Search results for: nonlinear identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1966

Search results for: nonlinear identification

586 Exploring Inter-Relationships between Events to Identify Strategic Technological Competencies: A Combined Approach

Authors: Cláudio Santos, Madalena Araújo, Nuno Correia

Abstract:

The inherent complexity in nowadays- business environments is forcing organizations to be attentive to the dynamics in several fronts. Therefore, the management of technological innovation is continually faced with uncertainty about the future. These issues lead to a need for a systemic perspective, able to analyze the consequences of interactions between different factors. The field of technology foresight has proposed methods and tools to deal with this broader perspective. In an attempt to provide a method to analyze the complex interactions between events in several areas, departing from the identification of the most strategic competencies, this paper presents a methodology based on the Delphi method and Quality Function Deployment. This methodology is applied in a sheet metal processing equipment manufacturer, as a case study.

Keywords: Competencies, Delphi Method, Quality Function Deployment, Technology Foresight.

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585 Temporal Analysis of Magnetic Nerve Stimulation–Towards Enhanced Systems via Virtualisation

Authors: Stefan M. Goetz, Thomas Weyh, Hans-Georg Herzog

Abstract:

The triumph of inductive neuro-stimulation since its rediscovery in the 1980s has been quite spectacular. In lots of branches ranging from clinical applications to basic research this system is absolutely indispensable. Nevertheless, the basic knowledge about the processes underlying the stimulation effect is still very rough and rarely refined in a quantitative way. This seems to be not only an inexcusable blank spot in biophysics and for stimulation prediction, but also a fundamental hindrance for technological progress. The already very sophisticated devices have reached a stage where further optimization requires better strategies than provided by simple linear membrane models of integrate-and-fire style. Addressing this problem for the first time, we suggest in the following text a way for virtual quantitative analysis of a stimulation system. Concomitantly, this ansatz seems to provide a route towards a better understanding by using nonlinear signal processing and taking the nerve as a filter that is adapted for neuronal magnetic stimulation. The model is compact and easy to adjust. The whole setup behaved very robustly during all performed tests. Exemplarily a recent innovative stimulator design known as cTMS is analyzed and dimensioned with this approach in the following. The results show hitherto unforeseen potentials.

Keywords: Theory of magnetic stimulation, inversion, optimization, high voltage oscillator, TMS, cTMS.

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584 The Optimization of Copper Sulfate and Tincalconite Molar Ratios on the Hydrothermal Synthesis of Copper Borates

Authors: E. Moroydor Derun, N. Tugrul, F. T. Senberber, A. S. Kipcak, S. Piskin

Abstract:

In this research, copper borates are synthesized by the reaction of copper sulfate pentahydrate (CuSO4.5H2O) and tincalconite (Na2O4B7.10H2O). The experimental parameters are selected as 80oC reaction temperature and 60 of reaction time. The effect of mole ratio of CuSO4.5H2O to Na2O4B7.5H2O is studied. For the identification analyses X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques are used. At the end of the experiments, synthesized copper borate is matched with the powder diffraction file of “00-001-0472” [Cu(BO2)2] and characteristic vibrations between B and O atoms are seen. The proper crystals are obtained at the mole ratio of 3:1. This study showed that simplified synthesis process is suitable for the production of copper borate minerals.

Keywords: Hydrothermal synthesis, copper borates, copper sulfate, tincalconite.

