Search results for: panel data analysis.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13619

Search results for: panel data analysis.

11159 Gutenberg-Richter Recurrence Law to Seismicity Analysis of Southern Segment of the Sagaing Fault and Its Associate Components

Authors: Yin Myo Min Htwe, Shen WenBin

Abstract:

The purpose of the present study is the calculation of Gutenber-Richter parameters (a, b) and analyze the mean annual rate of exceedance of earthquake magnitude (Om ) of southern segment of the Sagaing fault and its associate components. The study area is situated about 200 km radius centered at Yangon. Earthquake data file is using from 1975 to 2006 August 31. The bounded Gutenberg- Richter recurrence law for 0 M is 4.0 and max M is 7.5.

Keywords: Gutenberg-Richter recurrence law, meanannual rate of exceedance, Sagaing fault.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3503
11158 Aircraft Selection Using Preference Optimization Programming (POP)

Authors: C. Ardil

Abstract:

A multiple-criteria decision support system is proposed for the best aircraft selection decision. Various strategic, economic, environmental, and risk-related factors can directly or indirectly influence this choice, and they should be taken into account in the decision-making process. The paper suggests a multiple-criteria analysis to aid in the airline management's decision-making process when choosing an appropriate aircraft. In terms of the suggested approach, an integrated entropic preference optimization programming (POP) for fleet modeling risk analysis is applied. The findings of the study of multiple criteria analysis indicate that the A321(neo) aircraft type is the best alternative in this particular optimization instance. The proposed methodology can be applied to other complex engineering problems involving multiple criteria analysis.

Keywords: Aircraft selection, decision making, multiple criteria decision making, preference optimization programming, POP, entropic weight method, TOPSIS, WSM, WPM

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 625
11157 Building an Integrated Relational Database from Swiss Nutrition National Survey and Swiss Health Datasets for Data Mining Purposes

Authors: Ilona Mewes, Helena Jenzer, Farshideh Einsele

Abstract:

Objective: The objective of the study was to integrate two big databases from Swiss nutrition national survey (menuCH) and Swiss health national survey 2012 for data mining purposes. Each database has a demographic base data. An integrated Swiss database is built to later discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption. Design: Swiss nutrition national survey (menuCH) with approx. 2000 respondents from two different surveys, one by Phone and the other by questionnaire along with Swiss health national survey 2012 with 21500 respondents were pre-processed, cleaned and finally integrated to a unique relational database. Results: The result of this study is an integrated relational database from the Swiss nutritional and health databases.

Keywords: Health informatics, data mining, nutritional and health databases, nutritional and chronical databases.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1725
11156 A Cost-Effective Design and Analysis of Full Bridge LLC Resonant Converter

Authors: Kaibalya Prasad Panda, Sreyasee Rout

Abstract:

LLC (Inductor-inductor-capacitor) resonant converter has lots of advantages over other type of resonant converters which include high efficiency, more reliable and have high power density. This paper presents the design and analysis of a full bridge LLC resonant converter. In addition to the operational principle, the ZVS and ZCS conditions are also explained with the DC characteristics. Simulation of the LLC resonant converter is performed in MATLAB/ Simulink and the practical prototype setup is analyzed in Proteus software. The result is verified through analysis and design of a low cost, 200 watt prototype converter.

Keywords: LLC, Proteus, Resonant converter ZCS, ZVS.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3105
11155 Analysis and Flight Test for Small Inflatable Wing Design

Authors: Zhang Jun-Tao, Hou Zhong-xi, Guo Zheng, Chen Li-li

Abstract:

This article discusses stress analysis and the shape characteristics of the inflatable wing, and then introduces the design method of inflatable wing, in order to accurately approximate a standard airfoil. It specifically analyses the aerodynamic characteristics of the inflatable wing with the method of CFD, along with comparing to standard airfoil, afterwards we carries out the manufacture of inflatable wing and the flight test.

