Search results for: dynamic database

Authors: M. Reza Bagerzadeh Karimi, M. Ali Lotfollahi Yaghin, R. Mehdi Nezhad, V. Sadeghi, M. Aghabalaie

Abstract:

One of the main purposes of designing bucklingrestrained braces is the fact that the entire lateral load is wasted by the braces, the entire gravitational load is moved to the foundation through the beams, and the columns can be moved to the foundation. In other words, braces are designed for bearing lateral load. In the implementation of the structure, it should be noted that the implementation of various parts of the structure must be conducted in such a way that the buckling-restrained braces would not bear the gravitational load. Moreover, this type of brace has been investigated under impact loading, and the design goals of designing method (direct motion) are controlled under impact loading. The results of dynamic analysis are shown as the relocation charts of the floors and switch between the floors. Finally, the results are compared with each other.

Keywords: Buckling-Restrained Braced Frame (BRBF), energydissipating, ABAQUS, SAP2000, impact load.

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Authors: Clara Inés Pardo Martínez, William H. Alfonso Piña

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In emerging economies, recycling is an opportunity for the cities to increase the lifespan of sanitary landfills, reduce the costs of the solid waste management, decrease the environmental problems of the waste treatment through reincorporate waste in the productive cycle and protect and develop people’s livelihoods of informal waste pickers. However, few studies have analysed the possibilities and strategies to integrate formal and informal sectors in the solid waste management for the benefit of both. This study seek to make a strength, weakness, opportunity, and threat (SWOT) analysis in three recycling associations of Bogotá with the aim to understand and determine the situation of recycling from perspective of informal sector in its transition to enter as authorized waste providers. Data used in the analysis are derived from multiple strategies such as literature review, the Bogota’s recycling database, focus group meetings, governmental reports, national laws and regulations and specific interviews with key stakeholders. Results of this study show as the main stakeholders of formal and informal sector of waste management can identify the internal and internal conditions of recycling in Bogotá. Several strategies were designed based on the SWOTs determined, could be useful for Bogotá to advance and promote recycling as a key strategy for integrated sustainable waste management in the city.

Keywords: Bogotá, recycling, solid waste management, SWOT analysis.

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Authors: S. Lecheb, A. Nour, A. Chellil, H. Mechakra, N. Hamad, H. Kebir

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The work involves develops attended by a numerical execution of the eXtend Finite Element Method premises a measurement by the fracture process cracked so many cracked plates an application will be processed for the calculation of the stress intensity factor SIF. In the first we give in statically part the distribution of stress, displacement field and strain of composite plate in two cases uncrack/edge crack, also in dynamical part the first six modes shape. Secondly, we calculate Stress Intensity Factor SIF for different orientation angle θ of central crack with length (2a=0.4mm) in plan strain condition, KI and KII are obtained for mode I and mode II respectively using X-FEM method. Finally from crack inclined involving mixed modes results, the comparison we chose dangerous inclination and the best crack angle when K is minimal.

Keywords: Stress Intensity Factor (SIF), Crack orientation, Glass/Epoxy, natural Frequencies, X-FEM.

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Authors: A. Evans, M. McKinley

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Knowledge management (KM) is generally considered to be a positive process in an organisation, facilitating opportunities to achieve competitive advantage via better quality information handling, compilation of expert know-how and rapid response to fluctuations in the business environment. The KM paradigm as portrayed in the literature informs the processes that can increase intangible assets so that corporate knowledge is preserved. However, in some instances, knowledge management exists in a universe of dynamic tension among the conflicting needs to respect privacy and intellectual property (IP), to guard against data theft, to protect national security and to stay within the laws. While the Knowledge Management literature focuses on the bright side of the paradigm, there is also a different side in which knowledge is distorted, suppressed or misappropriated due to personal or organisational motives (the paradox). This paper describes the ethical paradoxes that occur within the taxonomy and deontology of knowledge management and suggests that recognising both the promises and pitfalls of KM requires wisdom.

Keywords: business ethics, data, knowledge, knowledgemanagement, privacy, protection.

