Search results for: mode prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4180

Search results for: mode prediction

4150 Detectability of Malfunction in Turboprop Engine

Authors: Tomas Vampola, Michael Valášek

Abstract:

On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

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4149 A Prediction Model of Adopting IPTV

Authors: Jeonghwan Jeon

Abstract:

With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

Procedia PDF Downloads 412
4148 Enhanced Extra Trees Classifier for Epileptic Seizure Prediction

Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

Abstract:

For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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4147 A Study of Traditional Mode in the Framework of Sustainable Urban Transportation

Authors: Juanita, B. Kombaitan, Iwan Pratoyo Kusumantoro

Abstract:

The traditional mode is a non-motorized vehicle powered by human or animal power. The objective of the study was to define the strategy of using traditional modes by the framework of sustainable urban transport in support of urban tourism activities. The study of the traditional mode does not include a modified mode using the engine power as motor tricycles are often called ‘bentor ‘in Indonesia. The use of non-motorized traditional mode in Indonesia has begun to shift, and its use began to be eliminated by the change of propulsion using the machine. In an effort to push back the use of traditional mode one of them with tourism activities. Strategies for the use of traditional modes within the framework of sustainable urban transport are seen from three dimensions: social, economic and environmental. The social dimension related to accessibility and livability, an economic dimension related to traditional modes can promote products and tourist attractions, while the environmental dimension related to the needs of the users/groups with respect to safety, comfort. The traditional mode is rarely noticed by the policy makers, and public opinion in its use needs attention. The involvement of policy-making between stakeholders and the community is needed in the development of sustainable traditional mode strategies in support of urban tourism activities.

Keywords: traditional mode, sustainable, urban, transportation

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4146 Experimental and Theoratical Methods to Increase Core Damping for Sandwitch Cantilever Beam

Authors: Iyd Eqqab Maree, Moouyad Ibrahim Abbood

Abstract:

The purpose behind this study is to predict damping effect for steel cantilever beam by using two methods of passive viscoelastic constrained layer damping. First method is Matlab Program, this method depend on the Ross, Kerwin and Unger (RKU) model for passive viscoelastic damping. Second method is experimental lab (frequency domain method), in this method used the half-power bandwidth method and can be used to determine the system loss factors for damped steel cantilever beam. The RKU method has been applied to a cantilever beam because beam is a major part of a structure and this prediction may further leads to utilize for different kinds of structural application according to design requirements in many industries. In this method of damping a simple cantilever beam is treated by making sandwich structure to make the beam damp, and this is usually done by using viscoelastic material as a core to ensure the damping effect. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. There is a very good agreement of the experimental results with the theoretical findings. The main ideas of this thesis are to find the transition region for damped steel cantilever beam (4mm and 8mm thickness) from experimental lab and theoretical prediction (Matlab R2011a). Experimentally and theoretically proved that the transition region for two specimens occurs at modal frequency between mode 1 and mode 2, which give the best damping, maximum loss factor and maximum damping ratio, thus this type of viscoelastic material core (3M468) is very appropriate to use in automotive industry and in any mechanical application has modal frequency eventuate between mode 1 and mode 2.

Keywords: 3M-468 material core, loss factor and frequency, domain method, bioinformatics, biomedicine, MATLAB

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4145 Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Temporal Convolutional Network for Remaining Useful Life Prediction of Lithium Ion Batteries

Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

Abstract:

Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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4144 Impact of Instructional Mode and Medium of Instruction on the Learning Outcomes of Secondary Level School Children

Authors: Dipti Parida, Atasi Mohanty

Abstract:

The focus of this research is to examine the interaction effect of flipped teaching and traditional teaching mode across two different medium (English and Odia) of instructional groups. Both Science and History subjects were taken to be taught in the Class- VIII in two different instructional mode/s. In total, 180 students of Class-VIII of both Odia and English medium schools were taken as the samples of this study; 90 participants (each group) were from both English and Odia medium schools ; 45 participants of each of these two groups were again assigned either to flip or traditional teaching method. We have two independent variables and each independent variable with two levels. Medium and mode of instruction are the two independent variables. Medium of instruction has two levels of Odia medium and English medium groups. The mode of instruction has also two levels of flip and traditional teaching method. Here we get 4 different groups, such as Odia medium students with traditional mode of teaching (O.M.T), Odia medium students with flipped mode of teaching (O.M.F), English medium students with traditional mode of teaching (E.M.T) and English medium students with flipped mode of teaching (E.M.F). Before the instructional administration, these four groups were given a test on the concerned topic to be taught. Based on this result, a one-way ANOVA was computed and the obtained result showed that these four groups don’t differ significantly from each other at the beginning. Then they were taught the concerned topic either in traditional or flip mode of teaching method. After that a 2×2×2 repeated measures ANOVA was done to analyze the group differences as well as the learning outcome before and after the teaching. The result table also shows that in post-test the learning outcome is highest in case of English medium students with flip mode of instruction. From the statistical analysis it is clear that the flipped mode of teaching is as effective for Odia medium students as it is for English medium students.