Keywords: Inflatable wing, Stress analysis, Aerodynamic characteristics, Flight test

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2696
11154 Seamless Handover in Urban 5G-UAV Systems Using Entropy Weighted Method

Authors: Anirudh Sunil Warrier, Saba Al-Rubaye, Dimitrios Panagiotakopoulos, Gokhan Inalhan, Antonios Tsourdos

Abstract:

The demand for increased data transfer rate and network traffic capacity has given rise to the concept of heterogeneous networks. Heterogeneous networks are wireless networks, consisting of devices using different underlying radio access technologies (RAT). For Unmanned Aerial Vehicles (UAVs) this enhanced data rate and network capacity are even more critical especially in their applications of medicine, delivery missions and military. In an urban heterogeneous network environment, the UAVs must be able switch seamlessly from one base station (BS) to another for maintaining a reliable link. Therefore, seamless handover in such urban environments has become a major challenge. In this paper, a scheme to achieve seamless handover is developed, an algorithm based on Received Signal Strength (RSS) criterion for network selection is used and Entropy Weighted Method (EWM) is implemented for decision making. Seamless handover using EWM decision-making is demonstrated successfully for a UAV moving across fifth generation (5G) and long-term evolution (LTE) networks via a simulation level analysis. Thus, a solution for UAV-5G communication, specifically the mobility challenge in heterogeneous networks is solved and this work could act as step forward in making UAV-5G architecture integration a possibility.

Keywords: Air to ground, A2G, fifth generation, 5G, handover, mobility, unmanned aerial vehicle, UAV, urban environments.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 433
11153 Seismic Behavior Evaluation of Semi-Rigid Steel Frames with Knee Bracing by Modal Pushover Analysis (MPA)

Authors: Farzan Namvari, Panam Zarfam

Abstract:

Nowadays use of a new structural bracing system called 'Knee Bracing System' have taken the specialists attention too much. On the other hand nonlinear static analysis procedures in estimate structures performance in earthquake time have taken attention too much. One of these procedure is modal pushover analysis (MPA) procedure. The accuracy of MPA procedure for simple steel moment resisting frame has been verified and considered in Chintanapakdee and Chopra-s article in 2003. Since the accuracy of MPA procedure has not verified for semi-rigid steel frames with knee bracing, we are going to get through with this matter in this study. For this purpose, the selected structures are four frames with different heights, 5 to 20 stories, will be designed according to AISC criteria. Then MPA procedure is used for the same frames with different rigidity percentiles of connections. The results of seismic responses are compared with dynamic nonlinear response history analysis as exact procedure and accuracy of MPA procedure is evaluated. It seems that MPA procedure accuracy will come down by reduction of the rigidity percentiles of semi-rigid connections.

Keywords: Knee Bracing, Modal Pushover Analysis, SeismicBehavior, Semi-Rigid Connections.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2135
11152 Application of Neural Networks in Financial Data Mining

Authors: Defu Zhang, Qingshan Jiang, Xin Li

Abstract:

This paper deals with the application of a well-known neural network technique, multilayer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-making for stock investors. The simulation result of seven years to Shanghai Composite Index shows that the return achieved by this mining system is about three times as large as that achieved by the buy and hold strategy, so it is advantageous to apply neural networks to forecast financial time series, the different investors could benefit from it.

Keywords: Data mining, neural network, stock forecasting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3590
11151 African Traditional Method of Social Control Mechanism: A Sociological Review of Native Charms in Farm Security in Ayetoro Community, Ogun State, Nigeria

Authors: Adebisi A. Sunday, Babajide Adeokin

Abstract:

