Search results for: Baseline estimation
483 Manufacturing Process and Cost Estimation through Process Detection by Applying Image Processing Technique
Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit
Abstract:
In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.
Keywords: Image processing technique, Feature detections, Surface registrations, Capturing multi-view images, Production costs, and Manufacturing processes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1976482 Analysis of Distribution of Thrust, Torque and Efficiency of a Constant Chord, Constant Pitch C.R.P. Fan by H.E.S. Method
Authors: Morteza Abbaszadeh, Parvin Nikpoorparizi, Mina Shahrooz
Abstract:
For the first time since 1940 and presentation of theodorson-s theory, distribution of thrust, torque and efficiency along the blade of a counter rotating propeller axial fan was studied with a novel method in this research. A constant chord, constant pitch symmetric fan was investigated with Reynolds Stress Turbulence method in this project and H.E.S. method was utilized to obtain distribution profiles from C.F.D. tests outcome. C.F.D. test results were validated by estimation from Playlic-s analytical method. Final results proved ability of H.E.S. method to obtain distribution profiles from C.F.D test results and demonstrated interesting facts about effects of solidity and differences between distributions in front and rear section.Keywords: C.F.D Test, Counter Rotating Propeller, H.E.S. Method, R.S.M. Method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3023481 Odor Discrimination Using Neural Decoding of Olfactory Bulbs in Rats
Authors: K.-J. You, H.J. Lee, Y. Lang, C. Im, C.S. Koh, H.-C. Shin
Abstract:
This paper presents a novel method for inferring the odor based on neural activities observed from rats- main olfactory bulbs. Multi-channel extra-cellular single unit recordings were done by micro-wire electrodes (tungsten, 50μm, 32 channels) implanted in the mitral/tufted cell layers of the main olfactory bulb of anesthetized rats to obtain neural responses to various odors. Neural response as a key feature was measured by substraction of neural firing rate before stimulus from after. For odor inference, we have developed a decoding method based on the maximum likelihood (ML) estimation. The results have shown that the average decoding accuracy is about 100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively. This work has profound implications for a novel brain-machine interface system for odor inference.Keywords: biomedical signal processing, neural engineering, olfactory, neural decoding, BMI
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614480 Using Morphological and Microsatellite (SSR) Markers to Assess the Genetic Diversity in Alfalfa (Medicago sativa L.)
Authors: T. Cholastova, D. Knotova
Abstract:
Utilization of diverse germplasm is needed to enhance the genetic diversity of cultivars. The objective of this study was to evaluate the genetic relationships of 98 alfalfa germplasm accessions using morphological traits and SSR markers. From the 98 tested populations, 81 were locals originating in Europe, 17 were introduced from USA, Australia, New Zealand and Canada. Three primers generated 67 polymorphic bands. The average polymorphic information content (PIC) was very high (> 0.90) over all three used primer combinations. Cluster analysis using Unweighted Pair Group Method with Arithmetic Means (UPGMA) and Jaccard´s coefficient grouped the accessions into 2 major clusters with 4 sub-clusters with no correlation between genetic and morphological diversity. The SSR analysis clearly indicated that even with three polymorphic primers, reliable estimation of genetic diversity could be obtained.Keywords: genetic diversity, Medicago sativa L., morphological traits, SSR markers
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3102479 Non-Linear Control Based on State Estimation for the Convoy of Autonomous Vehicles
Authors: M-M. Mohamed Ahmed, Nacer K. M’Sirdi, Aziz Naamane
Abstract:
In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.Keywords: Autonomous vehicles, convoy, nonlinear control, nonlinear observer, sliding mode.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 728478 Fault Location Identification in High Voltage Transmission Lines
Authors: Khaled M. El Naggar
Abstract:
This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.
Keywords: Optimization, estimation, faults, measurement, high voltage, simulated annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 841477 Angle of Arrival Estimation Using Maximum Likelihood Method
Authors: H. K. Hwang, Zekeriya Aliyazicioglu, Solomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr
Abstract:
Multiple-input multiple-output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection,resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO uniformly-spaced linear array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, pseudo random (PN) sequence length, number of snapshots, and signal to noise ratio (SNR). The results of MIMO are compared to a traditional array antenna.
Keywords: Multiple-input multiple-output (MIMO) radar, phased array antenna, target detection, radar signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2806476 Robust Adaptation to Background Noise in Multichannel C-OTDR Monitoring Systems
Authors: Andrey V. Timofeev, Viktor M. Denisov
Abstract:
A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.Keywords: Guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1948475 Integrated Power Saving for Multiple Relays and UEs in LTE-TDD
Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Chen-Ming Yang
Abstract:
In this paper, the design of integrated sleep scheduling for relay nodes and user equipments under a Donor eNB (DeNB) in the mode of Time Division Duplex (TDD) in LTE-A is presented. The idea of virtual time is proposed to deal with the discontinuous pattern of the available radio resource in TDD, and based on the estimation of the traffic load, three power saving schemes in the top-down strategy are presented. Associated mechanisms in each scheme including calculation of the virtual subframe capacity, the algorithm of integrated sleep scheduling, and the mapping mechanisms for the backhaul link and the access link are presented in the paper. Simulation study shows the advantage of the proposed schemes in energy saving over the standard DRX scheme.
