Search results for: Dynamic Memory Leak Detection (DMLD).

Authors: R. Kongnuy, P. Pongsumpun

Abstract:

Dengue, a disease found in most tropical and subtropical areas of the world. It has become the most common arboviral disease of humans. This disease is caused by any of four serotypes of dengue virus (DEN1-DEN4). In many endemic countries, the average age of getting dengue infection is shifting upwards, dengue in pregnancy and infancy are likely to be encountered more frequently. The dynamics of the disease is studied by a compartmental model involving ordinary differential equations for the pregnant, infant human and the vector populations. The stability of each equilibrium point is given. The epidemic dynamic is discussed. Moreover, the numerical results are shown for difference values of dengue antibody.

Keywords: Dengue antibody, infant, pregnant human, mathematical model.

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Authors: Mona Soliman Habib

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This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: Ani Grubišić, Slavomir Stankov, Branko Žitko

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This paper describes a concept of stereotype student model in adaptive knowledge acquisition e-learning system. Defined knowledge stereotypes are based on student's proficiency level and on Bloom's knowledge taxonomy. The teacher module is responsible for the whole adaptivity process: the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. The adaptation of courseware is realized according to student-s knowledge stereotype.

Keywords: Adaptive e-learning systems, adaptive courseware, stereotypes, Bloom's knowledge taxonomy.

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Authors: Renju Gangadharan, G. N. Pillai, Indra Gupta

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In this paper a novel method for finding the fault zone on a Thyristor Controlled Series Capacitor (TCSC) incorporated transmission line is presented. The method makes use of the Support Vector Machine (SVM), used in the classification mode to distinguish between the zones, before or after the TCSC. The use of Discrete Wavelet Transform is made to prepare the features which would be given as the input to the SVM. This method was tested on a 400 kV, 50 Hz, 300 Km transmission line and the results were highly accurate.

Keywords: Flexible ac transmission system (FACTS), thyristorcontrolled series-capacitor (TCSC), discrete wavelet transforms(DWT), support vector machine (SVM).

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Authors: K. Kalaikumar, E. Baburaj

Abstract:

One of the problems to be addressed in wireless sensor networks is the issues related to cross layer communication. Cross layer architecture shares the information across the layer, ensuring Quality of Services (QoS). With this shared information, MAC protocol adapts effective functionality maintenance such as route selection on changeable sensor network environment. However, time slot assignment and neighbour route selection time duration for cross layer have not been carried out. The time varying physical layer communication over cross layer causes high traffic load in the sensor network. Though, the traffic load was reduced using cross layer optimization procedure, the computational cost is high. To improve communication efficacy in the sensor network, a self-determined time slot based Cross-Layered Neighbour Route Discovery (C-LNRD) method is presented in this paper. In the presented work, the initial process is to discover the route in the sensor network using Dynamic Source Routing based Medium Access Control (MAC) sub layers. This process considers MAC layer operation with dynamic route neighbour table discovery. Then, the discovered route path for packet communication employs Broad Route Distributed Time Slot Assignment method on Cross-Layered Sensor Network system. Broad Route means time slotting on varying length of the route paths. During packet communication in this sensor network, transmission of packets is adjusted over the different time with varying ranges for controlling the traffic rate. Finally, Rayleigh fading model is developed in C-LNRD to identify the performance of the sensor network communication structure. The main task of Rayleigh Fading is to measure the power level of each communication under MAC sub layer. The minimized power level helps to easily reduce the computational cost of packet communication in the sensor network. Experiments are conducted on factors such as power factor, on packet communication, neighbour route discovery time, and information (i.e., packet) propagation speed.

