Search results for: Minkowski distance function
1218 A Hybrid Method for Determination of Effective Poles Using Clustering Dominant Pole Algorithm
Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma
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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA), is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.
Keywords: Balanced truncation, Clustering, Dominant pole, Hankel norm, Model reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26881217 Investigation on Machine Tools Energy Consumptions
Authors: Shiva Abdoli, Daniel T. Semere
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Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.
Keywords: Process parameters, cutting process, energy efficiency, Material Removal Rate (MRR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34081216 Leaching of Flotation Concentrate of Oxide Copper Ore from Sepon Mine, Lao PDR
Authors: C. Rattanakawin, S. Vasailor
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Acid leaching of flotation concentrate of oxide copper ore containing mainly of malachite was performed in a standard agitation tank with various parameters. The effects of solid to liquid ratio, sulfuric acid concentration, agitation speed, leaching temperature and time were examined to get proper conditions. The best conditions are 1:8 solid to liquid ratio, 10% concentration by weight, 250 rev/min, 30 oC and 5-min leaching time in respect. About 20% Cu grade assayed by atomic absorption technique with 98% copper recovery was obtained from these combined optimum conditions. Dissolution kinetics of the concentrate was approximated as a logarithmic function. As a result, the first-order reaction rate is suggested from this leaching study.Keywords: Agitation leaching, dissolution kinetics, flotation concentrate, oxide copper ore, sulfuric acid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6921215 Modeling and Control of a 4DoF Robotic Assistive Device for Hand Rehabilitation
Authors: Christopher Spiewak, M. R. Islam, Mohammad Arifur Rahaman, Mohammad H. Rahman, Roger Smith, Maarouf Saad
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For those who have lost the ability to move their hand, going through repetitious motions with the assistance of a therapist is the main method of recovery. We have been developed a robotic assistive device to rehabilitate the hand motions in place of the traditional therapy. The developed assistive device (RAD-HR) is comprised of four degrees of freedom enabling basic movements, hand function, and assists in supporting the hand during rehabilitation. We used a nonlinear computed torque control technique to control the RAD-HR. The accuracy of the controller was evaluated in simulations (MATLAB/Simulink environment). To see the robustness of the controller external disturbance as modelling uncertainty (±10% of joint torques) were added in each joints.Keywords: Biorobotics, rehabilitation, nonlinear control, robotic assistive device, exoskeleton.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17241214 An Approach to Control Design for Nonlinear Systems via Two-stage Formal Linearization and Two-type LQ Controls
Authors: Kazuo Komatsu, Hitoshi Takata
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In this paper we consider a nonlinear control design for nonlinear systems by using two-stage formal linearization and twotype LQ controls. The ordinary LQ control is designed on almost linear region around the steady state point. On the other region, another control is derived as follows. This derivation is based on coordinate transformation twice with respect to linearization functions which are defined by polynomials. The linearized systems can be made up by using Taylor expansion considered up to the higher order. To the resulting formal linear system, the LQ control theory is applied to obtain another LQ control. Finally these two-type LQ controls are smoothly united to form a single nonlinear control. Numerical experiments indicate that this control show remarkable performances for a nonlinear system.Keywords: Formal Linearization, LQ Control, Nonlinear Control, Taylor Expansion, Zero Function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16181213 Adaptive PID Control of Wind Energy Conversion Systems Using RASP1 Mother Wavelet Basis Function Networks
Authors: M. Sedighizadeh, A. Rezazadeh
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In this paper a PID control strategy using neural network adaptive RASP1 wavelet for WECS-s control is proposed. It is based on single layer feedforward neural networks with hidden nodes of adaptive RASP1 wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. This particular neuro PID controller assumes a certain model structure to approximately identify the system dynamics of the unknown plant (WECS-s) and generate the control signal. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution.Keywords: Adaptive PID Control, RASP1 Wavelets, WindEnergy Conversion Systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20041212 The Links between Brain Insulin Resistance and Alzheimer’s Disease
Authors: Negar Khezri, Golnaz Yaghoubnezhadzanganeh, Amirreza Attarzadeh
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Type 2 Diabetes (T2DM) and Alzheimer's disease (AD) are two main health problems influencing millions of people in the world. Neuron loss and synaptic impairment that interfere with cognition and memory cause for the behavioral indications of AD. While it is now accepted that insulin has central neuromodulatory purpose, it was contemplated for many years that brain is insusceptible to insulin, involving its function in memory and learning, which are impaired in AD. The common characteristics of both AD and T2D are impaired insulin signaling, oxidative stress, the excitation of inflammatory pathways and unqualified glucose metabolism. This review summarizes how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches. Here we summarize how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches.