Keywords: LTE-A, Relay, TDD, Power Saving.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1160474 Fractal - Wavelet Based Techniques for Improving the Artificial Neural Network Models
Authors: Reza Bazargan Lari, Mohammad H. Fattahi
Abstract:
Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.
Keywords: Wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2063473 Impairments Correction of Six-Port Based Millimeter-Wave Radar
Authors: Dan Ohev Zion, Alon Cohen
Abstract:
In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.Keywords: Radar, millimeter-wave, six-port, FMCW Radar, IQ mismatch.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 489472 Monotonic and Cyclic J-integral Estimation for Through-Wall Cracked Straight Pipes
Authors: Rohit, S. Vishnuvardhan, P. Gandhi, Nagesh R. Iyer
Abstract:
The evaluation of energy release rate and centre Crack Opening Displacement (COD) for circumferential Through-Wall Cracked (TWC) pipes is an important issue in the assessment of critical crack length for unstable fracture. The ability to predict crack growth continues to be an important component of research for several structural materials. Crack growth predictions can aid the understanding of the useful life of a structural component and the determination of inspection intervals and criteria. In this context, studies were carried out at CSIR-SERC on Nuclear Power Plant (NPP) piping components subjected to monotonic as well as cyclic loading to assess the damage for crack growth due to low-cycle fatigue in circumferentially TWC pipes.Keywords: 304LN stainless steel, cyclic J-integral, Elastic- Plastic Fracture Mechanics, J-integral, Through-wall crack
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2588471 Artificial Intelligence Applications in Aggregate Quarries: A Reality
Authors: J. E. Ortiz, P. Plaza, J. Herrero, I. Cabria, J. L. Blanco, J. Gavilanes, J. I. Escavy, I. López-Cilla, V. Yagüe, C. Pérez, S. Rodríguez, J. Rico, C. Serrano, J. Bernat
Abstract:
The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.
Keywords: Aggregates, artificial intelligence, automatization, mining operations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30470 Choosing Search Algorithms in Bayesian Optimization Algorithm
Authors: Hao Wu, Jonathan L. Shapiro
Abstract:
The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.
Keywords: Bayesian optimization algorithm, greedy search, KL divergence, stochastic search.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1700469 Normalizing Logarithms of Realized Volatility in an ARFIMA Model
Authors: G. L. C. Yap
Abstract:
Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.
Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1688468 Performance Evaluation of a Diesel Engine Fueled with Methyl Ester of shea Butter
Authors: Christopher C. Enweremadu, Hilary L. Rutto, Najeem Peleowo
Abstract:
Biodiesel as an alternative fuel for diesel engines has been developed for some three decades now. While it is gaining wide acceptance in Europe, USA and some parts of Asia, the same cannot be said of Africa. With more than 35 countries in the continent depending on imported crude oil, it is necessary to look for alternative fuels which can be produced from resources available locally within any country. Hence this study presents performance of single cylinder diesel engine using blends of shea butter biodiesel. Shea butter was transformed into biodiesel by transesterification process. Tests are conducted to compare the biodiesel with baseline diesel fuel in terms of engine performance and exhaust emission characteristics. The results obtained showed that the addition of biodiesel to diesel fuel decreases the brake thermal efficiency (BTE) and increases the brake specific fuel consumption (BSFC). These results are expected due to the lower energy content of biodiesel fuel. On the other hand while the NOx emissions increased with increase in biodiesel content in the fuel blends, the emissions of carbon monoxide (CO), un-burnt hydrocarbon (UHC) and smoke opacity decreased. The engine performance which indicates that the biodiesel has properties and characteristics similar to diesel fuel and the reductions in exhaust emissions make shea butter biodiesel a viable additive or substitute to diesel fuel.
Keywords: Biodiesel, diesel engine, engine performance and emission, shea butter, transesterification
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2592467 Free Fatty Acid Assessment of Crude Palm Oil Using a Non-Destructive Approach
Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak
Abstract:
Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.