Keywords: medium of instruction, mode of instruction, test mode, vernacular medium

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4143 An Improved Prediction Model of Ozone Concentration Time Series Based on Chaotic Approach

Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

Abstract:

This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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4142 Interaction of the Circumferential Lamb Wave with Delamination in the Middle of Pipe Wall

Authors: Li Ziming, He Cunfu, Liu Zenghua

Abstract:

With aim for delamination type defects detection in manufacturing process of seamless pipe,this paper studies the interaction of the circumferential lamb wave with delamination in aluminum pipe.The delamination is located in the middle of pipe wall.A numerical study is carried out,the circumferential lamb wave used here is CL0 mode,which is generated with a finite element method code.Wave structures from the simulation are compared with theoretical results to verify the model’s accuracy.Delamination along the circumferential direction is established by demerging nodes of the same coordinates.When CL0 mode is incident at the entrance and exit of a delamination,it generates new mode-CL1,undergoes multiple reverberation and mode conversions between the two ends of the delamination. Signals of different receptions are obtained to provide insight in using CL0 mode for locating the delamination.

Keywords: circumferential lamb wave, delamination, FEM, seamless pipe

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4141 Stock Movement Prediction Using Price Factor and Deep Learning

Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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4140 Cellular Traffic Prediction through Multi-Layer Hybrid Network

Authors: Supriya H. S., Chandrakala B. M.

Abstract:

Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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4139 Trajectory Tracking of a 2-Link Mobile Manipulator Using Sliding Mode Control Method

Authors: Abolfazl Mohammadijoo

Abstract:

In this paper, we are investigating the sliding mode control approach for trajectory tracking of a two-link-manipulator with a wheeled mobile robot in its base. The main challenge of this work is the dynamic interaction between mobile base and manipulator, which makes trajectory tracking more difficult than n-link manipulators with a fixed base. Another challenging part of this work is to avoid from chattering phenomenon of sliding mode control that makes lots of damages for actuators in real industrial cases. The results show the effectiveness of the sliding mode control approach for the desired trajectory.

Keywords: mobile manipulator, sliding mode control, dynamic interaction, mobile robotics

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4138 Sliding Mode Controller for Active Suspension System on a Passenger Car Model

Authors: Nouby M. Ghazaly, Ahmed O. Moaaz, Mostafa Makrahy

Abstract:

The main purpose of a car suspension system is to reduce the vibrations resulting from road roughness. The main objective of this research paper is to decrease vibration and improve passenger comfort through controlling car suspension system using sliding mode control techniques. The mathematical model for passive and active suspensions systems for quarter car model which subject to excitation from different road profiles is obtained. The active suspension system is synthesized based on sliding mode control for a quarter car model. The performance of the sliding mode control is determined through computer simulations using MATLAB and SIMULINK toolbox. The simulated results plotted in time domain, and root mean square values. It is found that active suspension system using sliding mode control improves the ride comfort and decrease vibration.

Keywords: quarter car model, active suspension system, sliding mode control, road profile

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4137 Sliding Mode Control of an Internet Teleoperated PUMA 600 Robot

Authors: Abdallah Ghoul, Bachir Ouamri, Ismail Khalil Bousserhane

Abstract:

In this paper, we have developed a sliding mode controller for PUMA 600 manipulator robot, to control the remote robot a teleoperation system was developed. This system includes two sites, local and remote. The sliding mode controller is installed at the remote site. The client asks for a position through an interface and receives the real positions after running of the task by the remote robot. Both sites are interconnected via the Internet. In order to verify the effectiveness of the sliding mode controller, that is compared with a classic PID controller. The developed approach is tested on a virtual robot. The results confirmed the high performance of this approach.

Keywords: internet, manipulator robot, PID controller, remote control, sliding mode, teleoperation

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4136 Sliding Mode Control of a Bus Suspension System

Authors: Mujde Turkkan, Nurkan Yagiz

Abstract:

The vibrations, caused by the irregularities of the road surface, are to be suppressed via suspension systems. In this paper, sliding mode control for a half bus model with air suspension system is presented. The bus is modelled as five degrees of freedom (DoF) system. The mathematical model of the half bus is developed using Lagrange Equations. For time domain analysis, the bus model is assumed to travel at certain speed over the bump road. The numerical results of the analysis indicate that the sliding mode controllers can be effectively used to suppress the vibrations and to improve the ride comfort of the busses.