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583 Application of the Piloting Law Based on Adaptive Differentiators via Second Order Sliding Mode for a Fixed Wing Aircraft

Authors: Zaouche Mohammed, Amini Mohammed, Foughali Khaled, Hamissi Aicha, Aktouf Mohand Arezki, Boureghda Ilyes

Abstract:

In this paper, we present a piloting law based on the adaptive differentiators via high order sliding mode controller, by using an aircraft in virtual simulated environment. To deal with the design of an autopilot controller, we propose a framework based on Software in the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. The aircraft dynamic model is nonlinear, Multi-Input Multi-Output (MIMO) and tightly coupled. The nonlinearity resides in the dynamic equations and also in the aerodynamic coefficients' variability. In our case, two (02) aircrafts are used in the flight tests, the Zlin-142 and MQ-1 Predator. For both aircrafts and in a very low altitude flight, we send the piloting control inputs to the aircraft which has stalled due to a command disconnection. Then, we present the aircraft’s dynamic behavior analysis while reestablishing the command transmission. Finally, a comparative study between the two aircraft’s dynamic behaviors is presented.

Keywords: Adaptive differentiators, Microsoft Flight Simulator, MQ-1 predator, second order sliding modes, Zlin-142.

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582 PUMA 560 Optimal Trajectory Control using Genetic Algorithm, Simulated Annealing and Generalized Pattern Search Techniques

Authors: Sufian Ashraf Mazhari, Surendra Kumar

Abstract:

Robot manipulators are highly coupled nonlinear systems, therefore real system and mathematical model of dynamics used for control system design are not same. Hence, fine-tuning of controller is always needed. For better tuning fast simulation speed is desired. Since, Matlab incorporates LAPACK to increase the speed and complexity of matrix computation, dynamics, forward and inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in such a way that all operations are matrix based which give very less simulation time. This paper compares PID parameter tuning using Genetic Algorithm, Simulated Annealing, Generalized Pattern Search (GPS) and Hybrid Search techniques. Controller performances for all these methods are compared in terms of joint space ITSE and cartesian space ISE for tracking circular and butterfly trajectories. Disturbance signal is added to check robustness of controller. GAGPS hybrid search technique is showing best results for tuning PID controller parameters in terms of ITSE and robustness.

Keywords: Controller Tuning, Genetic Algorithm, Pattern Search, Robotic Controller, Simulated Annealing.

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581 Optimal Retrofit Design of Reinforced Concrete Frame with Infill Wall Using Fiber Reinforced Plastic Materials

Authors: Sang Wook Park, Se Woon Choi, Yousok Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

Various retrofit techniques for reinforced concrete frame with infill wall have been steadily developed. Among those techniques, strengthening methodology based on diagonal FRP strips (FRP bracings) has numerous advantages such as feasibility of implementing without interrupting the building under operation, reduction of cost and time, and easy application. Considering the safety of structure and retrofit cost, the most appropriate retrofit solution is needed. Thus, the objective of this study is to suggest pareto-optimal solution for existing building using FRP bracings. To find pareto-optimal solution analysis, NSGA-II is applied. Moreover, the seismic performance of retrofit building is evaluated. The example building is 5-storey, 3-bay RC frames with infill wall. Nonlinear static pushover analyses are performed with FEMA 356. The criterion of performance evaluation is inter-story drift ratio at the performance level IO, LS, CP. Optimal retrofit solutions is obtained for 32 individuals and 200 generations. Through the proposed optimal solutions, we confirm the improvement of seismic performance of the example building.

Keywords: Retrofit, FRP bracings, reinforced concrete frame with infill wall, seismic performance evaluation, NSGA-II.

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580 On Identity Disclosure Risk Measurement for Shared Microdata

Authors: M. N. Huda, S. Yamada, N. Sonehara

Abstract:

Probability-based identity disclosure risk measurement may give the same overall risk for different anonymization strategy of the same dataset. Some entities in the anonymous dataset may have higher identification risks than the others. Individuals are more concerned about higher risks than the average and are more interested to know if they have a possibility of being under higher risk. A notation of overall risk in the above measurement method doesn-t indicate whether some of the involved entities have higher identity disclosure risk than the others. In this paper, we have introduced an identity disclosure risk measurement method that not only implies overall risk, but also indicates whether some of the members have higher risk than the others. The proposed method quantifies the overall risk based on the individual risk values, the percentage of the records that have a risk value higher than the average and how larger the higher risk values are compared to the average. We have analyzed the disclosure risks for different disclosure control techniques applied to original microdata and present the results.