Keywords: Alzheimer’s disease, diabetes, insulin resistance, neurodegenerative.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11381211 A Neural Approach for Color-Textured Images Segmentation
Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui
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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.Keywords: Segmentation, color-texture, neural networks, fractal, watershed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13741210 Reliability-Based Topology Optimization Based on Evolutionary Structural Optimization
Authors: Sang-Rak Kim, Jea-Yong Park, Won-Goo Lee, Jin-Shik Yu, Seog-Young Han
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This paper presents a Reliability-Based Topology Optimization (RBTO) based on Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of the uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.Keywords: Evolutionary Structural Optimization, PerformanceMeasure Approach, Reliability-Based Topology Optimization, Reliability Index Approach.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28011209 Genetic Combined with a Simplex Algorithm as an Efficient Method for the Detection of a Depressed Ellipsoidal Flaw using the Boundary Element Method
Authors: Clio G. Vossou, Ioannis N. Koukoulis, Christopher G. Provatidis
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The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.
Keywords: Defect identification, genetic algorithms, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12921208 Stochastic Learning Algorithms for Modeling Human Category Learning
Authors: Toshihiko Matsuka, James E. Corter
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Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16291207 Solving Partially Monotone Problems with Neural Networks
Authors: Marina Velikova, Hennie Daniels, Ad Feelders
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In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.Keywords: Mixture models, monotone neural networks, partially monotone models, partially monotone problems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16211206 The Explanation for Dark Matter and Dark Energy
Authors: Richard Lewis
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The following assumptions of the Big Bang theory are challenged and found to be false: the cosmological principle, the assumption that all matter formed at the same time and the assumption regarding the cause of the cosmic microwave background radiation. The evolution of the universe is described based on the conclusion that the universe is finite with a space boundary. This conclusion is reached by ruling out the possibility of an infinite universe or a universe which is finite with no boundary. In a finite universe, the centre of the universe can be located with reference to our home galaxy (The Milky Way) using the speed relative to the Cosmic Microwave Background (CMB) rest frame and Hubble's law. This places our home galaxy at a distance of approximately 26 million light years from the centre of the universe. Because we are making observations from a point relatively close to the centre of the universe, the universe appears to be isotropic and homogeneous but this is not the case. The CMB is coming from a source located within the event horizon of the universe. There is sufficient mass in the universe to create an event horizon at the Schwarzschild radius. Galaxies form over time due to the energy released by the expansion of space. Conservation of energy must consider total energy which is mass (+ve) plus energy (+ve) plus spacetime curvature (-ve) so that the total energy of the universe is always zero. The predominant position of galaxy formation moves over time from the centre of the universe towards the boundary so that today the majority of new galaxy formation is taking place beyond our horizon of observation at 14 billion light years.