Keywords: active suspension system, air suspension, bus model, sliding mode control

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4135 Mathematical Modeling of the Fouling Phenomenon in Ultrafiltration of Latex Effluent

Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

Abstract:

An efficient and well-planned ultrafiltration process is becoming a necessity for monetary returns in the industrial settings. The aim of the present study was to develop a mathematical model for an accurate prediction of ultrafiltration membrane fouling of latex effluent applied to homogeneous and heterogeneous membranes with uniform and non-uniform pore sizes, respectively. The models were also developed for an accurate prediction of power consumption that can handle the large-scale purposes. The model incorporated the fouling attachments as well as chemical and physical factors in membrane fouling for accurate prediction and scale-up application. Both Polycarbonate and Polysulfone flat membranes, with pore sizes of 0.05 µm and a molecular weight cut-off of 60,000, respectively, were used under a constant feed flow rate and a cross-flow mode in ultrafiltration of the simulated paint effluent. Furthermore, hydrophilic ultrafilic and hydrophobic PVDF membranes with MWCO of 100,000 were used to test the reliability of the models. Monodisperse particles of 50 nm and 100 nm in diameter, and a latex effluent with a wide range of particle size distributions were utilized to validate the models. The aggregation and the sphericity of the particles indicated a significant effect on membrane fouling.

Keywords: membrane fouling, mathematical modeling, power consumption, attachments, ultrafiltration

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4134 Large Core Silica Few-Mode Optical Fibers with Reduced Differential Mode Delay and Enhanced Mode Effective Area over 'C'-Band

Authors: Anton V. Bourdine, Vladimir A. Burdin, Oleg R. Delmukhametov

Abstract:

This work presents a fast and simple method for the design of large core silica optical fibers with differential mode delay (DMD) management. Some results are reported concerned with refractive index profile optimization for 42 µm core 16-LP-mode optical fiber for next-generation optical networks. Here special refractive index profile form provides total DMD reducing over all mode staff under desired enhanced mode effective area. Method for the simulation of 'real manufactured' few-mode optical fiber (FMF) core geometry differing from the desired optimized structure by core non-symmetrical ellipticity and refractive index profile deviation including local fluctuations is proposed. Results of the following analysis of optimized FMF with inserted geometry distortions performed by earlier on developed modification of rigorous mixed finite-element method showed strong DMD degradation that requires additional higher-order mode management. In addition, this work also presents a method for design mode division multiplexer channel precision spatial positioning scheme at FMF core end that provides one of the potentiality solutions of described DMD degradation problem concerned with 'distorted' core geometry due to features of optical fiber manufacturing techniques.

Keywords: differential mode delay, few-mode optical fibers, nonlinear Shannon limit, optical fiber non-circularity, ‘real manufactured’ optical fiber core geometry simulation, refractive index profile optimization

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4133 Theory of Gyrotron Amplifier in a Vane-Loaded Waveguide with Inner Dielectric Material

Authors: Reyhaneh Hashemi, Shahrooz Saviz

Abstract:

In his study, we have survey the theory of gyrotron amplifier in a vane-loaded waveguide with inner dielectric material. Dispersion relation for electromagnetic waves emitted by a cylindrical waveguide that provided with wedge-shaped metal vanes projecting radially inward from the wall of the guide and exited in the transverse-electric mode was analysed. From numerical analysis of this dispersion relation, it is shown that the stability behavior of the fast-wave mode is dependent of the dielectric constant. With a small axial momentum spreed, a super bandwidth is shown to be attainable by a mixed mode operation. Also, with the utilization from the numeric analysis of relation dispersion. We show that in the –speed mode, the constant is independent de-electric. With the ratio of dispersion of smell, high –bandwith was obtained for the combined mode. And at the end, we were comparing the result of our work (vane-loaded) by the waveguide with a smooth wall.

Keywords: gyrotron amplifier, waveguide, vane-loaded waveguide, dielectric material, dispersion relation, cylindrical waveguide, fast-wave mode, mixed mode operation

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4132 A Combined High Gain-Higher Order Sliding Mode Controller for a Class of Uncertain Nonlinear Systems

Authors: Abderraouf Gaaloul, Faouzi Msahli

Abstract:

The use of standard sliding mode controller, usually, leads to the appearing of an undesirable chattering phenomenon affecting the control signal. Such problem can be overcome using a higher-order sliding mode controller (HOSMC) which preserves the main properties of the standard sliding mode and deliberately increases the control smoothness. In this paper, we propose a new HOSMC for a class of uncertain multi-input multi-output nonlinear systems. Based on high gain and integral sliding mode paradigms, the established control scheme removes theoretically the chattering phenomenon and provides the stability of the control system. Numerical simulations are developed to show the effectiveness of the proposed controller when applied to solve a control problem of two water levels into a quadruple-tank process.