Keywords: Anonymization, microdata, disclosure risk, privacy.

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579 An Improved Learning Algorithm based on the Conjugate Gradient Method for Back Propagation Neural Networks

Authors: N. M. Nawi, M. R. Ransing, R. S. Ransing

Abstract:

The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast training multilayer perceptron (MLP) algorithm (CGFR/AG). The approaches presented in the paper consist of three steps: (1) Modification on standard back propagation algorithm by introducing gain variation term of the activation function, (2) Calculating the gradient descent on error with respect to the weights and gains values and (3) the determination of the new search direction by exploiting the information calculated by gradient descent in step (2) as well as the previous search direction. The proposed method improved the training efficiency of back propagation algorithm by adaptively modifying the initial search direction. Performance of the proposed method is demonstrated by comparing to the conjugate gradient algorithm from neural network toolbox for the chosen benchmark. The results show that the number of iterations required by the proposed method to converge is less than 20% of what is required by the standard conjugate gradient and neural network toolbox algorithm.

Keywords: Back-propagation, activation function, conjugategradient, search direction, gain variation.

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578 Modelling an Investment Portfolio with Mandatory and Voluntary Contributions under M-CEV Model

Authors: Amadi Ugwulo Chinyere, Lewis D. Gbarayorks, Emem N. H. Inamete

Abstract:

In this paper, the mandatory contribution, additional voluntary contribution (AVC) and administrative charges are merged together to determine the optimal investment strategy (OIS) for a pension plan member (PPM) in a defined contribution (DC) pension scheme under the modified constant elasticity of variance (M-CEV) model. We assume that the voluntary contribution is a stochastic process and a portfolio consisting of one risk free asset and one risky asset modeled by the M-CEV model is considered. Also, a stochastic differential equation consisting of PPM’s monthly contributions, voluntary contributions and administrative charges is obtained. More so, an optimization problem in the form of Hamilton Jacobi Bellman equation which is a nonlinear partial differential equation is obtained. Using power transformation and change of variables method, an explicit solution of the OIS and the value function are obtained under constant absolute risk averse (CARA). Furthermore, numerical simulations on the impact of some sensitive parameters on OIS were discussed extensively. Finally, our result generalizes some existing result in the literature.

Keywords: DC pension fund, modified constant elasticity of variance, optimal investment strategies, voluntary contribution, administrative charges.

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577 Inelastic Strength of Laterally Unsupported Top- Loaded Built-Up Slender Beams

Authors: M. Massoud El Sa'adawy, F. F. F. El Dib

Abstract:

Lateral-torsional buckling (LTB) is one of the phenomenae controlling the ultimate bending strength of steel Ibeams carrying distributed loads on top flange. Built-up I-sections are used as main beams and distributors. This study investigates the ultimate bending strength of such beams with sections of different classes including slender elements. The nominal strengths of the selected beams are calculated for different unsupported lengths according to the Provisions of the American Institute of Steel Constructions (AISC-LRFD). These calculations are compared with results of a nonlinear inelastic study using accurate FE model for this type of loading. The goal is to investigate the performance of the provisions for the selected sections. Continuous distributed load at the top flange of the beams was applied at the FE model. Imperfections of different values are implemented to the FE model to examine their effect on the LTB of beams at failure, and hence, their effect on the ultimate strength of beams. The study also introduces a procedure for evaluating the performance of the provisions compared with the accurate FEA results of the selected sections. A simplified design procedure is given and recommendations for future code updates are made.

Keywords: Lateral buckling, Top Loading, Ultimate load, Slender Sections.

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576 A Comparison of YOLO Family for Apple Detection and Counting in Orchards

Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

Abstract:

In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: Agricultural object detection, Deep learning, machine vision, YOLO family.