Keywords: Palm oil, fatty acid, NIRS, regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4372466 Modeling and Identification of Hammerstein System by using Triangular Basis Functions
Authors: K. Elleuch, A. Chaari
Abstract:
This paper deals with modeling and parameter identification of nonlinear systems described by Hammerstein model having Piecewise nonlinear characteristics such as Dead-zone nonlinearity characteristic. The simultaneous use of both an easy decomposition technique and the triangular basis functions leads to a particular form of Hammerstein model. The approximation by using Triangular basis functions for the description of the static nonlinear block conducts to a linear regressor model, so that least squares techniques can be used for the parameter estimation. Singular Values Decomposition (SVD) technique has been applied to separate the coupled parameters. The proposed approach has been efficiently tested on academic examples of simulation.Keywords: Identification, Hammerstein model, Piecewisenonlinear characteristic, Dead-zone nonlinearity, Triangular basisfunctions, Singular Values Decomposition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1920465 Detecting the Capacity Reserve in an Overhead Line
Authors: S. Berjozkina, A. Sauhats, V. Bargels, E. Vanzovichs
Abstract:
There are various solutions for improving existing overhead line systems with the general purpose of increasing their limited capacity. The capacity reserve of the existing overhead lines is an important problem that must be considered from different aspects. The paper contains a comparative analysis of the mechanical and thermal limitations of an existing overhead line based on certain calculation conditions characterizing the examined variants. The methodology of the proposed estimation of the permissible conductor temperature and maximum load current is described in detail. The transmission line model consists of specific information of an existing overhead line of the Latvian power network. The main purpose of the simulation tasks is to find an additional capacity reserve by using accurate mathematical models. The results of the obtained data are presented.
Keywords: capacity of an overhead line, mechanical conditions, permissible conductor temperature, thermal conditions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2003464 SPA-VNDN: Enhanced Smart Parking Application by Vehicular Named Data Networking
Authors: Bassma Aldahlan, Zongming Fei
Abstract:
Recently, there is a great interest in smart parking application. Theses applications are enhanced by a vehicular ad-hoc network, which helps drivers find and reserve satiable packing spaces for a period of time ahead of time. Named Data Networking (NDN) is a future Internet architecture that benefits vehicular ad-hoc networks because of its clean-slate design and pure communication model. In this paper, we proposed an NDN-based frame-work for smart parking that involved a fog computing architecture. The proposed application had two main directions: First, we allowed drivers to query the number of parking spaces in a particular parking lot. Second, we introduced a technique that enabled drivers to make intelligent reservations before their arrival time. We also introduced a “push-based” model supporting the NDN-based framework for smart parking applications. To evaluate the proposed solution’s performance, we analyzed the function for finding parking lots with available parking spaces and the function for reserving a parking space. Our system showed high performance results in terms of response time and push overhead. The proposed reservation application performed better than the baseline approach.
Keywords: Cloud Computing, Vehicular Named Data Networking, Smart Parking Applications, Fog Computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 227463 Using a Trust-Based Environment Key for Mobile Agent Code Protection
Authors: Salima Hacini, Zahia Guessoum, Zizette Boufaïda
Abstract:
Human activities are increasingly based on the use of remote resources and services, and on the interaction between remotely located parties that may know little about each other. Mobile agents must be prepared to execute on different hosts with various environmental security conditions. The aim of this paper is to propose a trust based mechanism to improve the security of mobile agents and allow their execution in various environments. Thus, an adaptive trust mechanism is proposed. It is based on the dynamic interaction between the agent and the environment. Information collected during the interaction enables generation of an environment key. This key informs on the host-s trust degree and permits the mobile agent to adapt its execution. Trust estimation is based on concrete parameters values. Thus, in case of distrust, the source of problem can be located and a mobile agent appropriate behavior can be selected.Keywords: Internet security, malicious host, mobile agent security, trust management
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1413462 Estimating 3D-Position of A Stationary Random Acoustic Source Using Bispectral Analysis of 4-Point Detected Signals
Authors: Katsumi Hirata
Abstract:
To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.
Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1437461 Modeling the Effects of Type and Intensity of Selective Logging on Forests of the Amazon
Authors: Theodore N.S. Karfakis, Anna Andrade, Carolina Volkmer-Castilho, Dennis R. Valle, Eric Arets, Paul van Gardingen
Abstract:
The aim of the work presented here was to either use existing forest dynamic simulation models or calibrate a new one both within the SYMFOR framework with the purpose of examining changes in stand level basal area and functional composition in response to selective logging considering trees > 10 cm d.b.h for two areas of undisturbed Amazonian non flooded tropical forest in Brazil and one in Peru. Model biological realism was evaluated for forest in the undisturbed and selectively logged state and it was concluded that forest dynamics were realistically represented. Results of the logging simulation experiments showed that in relation to undisturbed forest simulation subject to no form of harvesting intervention there was a significant amount of change over a 90 year simulation period that was positively proportional to the intensity of logging. Areas which had in the dynamic equilibrium of undisturbed forest a greater proportion of a specific ecological guild of trees known as the light hardwoods (LHW’s) seemed to respond more favorably in terms of less deviation but only within a specific range of baseline forest composition beyond which compositional diversity became more important. These finds are in line partially with practical management experience and partiality basic systematics theory respectively.