Keywords: Medium access control, neighbour route discovery, wireless sensor network, Rayleigh fading, distributed time slot assignment

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Authors: Heungsu Lee, Youngseok Kim, Jonghwa Yi, Chul Park

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A landing pier is subjected to safety assessment by visual inspection and design data, but it is difficult to check the damage in real-time. In this study, real - time damage detection and safety evaluation methods were studied. As a result of structural analysis of the arbitrary landing pier structure, the inflection point of deformation and moment occurred at 10%, 50%, and 90% of pile length. The critical value of Fiber Bragg Grating (FBG) sensor was set according to the safety factor, and the FBG sensor application method for real - time safety evaluation was derived.

Keywords: FBG sensor, harbor structure, maintenance, safety evaluation system.

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Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

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In this paper, some new nonlinear generalized Gronwall-Bellman-Type integral inequalities with mixed time delays are established. These inequalities can be used as handy tools to research stability problems of delayed differential and integral dynamic systems. As applications, based on these new established inequalities, some p-stable results of a integro-differential equation are also given. Two numerical examples are presented to illustrate the validity of the main results.

Keywords: Gronwall-Bellman-Type integral inequalities, integrodifferential equation, p-exponentially stable, mixed delays.

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Authors: S. Balaji, M. Rajaram

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The method of introducing the proxy interpretation for sending and receiving requests increase the capability of the server and our approach UDIV (User-Data Identity Security) to solve the data and user authentication without extending size of the data makes better than hybrid IDS (Intrusion Detection System). And at the same time all the security stages we have framed have to pass through less through that minimize the response time of the request. Even though an anomaly detected, before rejecting it the proxy extracts its identity to prevent it to enter into system. In case of false anomalies, the request will be reshaped and transformed into legitimate request for further response. Finally we are holding the normal and abnormal requests in two different queues with own priorities.

Keywords: IDS, Data & User authentication, UDIS.

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Authors: Arkadiusz Biernacki

Abstract:

In this paper we present a statistical analysis of Voice over IP (VoIP) packet streams produced by the G.711 voice coder with voice activity detection (VAD). During telephone conversation, depending whether the interlocutor speaks (ON) or remains silent (OFF), packets are produced or not by a voice coder. As index of dispersion for both ON and OFF times distribution was greater than one, we used hyperexponential distribution for approximation of streams duration. For each stage of the hyperexponential distribution, we tested goodness of our fits using graphical methods, we calculated estimation errors, and performed Kolmogorov-Smirnov test. Obtained results showed that the precise VoIP source model can be based on the five-state Markov process.

Keywords: VoIP source modelling, distribution approximation, hyperexponential distribution.

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Authors: Hoon Lee, Soonyoung Park, Kyoungho Choi

Abstract:

Understanding road features such as lanes, the color of lanes, and sidewalks in a live video captured from a moving vehicle is essential to build video-based navigation systems. In this paper, we present a novel idea to understand the road features using support vector machines. Various feature vectors including color components of road markings and the difference between two regions, i.e., chosen AOIs, and so on are fed into SVM, deciding colors of lanes and sidewalks robustly. Experimental results are provided to show the robustness of the proposed idea.

Keywords: video-based navigation system, lane detection, SVMs, autonomous vehicles

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Authors: M. Tridi, N. Nacereddine, N. Oucief

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This paper describes a novel method for automatic estimation of the contours of weld defect in radiography images. Generally, the contour detection is the first operation which we apply in the visual recognition system. Our approach can be described as a region based maximum likelihood formulation of parametric deformable contours. This formulation provides robustness against the poor image quality, and allows simultaneous estimation of the contour parameters together with other parameters of the model. Implementation is performed by a deterministic iterative algorithm with minimal user intervention. Results testify for the very good performance of the approach especially in synthetic weld defect images.

Keywords: Contour, gaussian, likelihood, rayleigh.

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Authors: Ali A. Ofoghi

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While the shear walls are not economical in buildings, thin shear walls are widely used in the buildings. In the present study, the ratio of different loads to their plasticity and seismic behavior of the wall under different loads have been investigated. Modeling and analysis are carried out by the finite element analysis software ABAQUS. The results show that any increase in the exerted loads will have adverse effects on the seismic behavior of the thin shear walls and causes the wall to collapse by small displacements.