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575 The Use of Process-Oriented Methods of Calculation to Determine the Costs of Logistics Processes

Authors: Tomas Cechura, Michal Simon

Abstract:

The aim of this paper is to create a proposal for determining the costs of logistics processes by using process-oriented calculation methods. The traditional approach is that logistics costs are part of manufacturing overhead which is usually calculated as a percentage surcharge. Therefore in the traditional approach it is not obvious where and in which activities costs were incurred. So it is impossible to trace logistics costs to products. Our point of view is trying to fix or at least improve this issue. Another benefit of applying the process approach is identification of logistics processes which are otherwise part of manufacturing overhead. In the first part this paper describes the development of process-oriented methods over time. The next part shows the possibility of implementing the process-oriented method called Prozesskostenrechnung to logistics processes. The conclusion summarizes advantages and disadvantages of using this method in logistics.

Keywords: Cost, logistics, calculation, process-oriented method.

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574 ANFIS Approach for Locating Faults in Underground Cables

Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

Abstract:

This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.

Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, Fault location, Underground Cable, Wavelet Transform.

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573 Tracking Activity of Real Individuals in Web Logs

Authors: Sándor Juhász, Renáta Iváncsy

Abstract:

This paper describes an enhanced cookie-based method for counting the visitors of web sites by using a web log processing system that aims to cope with the ambitious goal of creating countrywide statistics about the browsing practices of real human individuals. The focus is put on describing a new more efficient way of detecting human beings behind web users by placing different identifiers on the client computers. We briefly introduce our processing system designed to handle the massive amount of data records continuously gathered from the most important content providers of the Hungary. We conclude by showing statistics of different time spans comparing the efficiency of multiple visitor counting methods to the one presented here, and some interesting charts about content providers and web usage based on real data recorded in 2007 will also be presented.

Keywords: Cookie based identification, real data, user activitytracking, web auditing, web log processing

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572 Identification of Wideband Sources Using Higher Order Statistics in Noisy Environment

Authors: S. Bourennane, A. Bendjama

Abstract:

This paper deals with the localization of the wideband sources. We develop a new approach for estimating the wide band sources parameters. This method is based on the high order statistics of the recorded data in order to eliminate the Gaussian components from the signals received on the various hydrophones.In fact the noise of sea bottom is regarded as being Gaussian. Thanks to the coherent signal subspace algorithm based on the cumulant matrix of the received data instead of the cross-spectral matrix the wideband correlated sources are perfectly located in the very noisy environment. We demonstrate the performance of the proposed algorithm on the real data recorded during an underwater acoustics experiments.

Keywords: Higher-order statistics, high resolution array processing techniques, localization of acoustics sources, wide band sources.

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571 Influence of Argon Gas Concentration in N2-Ar Plasma for the Nitridation of Si in Abnormal Glow Discharge

Authors: K. Abbas, R. Ahmad, I. A. Khan, S. Saleem, U. Ikhlaq

Abstract:

Nitriding of p-type Si samples by pulsed DC glow discharge is carried out for different Ar concentrations (30% to 90%) in nitrogen-argon plasma whereas the other parameters like pressure (2 mbar), treatment time (4 hr) and power (175 W) are kept constant. The phase identification, crystal structure, crystallinity, chemical composition, surface morphology and topography of the nitrided layer are studied using X-ray diffraction (XRD), Fourier transform infra-red spectroscopy (FTIR), optical microscopy (OM), scanning electron microscopy (SEM) and atomic force microscopy (AFM) respectively. The XRD patterns reveal the development of different diffraction planes of Si3N4 confirming the formation of polycrystalline layer. FTIR spectrum confirms the formation of bond between Si and N. Results reveal that addition of Ar into N2 plasma plays an important role to enhance the production of active species which facilitate the nitrogen diffusion.

Keywords: Crystallinity, glow discharge, nitriding, sputtering.

