Search results for: seismic response analysis.

Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially the fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, ma-chine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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Authors: Musammat F. Nahar, Anna Roujeinikova

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Bacterial molecular chaperone DnaK plays an essential role in protein folding, stress response and transmembrane targeting of proteins. DnaKs from many bacterial species, including Escherichia coli, Salmonella typhimurium and Haemophilus infleunzae are the molecular targets for the insect-derived antimicrobial peptide pyrrhocoricin. Pyrrhocoricin-like peptides bind in the substrate recognition tunnel. Despite the high degree of crossspecies sequence conservation in the substrate-binding tunnel, some bacteria are not sensitive to pyrrhocoricin. This work addresses the molecular mechanism of resistance of Helicobacter pylori DnaK to pyrrhocoricin. Homology modelling, structural and sequence analysis identify a single aminoacid substitution at the interface between the lid and the β-sandwich subdomains of the DnaK substrate-binding domain as the major determinant for its resistance.

Keywords: Helicobacter pylori, molecular chaperone DnaK, pyrrhocoricin, structural biology.

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Authors: Amir Ayazi, Hamde Ahmadi, Soheil Shafaei

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Composite steel shear wall is a lateral load resisting system which consists of a steel plate with concrete wall attached to one or both sides to prevent it from elastic buckling. The composite behavior is ensured by utilizing high-strength bolts. This paper investigates the effect of distance between bolts, and for this purpose 14 one-story one-bay specimens with various bolts spacing were modeled by finite element code which is developed by the authors. To verify the model, numerical results were compared with a valid experiment which illustrate proper agreement. Results depict increasing the distance between bolts would improve the seismic ever, this increase must be limited, because of large distances will cause widespread buckling of the steel plate in free subpanels between bolts and would result in no improvement. By comparing the results in elastic region, it was observed initial stiffness is not affected by changing the distance.

Keywords: Composite steel shear wall, bolt, buckling, finite element.

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Authors: Daniel Y. Abebe, Sijeong Jeong, Jaehyouk Choi

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The use of eccentrically braced frame (EBF) is increasing day by day as EBF possesses high elastic stiffness, stable inelastic response under cyclic lateral loading, and excellent ductility and energy dissipation capacity. The ductility and energy dissipation capacity of EBF depends on the active link beams. Recently, there are two types EBFs; these are conventional EBFs and EBFs with replaceable links. The conventional EBF has a disadvantage during maintenance in post-earthquake. The concept of removable active link beam in EBF is developed to overcome the limitation of the conventional EBF in post-earthquake. In this study, a replaceable link with reduced web section is introduced and design equations are suggested. In addition, nonlinear finite element analysis was conducted in order to evaluate the proposed links.

Keywords: EBFs, replaceable link, earthquake disaster, reduced section.

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Authors: S. C. Kattimani

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This article deals with the analysis of active constrained layer damping (ACLD) of smart multiferroic or magneto-electro-elastic doubly curved shells. The kinematics of deformations of the multiferroic doubly curved shell is described by a layer-wise shear deformation theory. A three-dimensional finite element model of multiferroic shells has been developed taking into account the electro-elastic and magneto-elastic couplings. A simple velocity feedback control law is employed to incorporate the active damping. Influence of layer stacking sequence and boundary conditions on the response of the multiferroic doubly curved shell has been studied. In addition, for the different orientation of the fibers of the constraining layer, the performance of the ACLD treatment has been studied.

Keywords: Active constrained layer damping, doubly curved shells, magneto-electro-elastic, multiferroic composite, smart structures.

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Authors: N. Umasuthan, S. D. N. K. Bathige, W. S. Thulasitha, I. Whang, J. Lee

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The MyD88 is an evolutionarily conserved host-expressed adaptor protein that is essential for proper TLR/ IL1R immune-response signaling. A previously identified complete cDNA (1626 bp) of OfMyD88 comprised an ORF of 867 bp encoding a protein of 288 amino acids (32.9 kDa). The gDNA (3761 bp) of OfMyD88 revealed a quinquepartite genome organization composed of 5 exons (with the sizes of 310, 132, 178, 92 and 155 bp) separated by 4 introns. All the introns displayed splice signals consistent with the consensus GT/AG rule. A bipartite domain structure with two domains namely death domain (24-103) coded by 1^st exon, and TIR domain (151-288) coded by last 3 exons were identified through in silico analysis. Moreover, homology modeling of these two domains revealed a similar quaternary folding nature between human and rock bream homologs. A comprehensive comparison of vertebrate MyD88 genes showed that they possess a 5-exonic structure.In this structure, the last three exons were strongly conserved, and this suggests that a rigid structure has been maintained during vertebrate evolution.A cluster of TATA box-like sequences were found 0.25 kb upstream of cDNA starting position. In addition, putative 5'-flanking region of OfMyD88 was predicted to have TFBS implicated with TLR signaling, including copies of NFkB1, APRF/ STAT3, Sp1, IRF1 and 2 and Stat1/2. Using qPCR technique, a ubiquitous mRNA expression was detected in liver and blood. Furthermore, a significantly up-regulated transcriptional expression of OfMyD88 was detected in head kidney (12-24 h; >2-fold), spleen (6 h; 1.5-fold), liver (3 h; 1.9-fold) and intestine (24 h; ~2-fold) post-Fla challenge. These data suggest a crucial role for MyD88 in antibacterial immunity of teleosts.