Keywords: nonlinear systems, sliding mode control, high gain, higher order

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4131 Modelling Mode Choice Behaviour Using Cloud Theory

Authors: Leah Wright, Trevor Townsend

Abstract:

Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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4130 A Novel Fuzzy Second-Order Sliding Mode Control of a Doubly Fed Induction Generator for Wind Energy Conversion

Authors: Elhadj Bounadja, Mohand Oulhadj Mahmoudi, Abdelkader Djahbar, Zinelaabidine Boudjema

Abstract:

In this paper we present a novel fuzzy second-order sliding mode control (FSOSMC) for wind energy conversion system based on a doubly-fed induction generator (DFIG). The proposed control strategy combines a fuzzy logic and a second-order sliding mode for the DFIG control. This strategy presents attractive features such as chattering-free, compared to the conventional first and second order sliding mode techniques. The use of this method provides very satisfactory performance for the DFIG control. The overall strategy has been validated on a 1.5-MW wind turbine driven a DFIG using the Matlab/Simulink.

Keywords: doubly fed induction generator, fuzzy second-order sliding mode controller, wind energy

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4129 Interferometric Demodulation Scheme Using a Mode-Locker Fiber Laser

Authors: Liang Zhang, Yuanfu Lu, Yuming Dong, Guohua Jiao, Wei Chen, Jiancheng Lv

Abstract:

We demonstrated an interferometric demodulation scheme using a mode-locked fiber laser. The mode-locked fiber laser is launched into a two-beam interferometer. When the ratio between the fiber path imbalance of interferometer and the laser cavity length is close to an integer, an interferometric fringe emerges as a result of vernier effect, and then the phase shift of the interferometer can be demodulated. The mode-locked fiber laser provides a large bandwidth and reduces the cost for wavelength division multiplexion (WDM). The proposed interferometric demodulation scheme can be further applied in multi-point sensing system such as fiber optics hydrophone array, seismic wave detection network with high sensitivity and low cost.

Keywords: fiber sensing, interferometric demodulation, mode-locked fiber laser, vernier effect

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4128 Modeling and Simulations of Surface Plasmon Waveguide Structures

Authors: Moussa Hamdan, Abdulati Abdullah

Abstract:

This paper presents an investigation of the fabrication of the optical devices in terms of their characteristics based on the use of the electromagnetic waves. Planar waveguides are used to examine the field modes (bound modes) and the parameters required for this structure. The modifications are conducted on surface plasmons based waveguides. Simple symmetric dielectric slab structure is used and analyzed in terms of transverse electric mode (TE-Mode) and transverse magnetic mode (TM-Mode. The paper presents mathematical and numerical solutions for solving simple symmetric plasmons and provides simulations of surface plasmons for field confinement. Asymmetric TM-mode calculations for dielectric surface plasmons are also provided.

Keywords: surface plasmons, optical waveguides, semiconductor lasers, refractive index, slab dialectical

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4127 Traffic Prediction with Raw Data Utilization and Context Building

Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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4126 Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena

Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, seizure, phase correlation, fluctuation, deviation.

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4125 A Tunable Long-Cavity Passive Mode-Locked Fiber Laser Based on Nonlinear Amplifier Loop Mirror

Authors: Pinghe Wang

Abstract:

In this paper, we demonstrate a tunable long-cavity passive mode-locked fiber laser. The mode locker is a nonlinear amplifying loop mirror (NALM). The cavity frequency of the laser is 465 kHz because that 404m SMF is inserted in the cavity. A tunable bandpass filter with ~1nm 3dB bandwidth is inserted into the cavity to realize tunable mode locking. The passive mode-locked laser at a fixed wavelength is investigated in detail. The experimental results indicate that the laser operates in dissipative soliton resonance (DSR) region. When the pump power is 400mW, the laser generates the rectangular pulses with 10.58 ns pulse duration, 70.28nJ single-pulse energy. When the pump power is 400mW, the laser keeps stable mode locking status in the range from 1523.4nm to 1575nm. During the whole tuning range, the SNR, the pulse duration, the output power and single pulse energy have a little fluctuation because that the gain of the EDF changes with the wavelength.

Keywords: fiber laser, dissipative soliton resonance, mode locking, tunable

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4124 A Multilevel Approach for Stroke Prediction Combining Risk Factors and Retinal Images

Authors: Jeena R. S., Sukesh Kumar A.

Abstract:

Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

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4123 A Study of Mode Choice Model Improvement Considering Age Grouping

Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

Abstract:

The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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4122 Fuzzy-Sliding Controller Design for Induction Motor Control

Authors: M. Bouferhane, A. Boukhebza, L. Hatab

Abstract:

In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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4121 Analysis of Residents’ Travel Characteristics and Policy Improving Strategies

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

Abstract:

To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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