The persistent rise in farm theft in rural region of Nigeria is attributed to the lack of adequate and effective policing in the regions; thus, this brought about the inevitable introduction of native charms on farmlands as a means of fortification of harvests against theft in Ayetoro community. The use of charm by farmers as security on farmlands is a traditional crime control mechanism that is largely based on unwritten laws which greatly influenced the lives of people, and their attitudes toward the society. This research presents a qualitative sociological study on how native charms are deployed by farmers for protection against theft. The study investigated the various types of charms that are employed as security measures among farmers in Ayetoro community and the rationale behind the use of these mechanisms as farm security. The study utilized qualitative method to gather data in the research process. Under the qualitative method, in-depth interview method was adopted to generate a robust and detailed data from the respondents. Also the data generated were analysed qualitatively using thematic content analysis and simple description which was preceded by transcription of data from the recorder. It was revealed that amidst numerous charms known, two major charms are used on farmlands as a measure of social control in Ayetoro community, Ogun state South West Nigeria. Furthermore, the result of this study showed that, the desire for safekeeping of harvest from pilferers and the heavy punishments dispense on offenders by native charms are the reasons why farmers deploy charms on their farms. In addition, findings revealed that the adoption of these charms for protection has improved yields among farmers in the community because the safety of harvest has been made possible by virtue of the presence of various charms in the farm lands. Therefore, based on the findings of this study, it is recommended that such measures should be recognized in mainstream social control mechanisms in the fight against crime in Nigeria and the rest of the world. Lastly, native charms could be installed in all social and cooperate organisation and position of authority to prevent theft of valuables and things hold with utmost importance.

Keywords: Farm theft, native charms, mechanism, Ayetoro, pilferer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1726
11150 Adaptive Kalman Filter for Noise Estimation and Identification with Bayesian Approach

Authors: Farhad Asadi, S. Hossein Sadati

Abstract:

Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, adaptive Kalman filter with Bayesian approach for identification of variances in measurement parameter noise is developed. Next, it is applied for estimation of the dynamical state and measurement data in discrete linear dynamical system. This algorithm at each step time estimates noise variance in measurement noise and state of system with Kalman filter. Next, approximation is designed at each step separately and consequently sufficient statistics of the state and noise variances are computed with a fixed-point iteration of an adaptive Kalman filter. Different simulations are applied for showing the influence of noise variance in measurement data on algorithm. Firstly, the effect of noise variance and its distribution on detection and identification performance is simulated in Kalman filter without Bayesian formulation. Then, simulation is applied to adaptive Kalman filter with the ability of noise variance tracking in measurement data. In these simulations, the influence of noise distribution of measurement data in each step is estimated, and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained. 

Keywords: adaptive filtering, Bayesian approach Kalman filtering approach, variance tracking

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 619
11149 Effect of Valve Pressure Drop in Exergy Analysis of C2+ Recovery Plants Refrigeration Cycles

Authors: B. Tirandazi, M. Mehrpooya, A. Vatani

Abstract:

This paper provides an exergy analysis of the multistage refrigeration cycle used for C2+ recovery plant. The behavior of an industrial refrigeration cycle with refrigerant propane has been investigated by the exergy method. A computational model based on the exergy analysis is presented for the investigation of the effects of the valves on the exergy losses, the second law of efficiency, and the coefficient of performance (COP) of a vapor compression refrigeration cycle. The equations of exergy destruction and exergetic efficiency for the main cycle components such as evaporators, condensers, compressors, and expansion valves are developed. The relations for the total exergy destruction in the cycle and the cycle exergetic efficiency are obtained. An ethane recovery unit with its refrigeration cycle has been simulated to prepare the exergy analysis. Using a typical actual work input value; the exergetic efficiency of the refrigeration cycle is determined to be 39.90% indicating a great potential for improvements. The simulation results reveal that the exergetic efficiencies of the heat exchanger and expansion sections get the lowest rank among the other compartments of refrigeration cycle. Refrigeration calculations have been carried out through the analysis of T–S and P–H diagrams where coefficient of performance (COP) was obtained as 1.85. The novelty of this article includes the effect and sensitivity analysis of molar flow, pressure drops and temperature on the exergy efficiency and coefficient of performance of the cycle.

