Search results for: Data envelopment analysis

Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.

Keywords: Aggregation, Packet Merging, Query Processing.

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Authors: Imran Khan, Shujaat Ali Khan Tanoli, Nandana Rajatheva

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This paper presents an analysis on the capacity and performance of MIMO-OFDM systems. The work is focused on the capacity of MIMO-OFDM systems over rician fading channel, in the case of the channel being known at the receiver only, which is more practical case of the channel. Simple expression for capacity is derived for the case of correlated rician fading. The performance of some MIMO-OFDM implementations with rician fading model is presented using an Alamouti coding scheme and Simulation results are obtained for both capacity and performance analysis.

Keywords: MIMO, OFDM, rician distribution, space time blockcodes (STBC).

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Authors: R.Goudarzizadeh, N.Hedayat, S.H.Mousavi Jahromi

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Channel junctions can be analyzed in two ways of division (lateral intake) and combined flows (confluence). The present paper investigates 3D flow pattern at lateral intake using Navier-Stokes equation and κ -ε (RNG) turbulent model. The equations are solved by Finite-Volume Method (FVM) and results are compared with the experimental data of (Barkdoll, B.D., 1997) to test the validity of the findings. Comparison of the results with the experimental data indicated a close proximity between the two sets of data which suggest a very close simulation. Results further indicated an inverse relation between the effects of discharge ratio ( r Q ) on the length and width of the separation zone. In other words, as the discharge ration increases, the length and width of separation zone decreases.

Keywords: 900 junction, flow division, turbulent flow, numerical modeling, flow separation zone.

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Authors: Jonathan H. Perez, Fumihiko Tanaka, Daisuke Hamanaka, Toshitaka Uchino

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A finite element analysis was conducted to determine the effect of moisture diffusion and hygroscopic swelling in rice. A parallel simple stochastic modeling was performed to predict the number of grains cracked as a result of moisture absorption and hygroscopic swelling. Rice grains were soaked in thermally (25 oC) controlled water and then tested for compressive stress. The destructive compressive stress tests revealed through compressive stress calculation that the peak force required to cause cracking in grains soaked in water reduced with time as soaking duration was extended. Results of the experiment showed that several grains had their value of the predicted compressive stress below the von Mises stress and were interpreted as grains which become cracked and/or broke during soaking. The technique developed in this experiment will facilitate the approximation of the number of grains which will crack during soaking.

Keywords: Cracking, Finite element analysis, hygroscopic swelling, moisture diffusion, von Mises stress.

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Authors: F. Rasi Maezabadi, M. Masdari, M. R. Soltani

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Series of experimental tests were conducted on a section of a 660 kW wind turbine blade to measure the pressure distribution of this model oscillating in plunging motion. In order to minimize the amount of data required to predict aerodynamic loads of the airfoil, a General Regression Neural Network, GRNN, was trained using the measured experimental data. The network once proved to be accurate enough, was used to predict the flow behavior of the airfoil for the desired conditions. Results showed that with using a few of the acquired data, the trained neural network was able to predict accurate results with minimal errors when compared with the corresponding measured values. Therefore with employing this trained network the aerodynamic coefficients of the plunging airfoil, are predicted accurately at different oscillation frequencies, amplitudes, and angles of attack; hence reducing the cost of tests while achieving acceptable accuracy.

Keywords: Airfoil, experimental, GRNN, Neural Network, Plunging.

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Authors: Suman Bala, Sunil Kamboj, Vipin Saini

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Quantitative Structure Activity Relationship (QSAR) analysis has been developed to relate antifungal activity of novel substituted 1,3,4-oxadiazole against Candida albicans and Aspergillus niger using computer assisted multiple regression analysis. The study has shown the better relationship between antifungal activities with respect to various descriptors established by multiple regression analysis. The analysis has shown statistically significant correlation with R² values 0.932 and 0.782 against Candida albicans and Aspergillus niger respectively. These derivatives were further subjected to molecular docking studies to investigate the interactions between the target compounds and amino acid residues present in the active site of glucosamine-6-phosphate synthase. All the synthesized compounds have better docking score as compared to standard fluconazole. Our results could be used for the further design as well as development of optimal and potential antifungal agents.

Keywords: 1, 3, 4-Oxadiazole, QSAR, Multiple linear regression, Docking, Glucosamine-6-Phosphate Synthase.