Keywords: Amazonbasin, ecological species guild, selective logging, simulation modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1665460 Emotion Classification for Students with Autism in Mathematics E-learning using Physiological and Facial Expression Measures
Authors: Hui-Chuan Chu, Min-Ju Liao, Wei-Kai Cheng, William Wei-Jen Tsai, Yuh-Min Chen
Abstract:
Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.
Keywords: Emotion classification, Physiological and facial Expression measures, Students with autism, Mathematics e-learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1781459 CMOS Solid-State Nanopore DNA System-Level Sequencing Techniques Enhancement
Authors: Syed Islam, Yiyun Huang, Sebastian Magierowski, Ebrahim Ghafar-Zadeh
Abstract:
This paper presents system level CMOS solid-state nanopore techniques enhancement for speedup next generation molecular recording and high throughput channels. This discussion also considers optimum number of base-pair (bp) measurements through channel as an important role to enhance potential read accuracy. Effective power consumption estimation offered suitable range of multi-channel configuration. Nanopore bp extraction model in statistical method could contribute higher read accuracy with longer read-length (200 < read-length). Nanopore ionic current switching with Time Multiplexing (TM) based multichannel readout system contributed hardware savings.
Keywords: DNA, Nanopore, Amplifier, ADC, Multichannel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2932458 Facial Recognition on the Basis of Facial Fragments
Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza
Abstract:
There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.
Keywords: Face recognition, Labeled Faces in the Wild (LFW) database, Random Local Descriptor (RLD), random features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1013457 Video-Based System for Support of Robot-Enhanced Gait Rehabilitation of Stroke Patients
Authors: Matjaž Divjak, Simon Zelič, Aleš Holobar
Abstract:
We present a dedicated video-based monitoring system for quantification of patient’s attention to visual feedback during robot assisted gait rehabilitation. Two different approaches for eye gaze and head pose tracking are tested and compared. Several metrics for assessment of patient’s attention are also presented. Experimental results with healthy volunteers demonstrate that unobtrusive video-based gaze tracking during the robot-assisted gait rehabilitation is possible and is sufficiently robust for quantification of patient’s attention and assessment of compliance with the rehabilitation therapy.
Keywords: Video-based attention monitoring, gaze estimation, stroke rehabilitation, user compliance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1783456 Estimating Regression Parameters in Linear Regression Model with a Censored Response Variable
Authors: Jesus Orbe, Vicente Nunez-Anton
Abstract:
In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. In this context, most of the studies in the literature can be located in two possible general classes of regression models: models that study the effect the covariates have on the hazard function; and models that study the effect the covariates have on the censored response variable. Proposals in this paper are in the second class of models and, more specifically, on least squares based model approach. Thus, using the bootstrap estimate of the bias, we try to improve the estimation of the regression parameters by reducing their bias, for small sample sizes. Simulation results presented in the paper show that, for reasonable sample sizes and censoring levels, the bias is always smaller for the new proposals.
Keywords: Censored response variable, regression, bias.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1476455 Explicit Delay and Power Estimation Method for CMOS Inverter Driving on-Chip RLC Interconnect Load
Authors: Susmita Sahoo, Madhumanti Datta, Rajib Kar
Abstract:
The resistive-inductive-capacitive behavior of long interconnects which are driven by CMOS gates are presented in this paper. The analysis is based on the ¤Ç-model of a RLC load and is developed for submicron devices. Accurate and analytical expressions for the output load voltage, the propagation delay and the short circuit power dissipation have been proposed after solving a system of differential equations which accurately describe the behavior of the circuit. The effect of coupling capacitance between input and output and the short circuit current on these performance parameters are also incorporated in the proposed model. The estimated proposed delay and short circuit power dissipation are in very good agreement with the SPICE simulation with average relative error less than 6%.Keywords: Delay, Inverter, Short Circuit Power, ¤Ç-Model, RLCInterconnect, VLSI
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1692454 Predicting Dispersion Coefficient in Free-Flowing Zones of Rivers by Genetic Programming
Authors: Rajeev Ranjan Sahay
Abstract:
Transient storage zones along the flow paths of rivers have great influence on the dispersion of pollutants that are either accidentally or otherwise led into them. The speed with which these pollution clouds get transported and dispersed downstream is, to a large extent, explained by the longitudinal dispersion coefficients in the free-flowing zones of rivers (Kf). In the present work, a new empirical expression for Kf has been derived employing genetic programming (GP) on published dispersion data. The proposed expression uses few hydraulic and geometric characteristics of a river that are readily available to field engineers. Based on various performance indices, the proposed expression is found superior to other existing expression for Kf.
Keywords: Dispersion, parameter estimation, rivers, transient pollutant.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1721