Keywords: Thin shear wall, nonlinear dynamic analysis, reinforced concrete, plasticity.

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Authors: Abhishek Bansal, G. N. Pillai

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This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.

Keywords: Fault identification, distribution networks, high impedance arc-faults, feature vector, LVQ networks.

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Authors: Nidhi Sharma, V. K. Banga

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Nowadays, driving support systems, such as car navigation systems, are getting common, and they support drivers in several aspects. It is important for driving support systems to detect status of driver's consciousness. Particularly, detecting driver's drowsiness could prevent drivers from collisions caused by drowsy driving. In this paper, we discuss the various artificial detection methods for detecting driver's drowsiness processing technique. This system is based on facial images analysis for warning the driver of drowsiness or in attention to prevent traffic accidents.

Keywords: Neuro-Fuzzy Model, Halstead Model, Walston-FelixModel, Bailey-Basili Model, Doty Model, GA Based Model, GeneticAlgorithm.

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Authors: S. Rao, S. Khavtasi, C. Chassot, N. Van Wambeke, F. Armando, S. P. Romano, T. Castaldi

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The talks about technological convergence had been around for almost twenty years. Today Internet made it possible. And this is not only technical evolution. The way it changed our lives reflected in variety of applications, services and technologies used in day-to-day life. Such benefits imposed even more requirements on heterogeneous and unreliable IP networks. Current paper outlines QoS management system developed in the NetQoS [1] project. It describes an overall architecture of management system for heterogeneous networks and proposes automated multi-layer QoS management. Paper focuses on the structure of the most crucial modules of the system that enable autonomous and multi-layer provisioning and dynamic adaptation.

Keywords: Automated QoS management, multi-layerprovisioning and adaptation, QoS, QoE.

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Authors: Kangkang Wu, Kaizhi Wang, Zhijun Yuan

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This paper deals with a mini radar system aimed at detecting small targets at the low latitude. The radar operates at Ku-band in the frequency modulated continuous wave (FMCW) mode with two receiving channels. The radar system has the characteristics of compactness, mobility, and low power consumption. This paper focuses on the implementation of the radar system, and the Block least mean square (Block LMS) algorithm is applied to minimize the fortuitous distortion. It is validated from a series of experiments that the track of the unmanned aerial vehicle (UAV) can be easily distinguished with the radar system.

Keywords: Unmanned aerial vehicle, interference, block least mean square, frequency modulated continuous wave.

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Authors: Philippe Fauquet-Alekhine, Elena Fauquet-Alekhine-Pavlovskaia

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On the basis of questionnaires and interviews of two samples of subjects (French and Anglo-Saxon) for which two food products were presented (one of the subject’s country and one of the foreign country), we have shown how consumers could be sensitive to the label or brand written on the package of the food product. Furthermore, in the light of Intersubjectivity theory, we have shown the necessity for the consumer to find congruence between the direct and meta perspective towards the product for which the producer and especially the marketer is responsible. Taking into account these findings may help to avoid the commercial failure of a brand while exported abroad.

Keywords: Brand, failure, food industry.

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Authors: K. Barbar, M. Dehayni, A. Awada, M. Smaili

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Considering the theory of attribute grammars, we use logical formulas instead of traditional functional semantic rules. Following the decoration of a derivation tree, a suitable algorithm should maintain the consistency of the formulas together with the evaluation of the attributes. This may be a Prolog-like resolution, but this paper examines a somewhat different strategy, based on production specialization, local consistency and propagation: given a derivation tree, it is interactively decorated, i.e. incrementally checked and evaluated. The non-directed dependencies are dynamically directed during attribute evaluation.

Keywords: Input/Output attribute grammars, local consistency, logical programming, propagation, relational attribute grammars.