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Authors: M. Sasajima, T. Yamaguchi, Y. Hu, Y. Koike

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In this paper, we discuss the propagation of sound in the narrow pathways of an occluded-ear simulator typically used for the measurement of insert-type earphones. The simulator has a standardized frequency response conforming to the international standard (IEC60318-4). In narrow pathways, the speed and phase of sound waves are modified by viscous air damping. In our previous paper, we proposed a new finite element method (FEM) to consider the effects of air viscosity in this type of audio equipment. In this study, we will compare the results from the ear simulator FEM model, and those from a three dimensional human ear canal FEM model made from computed tomography images, with the measured frequency response data from the ear canals of 18 people.

Keywords: Ear simulator, FEM, viscosity, human ear canal.

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Authors: Mountassar Maamoun, Abdelhamid Meraghni, Abdelhalim Benbelkacem, Daoud Berkani

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This paper describes an efficient hardware implementation of a new technique for interfacing the data exchange between the microprocessor-based systems and the external devices. This technique, based on the use of software/hardware system and a reduced physical address, enlarges the interfacing capacity of the microprocessor-based systems, uses the Direct Memory Access (DMA) to increases the frequency of the new bus, and improves the speed of data exchange. While using this architecture in microprocessor-based system or in computer, the input of the hardware part of our system will be connected to the bus system, and the output, which is a new bus, will be connected to an external device. The new bus is composed of a data bus, a control bus and an address bus. A Xilinx Integrated Software Environment (ISE) 7.1i has been used for the programmable logic implementation.

Keywords: Interfacing, Software/hardware System, CPLD, programmable logic, DMA.

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: Band selection, fuzzy C-means, K-means, hyperspectral image.

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Authors: R. Usubamatov

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The velocity of a moving point in a general path is the vector quantity, which has both magnitude and direction. The magnitude or the direction of the velocity vector can change over time as a result of acceleration that the time rate of velocity changes. Acceleration analysis is important because inertial forces and inertial torques are proportional to rectilinear and angular accelerations accordingly. The loads must be determined in advance to ensure that a machine is adequately designed to handle these dynamic loads. For planar motion, the vector direction of acceleration is commonly separated into two elements: tangential and centripetal or radial components of a point on a rotating body. All textbooks in physics, kinematics and dynamics of machinery consider the magnitude of a radial acceleration at condition when a point rotates with a constant angular velocity and it means without acceleration. The magnitude of the tangential acceleration considered on a basis of acceleration for a rotating point. Such condition of presentation of magnitudes for two components of acceleration logically and mathematically is not correct and may cause further confusion in calculation. This paper presents new analytical expressions of the radial and absolute accelerations of a rotating point with acceleration and covers the gap in theoretical study of acceleration analysis.

Keywords: acceleration analysis, kinematics of mechanisms.

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Authors: Autcha Araveeporn

Abstract:

The Random Coefficient Dynamic Regression (RCDR) model is to developed from Random Coefficient Autoregressive (RCA) model and Autoregressive (AR) model. The RCDR model is considered by adding exogenous variables to RCA model. In this paper, the concept of the Maximum Likelihood (ML) method is used to estimate the parameter of RCDR(1,1) model. Simulation results have shown the AIC and BIC criterion to compare the performance of the the RCDR(1,1) model. The variables as the stationary and weakly stationary data are good estimates where the exogenous variables are weakly stationary. However, the model selection indicated that variables are nonstationarity data based on the stationary data of the exogenous variables.

Keywords: Autoregressive, Maximum Likelihood Method, Nonstationarity, Random Coefficient Dynamic Regression, Stationary.

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Authors: Eiko Takaoka, Ryohei Takahashi, Takashi Toyoda

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We installed solar panels and digital meteorological equipments whose electrical power is supplied using PV on July 13, 2011. Then, the relationship between the electric power generation and the irradiation, air temperature, and wind velocity was investigated on a roof at a university. The electrical power generation, irradiation, air temperature, and wind velocity were monitored over two years. By analyzing the measured meteorological data and electric power generation data using PTC, we calculated the size of the solar panel that is most suitable for this system. We also calculated the wasted power generation using PTC with the measured meteorological data obtained in this study. In conclusion, to reduce the "wasted power generation", a smaller-size solar panel is required for stable operation.

Keywords: Digital meteorological equipments, PV, photovoltaic, irradiation, PTC.

