smoothed Particle Hydrodynamic (SPH) method. Present proposed algorithm improves the Linked-list algorithm and adopts the Pair-Wise Interaction technique, which are widely used for evaluating kernel functions in fluid simulations using the SPH method. The algorithm is easy to be implemented without any complexities in programming. Some benchmark examples are used to show the simulation time saved by using the proposed algorithm. Parametric studies on the number of divisions for sub-domains, smoothing length and total amount of particles are conducted to show the effectiveness of the present technique. A compact formulation is proposed for practical usage.

Keywords: Technique, fluid simulation, smoothing particle hydrodynamic (SPH), particle interaction.

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Authors: Jun Yu, Yat-Hei Lam, Boris Grinberg, Kevin Chai Tshun Chuan

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This paper presents a 5-V to 30-V current-mode boost converter for powering the drive circuit of a micro-electro-mechanical sensor. The design of a transconductance amplifier and an integrated current sensing circuit are presented. In addition, essential building blocks for power-on protection such as a soft-start and clamp block and supply and clock ready block are discussed in details. The chip is fabricated in a 0.18-μm CMOS process. Measurement results show that the soft-start and clamp block can effectively limit the inrush current during startup and protect the boost converter from startup failure.

Keywords: Boost Converter, Current Sensing, Power-on protection, Step-up Converter, Soft-start.

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Authors: Mahamed G.H. Omran, Andries P Engelbrecht, Ayed Salman

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A new dynamic clustering approach (DCPSO), based on Particle Swarm Optimization, is proposed. This approach is applied to unsupervised image classification. The proposed approach automatically determines the "optimum" number of clusters and simultaneously clusters the data set with minimal user interference. The algorithm starts by partitioning the data set into a relatively large number of clusters to reduce the effects of initial conditions. Using binary particle swarm optimization the "best" number of clusters is selected. The centers of the chosen clusters is then refined via the Kmeans clustering algorithm. The experiments conducted show that the proposed approach generally found the "optimum" number of clusters on the tested images.

Keywords: Clustering Validation, Particle Swarm Optimization, Unsupervised Clustering, Unsupervised Image Classification.

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Authors: Azadeh Rouhandeh, Chris Joslin, Zhen Qu, Yuu Ono

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The centre of rotation of the hip joint is needed for an accurate simulation of the joint performance in many applications such as pre-operative planning simulation, human gait analysis, and hip joint disorders. In human movement analysis, the hip joint center can be estimated using a functional method based on the relative motion of the femur to pelvis measured using reflective markers attached to the skin surface. The principal source of errors in estimation of hip joint centre location using functional methods is soft tissue artefacts due to the relative motion between the markers and bone. One of the main objectives in human movement analysis is the assessment of soft tissue artefact as the accuracy of functional methods depends upon it. Various studies have described the movement of soft tissue artefact invasively, such as intra-cortical pins, external fixators, percutaneous skeletal trackers, and Roentgen photogrammetry. The goal of this study is to present a non-invasive method to assess the displacements of the markers relative to the underlying bone using optical motion capture data and tissue thickness from ultrasound measurements during flexion, extension, and abduction (all with knee extended) of the hip joint. Results show that the artefact skin marker displacements are non-linear and larger in areas closer to the hip joint. Also marker displacements are dependent on the movement type and relatively larger in abduction movement. The quantification of soft tissue artefacts can be used as a basis for a correction procedure for hip joint kinematics.

Keywords: Hip joint centre, motion capture, soft tissue artefact, ultrasound depth measurement.