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Authors: Ke Wang, Zhu Wang

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Coordinating and promoting urban and rural development has been a new round of institutional change in Zhejiang province since 2004. And this plan was fully implemented, which showed that the isolation between the urban and rural areas had gradually diminished. Little by little, an infiltration interface that is dynamic, flexible and interactive is formed, and this morphological structure starts to appear on the landscape form in the surrounding villages. In order to study the specific function and formation of the structure in the context of industrial revolution, Bimen village located on the interface between Anji Township, Huzhou and Yuhang District, Hangzhou is taken as the case. Anji township is in the cross area between Yangtze River delta economic circle and innovation center in Hangzhou. Awarded with ‘Chinese beautiful village’, Bimen has witnessed the growing process of infiltration in ecology, economy, technology and culture on the interface. Within the opportunity, Bimen village presents internal reformation to adapt to the energy exchange with urban areas. In the research, the reformation is to adjust the industrial structure, to upgrade the local special bamboo crafts, to release space for activities, and to establish infrastructures on the interface. The characteristic of an interface is elasticity achieved by introducing an Internet platform using ‘O2O’ agriculture method to connect cities and farmlands. There is a platform of this kind in Bimen named ‘Xiao Mei’. ‘Xiao’ in Chinese means small, ‘Mei’ means beautiful, which indicates the method to refine the landscape form. It turns out that the new agriculture mode will strengthen the interface by orienting the Third Party Platform upon the old dynamic basis and will bring new vitality for economy development in Bimen village. The research concludes opportunities and challenges generated by the evolution of the infiltration interface. It also proposes strategies for how to organically adapt to the urbanization process. Finally it demonstrates what will happen by increasing flexibility in the landscape forms of suburbs in the Bimen village.

Keywords: Bimen Village, infiltration interface, flexibility, suburban landscape form.

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper presents an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: Cloud, enhancing security, Fog, IoT, telehealth.

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Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: Deep learning, convolutional neural network, LSTM, housing prediction.

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Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

Abstract:

This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.

Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.

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Authors: Miquel Colobran, Josep M. Basart

Abstract:

One of the most ancient humankind concerns is knowledge formalization i.e. what a concept is. Concept Analysis, a branch of analytical philosophy, relies on the purpose of decompose the elements, relations and meanings of a concept. This paper aims at presenting a method to make a concept analysis obtaining a knowledge representation suitable to be processed by a computer system using either object-oriented or ontology technologies. Security notion is, usually, known as a set of different concepts related to “some kind of protection". Our method concludes that a more general framework for the concept, despite it is dynamic, is possible and any particular definition (instantiation) depends on the elements used by its construction instead of the concept itself.

Keywords: Concept analysis, Knowledge representation, Security, UML.

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Authors: Pavel Psota, Vít Lédl, Jan Václavík, Roman Doleček, Pavel Mokrý, Petr Vojtíšek

Abstract:

This paper presents advanced time average digital holography by means of frequency shift and phase modulation. This technique can measure amplitudes of vibrations at ultimate dynamic range while the amplitude distribution evaluation is done independently in every pixel. The main focus of the paper is to gain insight into behavior of the method at low amplitudes of vibrations. In order to reach that, a set of experiments was performed. Results of the experiments together with novel noise suppression show the limit of the method to be below 0.1 nm.

Keywords: Acousto-optical modulator, digital holography, low amplitudes, vibrometry.

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Authors: Erfan Asghari Fesaghandis, Reza Ghaffari Adli, Abbas Kianvash, Hossein Aghajani, Homa Homaie

Abstract:

NiTi alloys possess magnificent superelastic, shape memory, high strength and biocompatible properties. For improving mechanical properties, foremost, superelasticity behavior, heat treatment process is carried out. In this paper, two different heat treatment methods were undertaken: (1) solid solution, and (2) aging. The effect of each treatment in a constant time is investigated. Five samples were prepared to study the structure and optimize mechanical properties under different time and temperature. For measuring the upper plateau stress, lower plateau stress and residual strain, tensile test is carried out. The samples were aged at two different temperatures to see difference between aging temperatures. The sample aged at 500 °C has a bigger crystallite size and lower amount of Ni which causes the mentioned sample to possess poor pseudo elasticity behaviour than the other aged sample. The sample aged at 460 °C has shown remarkable superelastic properties. The mentioned sample’s higher plateau is 580 MPa with the lowest residual strain (0.17%) while other samples have possessed higher residual strains. X-ray diffraction was used to investigate the produced phases.