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Authors: E. V. Veraszto, J. T. F. Camargo, D. Silva, N. A. Miranda, F. O. Simon, S. F. Amaral, L. V. Freitas

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The concept of technology as well as itself has evolved continuously over time, such that, nowadays, this concept is still marked by myths and realities. Even the concept of science is frequently misunderstood as technology. In this way, this paper presents different forms of interpretation of the concept of technology in the course of history, as well as the social and cultural aspects associated with it, through an analysis made by means of insights from sociological studies of science and technology and its multiple relations with society. Through the analysis of contents, the paper presents a classification of how technology is interpreted in the social sphere and search channel efforts to show how a broader understanding can contribute to better interpretations of how scientific and technological development influences the environment in which we operate. The text also presents a particular point of view for the interpretation of the concept from the analysis throughout the whole work.

Keywords: Technology, conceptions of technology, technological myths, definition of technology.

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Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz

Abstract:

This study investigated the impact of inflectional and derivational morphemic analysis awareness on ESL secondary school students’ vocabulary learning strategy. The quasi-experimental study was conducted with 106 low proficiency secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morphemic Analysis Test and Vocabulary- Morphemic Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morphemic Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the results indicated that ESL low proficiency secondary school students performed better on inflectional morphemic awareness as compared to derivatives. The results also showed that the awareness of inflectional morphology contributed more on the vocabulary acquisition. Importantly, learning inflectional morphology can help ESL low proficiency secondary school students to develop both morphemic awareness and vocabulary gain. Theoretically, these findings show that not all morphemes are equally useful to students for their language development. Practically, these findings indicate that morphological instruction should at least be included in remediation and instructional efforts with struggling learners across all grade levels, allowing them to focus on meaning within the word before they attempt the text in large for better comprehension. Also, by methodologically, by conducting individualized intervention and assessment this study provided fresh empirical evidence to support the existing literature on morphemic analysis awareness and vocabulary learning strategy. Thus, a major pedagogical implication of the study is that morphemic analysis awareness strategy is a definite boon for ESL secondary school students in learning English vocabulary.

Keywords: ESL, instruction, morphemic analysis, vocabulary.

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Authors: Hossein Sahoolizadeh, Davood Sarikhanimoghadam, Hamid Dehghani

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This paper proposes new hybrid approaches for face recognition. Gabor wavelets representation of face images is an effective approach for both facial action recognition and face identification. Perform dimensionality reduction and linear discriminate analysis on the down sampled Gabor wavelet faces can increase the discriminate ability. Nearest feature space is extended to various similarity measures. In our experiments, proposed Gabor wavelet faces combined with extended neural net feature space classifier shows very good performance, which can achieve 93 % maximum correct recognition rate on ORL data set without any preprocessing step.

Keywords: Face detection, Neural Networks, Multi-layer Perceptron, Gabor wavelets.

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Authors: Taleb Hosni Abderrahmane, Berga Abdelmadjid

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The development of numerical analysis and its application to geomechanics problems have provided geotechnical engineers with extremely powerful tools. One of the most important problems in geotechnical engineering is the slope stability assessment. It is a very difficult task due to several aspects such the nature of the problem, experimental consideration, monitoring, controlling, and assessment. The main objective of this paper is to perform a comparative numerical study between the following methods: The Limit Equilibrium (LEM), Finite Element (FEM), Limit Analysis (LAM) and Distinct Element (DEM). The comparison is conducted in terms of the safety factors and the critical slip surfaces. Through the results, we see the feasibility to analyse slope stability by many methods.

Keywords: Comparison, factor of safety, geomechanics, numerical methods, slope analysis, slip surfaces.

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Authors: H. Urbancova, J. Urbanec

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Today the intangible assets are the capital of knowledge and are the most important and the most valuable resource for organizations. All employees have knowledge independently of the kind of jobs they do. Knowledge is thus an asset, which influences business operations. The objective of this article is to identify knowledge continuity as an objective of business continuity management. The article has been prepared based on the analysis of secondary sources and the evaluation of primary sources of data by means of a quantitative survey conducted in the Czech Republic. The conclusion of the article is that organizations that apply business continuity management do not focus on the preservation of the knowledge of key employees. Organizations ensure knowledge continuity only intuitively, on a random basis, non-systematically and discontinuously. The non-ensuring of knowledge continuity represents a threat of loss of key knowledge for organizations and can also negatively affect business continuity.

Keywords: Business continuity, knowledge, organizations, survey.

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Authors: Ke Wang, Zhi-Qiang Zhang, Z. Chen

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A submerged horizontal plate type breakwater is pointed out as an efficient wave protection device for cage culture in marine fishery. In order to reveal the wave elimination principle of this type breakwater, boundary element method is utilized to investigate this problem. The flow field and the trajectory of water particles are studied carefully. The flow field analysis shows that: the interaction of incident wave and adverse current above the plate disturbs the water domain drastically. This can slow down the horizontal velocity and vertical velocity of the water particles.