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Authors: V. Azadeh Ranjbar

Abstract:

Rarefied gas flows are often occurred in micro electro mechanical systems and classical CFD could not precisely anticipate the flow and thermal behavior due to the high Knudsen number. Therefore, the heat transfer and the fluid dynamics characteristics of rarefied gas flows in both a two-dimensional simple microchannel and geometry similar to single Knudsen compressor have been investigated with a goal of increasing performance of a actual Knudsen compressor by using a particle simulation method. Thermal transpiration and thermal creep, which are rarefied gas dynamic phenomena, that cause movement of the flow from less to higher temperature is generated by using two different longitude temperature gradients (Linear, Step) along the walls of the flow microchannel. In this study the influence of amount of temperature gradient and governing pressure in various Knudsen numbers and length-to-height ratios have been examined.

Keywords: DSMC, Thermal transpiration, Thermal creep, MEMS, Knudsen Compressor.

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Authors: R. Rezaeipour

Abstract:

One of the key aspects of power quality improvement in power system is the mitigation of voltage sags/swells and flicker. Custom power devices have been known as the best tools for voltage disturbances mitigation as well as reactive power compensation. Dynamic Voltage Restorer (DVR) which is the most efficient and effective modern custom power device can provide the most commercial solution to solve several problems of power quality in distribution networks. This paper deals with analysis and simulation technique of DVR based on instantaneous power theory which is a quick control to detect signals. The main purpose of this work is to remove three important disturbances including voltage sags/swells and flicker. Simulation of the proposed method was carried out on two sample systems by using Matlab software environment and the results of simulation show that the proposed method is able to provide desirable power quality in the presence of wide range of disturbances.

Keywords: DVR, Power quality, Voltage sags, Voltage swells, Flicker.

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Authors: Abhishek Swaroop, Awadhesh Kumar Singh

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The group mutual exclusion (GME) problem is an interesting generalization of the mutual exclusion problem. Several solutions of the GME problem have been proposed for message passing distributed systems. However, none of these solutions is suitable for real time distributed systems. In this paper, we propose a token-based distributed algorithms for the GME problem in soft real time distributed systems. The algorithm uses the concepts of priority queue, dynamic request set and the process state. The algorithm uses first come first serve approach in selecting the next session type between the same priority levels and satisfies the concurrent occupancy property. The algorithm allows all n processors to be inside their CS provided they request for the same session. The performance analysis and correctness proof of the algorithm has also been included in the paper.

Keywords: Concurrency, Group mutual exclusion, Priority, Request set, Token.

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Authors: Jing Zhou, Weiqun Su, Naying Luo, Min Shang, Li Wu

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The coupling of land use system in geographical research is mainly the coupling of pattern and process, which is essentially the human-land coupling, and is an important part of the research and discussion of human-land relationship. Based on the Web of Science database, the paper titles, authors, keywords, and references from 1997-2020 related to land use coupling were used as data sources to explore the research progress of land use coupling. Cite Space bibliometric tool was used for co-occurrence analysis of the issuing country, issuing institution, co-cited author, disciplinary institution, and keywords. The results are shown as follows: (1) From 1997 to 2020, the United States, China, and Germany rank the top, with more than 250 published papers. Although China ranks second in the number of published papers on foreign literature, it has less centrality and less influence. (2) The top 10 institutions (universities) in the number of published papers (more than 300 articles) are mainly from the United States and China, and the University of Chinese Academy of Sciences has the highest output of papers. At the same time, the phenomenon of multi-institutional cooperation has increased in the field of land use coupling research. (3) From 1997 to 2020, land sensitivity research and the impact of climate change on land use patterns are the main directions of land use coupling research. However, in the past five years, scholars have mainly focused on the coupling research methods of land use and the coupling relationship between ecological and environmental factors and land use.

Keywords: Land use coupling, cite space, knowledge graph, visual analysis, research progress.

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.

As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.

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Authors: Somkiat Lerkvaranyu, Yoshikazu Miyanaga

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In this paper, a new technique of signal detection has been proposed for detecting the orthogonal frequency-division multiplexing (OFDM) signal in the presence of nonlinear distortion.There are several advantages of OFDM communications system.However, one of the existing problems is remain considered as the nonlinear distortion generated by high-power-amplifier at the transmitter end due to the large dynamic range of an OFDM signal. The proposed method is the maximum likelihood detection with the symbol estimation. When the training data are available, the neural network has been used to learn the characteristic of received signal and to estimate the new positions of the transmitted symbol which are provided to the maximum likelihood detector. Resulting in the system performance, the nonlinear distortions of a traveling wave tube amplifier with OFDM signal are considered in this paper.Simulation results of the bit-error-rate performance are obtained with 16-QAM OFDM systems.