Keywords: Heat treatment, phase transformation, superelasticity, NiTi alloy.

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Authors: I. Kurashvili, G. Darsavelidze, G. Bokuchava, A. Sichinava, I. Tabatadze

Abstract:

The impact of boron doping on the internal friction (IF) and shear modulus temperature spectra of Si_1-xGe_x(x≤0,02) monocrsytals has been investigated by reverse torsional pendulum oscillations characteristics testing. At room temperatures, microhardness and indentation modulus of the same specimens have been measured by dynamic ultra microhardness tester. It is shown that boron doping causes two kinds effect: At low boron concentration (~10¹⁵ cm^-3) significant strengthening is revealed, while at the high boron concentration (~10¹⁹ cm^-3) strengthening effect and activation characteristics of relaxation origin IF processes are reduced.

Keywords: Dislocation, internal friction, microhardness, relaxation.

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Authors: G. Reinhart, J. Pohl

Abstract:

Manufacturing companies are facing a broad variety of challenges caused by a dynamic production environment. To succeed in such an environment, it is crucial to minimize the loss of time required to trigger the adaptation process of a company-s production structures. This paper presents an approach for the continuous monitoring of production structures by neurologic principles. It enhances classical monitoring concepts, which are principally focused on reactive strategies, and enables companies to act proactively. Thereby, strategic aspects regarding the harmonization of certain life cycles are integrated into the decision making process for triggering the reconfiguration process of the production structure.

Keywords: Continuous Factory Planning, Production Structure, Production Management.

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Authors: Irina Eglite, Andrei A. Kolyshkin

Abstract:

Method of multiple scales is used in the paper in order to derive an amplitude evolution equation for the most unstable mode from two-dimensional shallow water equations under the rigid-lid assumption. It is assumed that shallow mixing layer is slightly curved in the longitudinal direction and contains small particles. Dynamic interaction between carrier fluid and particles is neglected. It is shown that the evolution equation is the complex Ginzburg-Landau equation. Explicit formulas for the computation of the coefficients of the equation are obtained.

Keywords: Shallow water equations, mixing layer, weakly nonlinear analysis, Ginzburg-Landau equation

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Authors: A. Bennassar, A. Abbou, M. Akherraz, M. Barara

Abstract:

In this paper, we propose a sensorless backstepping control of induction motor (IM) associated with three levels neutral clamped (NPC) inverter. First, the backstepping approach is designed to steer the flux and speed variables to theirs references and to compensate the uncertainties. A Lyapunov theory is used and it demonstrates that the dynamic trajectories tracking are asymptotically stable. Second, we estimate the rotor flux and speed by using the adaptive Luenberger observer (ALO). Simulation results are provided to illustrate the performance of the proposed approach in high and low speeds and load torque disturbance.

Keywords: Sensorless backstepping, IM, Three levels NPC inverter, Lyapunov theory, ALO.

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Authors: P. Jelodarian , E. Farshidi

Abstract:

In this paper, a new approach for design of a fully differential second order current mode continuous-time sigma-delta modulator is presented. For circuit implementation, square root domain (SRD) translinear loop based on floating-gate MOS transistors that operate in saturation region is employed. The modulator features, low supply voltage, low power consumption (8mW) and high dynamic range (55dB). Simulation results confirm that this design is suitable for data converters.

Keywords: Sigma-delta, current-mode, translinear loop, geometric mean, squarer/divider.

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