Keywords: MyD88, Innate immunity, Flagellin, Genomic analysis.

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Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

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Fabric textures are very common in our daily life. However, the representation of fabric textures has never been explored from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. We choose 140 types of fabrics to get the classical fabric textures as materials. Experiment results indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: Fabric Texture, Receptive Filed, Simple Cell, Spare Coding.

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Authors: Madihah Mohd Saudi, Zul Hilmi Abdullah

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This research paper presents a framework on how to build up malware dataset.Many researchers took longer time to clean the dataset from any noise or to transform the dataset into a format that can be used straight away for testing. Therefore, this research is proposing a framework to help researchers to speed up the malware dataset cleaningprocesses which later can be used for testing. It is believed, an efficient malware dataset cleaning processes, can improved the quality of the data, thus help to improve the accuracy and the efficiency of the subsequent analysis. Apart from that, an in-depth understanding of the malware taxonomy is also important prior and during the dataset cleaning processes. A new Trojan classification has been proposed to complement this framework.This experiment has been conducted in a controlled lab environment and using the dataset from VxHeavens dataset. This framework is built based on the integration of static and dynamic analyses, incident response method and knowledge database discovery (KDD) processes.This framework can be used as the basis guideline for malware researchers in building malware dataset.

Keywords: Dataset, knowledge database discovery (KDD), malware, static and dynamic analyses.

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Authors: Israel Núñez-Hernández, Peter C. Breedveld, Paul B. T. Weustink, Gilberto Gonzalez-A

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This paper presents the use of phasor bond graphs to obtain the steady-state behavior of a synchronous generator. The phasor bond graph elements are built using 2D multibonds, which represent the real and imaginary part of the phasor. The dynamic bond graph model of a salient-pole synchronous generator is showed, and verified viz. a sudden short-circuit test. The reduction of the dynamic model into a phasor representation is described. The previous test is executed on the phasor bond graph model, and its steady-state values are compared with the dynamic response. Besides, the widely used power (torque)-angle curves are obtained by means of the phasor bond graph model, to test the usefulness of this model.

Keywords: Bond graphs, complex power, phasors, synchronous generator, short-circuit, open-circuit, power-angle curve.

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Authors: Hyeyoung Cho, Sungho Kim, SangDong Lee

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I/O workload is a critical and important factor to analyze I/O pattern and file system performance. However tracing I/O operations on the fly distributed parallel file system is non-trivial due to collection overhead and a large volume of data. In this paper, we design and implement a parallel file system logging method for high performance computing using shared memory-based multi-layer scheme. It minimizes the overhead with reduced logging operation response time and provides efficient post-processing scheme through shared memory. Separated logging server can collect sequential logs from multiple clients in a cluster through packet communication. Implementation and evaluation result shows low overhead and high scalability of this architecture for high performance parallel logging analysis.

Keywords: I/O workload, PVFS, I/O Trace.

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Authors: Onesmus Muvengei, John Kihiu, Bernard Ikua

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This paper numerically investigates the effects of input speed on the overall dynamic characteristics of a multi-body system with differently located revolute clearance joints without friction. A typical planar slider-crank mechanism is used as a demonstration case in which the effects of the input speed on the dynamic performance of the mechanism with a revolute clearance joint between the crank and connecting rod, and between the connecting rod and slider are separately investigated with comprehensive observations numerically presented. It is observed that, changing the driving speed of a multibody system makes the behavior of the system to change from either periodic to chaotic, or chaotic to periodic depending on which joint has clearance. The location of the clearance revolute joint and the operating speed of a multi-body system play a crucial role in predicting accurately the dynamic responses of the system. Therefore the dynamic behavior of one clearance revolute joint cannot be used as a general case for a mechanical system.