Keywords: exergy; Valve; CRP; refrigeration cycle; propane refrigerant; C2+ Recovery; Ethane Recovery;.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1208
11148 Comparison of Newton Raphson and Gauss Seidel Methods for Power Flow Analysis

Authors: H. Abaali, T. Talbi, R.Skouri

Abstract:

This paper presents a comparative study of the Gauss Seidel and Newton-Raphson polar coordinates methods for power flow analysis. The effectiveness of these methods are evaluated and tested through a different IEEE bus test system on the basis of number of iteration, computational time, tolerance value and convergence.

Keywords: Convergence time, Gauss-Seidel Method, Newton-Raphson Method, number of iteration, power flow analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2545
11147 Analysis of Acoustic Emission Signal for the Detection of Defective Manufactures in Press Process

Authors: Dong Hun Kim, Won Kyu Lee, Sok Won Kim

Abstract:

Small cracks or chips of a product appear very frequently in the course of continuous production of an automatic press process system. These phenomena become the cause of not only defective product but also damage of a press mold. In order to solve this problem AE system was introduced. AE system was expected to be very effective to real time detection of the defective product and to prevention of the damage of the press molds. In this study, for pick and analysis of AE signals generated from the press process, AE sensors/pre-amplifier/analysis and processing board were used as frequently found in the other similar cases. For analysis and processing the AE signals picked in real time from the good or bad products, specialized software called cdm8 was used. As a result of this work it was conformed that intensity and shape of the various AE signals differ depending on the weight and thickness of metal sheet and process type.

Keywords: press, acoustic emission, signal processing

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1631
11146 Thermographic Tests of Curved GFRP Structures with Delaminations: Numerical Modelling vs. Experimental Validation

Authors: P. D. Pastuszak

Abstract:

The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: Active thermography, finite element analysis, composite, curved structures, defects.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1711
11145 Neuron Dynamics of Single-Compartment Traub Model for Hardware Implementations

Authors: J. C. Moctezuma, V. Breña-Medina, Jose Luis Nunez-Yanez, Joseph P. McGeehan

Abstract:

In this work we make a bifurcation analysis for a single compartment representation of Traub model, one of the most important conductance-based models. The analysis focus in two principal parameters: current and leakage conductance. Study of stable and unstable solutions are explored; also Hop-bifurcation and frequency interpretation when current varies is examined. This study allows having control of neuron dynamics and neuron response when these parameters change. Analysis like this is particularly important for several applications such as: tuning parameters in learning process, neuron excitability tests, measure bursting properties of the neuron, etc. Finally, a hardware implementation results were developed to corroborate these results.

Keywords: Traub model, Pinsky-Rinzel model, Hopf bifurcation, single-compartment models, Bifurcation analysis, neuron modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1205
11144 A Generic Middleware to Instantly Sync Intensive Writes of Heterogeneous Massive Data via Internet

Authors: Haitao Yang, Zhenjiang Ruan, Fei Xu, Lanting Xia

Abstract:

Industry data centers often need to sync data changes reliably and instantly from a large-scale of heterogeneous autonomous relational databases accessed via the not-so-reliable Internet, for which a practical generic sync middleware of low maintenance and operation costs is most wanted. To this demand, this paper presented a generic sync middleware system (GSMS), which has been developed, applied and optimized since 2006, holding the principles or advantages that it must be SyncML-compliant and transparent to data application layer logic without referring to implementation details of databases synced, does not rely on host computer operating systems deployed, and its construction is light weighted and hence of low cost. Regarding these hard commitments of developing GSMS, in this paper we stressed the significant optimization breakthrough of GSMS sync delay being well below a fraction of millisecond per record sync. A series of ultimate tests with GSMS sync performance were conducted for a persuasive example, in which the source relational database underwent a broad range of write loads (from one thousand to one million intensive writes within a few minutes). All these tests showed that the performance of GSMS is competent and smooth even under ultimate write loads.