Keywords: OFDM, TWTA, nonlinear distortion, detection.

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Authors: Inta Volodko, Valentina Koliskina

Abstract:

Linear stability of wake-shear layers in two-phase shallow flows is analyzed in the present paper. Stability analysis is based on two-dimensional shallow water equations. It is assumed that the fluid contains uniformly distributed solid particles. No dynamic interaction between the carrier fluid and particles is expected in the initial moment. Linear stability curves are obtained for different values of the particle loading parameter, the velocity ratio and the velocity deficit. It is shown that the increase in the velocity ratio destabilizes the flow. The particle loading parameter has a stabilizing effect on the flow. The role of the velocity deficit is also destabilizing: the increase of the velocity deficit leads to less stable flow.

Keywords: Linear stability, Shallow flows, Wake-shear flows.

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Authors: Aya Salama

Abstract:

Digital Twin has emerged as a compelling research area, capturing the attention of scholars over the past decade. It finds applications across diverse fields, including smart manufacturing and healthcare, offering significant time and cost savings. Notably, it often intersects with other cutting-edge technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, the concept of a Human Digital Twin (HDT) is still in its infancy and requires further demonstration of its practicality. HDT takes the notion of Digital Twin a step further by extending it to living entities, notably humans, who are vastly different from inanimate physical objects. The primary objective of this research was to create an HDT capable of automating real-time human responses by simulating human behavior. To achieve this, the study delved into various areas, including clustering, supervised classification, topic extraction, and sentiment analysis. The paper successfully demonstrated the feasibility of HDT for generating personalized responses in social messaging applications. Notably, the proposed approach achieved an overall accuracy of 63%, a highly promising result that could pave the way for further exploration of the HDT concept. The methodology employed Random Forest for clustering the question database and matching new questions, while K-nearest neighbor was utilized for sentiment analysis.

Keywords: Human Digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification and clustering.

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Authors: Ion Smeureanu, Marian Dardala, Adriana Reveiu

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The new programming technologies allow for the creation of components which can be automatically or manually assembled to reach a new experience in knowledge understanding and mastering or in getting skills for a specific knowledge area. The project proposes an interactive framework that permits the creation, combination and utilization of components that are specific to mathematical training in high schools. The main framework-s objectives are: • authoring lessons by the teacher or the students; all they need are simple operating skills for Equation Editor (or something similar, or Latex); the rest are just drag & drop operations, inserting data into a grid, or navigating through menus • allowing sonorous presentations of mathematical texts and solving hints (easier understood by the students) • offering graphical representations of a mathematical function edited in Equation • storing of learning objects in a database • storing of predefined lessons (efficient for expressions and commands, the rest being calculations; allows a high compression) • viewing and/or modifying predefined lessons, according to the curricula The whole thing is focused on a mathematical expressions minicompiler, storing the code that will be later used for different purposes (tables, graphics, and optimisations). Programming technologies used. A Visual C# .NET implementation is proposed. New and innovative digital learning objects for mathematics will be developed; they are capable to interpret, contextualize and react depending on the architecture where they are assembled.

Keywords: Adaptor, automatic assembly learning component and user control.

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Authors: Sahba Sadir, M. R. A. Kadir, A. Öchsner, M. N. Harun

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Scaffolds play a key role in tissue engineering and can be produced in many different ways depending on the applications and the materials used. Most researchers used an experimental trialand- error approach into new biomaterials but computer simulation applied to tissue engineering can offer a more exhaustive approach to test and screen out biomaterials. This paper develops the model of scaffolds and Computational Fluid Dynamics that show the value of computer simulations in determining the influence of the geometrical scaffold parameter porosity, pore size and shape on the permeability of scaffolds, magnitude of velocity, drop pressure, shear stress distribution and level and the proper design of the geometry of the scaffold. This creates a need for more advanced studies that include aspects of dynamic conditions of a micro fluid passing through the scaffold were characterized for tissue engineering applications and differentiation of tissues within scaffolds.

Keywords: Scaffold engineering, Tissue engineering, Cellularstructure, Biomaterial, Computational fluid dynamics.