Keywords: Chaotic behavior, Contact-impact forces, Dynamic response, Multi-body mechanical system, Periodic behavior, Poincare maps, Quasi-periodic behavior, Revolute clearance joint

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.

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Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz

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The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

Keywords: Data clustering, medical data, principal components analysis.

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact loads and some hard-to-obtain system parameters is crucial for analysis, validation, and evaluation activities in the engineering field. This paper proposes a method based on 1D-CNN to identify impact loads and partial system parameters from the measured responses. To this end, forward computations are conducted to provide datasets consisting of triples (parameter θ, input u, output y). Two neural networks are then trained: one to learn the mapping from output y to input u and another to learn the mapping from input and output (u, y) to parameter θ. Subsequently, by feeding the measured output response into the trained neural networks, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameter.

Keywords: Convolutional neural network, impact load identification, system parameter identification, inverse problem.

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Authors: Abdel Aziz, Hadia H.

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Since the 1980s, banks and financial service institutions have been running in an endless race of innovation to cope with the advancing technology, the fierce competition, and the more sophisticated and demanding customers. In order to guide their innovation efforts, several researches were conducted to identify the success and failure factors of new financial services. These mainly included organizational factors, marketplace factors and new service development process factors. They almost all emphasized the importance of customer and market orientation as a response to the highly perceptual and intangible characteristics of financial services. However, they deemphasized the critical characteristics of high involvement of risk and close correlation with the economic conditions, a factor that heavily contributed to the Global financial Crisis of 2008. This paper reviews the success and failure factors of new financial services. It then adds new perspectives emerging from the analysis of the role of innovation in the global financial crisis.

Keywords: Financial innovation, global financial crisis, lessons learned from global financial crisis, success factors in financial innovation.

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Authors: Salim Cerig, Fatime Geyikoglu, Murat Bakir, Suat Colak, Merve Sonmez, Kubra Koc

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Cisplatin (CIS) is one of the most effective an anticancer drug and also toxic to cells by activating oxidative stress. Oleuropein (OLE) has key role against oxidative stress in mammalian cells, but the role of this antioxidant in the toxicity of CIS remains unknown. The aim of the present study was to investigate the efficacy of OLE on CIS-induced liver damages in male rats. With this aim, male Sprague Dawley rats were randomly assigned to one of eight groups: Control group; the group treated with 7 mg/kg/day CIS; the groups treated with 50, 100 and 200 mg/kg/day OLE (i.p.); and the groups treated with OLE for three days starting at 24 h following CIS injection. After 4 days of injections, serum was provided to assess the blood AST, ALT and LDH values. The liver tissues were removed for histological, biochemical (TAC, TOS and MDA) and genotoxic evaluations. In the CIS treated group, the whole liver tissue showed significant histological changes. Also, CIS significantly increased both the incidence of oxidative stress and the induction of 8-hydroxy-deoxyguanosine (8-OH-dG). Moreover, the rats taking CIS have abnormal results on liver function tests. However, these parameters reached to the normal range after administration of OLE for 3 days. Finally, OLE demonstrated an acceptable high potential and was effective in attenuating CIS-induced liver injury. In this trial, the 200 mg/kg dose of OLE firstly appeared to induce the most optimal protective response.

Keywords: Antioxidant response, cisplatin, histology, liver, oleuropein, 8-OhdG.

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Authors: P. Bogas

Abstract:

As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences resulted from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the students' response can be described as: students who reinforce the initial deep approach, students who maintain the initial deep approach level and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to a possible adoption of deep approaches to learning, since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding to the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: Experiential learning, higher education, marketing, mixed methods, reflective thinking.

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Authors: Dana M. Ragab, Jasim A. Ghaeb

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The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: Three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality.

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.

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Authors: Peter Ndichu Muriuki

Abstract:

The 9/11 suicide attacks in New York, Washington, D.C., and Pennsylvania, triggered a number of security responses both in the United States of America and other Countries in the World. Kenya, which is an ally and a close partner to North America and Europe, was not left behind. While many states had been parties to numerous terrorism conventions, their response in implementing them had been slow and needed this catalyst. This special case offered a window of opportunity for many “security conscious" regimes in cementing their legal-criminological and political security apparatus. At the international level, the 9/11 case led to the hasty adoption of Security Council resolution 1373 in 2001, which called upon states to adopt wide-ranging and comprehensive steps and strategies to combat international terrorism and to become parties to the relevant international conventions and protocols relating to terrorism. Since then, Kenya has responded with speed in devising social-legal-criminological-political actions.

