Search results for: Sub-Nyquist sampling jamming method
7208 Neighbour Cell List Reduction in Multi-Tier Heterogeneous Networks
Authors: Mohanad Alhabo, Naveed Nawaz
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The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing handover procedure while the user is on the move. However, dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and/or handover failure because of short time of stay of a user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method decreases the candidate small cell list, unnecessary handovers, handover failure and short time of stay cells compared to the competitive method.
Keywords: Handover, HetNets, MADM, small cells.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5247207 Evolving Neural Networks using Moment Method for Handwritten Digit Recognition
Authors: H. El Fadili, K. Zenkouar, H. Qjidaa
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This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.Keywords: Genetic algorithm, Legendre Moments, MEP, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16547206 Optimization of Molasses Desugarization Process Using Steffen Method in Sugar Beet Factories
Authors: Simin Asadollahi, Mohammad Hossein Haddad Khodaparast
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Molasses is one of the most important by-products in sugar industry, which contains a large amount of sucrose. The routine way to separate the sucrose from molasses is using steffen method. Whereas this method is very usual in sugar factories, the aim of this research is optimization of this method. Mentioned optimization depends to three factors of reactor alkality, reactor temperature and diluted molasses brix. Accordingly, three different stages must be done:
- Construction of a pilot plant similar to actual steffen system in sugar factories
- Experimenting using the pilot plant
- Laboratory analysis
These experiences included 27 treatments in three replications. In each replication, brix, polarization and purity characters in Saccharate syrup and hot and cold waste were measured. The results showed that diluted molasses brix, reactor alkality and reactor temperature had many significant effects on Saccharate purity and efficiency of molasses desugarization. This research was performed in "randomize complete design" form & was analyzed with "duncan multiple range test". The significant difference in the level of α = 5% is observed between the treatments. The results indicated that the optimal conditions for molasses desugarization by steffen method are: diluted molasses brix= 10, reactor alkality= 10 and reactor temperature=8˚C.
Keywords: Molasses desugarization, Saccharate purity, Steffen process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29787205 Determining Optimum Time Multiplier Setting of Overcurrent Relays Using Mixed Integer Linear Programming
Authors: P. N. Korde, P. P. Bedekar
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The time coordination of overcurrent relays (OCR) in a power distribution network is of great importance, as it reduces the power outages by avoiding the mal-operation of the backup relays. For this, the optimum value of the time multiplier setting (TMS) of OCRs should be chosen. The problem of determining the optimum value of TMS of OCRs in power distribution networks is formulated as a constrained optimization problem. The objective is to find the optimum value of TMS of OCRs to minimize the time of operation of relays under the constraint of maintaining the coordination of relays. A power distribution network can have a combination of numerical and electromechanical relays. The TMS of numerical relays can be set to any real value (which satisfies the constraints of the problem), whereas the TMS of electromechanical relays can be set in fixed step (0 to 1 in steps of 0.05). The main contribution of this paper is a formulation of the problem as a mixed-integer linear programming (MILP) problem and application of Gomory's cutting plane method to find the optimum value of TMS of OCRs. The TMS of electromechanical relays are taken as integers in the range 1 to 20 in the step of 1, and these values are mapped to 0.05 to 1 in the step of 0.05. The results obtained are compared with those obtained using a simplex method and its variants. It has been shown that the mixed-integer linear programming method outperforms the simplex method (and its variants) in the case of a system having a combination of numerical and electromechanical relays.