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570 Minimum-Fuel Optimal Trajectory for Reusable First-Stage Rocket Landing Using Particle Swarm Optimization

Authors: Kevin Spencer G. Anglim, Zhenyu Zhang, Qingbin Gao

Abstract:

Reusable launch vehicles (RLVs) present a more environmentally-friendly approach to accessing space when compared to traditional launch vehicles that are discarded after each flight. This paper studies the recyclable nature of RLVs by presenting a solution method for determining minimum-fuel optimal trajectories using principles from optimal control theory and particle swarm optimization (PSO). This problem is formulated as a minimum-landing error powered descent problem where it is desired to move the RLV from a fixed set of initial conditions to three different sets of terminal conditions. However, unlike other powered descent studies, this paper considers the highly nonlinear effects caused by atmospheric drag, which are often ignored for studies on the Moon or on Mars. Rather than optimizing the controls directly, the throttle control is assumed to be bang-off-bang with a predetermined thrust direction for each phase of flight. The PSO method is verified in a one-dimensional comparison study, and it is then applied to the two-dimensional cases, the results of which are illustrated.

Keywords: Minimum-fuel optimal trajectory, particle swarm optimization, reusable rocket, SpaceX.

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569 A Robust Image Watermarking Scheme using Image Moment Normalization

Authors: Latha Parameswaran, K. Anbumani

Abstract:

Multimedia security is an incredibly significant area of concern. A number of papers on robust digital watermarking have been presented, but there are no standards that have been defined so far. Thus multimedia security is still a posing problem. The aim of this paper is to design a robust image-watermarking scheme, which can withstand a different set of attacks. The proposed scheme provides a robust solution integrating image moment normalization, content dependent watermark and discrete wavelet transformation. Moment normalization is useful to recover the watermark even in case of geometrical attacks. Content dependent watermarks are a powerful means of authentication as the data is watermarked with its own features. Discrete wavelet transforms have been used as they describe image features in a better manner. The proposed scheme finds its place in validating identification cards and financial instruments.

Keywords: Watermarking, moments, wavelets, content-based, benchmarking.

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568 Clustering of Variables Based On a Probabilistic Approach Defined on the Hypersphere

Authors: Paulo Gomes, Adelaide Figueiredo

Abstract:

We consider n individuals described by p standardized variables, represented by points of the surface of the unit hypersphere Sn-1. For a previous choice of n individuals we suppose that the set of observables variables comes from a mixture of bipolar Watson distribution defined on the hypersphere. EM and Dynamic Clusters algorithms are used for identification of such mixture. We obtain estimates of parameters for each Watson component and then a partition of the set of variables into homogeneous groups of variables. Additionally we will present a factor analysis model where unobservable factors are just the maximum likelihood estimators of Watson directional parameters, exactly the first principal component of data matrix associated to each group previously identified. Such alternative model it will yield us to directly interpretable solutions (simple structure), avoiding factors rotations.

Keywords: Dynamic Clusters algorithm, EM algorithm, Factor analysis model, Hierarchical Clustering, Watson distribution.

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567 Changes in Fish and Shellfish in Thondamanaru Lagoon, Jaffna, Sri Lanka

Authors: S. Piratheepa, G. Rajendramani, T. Eswaramohan

Abstract:

Current study was conducted for one year from June 2014 to May 2015, with an objective of identification of fish and shellfish diversity in the Thondamanaru lagoon ecosystem. In this study, 11 species were identified from Thondamanaru lagoon, Jaffna, Sri Lanka. There are four fishes, Chanos chanos, Hemirhamphus sp., Nematalosa sp. and Mugil cephalus and seven shell fishes, Penaeus indicus, Penaeus monodon, Penaeus latisulcatus, Penaeus semisulcatus, Metapenaeus monoceros, Portunus pelagicus and Scylla serrata. Species composition of Mugil cephalus, Penaeus indicus and Metapenaeus monoceros was high during rainy seasons. However, lagoon is being subjected to adverse environmental conditions that threaten its fish and shellfish biodiversity due to lack of saline water availability and changes in rainfall pattern.