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Authors: Kent Salomonsson, Xuefang Zhao, Sara Kallin

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Human soft tissue is loaded and deformed by any activity, an effect known as a stress-strain relationship, and is often described by a load and tissue elongation curve. Several advances have been made in the fields of biology and mechanics of soft human tissue. However, there is limited information available on in vivo tissue mechanical characteristics and behavior. Confident mechanical properties of human soft tissue cannot be extrapolated from e.g. animal testing. Thus, there is need for non invasive methods to analyze mechanical characteristics of soft human tissue. In the present study, the internal mechanical conditions of the lower limb, which is subject to an external load, is studied by use of the finite element method. A detailed finite element model of the lower limb is made possible by use of MRI scans. Skin, fat, bones, fascia and muscles are represented separately and the material properties for them are obtained from literature. Previous studies have been shown to address macroscopic deformation features, e.g. indentation depth, to a large extent. However, the detail in which the internal anatomical features have been modeled does not reveal the critical internal strains that may induce hypoxia and/or eventual tissue damage. The results of the present study reveals that lumped material models, i.e. averaging of the material properties for the different constituents, does not capture regions of critical strains in contrast to more detailed models.

Keywords: FEM, human soft tissue, indentation, properties.

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Authors: Caje F. Pinto, Jivan S. Parab, Gourish M. Naik

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This paper is about the development of non-invasive heart rate and oxygen saturation in human blood using Altera NIOS II soft-core processor system. In today's world, monitoring oxygen saturation and heart rate is very important in hospitals to keep track of low oxygen levels in blood. We have designed an Embedded System On Peripheral Chip (SOPC) reconfigurable system by interfacing two LED’s of different wavelengths (660 nm/940 nm) with a single photo-detector to measure the absorptions of hemoglobin species at different wavelengths. The implementation of the interface with Finger Probe and Liquid Crystal Display (LCD) was carried out using NIOS II soft-core system running on Altera NANO DE0 board having target as Cyclone IVE. This designed system is used to monitor oxygen saturation in blood and heart rate for different test subjects. The designed NIOS II processor based non-invasive heart rate and oxygen saturation was verified with another Operon Pulse oximeter for 50 measurements on 10 different subjects. It was found that the readings taken were very close to the Operon Pulse oximeter.

Keywords: Heart rate, NIOS II, Oxygen Saturation, photoplethysmography, soft-core, SOPC.

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Authors: Wei-Lun Hsu, Mon-Jyh Lin, Jyh-Ping Hsu

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The dissolution of spherical particles in liquids is analyzed dynamically. Here, we consider the case the dissolution of solute yields a solute-free solid phase in the outer portion of a particle. As dissolution proceeds, the interface between the undissolved solid phase and the solute-free solid phase moves towards the center of the particle. We assume that there exist two resistances for the diffusion of solute molecules: the resistance due to the solute-free portion of the particle and that due to a surface layer near solid-liquid interface. In general, the equation governing the dynamic behavior of dissolution needs to be solved numerically. However, analytical expressions for the temporal variation of the size of the undissoved portion of a particle and the variation of dissolution time can be obtained in some special cases. The present analysis takes the effect of variable bulk solute concentration on dissolution into account.

Keywords: dissolution of particles, surface layer, shrinking core model, dissolution time.

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Authors: A. Borji, M. Hamidi

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A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together in colonies. We use comprehensive learning particle swarm optimization (CLPSO) technique to find optimal fuzzy rules and membership functions because it discourages premature convergence. Here each particle of the swarm codes a set of fuzzy rules. During evolution, a population member tries to maximize a fitness criterion which is here high classification rate and small number of rules. Finally, particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Our results, using this method for soccer field image segmentation in Robocop contests shows 89% performance. Less computational load is needed when using this method compared with other methods like ANFIS, because it generates a smaller number of fuzzy rules. Large train dataset and its variety, makes the proposed method invariant to illumination noise

Keywords: Comprehensive learning Particle Swarmoptimization, fuzzy classification.