Keywords: Backup protection, constrained optimization, Gomory's cutting plane method, mixed-integer linear programming, overcurrent relay coordination, simplex method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4077204 The Dialectic between Effectiveness and Humanity in the Era of Open Knowledge from the Perspective of Pedagogy
Authors: Sophia Ming Lee Wen, Chao-Ching Kuo, Yu-Line Hu, Yu-Lung Ho, Chih-Cheng Huang, Yi-Hwa Lee
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Teaching and learning should involve social issues by which effectiveness and humanity is due consideration as a guideline for sharing and co-creating knowledge. A qualitative method was used after a pioneer study to confirm pre-service teachers’ awareness of open knowledge. There are 17 in-service teacher candidates sampling from 181 schools in Taiwan. Two questions are to resolve: a) How did teachers change their educational ideas, in particular, their attitudes to meet the needs of knowledge sharing and co-creativity; and b) How did they acknowledge the necessity of working out an appropriate way between the educational efficiency and the nature of education for high performance management. This interview investigated teachers’ attitude of sharing and co-creating knowledge. The results show two facts in Taiwan: A) Individuals who must be able to express themselves will be capable of taking part in an open learning environment; and B) Teachers must lead the direction to inspire high performance and improve students’ capacity via knowledge sharing and co-creating knowledge, according to the student-centered philosophy. Collected data from interviewing showed that the teachers were well aware of changing their teaching methods and make some improvements to balance the educational efficiency and the nature of education. Almost all teachers acknowledge that ICT is helpful to motivate learning enthusiasm. Further, teaching integrated with ICT saves teachers’ time and energy on teaching preparation and promoting effectiveness. Teachers are willing to co-create knowledge with students, though using information is not easy due to the lack of operating skills of the website and ICT. Some teachers are against to co-create knowledge in the informational background since they hold that is not feasible for there being a knowledge gap between teachers and students. Technology would easily mislead teachers and students to the goal of instrumental rationality, which makes pedagogy dysfunctional and inhumane; however, any high quality of teaching should take a dialectical balance between effectiveness and humanity.Keywords: Open knowledge, dialect between effectiveness and humanity, pedagogy, critical thinking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13677203 Reading Literacy and Methods of Improving Reading
Authors: Iva Košek Bartošová, Andrea Jokešová, Eva Kozlová, Helena Matějová
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The paper presents results of a research team from Faculty of Education, University of Hradec Králové in the Czech Republic. It introduces with the most reading methods used in the 1st classes of a primary school and presents results of a pilot research focused on mastering reading techniques and the quality of reading comprehension of pupils in the first half of a school year during training in teaching reading by an analytic-synthetic method and by a genetic method. These methods of practicing reading skills are the most used ones in the Czech Republic. During the school year 2015/16 there has been a measurement made of two groups of pupils of the 1st year and monitoring of quantitative and qualitative parameters of reading pupils’ outputs by several methods. Both of these methods are based on different theoretical basis and each of them has a specific educational and methodical procedure. This contribution represents results during a piloting project and draws pilot conclusions which will be verified in the subsequent broader research at the end of the school year of the first class of primary school.
Keywords: Analytic-synthetic method of reading, genetic method of reading, reading comprehension, reading literacy, reading methods, reading speed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10337202 A C1-Conforming Finite Element Method for Nonlinear Fourth-Order Hyperbolic Equation
Authors: Yang Liu, Hong Li, Siriguleng He, Wei Gao, Zhichao Fang
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In this paper, the C1-conforming finite element method is analyzed for a class of nonlinear fourth-order hyperbolic partial differential equation. Some a priori bounds are derived using Lyapunov functional, and existence, uniqueness and regularity for the weak solutions are proved. Optimal error estimates are derived for both semidiscrete and fully discrete schemes.
Keywords: Nonlinear fourth-order hyperbolic equation, Lyapunov functional, existence, uniqueness and regularity, conforming finite element method, optimal error estimates.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18757201 Self-Organizing Control Systems for Unstable and Deterministic Chaotic Processes
Authors: M. A. Beisenbi, N. M. Kissikova, S. E. Beisembina, S. T. Suleimenova, S. A. Kaliyeva
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The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector-functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.
Keywords: Gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4277200 Estimation of OPC, Fly Ash and Slag Contents in Blended and Composite Cements by Selective Dissolution Method
Authors: Suresh Palla, Suresh Vanguri, Anitha, B. N. Mohapatra
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This paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by selective dissolution method. Types of cement samples investigated include Ordinary Portland Cement (OPC) with fly ash as performance improver, OPC with slag as performance improver, Portland Pozzolana Cement (PPC), Portland Slag Cement (PSC) and composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement is dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this selective dissolution method can be successfully used for estimation of OPC and Supplementary Cementitious material (SCM) contents in different types of cements.