Keywords: Heterogeneous massive data, instantly sync intensive writes, Internet generic middleware design, optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 455
11143 Application of Artificial Intelligence Techniques for Dissolved Gas Analysis of Transformers-A Review

Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

Abstract:

The gases generated in oil filled transformers can be used for qualitative determination of incipient faults. The Dissolved Gas Analysis has been widely used by utilities throughout the world as the primarily diagnostic tool for transformer maintenance. In this paper, various Artificial Intelligence Techniques that have been used by the researchers in the past have been reviewed, some conclusions have been drawn and a sequential hybrid system has been proposed. The synergy of ANN and FIS can be a good solution for reliable results for predicting faults because one should not rely on a single technology when dealing with real–life applications.

Keywords: Dissolved Gas Analysis, Artificial IntelligenceTechniques, Incipient Faults, Transformer Fault Diagnosis, andHybrid Systems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4066
11142 Two Degree of Freedom Spherical Mechanism Design for Exact Sun Tracking

Authors: Osman Acar

Abstract:

Sun tracking systems are the systems following the sun ray by a right angle or by predetermined certain angle. In this study, we used theoretical trajectory of sun for latitude of central Anatolia in Turkey. A two degree of freedom spherical mechanism was designed to have a large workspace able to follow the sun's theoretical motion by the right angle during the whole year. An inverse kinematic analysis was generated to find the positions of mechanism links for the predicted trajectory. Force and torque analysis were shown for the first day of the year.

Keywords: Sun tracking, theoretical sun trajectory, spherical mechanism, inverse kinematic analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1412
11141 Seamless Multicast Handover in Fmipv6-Based Networks

Authors: Moneeb Gohar, Seok Joo Koh, Tae-Won Um, Hyun-Woo Lee

Abstract:

This paper proposes a fast tree join scheme to provide seamless multicast handover in the mobile networks based on the Fast Mobile IPv6 (FMIPv6). In the existing FMIPv6-based multicast handover scheme, the bi-directional tunnelling or the remote subscription is employed with the packet forwarding from the previous access router (AR) to the new AR. In general, the remote subscription approach is preferred to the bi-directional tunnelling one, since in the remote subscription scheme we can exploit an optimized multicast path from a multicast source to many mobile receivers. However, in the remote subscription scheme, if the tree joining operation takes a long time, the amount of data packets to be forwarded and buffered for multicast handover will increase, and thus the corresponding buffer may overflow, which results in severe packet losses. In order to reduce these costs associated with packet forwarding and buffering, this paper proposes the fast join to multicast tree, in which the new AR will join the multicast tree as fast as possible, so that the new multicast data packets can also arrive at the new AR, by which the packet forwarding and buffering costs can be reduced. From numerical analysis, it is shown that the proposed scheme can give better performance than the existing FMIPv6-based multicast handover schemes in terms of the multicast packet delivery costs.

Keywords: Mobile Multicast, FMIPv6, Seamless Handover, Fast Tree Join.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1426
11140 SEM Image Classification Using CNN Architectures

Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 198
11139 Fuzzy Wavelet Packet based Feature Extraction Method for Multifunction Myoelectric Control

Authors: Rami N. Khushaba, Adel Al-Jumaily

Abstract:

The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1737
11138 User Requirements Analysis for the Development of Assistive Navigation Mobile Apps for Blind and Visually Impaired People

Authors: Paraskevi Theodorou, Apostolos Meliones

Abstract:

In the context of the development process of two assistive navigation mobile apps for blind and visually impaired people (BVI) an extensive qualitative analysis of the requirements of potential users has been conducted. The analysis was based on interviews with BVIs and aimed to elicit not only their needs with respect to autonomous navigation but also their preferences on specific features of the apps under development. The elicited requirements were structured into four main categories, namely, requirements concerning the capabilities, functionality and usability of the apps, as well as compatibility requirements with respect to other apps and services. The main categories were then further divided into nine sub-categories. This classification, along with its content, aims to become a useful tool for the researcher or the developer who is involved in the development of digital services for BVI.