Keywords: Cosmic microwave background, dark energy, dark matter, evolution of the universe.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9051205 All Proteins Have a Basic Molecular Formula
Authors: Homa Torabizadeh
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This study proposes a basic molecular formula for all proteins. A total of 10,739 proteins belonging to 9 different protein groups classified on the basis of their functions were selected randomly. They included enzymes, storage proteins, hormones, signalling proteins, structural proteins, transport proteins, immunoglobulins or antibodies, motor proteins and receptor proteins. After obtaining the protein molecular formula using the ProtParam tool, the H/C, N/C, O/C, and S/C ratios were determined for each randomly selected sample. In this case, H, N, O, and S coefficients were specified per carbon atom. Surprisingly, the results demonstrated that H, N, O, and S coefficients for all 10,739 proteins are similar and highly correlated. This study demonstrates that despite differences in the structure and function, all known proteins have a similar basic molecular formula CnH1.58 ± 0.015nN0.28 ± 0.005nO0.30 ± 0.007nS0.01 ± 0.002n. The total correlation between all coefficients was found to be 0.9999.Keywords: Protein molecular formula, Basic unit formula, Protparam tool.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 80811204 A System of Automatic Speech Recognition based on the Technique of Temporal Retiming
Authors: Samir Abdelhamid, Noureddine Bouguechal
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We report in this paper the procedure of a system of automatic speech recognition based on techniques of the dynamic programming. The technique of temporal retiming is a technique used to synchronize between two forms to compare. We will see how this technique is adapted to the field of the automatic speech recognition. We will expose, in a first place, the theory of the function of retiming which is used to compare and to adjust an unknown form with a whole of forms of reference constituting the vocabulary of the application. Then we will give, in the second place, the various algorithms necessary to their implementation on machine. The algorithms which we will present were tested on part of the corpus of words in Arab language Arabdic-10 [4] and gave whole satisfaction. These algorithms are effective insofar as we apply them to the small ones or average vocabularies.Keywords: Continuous speech recognition, temporal retiming, phonetic decoding, algorithms, vocal signal, dynamic programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13481203 Material and Parameter Analysis of the PolyJet Process for Mold Making Using Design of Experiments
Authors: A. Kampker, K. Kreisköther, C. Reinders
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Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.
Keywords: Additive manufacturing, design of experiments, mold making, PolyJet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17301202 Intention Recognition using a Graph Representation
Authors: So-Jeong Youn, Kyung-Whan Oh
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The human friendly interaction is the key function of a human-centered system. Over the years, it has received much attention to develop the convenient interaction through intention recognition. Intention recognition processes multimodal inputs including speech, face images, and body gestures. In this paper, we suggest a novel approach of intention recognition using a graph representation called Intention Graph. A concept of valid intention is proposed, as a target of intention recognition. Our approach has two phases: goal recognition phase and intention recognition phase. In the goal recognition phase, we generate an action graph based on the observed actions, and then the candidate goals and their plans are recognized. In the intention recognition phase, the intention is recognized with relevant goals and user profile. We show that the algorithm has polynomial time complexity. The intention graph is applied to a simple briefcase domain to test our model.Keywords: Intention recognition, intention, graph, HCI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33981201 Genetic Programming Approach to Hierarchical Production Rule Discovery
Authors: Basheer M. Al-Maqaleh, Kamal K. Bharadwaj
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Automated discovery of hierarchical structures in large data sets has been an active research area in the recent past. This paper focuses on the issue of mining generalized rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses flat rules as initial individuals of GP and discovers hierarchical structure. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy. Experimental results are presented to demonstrate the performance of the proposed algorithm.Keywords: Genetic Programming, Hierarchy, Knowledge Discovery in Database, Subsumption Matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14511200 Spectrum Sensing Based On the Cyclostationarity of PU Signals in High Traffic Environments
Authors: Keunhong Chae, Youngpo Lee, Seokho Yoon
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In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral autocoherence function of the PU signal to the generalized- likelihood ratio. From numerical results, it is confirmed that the proposed scheme provides a better spectrum sensing performance compared with the conventional spectrum sensing scheme based on the energy of the PU signals in high traffic environments.
Keywords: Spectrum sensing, cyclostationarity, high traffic environments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18551199 Restoration of Biological Function of Degraded Soil via Chemical Method
Authors: M. Chomczyńska
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The studies concerned an effect of six variants of ion exchange substrate (nutrient carriers with a different potential impact on pH of soil solution) on vegetation of orchard grass during two different periods (42 and 84 days). In the pot experiment plants were grown on sand (model of degraded soil) and six mixtures of sand and 2% (v/v) additions of particular variants of ion exchange substrate (with pH ranged from 5.5 to 8.0). The study results showed that the addition of the substrate at pH=6.5 caused the highest increase in plant yield after shorter vegetation period whereas the addition of the substrate at pH=5.5 increased dry stem and root biomass of orchard grass after longer vegetation period. Thus, the ion exchange substrate at pH=6.5 can be recommended for restoration of exhausted soils when shorter vegetation period is planned; the ion exchange substrate at pH=5.5 can be used for the same purpose when longer periods of vegetative growth are considered.Keywords: ion exchanger, ion exchange substrate, soilrestoration
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13381198 Color Image Segmentation using Adaptive Spatial Gaussian Mixture Model
Authors: M.Sujaritha, S. Annadurai
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An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.