Keywords: Selective dissolution method, fly ash, Ground Granulated blast furnace slag, EDTA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3827199 Determinants of the Income of Household Level Coir Yarn Labourers in Sri Lanka
Authors: G. H. B. Dilhari, A. A. D. T. Saparamadu
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Sri Lanka is one of the prominent countries for the coir production. The coir is one of the by-products of the coconut and the coir industry is considered to be one of the traditional industries in Sri Lanka. Because of the inherent nature of the coir industry, labourers play a significant role in the coir production process. The study has analyzed the determinants of the income of the household level coir yarn labourers. The study was conducted in the Kumarakanda Grama Niladhari division. Simple random sampling was used to generate a sample of 100 household level coir yarn labourers and structured questionnaire, personal interviews, and discussion were performed to gather the required data. The obtained data were statistically analyzed by using Statistical Package for Social Science (SPSS) software. Mann-Whitney U and Kruskal-Wallis test were performed for mean comparison. The findings revealed that the household level coir yarn industry is dominated by the female workers and it was identified that fewer numbers of workers have engaged in this industry as the main occupation. In addition to that, elderly participation in the industry is higher than the younger participation and most of them have engaged in the industry as a source of extra income. Level of education, the methods of engagement, satisfaction, engagement in the industry by the next generation, support from the government, method of government support, working hours per day, employed as a main job, number of completed units per day, suffering from job related diseases and type of the diseases were related with income level of household level coir yarn laboures. The recommendations as to flourish in future includes, technological transformation for coir yarn production, strengthening the raw material base and regulating the raw material supply, introduction of new technologies, markets and training programmes, the establishment of the labourers’ association, the initiation of micro credit schemes and better consideration about the job oriented diseases.Keywords: Coir, Income, Sri Lanka.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15077198 Independent Component Analysis to Mass Spectra of Aluminium Sulphate
Authors: M. Heikkinen, A. Sarpola, H. Hellman, J. Rämö, Y. Hiltunen
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Independent component analysis (ICA) is a computational method for finding underlying signals or components from multivariate statistical data. The ICA method has been successfully applied in many fields, e.g. in vision research, brain imaging, geological signals and telecommunications. In this paper, we apply the ICA method to an analysis of mass spectra of oligomeric species emerged from aluminium sulphate. Mass spectra are typically complex, because they are linear combinations of spectra from different types of oligomeric species. The results show that ICA can decomposite the spectral components for useful information. This information is essential in developing coagulation phases of water treatment processes.
Keywords: Independent component analysis, massspectroscopy, water treatment, aluminium sulphate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23607197 An Evaluation of Software Connection Methods for Heterogeneous Sensor Networks
Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read
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The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.
Keywords: Wireless sensor networks, remote method invocation, transmission time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15067196 Statistical Properties and Performance of Ecological Indices Based On Relative Abundances
Authors: Gebriel M. Shamia
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The Improved Generalized Diversity Index (IGDI) has been proposed as a tool that can be used to identify areas that have high conservation value and measure the ecological condition of an area. IGDI is based on the species relative abundances. This paper is concerned with particular attention is given to comparisons involving the MacArthur model of species abundances. The properties and performance of various species indices were assessed. Both IGDI and species richness increased with sampling area according to a power function. IGDI were also found to be acceptable ecological indicators of conditions and consistently outperformed coefficient of conservatism indices.Keywords: Statistical ecology, MacArthur model, Functional Diversity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20047195 Knowledge and Eating Behavior of Teenage Pregnancy
Authors: Udomporn Yingpaisuk, Premwadee Karuhadej
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The purposed of this research was to study the eating habit of teenage pregnancy and its relationship to the knowledge of nutrition during pregnancy. The 100 samples were derived from simple random sampling technique of the teenage pregnancy in Bangkae District. The questionnaire was used to collect data with the reliability of 0.8. The data were analyzed by SPSS for Windows with multiple regression technique. Percentage, mean and the relationship of knowledge of eating and eating behavior were obtained. The research results revealed that their knowledge in nutrition was at the average of 4.07 and their eating habit that they mentioned most was to refrain from alcohol and caffeine at 82% and the knowledge in nutrition influenced their eating habits at 54% with the statistically significant level of 0.001.Keywords: Teenage pregnancy, knowledge of nutrition, eating habit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14727194 Morphing Human Faces: Automatic Control Points Selection and Color Transition
Authors: Stephen Karungaru, Minoru Fukumi, Norio Akamatsu
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In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. This method is fully automatic in that it can morph two face images by automatically detecting all the control points necessary to perform the morph. A face detection neural network, edge detection and medium filters are employed to detect the face position and features. Five control points, for both the source and target images, are then extracted based on the facial features. Triangulation method is then used to match and warp the source image to the target image using the control points. Finally color interpolation is done using a color Gaussian model that calculates the color for each particular frame depending on the number of frames used. A real coded Genetic algorithm is used in both the image warping and color blending steps to assist in step size decisions and speed up the morphing. This method results in ''very smooth'' morphs and is fast to process.