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Authors: Monis Akhlaq, M Noman Jafri, Muzammil A Khan, Baber Aslam

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The Ad Hoc on demand distance vector (AODV) routing protocol is designed for mobile ad hoc networks (MANETs). AODV offers quick adaptation to dynamic link conditions; it is characterized by low memory overhead and low network utilization. The security issues related to the protocol remain challenging for the wireless network designers. Numerous schemes have been proposed for establishing secure communication between end users, these schemes identify that the secure operation of AODV is a bi tier task (routing and secure exchange of information at separate levels). Our endeavor in this paper would focus on achieving the routing and secure data exchange in a single step. This will facilitate the user nodes to perform routing, mutual authentications, generation and secure exchange of session key in one step thus ensuring confidentiality, integrity and authentication of data exchange in a more suitable way.

Keywords: AODV, key management, security, wirelessnetworks.

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Authors: Y. Harold Robinson, M. Rajaram

Abstract:

The Trustworthy link failure recovery algorithm is introduced in this paper, to provide the forwarding continuity even with compound link failures. The ephemeral failures are common in IP networks and it also has some proposals based on local rerouting. To ensure forwarding continuity, we are introducing the compound link failure recovery algorithm, even with compound link failures. For forwarding the information, each packet carries a blacklist, which is a min set of failed links encountered along its path, and the next hop is chosen by excluding the blacklisted links. Our proposed method describes how it can be applied to ensure forwarding to all reachable destinations in case of any two or more link or node failures in the network. After simulating with NS2 contains lot of samples proved that the proposed protocol achieves exceptional concert even under elevated node mobility using Trustworthy link Failure Recovery Algorithm.

Keywords: Wireless Sensor Networks, Predistribution Scheme, Cryptographic Techniques.

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Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

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Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: Air pollution, routing protocol, network simulator, rescheduling.

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Authors: Mu-Jen Young, Cheng-Yen Wu, Wen-Yuan Hsieh

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Iron oxide nanoparticle was synthesized by reactive-precipitation method followed by high speed centrifuge and phase transfer in order to stabilized nanoparticles in the solvent. Particle size of SPIO was 8.2 nm by SEM, and the hydraulic radius was 17.5 nm by dynamic light scattering method. Coercivity and saturated magnetism were determined by VSM (vibrating sample magnetometer), coercivity of nanoparticle was lower than 10 Hc, and the saturated magnetism was higher than 65 emu/g. Stabilized SPIO was then transferred to aqueous phase by reacted with excess amount of poly (ethylene glycol) (PEG) silane. After filtration and dialysis, the SPIO T2 contrast agent was ready to use. The hydraulic radius of final product was about 70~100 nm, the relaxation rates R2 (1/T2) measured by magnetic resonance imaging (MRI) was larger than 200(sec-1).

Keywords: Contrast Agent, Iron Oxide Nanoparticle, Magnetic Resonance Imaging, Nanoparticle Stabilization

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Authors: H. Shayeghi, A. Safari, H. A. Shayanfar

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In this paper, multiobjective design of multi-machine Power System Stabilizers (PSSs) using Particle Swarm Optimization (PSO) is presented. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electro-mechanical modes of all machines to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The PSSs parameters tuning problem is converted to an optimization problem which is solved by PSO with the eigenvalue-based multiobjective function. The proposed PSO based PSSs is tested on a multimachine power system under different operating conditions and disturbances through eigenvalue analysis and some performance indices to illustrate its robust performance.

Keywords: PSS Design, Particle Swarm Optimization, Dynamic Stability, Multiobjective Optimization.

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Authors: Andrea Bellucci, Martina Tofi

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The aim of paper is to analyze business models of bancassurance in Italy for life business. The life insurance business is very developed in the Italian market and banks branches have 80% of the market share. Given its maturity, the life insurance market needs to consolidate its organizational form to allow for the development of non-life business, which nowadays collects few premiums but represents a great opportunity to enlarge the market share of bancassurance using its strength in the distribution channel while the market share of independent agents is decreasing. Starting with the main business model of bancassurance for life business, this paper will analyze the performances of life companies in the Italian market by balance sheet indicators and by main discriminant variables of business models. The study will observe trends from 2013 to 2015 for the Italian market by exploiting a database managed by Associazione Nazionale delle Imprese di Assicurazione (ANIA). The applied approach is based on a bottom-up analysis starting with variables and indicators to define business models’ classification. The statistical classification algorithm proposed by Ward is employed to design business models’ profiles. Results from the analysis will be a representation of the main business models built by their profile related to indicators. In that way, an unsupervised analysis is developed that has the limit of its judgmental dimension based on research opinion, but it is possible to obtain a design of effective business models.