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Authors: A. Yazdanpanah Goharrizi

Abstract:

An improved topology of a voltage-fed quasi-resonant soft switching LCrCdc series-parallel half bridge inverter with a constant-frequency for electronic ballast applications is proposed in this paper. This new topology introduces a low-cost solution to reduce switching losses and circuit rating to achieve high-efficiency ballast. Switching losses effect on ballast efficiency is discussed through experimental point of view. In this discussion, an improved topology in which accomplishes soft switching operation over a wide power regulation range is proposed. The proposed structure uses reverse recovery diode to provide better operation for the ballast system. A symmetrical pulse wide modulation (PWM) control scheme is implemented to regulate a wide range of out-put power. Simulation results are kindly verified with the experimental measurements obtained by ballast-lamp laboratory prototype. Different load conditions are provided in order to clarify the performance of the proposed converter.

Keywords: Electronic ballast, Pulse wide modulation (PWM) Reverse recovery diode, Soft switching.

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Authors: Chen-Chien Hsu, Guo-Tang Dai

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This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image

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Authors: XueSong Yu, JiaFeng Liu, XiangLong Tang, JianHua Huang

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For improving the efficiency of human 3D tracking, we present an algorithm to track 3D Arm Motion. First, the Hierarchy Limb Model (HLM) is proposed based on the human 3D skeleton model. Second, via graph decomposition, the arm motion state space, modeled by HLM, can be discomposed into two low dimension subspaces: root nodes and leaf nodes. Finally, Rao-Blackwellised Particle Filter is used to estimate the 3D arm motion. The result of experiment shows that our algorithm can advance the computation efficiency.

Keywords: Hierarchy Limb Model; Rao-Blackwellised Particle Filter; 3D tracking

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Hassnen M. Jafer, W. Atherton, F. Ruddock, E. Loffill

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This study represents the results of an experimental work using two types of fly ashes as a cement replacement in soft soil stabilisation. The fly ashes (FA1 and FA2) used in this study are by-products resulting from an incineration processes between 800 and 1200 ˚C. The stabilised soil in this study was an intermediate plasticity silty clayey soil with medium organic matter content. The experimental works were initially conducted on soil treated with different percentages of FA1 (0, 3, 6, 9, 12, and 15%) to identify the optimum FA1 content. Then FA1 was chemically activated by FA2 which has high alkalinity by blending the optimum content of FA1 with different portions of FA2. The improvement levels were evaluated dependent on the results obtained from consistency limits and compaction tests along with the results of unconfined compressive strength (UCS) tests which were conducted on specimens of soil treated with FA1 and FA2 and exposed to different periods of curing (zero, 7, 14, and 28 days). The results indicated that the FA1 and FA2 used in this study effectively improved the physical and geotechnical properties of the soft soil where the index of plasticity (IP) was decreased significantly from 21 to 13.17 with 12% of FA1; however, there was a slight increase in IP with the use of FA2. Meanwhile, 12% of FA1 was identified as the optimum percentage improving the UCS of stabilised soil significantly. Furthermore, FA2 was found effective as a chemical activator to FA1 where the UCS was improved significantly after using FA2.

Keywords: Soft soil stabilisation, waste materials, unconfined compressive strength.

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Authors: Alhasan Hakami, Arun Kumar, Sung J Shim, Yousef Abu Nahleh

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In recent years, many high intensity earthquakes have occurred around the world, such as the 2011 earthquake in Tohoku, Japan. These large-scale disasters caused huge casualties and losses. In addition, inefficient disaster response operations also caused the second wave of casualties and losses, and expanded the damage. Effective disaster management can be used to respond to the chaotic situation, and reduce the damage; however, some inefficient disaster response operations are still used. Therefore, this case study chose the 921 earthquake for analyzing disaster emergency logistics problems and proposed the Soft Systems Methodology (SSM) to solve disaster emergency logistics problems. Moreover, it analyses the effect of human factors on system operation, and suggests a solution to improve the system.

Keywords: Soft systems methodology, emergency logistics.