Keywords: color transition, genetic algorithms morphing, warping
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28097193 Determination of EDTA in Dairy Wastewater and Adjacent Surface Water
Authors: Congmin Z. Xie, Terry Healy, Peter Robinson, Kevin Stewart
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An HPLC-UV analytical method was developed to determine ethylenediaminetetraacetic acid (EDTA) in dairy wastewater and surface water. The optimizing separation was achieved by reversed–phase ion-pair liquid chromatography on a C18 column using methanol as mobile phase solvent, tetrabutylammonium bromide as the ion-pair reagent in pH 3.3 formate buffer solution at a flow rate of 0.9 mL min-1 with a UV detector at 265 nm. No interference of Ca, Mg or NO3 - was detected. Method performance was evaluated in terms of linearity, repeatability and reproducibility. The method detection limit was 5 μg L-1. The contents of EDTA in dairy effluents were 72 ~ 261 μg L-1 at a large dairy site. A change of EDTA concentration was observed downstream of the dairy effluent discharge, but this was well under the predicted no effect concentration for aquatic ecosystem.Keywords: Dairy wastewater, EDTA, HPLC, surface water.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18997192 Investigation of Fire Damaged Concrete Using Nonlinear Resonance Vibration Method
Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak
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This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.
Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21107191 How the Iranian Free-Style Wrestlers Know and Think about Doping? – A Knowledge and Attitude Study
Authors: F. Halabchi, A. Esteghamati, A. Razzaghi, A. Noori
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Nowadays, doping is an intricate dilemma. Wrestling is the nationally popular sport in Iran. Also the prevalence of doping may be high, due to its power demanding characteristics. So, we aimed to assess the knowledge and attitudes toward doping among the club wrestlers. In a cross sectional study, 426 wrestlers were studied. For this reason, a researcher made questionnaire was used. In this study, researchers selected the clubs by randomized clustered sampling and distributed the questionnaire among wrestlers. Knowledge of wrestlers in three categories of doping definitions, recognition of prohibited drugs and side effects was poor or moderate in 70.8%, 95.8% and 99.5%, respectively. Wrestlers have poor knowledge in doping. Furthermore, they believe some myths which are unfavorable. It seems necessary to design a comprehensive educational program for all of the athletes and coaches.Keywords: Attitude, Doping, Knowledge, Wrestling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16037190 The Classification Model for Hard Disk Drive Functional Tests under Sparse Data Conditions
Authors: S. Pattanapairoj, D. Chetchotsak
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This paper proposed classification models that would be used as a proxy for hard disk drive (HDD) functional test equitant which required approximately more than two weeks to perform the HDD status classification in either “Pass" or “Fail". These models were constructed by using committee network which consisted of a number of single neural networks. This paper also included the method to solve the problem of sparseness data in failed part, which was called “enforce learning method". Our results reveal that the constructed classification models with the proposed method could perform well in the sparse data conditions and thus the models, which used a few seconds for HDD classification, could be used to substitute the HDD functional tests.Keywords: Sparse data, Classifications, Committee network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17247189 Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs
Authors: Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan
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Many-core GPUs provide high computing ability and substantial bandwidth; however, optimizing irregular applications like SpMV on GPUs becomes a difficult but meaningful task. In this paper, we propose a novel method to improve the performance of SpMV on GPUs. A new storage format called HYB-R is proposed to exploit GPU architecture more efficiently. The COO portion of the matrix is partitioned recursively into a ELL portion and a COO portion in the process of creating HYB-R format to ensure that there are as many non-zeros as possible in ELL format. The method of partitioning the matrix is an important problem for HYB-R kernel, so we also try to tune the parameters to partition the matrix for higher performance. Experimental results show that our method can get better performance than the fastest kernel (HYB) in NVIDIA-s SpMV library with as high as 17% speedup.Keywords: GPU, HYB-R, Many-core, Performance Tuning, SpMV
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19797188 2D and 3D Finite Element Method Packages of CEMTool for Engineering PDE Problems
Authors: Choon Ki Ahn, Jung Hun Park, Wook Hyun Kwon
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CEMTool is a command style design and analyzing package for scientific and technological algorithm and a matrix based computation language. In this paper, we present new 2D & 3D finite element method (FEM) packages for CEMTool. We discuss the detailed structures and the important features of pre-processor, solver, and post-processor of CEMTool 2D & 3D FEM packages. In contrast to the existing MATLAB PDE Toolbox, our proposed FEM packages can deal with the combination of the reserved words. Also, we can control the mesh in a very effective way. With the introduction of new mesh generation algorithm and fast solving technique, our FEM packages can guarantee the shorter computational time than MATLAB PDE Toolbox. Consequently, with our new FEM packages, we can overcome some disadvantages or limitations of the existing MATLAB PDE Toolbox.Keywords: CEMTool, Finite element method (FEM), Numericalanalysis, Partial differential equation (PDE)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37887187 Low Power Bus Binding Based on Dynamic Bit Reordering