Keywords: Diversity, shell fish, shrimp, Thondamanaru lagoon.

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566 Self Organizing Mixture Network in Mixture Discriminant Analysis: An Experimental Study

Authors: Nazif Çalış, Murat Erişoğlu, Hamza Erol, Tayfun Servi

Abstract:

In the recent works related with mixture discriminant analysis (MDA), expectation and maximization (EM) algorithm is used to estimate parameters of Gaussian mixtures. But, initial values of EM algorithm affect the final parameters- estimates. Also, when EM algorithm is applied two times, for the same data set, it can be give different results for the estimate of parameters and this affect the classification accuracy of MDA. Forthcoming this problem, we use Self Organizing Mixture Network (SOMN) algorithm to estimate parameters of Gaussians mixtures in MDA that SOMN is more robust when random the initial values of the parameters are used [5]. We show effectiveness of this method on popular simulated waveform datasets and real glass data set.

Keywords: Self Organizing Mixture Network, MixtureDiscriminant Analysis, Waveform Datasets, Glass Identification, Mixture of Multivariate Normal Distributions

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565 Trust Building Mechanisms for Electronic Business Networks and Their Relation to eSkills

Authors: Radoslav Delina, Michal Tkáč

Abstract:

Globalization, supported by information and communication technologies, changes the rules of competitiveness and increases the significance of information, knowledge and network cooperation. In line with this trend, the need for efficient trust-building tools has emerged. The absence of trust building mechanisms and strategies was identified within several studies. Through trust development, participation on e-business network and usage of network services will increase and provide to SMEs new economic benefits. This work is focused on effective trust building strategies development for electronic business network platforms. Based on trust building mechanism identification, the questionnairebased analysis of its significance and minimum level of requirements was conducted. In the paper, we are confirming the trust dependency on e-Skills which play crucial role in higher level of trust into the more sophisticated and complex trust building ICT solutions.

Keywords: Correlation analysis, decision trees, e-marketplace, trust building

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564 Identifying Unknown Dynamic Forces Applied on Two Dimensional Frames

Authors: H. Katkhuda

Abstract:

A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: Dynamic Force Identification, Dynamic Responses, Sub-structure and Time Domain.

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563 An Automatic Sleep Spindle Detector based on WT, STFT and WMSD

Authors: J. Costa, M. Ortigueira, A. Batista, T. Paiva

Abstract:

Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Sleep Spindles are also promising objective indicators for neurodegenerative disorders. Visual spindle scoring however is a tedious workload. In this paper three different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform, Wavelet Transform and Wave Morphology for Spindle Detection. In order to improve the results, a combination of the three detectors is presented and comparison with human expert scorers is performed. The best performance is obtained with a combination of the three algorithms which resulted in a sensitivity and specificity of 94% when compared to human expert scorers.

Keywords: EEG, Short Time Fourier Transform, Sleep Spindles, Wave Morphology for Spindle Detection, Wavelet Transform.

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562 Hybrid Neural Network Methods for Lithology Identification in the Algerian Sahara

Authors: S. Chikhi, M. Batouche, H. Shout

Abstract:

In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.

Keywords: Classification, Lithofacies, Probabilistic formalism, Reservoir characterization, Well-log data.

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561 Criticality Assessment of Failures in Multipoint Communication Networks

Authors: Myriam Noureddine, Rachid Noureddine

Abstract:

Following the current economic challenges and competition, all systems, whatever their field, must be efficient and operational during their activity. In this context, it is imperative to anticipate, identify, eliminate and estimate the failures of systems, which may lead to an interruption of their function. This need requires the management of possible risks, through an assessment of the failures criticality following a dependability approach. On the other hand, at the time of new information technologies and considering the networks field evolution, the data transmission has evolved towards a multipoint communication, which can simultaneously transmit information from a sender to multiple receivers. This article proposes the failures criticality assessment of a multipoint communication network, integrates a database of network failures and their quantifications. The proposed approach is validated on a case study and the final result allows having the criticality matrix associated with failures on the considered network, giving the identification of acceptable risks.