Keywords: Accessibility, assistive mobile apps, blind and visually impaired people, user requirements analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 947
11137 Using Data Mining in Automotive Safety

Authors: Carine Cridelich, Pablo Juesas Cano, Emmanuel Ramasso, Noureddine Zerhouni, Bernd Weiler

Abstract:

Safety is one of the most important considerations when buying a new car. While active safety aims at avoiding accidents, passive safety systems such as airbags and seat belts protect the occupant in case of an accident. In addition to legal regulations, organizations like Euro NCAP provide consumers with an independent assessment of the safety performance of cars and drive the development of safety systems in automobile industry. Those ratings are mainly based on injury assessment reference values derived from physical parameters measured in dummies during a car crash test. The components and sub-systems of a safety system are designed to achieve the required restraint performance. Sled tests and other types of tests are then carried out by car makers and their suppliers to confirm the protection level of the safety system. A Knowledge Discovery in Databases (KDD) process is proposed in order to minimize the number of tests. The KDD process is based on the data emerging from sled tests according to Euro NCAP specifications. About 30 parameters of the passive safety systems from different data sources (crash data, dummy protocol) are first analysed together with experts opinions. A procedure is proposed to manage missing data and validated on real data sets. Finally, a procedure is developed to estimate a set of rough initial parameters of the passive system before testing aiming at reducing the number of tests.

Keywords: KDD process, passive safety systems, sled test, dummy injury assessment reference values, frontal impact

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2844
11136 Asset Management for Educational Buildings in Egypt

Authors: M. Abdelhamid, I. Beshara, M. Ghoneim

Abstract:

In Egypt, the concept of Asset Management (AM) is new; however, the need for applying it has become crucial because deteriorating or losing an asset is unaffordable in a developing country like Egypt. Therefore the current study focuses on educational buildings as one of the most important assets regarding planning, building, operating and maintenance expenditures. The main objective of this study is to develop a SAMF for educational buildings in Egypt. The General Authority for Educational Buildings (GAEB) was chosen as a case study of the current research as it represents the biggest governmental organization responsible for planning, operating and maintaining schools in Egypt. To achieve the research objective, structured interviews were conducted with senior managers of GAEB using a pre designed questionnaire to explore the current practice of AM. Gab analysis technique was applied against best practices compounded from a vast literature review to identify gaps between current practices and the desired one. The previous steps mainly revealed; limited knowledge about strategic asset management, no clear goals, no training, no real risk plan and lack of data, technical and financial resources. Based on the findings, a SAMF for GAEB was introduced and Framework implementation steps and assessment techniques were explained in detail.

Keywords: Strategic Asset Management, Educational Building, Framework, Gab Analysis, Developing Country.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2334
11135 A Specification-Based Approach for Retrieval of Reusable Business Component for Software Reuse

Authors: Meng Fanchao, Zhan Dechen, Xu Xiaofei

Abstract:

Software reuse can be considered as the most realistic and promising way to improve software engineering productivity and quality. Automated assistance for software reuse involves the representation, classification, retrieval and adaptation of components. The representation and retrieval of components are important to software reuse in Component-Based on Software Development (CBSD). However, current industrial component models mainly focus on the implement techniques and ignore the semantic information about component, so it is difficult to retrieve the components that satisfy user-s requirements. This paper presents a method of business component retrieval based on specification matching to solve the software reuse of enterprise information system. First, a business component model oriented reuse is proposed. In our model, the business data type is represented as sign data type based on XML, which can express the variable business data type that can describe the variety of business operations. Based on this model, we propose specification match relationships in two levels: business operation level and business component level. In business operation level, we use input business data types, output business data types and the taxonomy of business operations evaluate the similarity between business operations. In the business component level, we propose five specification matches between business components. To retrieval reusable business components, we propose the measure of similarity degrees to calculate the similarities between business components. Finally, a business component retrieval command like SQL is proposed to help user to retrieve approximate business components from component repository.