Keywords: Adaptive; Spatial, Mixture model, Segmentation, Color.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24981197 Mathematical Simulation of Acid Concentration Effects during Acid Nitric Leaching of Cobalt from a Mixed Cobalt-Copper Oxide
Authors: Ek Ngoy, A F Mulaba-Bafubiandi
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Cobalt was acid nitric leached from a mixed cobaltcopper oxide with variable acid concentration. Resulting experimental data were used to analyze effects of increase in acid concentration, based on a shrinking core model of the process. The mathematical simulation demonstrated that the time rate of the dissolution mechanism is an increasing function of acid concentration. It was also shown that the magnitude of the acid concentration effect is time dependent and the increase in acid concentration is more effective at earlier stage of the dissolution than at later stage. The remaining process parameters are comprehensively affected by acid concentration and their interaction is synergetic.Keywords: Acid effect, Cobalt, Cobalt-copper oxide, Leaching, Simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18451196 Experimental Investigation of Plane Jets Exiting Five Parallel Channels with Large Aspect Ratio
Authors: Laurentiu Moruz, Jens Kitzhofer, Mircea Dinulescu
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The paper aims to extend the knowledge about jet behavior and jet interaction between five plane unventilated jets with large aspect ratio (AR). The distance between the single plane jets is two times the channel height. The experimental investigation applies 2D Particle Image Velocimetry (PIV) and static pressure measurements. Our study focuses on the influence of two different outlet nozzle geometries (triangular shape with 2 x 7.5° and blunt geometry) with respect to variation of Reynolds number from 5500 - 12000. It is shown that the outlet geometry has a major influence on the jet formation in terms of uniformity of velocity profiles downstream of the sudden expansion. Furthermore, we describe characteristic regions like converging region, merging region and combined region. The triangular outlet geometry generates most uniform velocity distributions in comparison to a blunt outlet nozzle geometry. The blunt outlet geometry shows an unstable behavior where the jets tend to attach to one side of the walls (ceiling) generating a large recirculation region on the opposite side. Static pressure measurements confirm the observation and indicate that the recirculation region is connected to larger pressure drop.
Keywords: 2D particle image velocimetry, parallel jet interaction, pressure drop, sudden expansion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8771195 Self-Assembling Hypernetworks for Cognitive Learning of Linguistic Memory
Authors: Byoung-Tak Zhang, Chan-Hoon Park
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Hypernetworks are a generalized graph structure representing higher-order interactions between variables. We present a method for self-organizing hypernetworks to learn an associative memory of sentences and to recall the sentences from this memory. This learning method is inspired by the “mental chemistry" model of cognition and the “molecular self-assembly" technology in biochemistry. Simulation experiments are performed on a corpus of natural-language dialogues of approximately 300K sentences collected from TV drama captions. We report on the sentence completion performance as a function of the order of word-interaction and the size of the learning corpus, and discuss the plausibility of this architecture as a cognitive model of language learning and memory.Keywords: Linguistic recall memory, sentence completion task, self-organizing hypernetworks, cognitive learning and memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14971194 Coding Considerations for Standalone Molecular Dynamics Simulations of Atomistic Structures
Authors: R. O. Ocaya, J. J. Terblans
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The laws of Newtonian mechanics allow ab-initio molecular dynamics to model and simulate particle trajectories in material science by defining a differentiable potential function. This paper discusses some considerations for the coding of ab-initio programs for simulation on a standalone computer and illustrates the approach by C language codes in the context of embedded metallic atoms in the face-centred cubic structure. The algorithms use velocity-time integration to determine particle parameter evolution for up to several thousands of particles in a thermodynamical ensemble. Such functions are reusable and can be placed in a redistributable header library file. While there are both commercial and free packages available, their heuristic nature prevents dissection. In addition, developing own codes has the obvious advantage of teaching techniques applicable to new problems.Keywords: C-language, molecular dynamics, simulation, embedded atom method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14081193 Visualized Characterization of Molecular Mobility for Water Species in Foods