Keywords: Balance sheet indicators, Bancassurance, business models, ward algorithm.

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Authors: Fatemeh Behjati Ardakani, Fatemeh Khademian, Abbas Nowzari Dalini, Reza Ebrahimpour

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Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this paper we introduce a new low resolution face recognition system based on mixture of expert neural networks. In order to produce the low resolution input images we down-sampled the 48 × 48 ORL images to 12 × 12 ones using the nearest neighbor interpolation method and after that applying the bicubic interpolation method yields enhanced images which is given to the Principal Component Analysis feature extractor system. Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in low resolution face recognition that is the recognition rate of 100% for the training set and 96.5% for the test set.

Keywords: Low resolution face recognition, Multilayered neuralnetwork, Mixture of experts neural network, Principal componentanalysis, Bicubic interpolation, Nearest neighbor interpolation.

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Authors: Han-Soo Kim, Jae-Gyun Ahn, Hyo-Seung Ahn

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Though nonlinear dynamic analysis using a specialized hydro-code such as AUTODYN is accurate and useful tool for progressive collapse assessment of a multi-story building subjected to blast load, it takes too much time to be applied to a practical simulation of progressive collapse of a tall building. In this paper, blast analysis of a RC frame structure using a simplified model with Reinforcement Contact technique provided in Ansys Workbench was introduced and investigated on its accuracy. Even though the simplified model has a fraction of elements of the detailed model, the simplified model with this modeling technique shows similar structural behavior under the blast load to the detailed model. The proposed modeling method can be effectively applied to blast loading progressive collapse analysis of a RC frame structure.

Keywords: Autodyn, Blast Load, Progressive Collapse, Reinforcement Contact.

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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Authors: Kasthurirangan Gopalakrishnan, Marshall R. Thompson, Anshu Manik

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This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data. The HWD test is one of the most widely used tests for routinely assessing the structural integrity of airport pavements in a non-destructive manner. The elastic moduli of the individual pavement layers backcalculated from the HWD deflection profiles are effective indicators of layer condition and are used for estimating the pavement remaining life. HWD tests were periodically conducted at the Federal Aviation Administration-s (FAA-s) National Airport Pavement Test Facility (NAPTF) to monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test gear trafficking on the structural condition of flexible pavement sections. In this study, a multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD backcalculation function. The synthetic database generated using an advanced non-linear pavement finite-element program was used to train the ANN to overcome the limitations associated with conventional pavement moduli backcalculation. The changes in ANN-based backcalculated pavement moduli with trafficking were used to compare the relative severity effects of the aircraft landing gears on the NAPTF test pavements.

Keywords: Airfield pavements, ANN, backcalculation, newgeneration aircraft

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Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

Abstract:

Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: Multi-temporal satellite image, urban growth, Non-stationarity, stochastic modeling.

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Authors: Ming-Hui Lee, Iau-Teh Wang

Abstract:

The innovative fuzzy estimator is used to estimate the ground motion acceleration of the retaining structure in this study. The Kalman filter without the input term and the fuzzy weighting recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the fuzzy weighting recursive least square estimator to estimate the acceleration input over time. The excellent performance of this estimator is demonstrated by comparing it with the use of difference weighting function, the distinct levels of the measurement noise covariance and the initial process noise covariance. The availability and the precision of the proposed method proposed in this study can be verified by comparing the actual value and the one obtained by numerical simulation.

Keywords: Earthquake, Fuzzy Estimator, Kalman Filter, Recursive Least Square Estimator.

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Authors: Rani Astya, S.C. Sharma

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The wireless adhoc network is comprised of wireless node which can move freely and are connected among themselves without central infrastructure. Due to the limited transmission range of wireless interfaces, in most cases communication has to be relayed over intermediate nodes. Thus, in such multihop network each node (also called router) is independent, self-reliant and capable to route the messages over the dynamic network topology. Various protocols are reported in this field and it is very difficult to decide the best one. A key issue in deciding which type of routing protocol is best for adhoc networks is the communication overhead incurred by the protocol. In this paper STAR a table driven and DSR on demand protocols based on IEEE 802.11 are analyzed for their performance on different performance measuring metrics versus varying traffic CBR load using QualNet 5.0.2 network simulator.