Keywords: Justice, Policing, Security, Terrorism

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Authors: C. S. Tsai, Yung-Chang Lin

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In order to upgrade the seismic resistibility of structures and enhance the functionality of an isolator, a new base isolator called the multiple trench friction pendulum system (MTFPS) is proposed in this study. The proposed MTFPS isolator is composed of a trench concave surface and several intermediate sliding plates in two orthogonal directions. Mathematical formulations have been derived to examine the characteristics of the proposed MTFPS isolator possessing multiple intermediate sliding plates. By means of mathematical formulations, it can be inferred that the natural period and damping effect of the MTFPS isolator with several intermediate sliding plates can be altered continually and controllably during earthquakes. Furthermore, results obtained from shaking table tests demonstrate that the proposed isolator provides good protection to structures for prevention of damage from strong earthquakes.

Keywords: Friction Pendulum System, Multiple Friction Pendulum System, Base Isolation, Earthquake Engineering

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Authors: Anjali Haloi, Debabrata Das

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Silver nanoparticles inhibit a wide variety of microorganisms. The mechanism of inhibition is not entirely known although it is recognized to be concentration dependent and associated with the disruption of membrane permeability. Data on differential gene expression as a response to nanoparticles could provide insights into the mechanism of this inhibitory effect. Silver nanoparticles were synthesized in yeast growth media using a modification of the Creighton method and characterized with UV-Vis spectrophotometry, transmission electron microscopy (TEM), and X-ray diffraction (XRD). In yeasts grown in the presence of silver nanoparticles, we observed that at concentrations below the minimum inhibitory concentration (MIC) of 48.51 µg/ml, the total RNA content was steady while the cellular protein content declined rapidly. The analysis of the expression levels of KRR1 and PWP2, two important genes involved in rRNA maturation in yeasts, showed up to 258 and 42-fold decreases, respectively, compared to that of control samples. Whether silver nanoparticles have an adverse effect on ribosome assembly and function could be an area of further investigation.

Keywords: Ag NP, yeast, qRT-PCR, KRR1, PWP2.

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Authors: A. M. Azad, M. Alam, C. M. Hussain

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In this paper, we have presented the effect of varying time-delays on performance and stability in the single-channel multirate sampled-data system in hard real-time (RT-Linux) environment. The sampling task require response time that might exceed the capacity of RT-Linux. So a straight implementation with RT-Linux is not feasible, because of the latency of the systems and hence, sampling period should be less to handle this task. The best sampling rate is chosen for the sampled-data system, which is the slowest rate meets all performance requirements. RT-Linux is consistent with its specifications and the resolution of the real-time is considered 0.01 seconds to achieve an efficient result. The test results of our laboratory experiment shows that the multi-rate control technique in hard real-time operating system (RTOS) can improve the stability problem caused by the random access delays and asynchronization.

Keywords: Multi-rate, PID, RT-Linux, Sampled-data, Servo.

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Authors: Shuenn-Yih Chang, Chiu-Li Huang

Abstract:

Three structure-dependent integration methods have been developed for solving equations of motion, which are second-order ordinary differential equations, for structural dynamics and earthquake engineering applications. Although they generally have the same numerical properties, such as explicit formulation, unconditional stability and second-order accuracy, a different performance is found in solving the free vibration response to either linear elastic or nonlinear systems with high frequency modes. The root cause of this different performance in the free vibration responses is analytically explored herein. As a result, it is verified that a weak instability is responsible for the different performance of the integration methods. In general, a weak instability will result in an inaccurate solution or even numerical instability in the free vibration responses of high frequency modes. As a result, a weak instability must be prohibited for time integration methods.

Keywords: Dynamic analysis, high frequency, integration method, overshoot, weak instability.

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Authors: R. A. Temah, L. A. Nkengla-Asi

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Planning for future disasters sets the stage for a variety of activities that may trigger multiple recurring operations and expose the community to opportunities to minimize risks. Local communities are increasingly embracing the necessity for planning based on local risks, but are also significantly challenged to effectively plan and response to disasters. This research examines basic risk-based disaster planning model and compares it with advanced risk-based planning that introduces the identification and alignment of varieties of local capabilities within and out of the local community that can be pivotal to facilitate the management of local risks and cascading effects prior to a disaster. A critical review shows that the identification and alignment of capabilities can potentially enhance risk-based disaster planning. A tailored holistic approach to risk based disaster planning is pivotal to enhance collective action and a reduction in disaster collective cost.

Keywords: Capabilities, disaster planning, hazards, local community, risk-based.

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Authors: Sathans, A. Swarup

Abstract:

This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.