Keywords: Dependability, failure, multipoint network, criticality matrix.

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560 A Taguchi Approach to Investigate Impact of Factors for Reusability of Software Components

Authors: Parvinder S. Sandhu, Pavel Blecharz, Hardeep Singh

Abstract:

Quantitative Investigation of impact of the factors' contribution towards measuring the reusability of software components could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable component from existing legacy systems; that can save cost of developing the software from scratch. But the issue of the relative significance of contributing factors has remained relatively unexplored. In this paper, we have use the Taguchi's approach in analyzing the significance of different structural attributes or factors in deciding the reusability level of a particular component. The results obtained shows that the complexity is the most important factor in deciding the better Reusability of a function oriented Software. In case of Object Oriented Software, Coupling and Complexity collectively play significant role in high reusability.

Keywords: Taguchi Approach, Reusability, SoftwareComponents, Structural Attributes.

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559 Pension Plan Member’s Investment Strategies with Transaction Cost and Couple Risky Assets Modelled by the O-U Process

Authors: Udeme O. Ini, Edikan E. Akpanibah

Abstract:

This paper studies the optimal investment strategies for a plan member (PM) in a defined contribution (DC) pension scheme with transaction cost, taxes on invested funds and couple risky assets (stocks) under the Ornstein-Uhlenbeck (O-U) process. The PM’s portfolio is assumed to consist of a risk-free asset and two risky assets where the two risky assets are driven by the O-U process. The Legendre transformation and dual theory is use to transform the resultant optimal control problem which is a nonlinear partial differential equation (PDE) into linear PDE and the resultant linear PDE is then solved for the explicit solutions of the optimal investment strategies for PM exhibiting constant absolute risk aversion (CARA) using change of variable technique. Furthermore, theoretical analysis is used to study the influences of some sensitive parameters on the optimal investment strategies with observations that the optimal investment strategies for the two risky assets increase with increase in the dividend and decreases with increase in tax on the invested funds, risk averse coefficient, initial fund size and the transaction cost.

Keywords: Ornstein-Uhlenbeck process, portfolio management, Legendre transforms, CARA utility.

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558 A New Perturbation Technique in Numerical Study on Buckling of Composite Shells under Axial Compression

Authors: Zia R. Tahir, P. Mandal

Abstract:

A numerical study is presented on buckling and post buckling behaviour of laminated carbon fiber reinforced plastic (CFRP) thin-walled cylindrical shells under axial compression using asymmetric meshing technique (AMT). Asymmetric meshing technique is a perturbation technique to introduce disturbance without changing geometry, boundary conditions or loading conditions. Asymmetric meshing affects predicted buckling load, buckling mode shape and post-buckling behaviour. Linear (eigenvalue) and nonlinear (Riks) analyses have been performed to study the effect of asymmetric meshing in the form of a patch on buckling behaviour. The reduction in the buckling load using Asymmetric meshing technique was observed to be about 15%. An isolated dimple formed near the bifurcation point and the size of which increased to reach a stable state in the post-buckling region. The load-displacement curve behaviour applying asymmetric meshing is quite similar to the curve obtained using initial geometric imperfection in the shell model.

Keywords: CFRP Composite Cylindrical Shell, Finite Element Analysis, Perturbation Technique, Asymmetric Meshing Technique, Linear Eigenvalue analysis, Non-linear Riks Analysis

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557 Identification of Vessel Class with LSTM using Kinematic Features in Maritime Traffic Control

Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

Abstract:

Prevent abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behaviour analysis, LSTM

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