Authors: Yasuyuki Konishi, Masayoshi Kobayashi
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Six parameters, the effective diffusivity (De), activation energy of De, pre-exponential factor of De, amount (ASOW) of self-organized water species, and amplitude (α) of the forced oscillation of the molecular mobility (1/tC) derived from the forced cyclic temperature change operation, were characterized by using six typical foods, squid, sardines, scallops, salmon, beef, and pork, as a function of the correlation time (tC) of the water molecule-s proton retained in the foods. Each of the six parameters was clearly divided into the water species A1 and A2 at a specified value of tC =10-8s (=CtC), indicating an anomalous change in the physicochemical nature of the water species at the CtC. The forced oscillation of 1/tC clearly demonstrated a characteristic mode depending on the food shown as a three dimensional map associated with 1/tC, the amount of self-organized water, and tC.Keywords: molecular mobility, self-organization, hysteresis, water species A1 and A2, forced cyclic temperature change operation (FCTCO)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14031192 Micropower Fuzzy Linguistic-Hedges Circuit in Current-Mode Approach
Authors: E. Farshidi
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In this paper, based on a novel synthesis, a set of new simplified circuit design to implement the linguistic-hedge operations for adjusting the fuzzy membership function set is presented. The circuits work in current-mode and employ floating-gate MOS (FGMOS) transistors that operate in weak inversion region. Compared to the other proposed circuits, these circuits feature severe reduction of the elements number, low supply voltage (0.7V), low power consumption (<200nW), immunity from body effect and wide input dynamic range (>60dB). In this paper, a set of fuzzy linguistic hedge circuits, including absolutely, very, much more, more, plus minus, more or less and slightly, has been implemented in 0.18 mm CMOS process. Simulation results by Hspice confirm the validity of the proposed design technique and show high performance of the circuits.
Keywords: Current-mode, Linguistic-Hedge, Fuzzy Logic, lowpower
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17641191 Slice Bispectrogram Analysis-Based Classification of Environmental Sounds Using Convolutional Neural Network
Authors: Katsumi Hirata
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Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.
Keywords: Bispectrum, convolutional neural network, environmental sound, slice bispectrogram, spectrogram.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6191190 Development of a Cost Effective Two Wheel Tractor Mounted Mobile Maize Sheller for Small Farmers in Bangladesh
Authors: M. Israil Hossain, T. P. Tiwari, Ashrafuzzaman Gulandaz, Nusrat Jahan
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Two-wheel tractor (power tiller) is a common tillage tool in Bangladesh agriculture for easy access in fragmented land with affordable price of small farmers. Traditional maize sheller needs to be carried from place to place by hooking with two-wheel tractor (2WT) and set up again for shelling operation which takes longer time for preparation of maize shelling. The mobile maize sheller eliminates the transportation problem and can start shelling operation instantly any place as it is attached together with 2WT. It is counterclockwise rotating cylinder, axial flow type sheller, and grain separated with a frictional force between spike tooth and concave. The maize sheller is attached with nuts and bolts in front of the engine base of 2WT. The operating power of the sheller comes from the fly wheel of the engine of the tractor through ‘V” belt pulley arrangement. The average shelling capacity of the mobile sheller is 2.0 t/hr, broken kernel 2.2%, and shelling efficiency 97%. The average maize shelling cost is Tk. 0.22/kg and traditional custom hire rate is Tk.1.0/kg, respectively (1 US$=Tk.78.0). The service provider of the 2WT can transport the mobile maize sheller long distance in operator’s seating position. The manufacturers started the fabrication of mobile maize sheller. This mobile maize sheller is also compatible for the other countries where 2WT is available for farming operation.
Keywords: Cost effective, mobile maize sheller, maize shelling capacity, small farmers, two-wheel tractor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9061189 Pre-Operative Tool for Facial-Post-Surgical Estimation and Detection
Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary
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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.
Keywords: K-nearest neighbor, face detection, vitiligo, bone deformity.
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