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Authors: Sharifullah Ahmed, Sarwar Jahan Md. Yasin

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Shallow foundations on unimproved soft natural soils can undergo a high consolidation and secondary settlement. For low and medium rise building projects on such soil condition, pile foundation may not be cost effective. In such cases an alternative to pile foundations may be shallow strip footings placed on a double layered improved soil system soil. The upper layer of this system is untreated or cement treated compacted sand and underlying layer is natural soft clay. This system will reduce the settlement to an allowable limit. The current research has been conducted with the settlement of a rigid plane-strain strip footing of 2.5 m width placed on the surface of a soil consisting of an untreated or cement treated sand layer overlying a bed of homogeneous soft clay. The settlement of the mentioned shallow foundation has been studied considering both cases with the thicknesses of the sand layer are 0.3 to 0.9 times the width of footing. The response of the clay layer is assumed as undrained for plastic loading stages and drained during consolidation stages. The response of the sand layer is drained during all loading stages. FEM analysis was done using PLAXIS 2D Version 8.0. A natural clay deposit of 15 m thickness and 18 m width has been modeled using Hardening Soil Model, Soft Soil Model, Soft Soil Creep Model, and upper improvement layer has been modeled using only Hardening Soil Model. The groundwater level is at the top level of the clay deposit that made the system fully saturated. Parametric study has been conducted to determine the effect of thickness, density, cementation of the sand mat and density, shear strength of the soft clay layer on the settlement of strip foundation under the uniformly distributed vertical load of varying value. A set of the chart has been established for designing shallow strip footing on the sand mat over thick, soft clay deposit through obtaining the particular thickness of sand mat for particular subsoil parameter to ensure no punching shear failure and no settlement beyond allowable level. Design guideline in the form of non-dimensional charts has been developed for footing pressure equivalent to medium-rise residential or commercial building foundation with strip footing on soft inorganic Normally Consolidated (NC) soil of Bangladesh having void ratio from 1.0 to 1.45.

Keywords: Design charts, ground improvement, PLAXIS 2D, primary and secondary settlement, sand Mat, soft clay.

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Authors: R. Bures, M. Streckova, M. Faberova, P. Kurek

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Composite material based on Fe3Si micro-particles and Mn-Zn nano-ferrite was prepared using powder metallurgy technology. The sol-gel followed by autocombustion process was used for synthesis of Mn0.8Zn0.2Fe2O4 ferrite. 3 wt.% of mechanically milled ferrite was mixed with Fe3Si powder alloy. Mixed micro-nano powder system was homogenized by the Resonant Acoustic Mixing using ResodynLabRAM Mixer. This non-invasive homogenization technique was used to preserve spherical morphology of Fe3Si powder particles. Uniaxial cold pressing in the closed die at pressure 600 MPa was applied to obtain a compact sample. Microwave sintering of green compact was realized at 800°C, 20 minutes, in air. Density of the powders and composite was measured by Hepycnometry. Impulse excitation method was used to measure elastic properties of sintered composite. Mechanical properties were evaluated by measurement of transverse rupture strength (TRS) and Vickers hardness (HV). Resistivity was measured by 4 point probe method. Ferrite phase distribution in volume of the composite was documented by metallographic analysis. It has been found that nano-ferrite particle distributed among micro- particles of Fe3Si powder alloy led to high relative density (~93%) and suitable mechanical properties (TRS >100 MPa, HV ~1GPa, E-modulus ~140 GPa) of the composite. High electric resistivity (R~6.7 ohm.cm) of prepared composite indicate their potential application as soft magnetic material at medium and high frequencies.

Keywords: Micro- and nano-composite, soft magnetic materials, microwave sintering, mechanical and electric properties.

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Authors: S. G. Ponnambalam, Low Seng Kiat

Abstract:

In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve machine loading problem in flexible manufacturing system (FMS), with bicriterion objectives of minimizing system unbalance and maximizing system throughput in the occurrence of technological constraints such as available machining time and tool slots. A mathematical model is used to select machines, assign operations and the required tools. The performance of the PSO is tested by using 10 sample dataset and the results are compared with the heuristics reported in the literature. The results support that the proposed PSO is comparable with the algorithms reported in the literature.

Keywords: Machine loading problem, FMS, Particle Swarm Optimization.

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