Authors: Jihyung Kim, Taejin Kim, Sungho Park, Jun-Dong Cho
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In this paper, the problem of reducing switching activity in on-chip buses at the stage of high-level synthesis is considered, and a high-level low power bus binding based on dynamic bit reordering is proposed. Whereas conventional methods use a fixed bit ordering between variables within a bus, the proposed method switches a bit ordering dynamically to obtain a switching activity reduction. As a result, the proposed method finds a binding solution with a smaller value of total switching activity (TSA). Experimental result shows that the proposed method obtains a binding solution having 12.0-34.9% smaller TSA compared with the conventional methods.Keywords: bit reordering, bus binding, low power, switching activity matrix
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12897186 Bayesian Inference for Phase Unwrapping Using Conjugate Gradient Method in One and Two Dimensions
Authors: Yohei Saika, Hiroki Sakaematsu, Shota Akiyama
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We investigated statistical performance of Bayesian inference using maximum entropy and MAP estimation for several models which approximated wave-fronts in remote sensing using SAR interferometry. Using Monte Carlo simulation for a set of wave-fronts generated by assumed true prior, we found that the method of maximum entropy realized the optimal performance around the Bayes-optimal conditions by using model of the true prior and the likelihood representing optical measurement due to the interferometer. Also, we found that the MAP estimation regarded as a deterministic limit of maximum entropy almost achieved the same performance as the Bayes-optimal solution for the set of wave-fronts. Then, we clarified that the MAP estimation perfectly carried out phase unwrapping without using prior information, and also that the MAP estimation realized accurate phase unwrapping using conjugate gradient (CG) method, if we assumed the model of the true prior appropriately.
Keywords: Bayesian inference using maximum entropy, MAP estimation using conjugate gradient method, SAR interferometry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17357185 Effective Traffic Lights Recognition Method for Real Time Driving Assistance Systemin the Daytime
Authors: Hyun-Koo Kim, Ju H. Park, Ho-Youl Jung
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This paper presents an effective traffic lights recognition method at the daytime. First, Potential Traffic Lights Detector (PTLD) use whole color source of YCbCr channel image and make each binary image of green and red traffic lights. After PTLD step, Shape Filter (SF) use to remove noise such as traffic sign, street tree, vehicle, and building. At this time, noise removal properties consist of information of blobs of binary image; length, area, area of boundary box, etc. Finally, after an intermediate association step witch goal is to define relevant candidates region from the previously detected traffic lights, Adaptive Multi-class Classifier (AMC) is executed. The classification method uses Haar-like feature and Adaboost algorithm. For simulation, we are implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM and tested in the urban and rural roads. Through the test, we are compared with our method and standard object-recognition learning processes and proved that it reached up to 94 % of detection rate which is better than the results achieved with cascade classifiers. Computation time of our proposed method is 15 ms.Keywords: Traffic Light Detection, Multi-class Classification, Driving Assistance System, Haar-like Feature, Color SegmentationMethod, Shape Filter
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27687184 Calibration of Syringe Pumps Using Interferometry and Optical Methods
Authors: E. Batista, R. Mendes, A. Furtado, M. C. Ferreira, I. Godinho, J. A. Sousa, M. Alvares, R. Martins
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Syringe pumps are commonly used for drug delivery in hospitals and clinical environments. These instruments are critical in neonatology and oncology, where any variation in the flow rate and drug dosing quantity can lead to severe incidents and even death of the patient. Therefore it is very important to determine the accuracy and precision of these devices using the suitable calibration methods. The Volume Laboratory of the Portuguese Institute for Quality (LVC/IPQ) uses two different methods to calibrate syringe pumps from 16 nL/min up to 20 mL/min. The Interferometric method uses an interferometer to monitor the distance travelled by a pusher block of the syringe pump in order to determine the flow rate. Therefore, knowing the internal diameter of the syringe with very high precision, the travelled distance, and the time needed for that travelled distance, it was possible to calculate the flow rate of the fluid inside the syringe and its uncertainty. As an alternative to the gravimetric and the interferometric method, a methodology based on the application of optical technology was also developed to measure flow rates. Mainly this method relies on measuring the increase of volume of a drop over time. The objective of this work is to compare the results of the calibration of two syringe pumps using the different methodologies described above. The obtained results were consistent for the three methods used. The uncertainties values were very similar for all the three methods, being higher for the optical drop method due to setup limitations.