Keywords: Business component, business operation, business data type, specification matching.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1409
11134 Inter-Area Oscillation Monitoring in Maghrebian Power Grid Using Phasor Measurement Unit

Authors: M. Tsebia, H. Bentarzi

Abstract:

In the inter-connected power systems, a phenomenon called inter-area oscillation may be caused by several defects. In this paper, a study of the Maghreb countries inter-area power networks oscillation has been investigated. The inter-area oscillation monitoring can be enhanced by integrating Phasor Measurement Unit (PMU) technology installed in different places. The data provided by PMU and recorded by PDC will be used for the monitoring, analysis, and control purposes. The proposed approach has been validated by simulation using MATLAB/Simulink.

Keywords: Inter-area oscillation, Maghrebian power system, Simulink, PMU.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 978
11133 Face Recognition using Radial Basis Function Network based on LDA

Authors: Byung-Joo Oh

Abstract:

This paper describes a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers. The face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). LDA features of the face image are taken as the input of the Radial Basis Function Network (RBFN). The proposed approach has been tested on the ORL database. The experimental results show that the LDA+RBFN algorithm has achieved a recognition rate of 93.5%

Keywords: Face recognition, linear discriminant analysis, radial basis function network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2122
11132 Finding an Optimized Discriminate Function for Internet Application Recognition

Authors: E. Khorram, S.M. Mirzababaei

Abstract:

Everyday the usages of the Internet increase and simply a world of the data become accessible. Network providers do not want to let the provided services to be used in harmful or terrorist affairs, so they used a variety of methods to protect the special regions from the harmful data. One of the most important methods is supposed to be the firewall. Firewall stops the transfer of such packets through several ways, but in some cases they do not use firewall because of its blind packet stopping, high process power needed and expensive prices. Here we have proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. So an administrator can alarm to the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1408
11131 Human Resource Development Strategy in Automotive Industry (Eco-Car) for ASEAN Hub

Authors: Phichak Phutrakhul

Abstract:

The purposes of this research were to study concepts and strategies of human resource development in the automotive manufacturers and to articulate the proposals against the government about the human resource development for automotive industry. In the present study, qualitative study was an in-depth interview in which the qualitative data were collected from the executive or the executive of human resource division from five automotive companies - Toyota Motor (Thailand) Co., Ltd., Nissan Motor (Thailand) Co., Ltd., Mitsubishi Motors (Thailand) Co., Ltd., Honda Automobile (Thailand) Co., Ltd., and Suzuki Motor (Thailand) Co., Ltd. Qualitative data analysis was performed by using inter-coder agreement technique. The research findings were as follows: The external factors included the current conditions of the automotive industry, government’s policy related to the automotive industry, technology, labor market and human resource development systems of the country. The internal factors included management, productive management, organizational strategies, leadership, organizational culture and philosophy of human resource development. These factors were affected to the different concept of human resources development -the traditional human resource development and the strategies of human resource development. The organization focuses on human resources as intellectual capital and uses the strategies of human resource development in all development processes. The strategies of human resource development will enhance the ability of human resources in the organization and the country.

Keywords: Human Resource Development Strategy, Automotive industry, Eco-Cars, ASEAN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7720
11130 Marketing Segmentation of Students Willing to Study Abroad based on Cluster Analysis

Authors: Kamila Tislerova, Marta Zambochova

Abstract:

Market segmentation is one of the most fundamental strategic marketing concepts. The better the segment which is chosen for targeting by a particular organisation, the more successful the organisation is assumed to be in the marketplace. Also higher education institutions have to improve their marketing tools for attracting foreign students, particularly when demanding tuition fees. This contribution aims at demonstrating the proper usage of the cluster analysis for segmentation (represented by students' willingness to study abroad) and also, based on large international survey, offers some practical marketing implications.

Keywords: Market Segmentation, Students' Preferences, Study Abroad, Cluster Analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2213