Keywords: Automatic generation control, ANFIS, LQR, Hybrid neuro fuzzy controller

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Authors: M. Ghanbari, S. Hossainpour, G. Rezazadeh

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In this paper, longitudinal vibration of a micro-beam in micro-scale fluid media has been investigated. The proposed mathematical model for this study is made up of a micro-beam and a micro-plate at its free end. An AC voltage is applied to the pair of piezoelectric layers on the upper and lower surfaces of the micro-beam in order to actuate it longitudinally. The whole structure is bounded between two fixed plates on its upper and lower surfaces. The micro-gap between the structure and the fixed plates is filled with fluid. Fluids behave differently in micro-scale than macro, so the fluid field in the gap has been modeled based on micro-polar theory. The coupled governing equations of motion of the micro-beam and the micro-scale fluid field have been derived. Due to having non-homogenous boundary conditions, derived equations have been transformed to an enhanced form with homogenous boundary conditions. Using Galerkin-based reduced order model, the enhanced equations have been discretized over the beam and fluid domains and solve simultaneously in order to obtain force response of the micro-beam. Effects of micro-polar parameters of the fluid as characteristic length scale, coupling parameter and surface parameter on the response of the micro-beam have been studied.

Keywords: Micro-polar theory, Galerkin method, MEMS, micro-fluid.

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Authors: S. Mezghani, E. Perrin, J. L Bodnar, J. Marthe, B. Cauwe, V. Vrabie

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Non contact evaluation of the thickness of paint coatings can be attempted by different destructive and nondestructive methods such as cross-section microscopy, gravimetric mass measurement, magnetic gauges, Eddy current, ultrasound or terahertz. Infrared thermography is a nondestructive and non-invasive method that can be envisaged as a useful tool to measure the surface thickness variations by analyzing the temperature response. In this paper, the thermal quadrupole method for two layered samples heated up with a pulsed excitation is firstly used. By analyzing the thermal responses as a function of thermal properties and thicknesses of both layers, optimal parameters for the excitation source can be identified. Simulations show that a pulsed excitation with duration of ten milliseconds allows obtaining a substrate-independent thermal response. Based on this result, an experimental setup consisting of a near-infrared laser diode and an Infrared camera was next used to evaluate the variation of paint coating thickness between 60 μm and 130 μm on two samples. Results show that the parameters extracted for thermal images are correlated with the estimated thicknesses by the Eddy current methods. The laser pulsed thermography is thus an interesting alternative nondestructive method that can be moreover used for nonconductive substrates.

Keywords: Nondestructive, paint coating, thickness, infrared thermography, laser, heterogeneity.

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Authors: Ho-Hyun Park, Woosik Kim, Miae Woo

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It is expected that ubiquitous era will come soon. A ubiquitous environment has features like peer-to-peer and nomadic environments. Such features can be represented by peer-to-peer systems and mobile ad-hoc networks (MANETs). The features of P2P systems and MANETs are similar, appealing for implementing P2P systems in MANET environment. It has been shown that, however, the performance of the P2P systems designed for wired networks do not perform satisfactorily in mobile ad-hoc environment. Subsequently, this paper proposes a method to improve P2P performance using cross-layer design and the goodness of a node as a peer. The proposed method uses routing metric as well as P2P metric to choose favorable peers to connect. It also utilizes proactive approach for distributing peer information. According to the simulation results, the proposed method provides higher query success rate, shorter query response time and less energy consumption by constructing an efficient overlay network.

Keywords: Ad-hoc Networks, Cross-layer, Peer-to-Peer, Performance Analysis.

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Authors: M. F. Yilmaz, B. Ö. Çağlayan

Abstract:

Fragility curve is an effective common used tool to determine the earthquake performance of structural and nonstructural components. Also, it is used to determine the nonlinear behavior of bridges. There are many historical bridges in the Turkish railway network; the earthquake performances of these bridges are needed to be investigated. To derive fragility curve Intensity measures (IMs) and Engineering demand parameters (EDP) are needed to be determined. And the relation between IMs and EDP are needed to be derived. In this study, a typical simply supported steel girder riveted railway bridge is studied. Fragility curves of this bridge are derived by two parameters lognormal distribution. Time history analyses are done for selected 60 real earthquake data to determine the relation between IMs and EDP. Moreover, efficiency, practicality, and sufficiency of three different IMs are discussed. PGA, Sa(0.2s) and Sa(1s), the most common used IMs parameters for fragility curve in the literature, are taken into consideration in terms of efficiency, practicality and sufficiency.

Keywords: Railway bridges, earthquake performance, fragility analyses, selection of intensity measures.

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