Keywords: Adhoc networks, wireless networks, CBR, routingprotocols, route discovery, simulation, performance evaluation, MAC, IEEE 802.11, STAR, DSR

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Authors: Nawfal A. Mehdi, Ali Mamat, Hamidah Ibrahim, Shamala K. Syrmabn

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The increase on the demand of IT resources diverts the enterprises to use the cloud as a cheap and scalable solution. Cloud computing promises achieved by using the virtual machine as a basic unite of computation. However, the virtual machine pre-defined settings might be not enough to handle jobs QoS requirements. This paper addresses the problem of mapping jobs have critical start deadlines to virtual machines that have predefined specifications. These virtual machines hosted by physical machines and shared a fixed amount of bandwidth. This paper proposed an algorithm that uses the idle virtual machines bandwidth to increase the quote of other virtual machines nominated as executors to urgent jobs. An algorithm with empirical study have been given to evaluate the impact of the proposed model on impatient jobs. The results show the importance of dynamic bandwidth allocation in virtualized environment and its affect on throughput metric.

Keywords: Insufficient bandwidth, virtual machine, cloudprovider, impatient jobs.

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Authors: Ren-Jy Ben, Jo-Chi Jao, Chiu-Ya Liao, Ya-Ru Tsai, Lain-Chyr Hwang, Po-Chou Chen

Abstract:

Cancer is still one of the serious diseases threatening the lives of human beings. How to have an early diagnosis and effective treatment for tumors is a very important issue. The animal carcinoma model can provide a simulation tool for the studies of pathogenesis, biological characteristics, and therapeutic effects. Recently, drug delivery systems have been rapidly developed to effectively improve the therapeutic effects. Liposome plays an increasingly important role in clinical diagnosis and therapy for delivering a pharmaceutic or contrast agent to the targeted sites. Liposome can be absorbed and excreted by the human body, and is well known that no harm to the human body. This study aimed to compare the therapeutic effects between encapsulated (doxorubicin liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox) anti-tumor drugs using magnetic resonance imaging (MRI). Twenty-four New Zealand rabbits implanted with VX2 carcinoma at left thighs were classified into three groups: control group (untreated), Dox-treated group, and LipoDox-treated group, 8 rabbits for each group. MRI scans were performed three days after tumor implantation. A 1.5T GE Signa HDxt whole body MRI scanner with a high resolution knee coil was used in this study. After a 3-plane localizer scan was performed, three-dimensional (3D) fast spin echo (FSE) T2-weighted Images (T2WI) was used for tumor volumetric quantification. Afterwards, two-dimensional (2D) spoiled gradient recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was used for tumor perfusion evaluation. DCE-MRI was designed to acquire four baseline images, followed by contrast agent Gd-DOTA injection through the ear vein of rabbit. A series of 32 images were acquired to observe the signals change over time in the tumor and muscle. The MRI scanning was scheduled on a weekly basis for a period of four weeks to observe the tumor progression longitudinally. The Dox and LipoDox treatments were prescribed 3 times in the first week immediately after the first MRI scan; i.e. 3 days after VX2 tumor implantation. ImageJ was used to quantitate tumor volume and time course signal enhancement on DCE images. The changes of tumor size showed that the growth of VX2 tumors was effectively inhibited for both LipoDox-treated and Dox-treated groups. Furthermore, the tumor volume of LipoDox-treated group was significantly lower than that of Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is significantly lower than that of the other two groups, which implies that targeted therapeutic drug remained in the tumor tissue. This study provides a radiation-free and non-invasive MRI method for therapeutic monitoring of targeted liposome on an animal tumor model.

Keywords: Doxorubicin, dynamic contrast-enhanced MRI, lipodox, magnetic resonance imaging, VX2 tumor model.

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Authors: Ming-Hui Lee, Tsung-Chien Chen, Yuh-Shiou Tai

Abstract:

The intelligent fuzzy input estimator is used to estimate the input force of the rigid bar structural system in this study. The fuzzy Kalman filter without the input term and the fuzzy weighting recursive least square estimator are two main portions of this method. The practicability and accuracy of the proposed method were verified with numerical simulations from which the input forces of a rigid bar structural system were estimated from the output responses. In order to examine the accuracy of the proposed method, a rigid bar structural system is subjected to periodic sinusoidal dynamic loading. The excellent performance of this estimator is demonstrated by comparing it with the use of difference weighting function and improper the initial process noise covariance. The estimated results have a good agreement with the true values in all cases tested.

Keywords: Fuzzy Input Estimator, Kalman Filter, RecursiveLeast Square Estimator.

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