Keywords: boundary element method, plate type breakwater, flow field analysis

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native Language Identification is one of the growing subfields in Natural Language Processing (NLP). The task of Native Language Identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL) and then the trained models are evaluated on a different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and Logistic Regression. Results show that content-based features are more accurate and robust than content independent ones when tested within corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML.

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: Dynamic modeling, missing data, multiple imputation, physiological measures.

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Authors: Matthias Dehmer, Frank Emmert Streib, Jürgen Kilian, Andreas Zulauf

Abstract:

Methods for organizing web data into groups in order to analyze web-based hypertext data and facilitate data availability are very important in terms of the number of documents available online. Thereby, the task of clustering web-based document structures has many applications, e.g., improving information retrieval on the web, better understanding of user navigation behavior, improving web users requests servicing, and increasing web information accessibility. In this paper we investigate a new approach for clustering web-based hypertexts on the basis of their graph structures. The hypertexts will be represented as so called generalized trees which are more general than usual directed rooted trees, e.g., DOM-Trees. As a important preprocessing step we measure the structural similarity between the generalized trees on the basis of a similarity measure d. Then, we apply agglomerative clustering to the obtained similarity matrix in order to create clusters of hypertext graph patterns representing navigation structures. In the present paper we will run our approach on a data set of hypertext structures and obtain good results in Web Structure Mining. Furthermore we outline the application of our approach in Web Usage Mining as future work.

Keywords: Clustering methods, graph-based patterns, graph similarity, hypertext structures, web structure mining

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Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz

Abstract:

The research explored the effect of morphemic analysis awareness on ESL secondary school students’ vocabulary acquisition. The quasi-experimental study was conducted with 100 ESL secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morph-Analysis Test and Morph-Vocabulary Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morph- Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the findings of the research are discussed in two main areas. First, individual instructions of two types of morphemic awareness have contributed significant results on inflectional and derivational awareness among the ESL secondary school students. Nevertheless, derivational morphology achieved a significant but relatively smaller amount of effect on secondary school students’ morphological awareness compared to inflectional morphology in this research. Second finding showed that the awareness of inflectional and derivational morphology was found significantly related to vocabulary achievement of ESL secondary school students. Nevertheless, inflectional morphemic awareness had higher significant effect on ESL secondary school students’ vocabulary acquisition. Despite these findings, the study implies that morphemic analysis awareness can serve as an alternative strategy for ESL secondary school students in acquiring English vocabulary.

Keywords: Morphemic analysis, vocabulary, ESL students.

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Authors: Omid A. Zargar

Abstract:

Vibration monitoring methods of most critical equipment like main turbine and compressors always plays important role in preventive maintenance and management consideration in big industrial plants. There are a number of traditional methods like monitoring the overall vibration data from Bently Nevada panel and the time wave form (TWF) or fast Fourier transform (FFT) monitoring. Besides, Shaft centerline monitoring method developed too much in recent years. There are a number of arguments both in favor of and against this method between people who work in preventive maintenance and condition monitoring systems (vibration analysts). In this paper basic principal of Turbine compressor vibration analysis and rotor movement evaluation by shaft centerline method discussed in details through a case history. This case history is related to main turbine compressor of an olefin plant in Iran oil industry. In addition, some common mistakes that may occur by vibration analyst during the process discussed in details. It is worthy to know that, these mistakes may one of the reasons that sometimes this method seems to be not effective. Furthermore, recent patent and innovation in shaft position and movement evaluation are discussed in this paper.

Keywords: Shaft centerline position, attitude angle, journal bearing, sleeve bearing, tilting pad, steam turbine, main compressor, multistage compressor, condition monitoring, non-contact probe

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Authors: M. Karami Khorramabadi, A. R. Nezamabadi

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This paper studies mechanical buckling of functionally graded beams subjected to axial compressive load that is simply supported at both ends lies on a continuous elastic foundation. The displacement field of beam is assumed based on Engesser-Timoshenko beam theory. Applying the Hamilton's principle, the equilibrium equation is established. The influences of dimensionless geometrical parameter, functionally graded index and foundation coefficient on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: Mechanical Buckling, Functionally graded beam- Engesser-Timoshenko beam theory

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Authors: Karamitsos Ioannis, Orfanidis Konstantinos

Abstract:

In this paper an analysis of blackouts in electric power transmission systems is implemented using a model and studied in simple networks with a regular topology. The proposed model describes load demand and network improvements evolving on a slow timescale as well as the fast dynamics of cascading overloads and outages.