Keywords: Calibration, interferometry, syringe pump, optical method, uncertainty.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7597183 Unscented Grid Filtering and Smoothing for Nonlinear Time Series Analysis
Authors: Nikolay Nikolaev, Evgueni Smirnov
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This paper develops an unscented grid-based filter and a smoother for accurate nonlinear modeling and analysis of time series. The filter uses unscented deterministic sampling during both the time and measurement updating phases, to approximate directly the distributions of the latent state variable. A complementary grid smoother is also made to enable computing of the likelihood. This helps us to formulate an expectation maximisation algorithm for maximum likelihood estimation of the state noise and the observation noise. Empirical investigations show that the proposed unscented grid filter/smoother compares favourably to other similar filters on nonlinear estimation tasks. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13207182 A Family Cars- Life Cycle Cost (LCC)-Oriented Hybrid Modelling Approach Combining ANN and CBR
Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li
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Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19507181 An Organizational Strategic Analysis for Dynamics of Generating Firms- Alliance Networks
Authors: Takao Sakakura, Kazunori Fujimoto
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This paper proposes an analytical method for the dynamics of generating firms- alliance networks along with business phases. Dynamics in network developments have previously been discussed in the research areas of organizational strategy rather than in the areas of regional cluster, where the static properties of the networks are often discussed. The analytical method introduces the concept of business phases into innovation processes and uses relationships called prior experiences; this idea was developed in organizational strategy to investigate the state of networks from the viewpoints of tradeoffs between link stabilization and node exploration. This paper also discusses the results of the analytical method using five cases of the network developments of firms. The idea of Embeddedness helps interpret the backgrounds of the analytical results. The analytical method is useful for policymakers of regional clusters to establish concrete evaluation targets and a viewpoint for comparisons of policy programs.Keywords: Regional Clusters, Alliance Networks, Innovation Processes, Prior Experiences, Embeddedness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12607180 Analysis of a Self-Acting Air Journal Bearing: Effect of Dynamic Deformation of Bump Foil
Authors: H. Bensouilah, H. Boucherit, M. Lahmar
Abstract:
A theoretical investigation on the effects of both steady-state and dynamic deformations of the foils on the dynamic performance characteristics of a self-acting air foil journal bearing operating under small harmonic vibrations is proposed. To take into account the dynamic deformations of foils, the perturbation method is used for determining the gas-film stiffness and damping coefficients for given values of excitation frequency, compressibility number, and compliance factor of the bump foil. The nonlinear stationary Reynolds’ equation is solved by means of the Galerkins’ finite element formulation while the finite differences method are used to solve the first order complex dynamic equations resulting from the perturbation of the nonlinear transient compressible Reynolds’ equation. The stiffness of a bump is uniformly distributed throughout the bearing surface (generation I bearing). It was found that the dynamic properties of the compliant finite length journal bearing are significantly affected by the compliance of foils especially whenthe dynamic deformation of foils is considered in addition to the static one by applying the principle of superposition.
Keywords: Elasto-aerodynamic lubrication, Air foil bearing, Steady-state deformation, Dynamic deformation, Stiffness and damping coefficients, Perturbation method, Fluid-structure interaction, Galerk infinite element method, Finite difference method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27417179 Performance Analysis of Genetic Algorithm with kNN and SVM for Feature Selection in Tumor Classification
Authors: C. Gunavathi, K. Premalatha
Abstract:
Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.
Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.
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