Keywords: Blackout, Generator, Load, Power Load.

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Authors: Mehmet Savsar

Abstract:

Reliability and availability of power stations are extremely important in order to achieve a required level of power generation. In particular, in the hot desert climate of Kuwait, reliable power generation is extremely important because of cooling requirements at temperatures exceeding 50-centigrade degrees. In this paper, a particular power plant, named Sabiya Power Plant, which has 8 steam turbines and 13 gas turbine stations, has been studied in detail; extensive data are collected; and availability of station units are determined. Furthermore, a simulation model is developed and used to analyze the effects of different maintenance policies on availability of these stations. The results show that significant improvements can be achieved in power plant availabilities if appropriate maintenance policies are implemented.

Keywords: Power plants, steam turbines, gas turbines, maintenance, availability, simulation.

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Authors: C. Ardil

Abstract:

In this paper, composite programming is discussed for aircraft evaluation and selection problem using the multiple criteria decision analysis method. The decision criteria and aircraft alternatives were identified from the literature review. The importance of criteria weights was determined by the standard deviation method. The proposed model is applied to a practical decision problem for evaluating and selecting advanced jet trainer and light attack aircraft. The proposed technique gives robust and efficient results in modeling multiple criteria decisions. As a result of composite programming analysis, Hürjet, an advanced jet trainer and light attack aircraft alternative (a3), was chosen as the most suitable aircraft candidate.  

Keywords: composite programming, additive weighted model, multiplicative weighted model, multiple criteria decision making analysis, MCDMA, aircraft selection, advanced jet trainer and light attack aircraft, M-346, FA-50, Hürjet

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Authors: Yaser E. Hawas, Md. Didarul Alam

Abstract:

Rollover crashes are complex events entailing interactions of driver, road, vehicle, and environmental factors. The primary objective of this paper is to present an empirical approach that can be used to characterise the rollover crashes and to identify some of the important factors that may lead to rollovers. Among the studied factors are the vehicle types and the rollover occurrence rate after hitting various barrier types. The carried analysis indicated that 71% of the rollover crashes occurred after impact and the type of rollover initiation is “trip/turn over” (nearly 50%). It was also found that light trucks (LTVs) vehicles are more likely to rollover than the sedan vehicles. Barrier impacts are associated with increased incidence of rollover.

Keywords: Empirical, hitting barrier, in-depth crash investigation, rollover, severe crash.

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Authors: H.Hosseini, A.A. Azemati

Abstract:

The fundamental defect inherent to the thermoforming technology is wall-thickness variation of the products due to inadequate thermal processing during production of polymer. A nonlinear viscoelastic rheological model is implemented for developing the process model. This model describes deformation process of a sheet in thermoforming process. Because of relaxation pause after plug-assist stage and also implementation of two stage thermoforming process have minor wall-thickness variation and consequently better mechanical properties of polymeric articles. For model validation, a comparative analysis of the theoretical and experimental data is presented.

Keywords: High-quality polymeric article, Thermal Processing, Rheological model, Minor wall-thickness variation.

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Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss

Abstract:

The ElectroEncephaloGram (EEG) is useful for clinical diagnosis and biomedical research. EEG signals often contain strong ElectroOculoGram (EOG) artifacts produced by eye movements and eye blinks especially in EEG recorded from frontal channels. These artifacts obscure the underlying brain activity, making its visual or automated inspection difficult. The goal of ocular artifact removal is to remove ocular artifacts from the recorded EEG, leaving the underlying background signals due to brain activity. In recent times, Independent Component Analysis (ICA) algorithms have demonstrated superior potential in obtaining the least dependent source components. In this paper, the independent components are obtained by using the JADE algorithm (best separating algorithm) and are classified into either artifact component or neural component. Neural Network is used for the classification of the obtained independent components. Neural Network requires input features that exactly represent the true character of the input signals so that the neural network could classify the signals based on those key characters that differentiate between various signals. In this work, Auto Regressive (AR) coefficients are used as the input features for classification. Two neural network approaches are used to learn classification rules from EEG data. First, a Polynomial Neural Network (PNN) trained by GMDH (Group Method of Data Handling) algorithm is used and secondly, feed-forward neural network classifier trained by a standard back-propagation algorithm is used for classification and the results show that JADE-FNN performs better than JADEPNN.

Keywords: Auto Regressive (AR) Coefficients, Feed Forward Neural Network (FNN), Joint Approximation Diagonalisation of Eigen matrices (JADE) Algorithm, Polynomial Neural Network (PNN).

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