Search results for: linear array

Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

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Authors: M. P. Nanda Kumar, K. Dheeraj

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The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.

Keywords: inverse optimal control, radial basis function, neural network, controller design

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Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

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The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

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Authors: Yihua Wang, Yunru Lai

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Statistical process control has been successfully applied in a variety of industries. In some applications, the quality of a process or product is better characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. A collection of this type of data is called a profile. Profile monitoring is used to understand and check the stability of this relationship or curve over time. The independent assumption for the error term is commonly used in the existing profile monitoring studies. However, in many applications, the profile data show correlations over time. Therefore, we focus on a general linear regression model with a first-order autocorrelation between profiles in this study. We propose an exponentially weighted moving average charting scheme to monitor this type of profile. The simulation study shows that our proposed methods outperform the existing schemes based on the average run length criterion.

Keywords: autocorrelation, EWMA control chart, general linear regression model, profile monitoring

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Authors: A. A. Behroozpoor, M. M. Mazarei

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In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: Wei-Na Li, Mei-Lan Piao, Nam Kim

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We proposed a novel computer-generated hologram (CGH) achieved scheme, wherein the CGH is generated from a point cloud which is transformed by a mapping relationship of a series of elemental images captured from a real three-dimensional (3D) object by using a lens array. This scheme is composed of three procedures: mapping from elemental images to point cloud, hologram generation, and hologram display. A mapping method is figured out to achieve a virtual volume date (point cloud) from a series of elemental images. This mapping method consists of two steps. Firstly, the coordinate (x, y) pairs and its appearing number are calculated from the series of sub-images, which are generated from the elemental images. Secondly, a series of corresponding coordinates (x, y, z) are calculated from the elemental images. Then a hologram is generated from the volume data that is calculated by the previous two steps. Eventually, a spatial light modulator (SLM) and a green laser beam are utilized to display this hologram and reconstruct the original 3D object. In this paper, in order to show a more auto stereoscopic display of a real 3D object, we successfully obtained the actual depth data of every discrete point of the real 3D object, and overcame the inherent drawbacks of the depth camera by obtaining point cloud from the elemental images.

Keywords: elemental image, point cloud, computer-generated hologram (CGH), autostereoscopic display

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Authors: Lahlou Dahmani, Warda Mekiri, Ahmed Boudjemia

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This scientific paper explores the comparison between the ultimate buckling load obtained through the Eurocode 3 methodology and the ultimate buckling load obtained through finite element simulations for steel columns under compression. The study aims to provide insights into the adequacy of the design rules proposed in Eurocode 3 for different slenderness ratios. The finite element simulations with the Ansys commercial program involve a geometrical and material non-linear analysis of the columns with imperfections. The loss of equilibrium is generally caused by the geometrically nonlinear effects where the column begins to buckle and lose its stability when the load reaches a certain critical value. The linear buckling analysis predicts the theoretical buckling strength of an elastic structure but the nonlinear one is more accurate with taking into account the initial imperfection.

Keywords: Ansys, linear buckling, eigen value, nonlinear buckling, slenderness ratio, Eurocode 3

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Authors: J. Jena, Monica Saxena

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In this paper, the propagation of weak nonlinear waves in non-equilibrium flow has been studied in detail using the perturbation method. The expansive action of receding piston undergoing infinite acceleration has been discussed. Central expansion fan, compression waves and shock fronts have been discussed and the solutions up to the first order in the characteristic plane and physical plane have been obtained.

Keywords: Characteristic wave front, weak non-linear waves, central expansion fan, compression waves

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Authors: Harika Atmaca, Emir Bozkurt, Latife Merve Oktay, Selim Uzunoglu, Ruchan Uslu, Burçak Karaca

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Microarrays have been developed for highly parallel enzyme-linked immunosorbent assay (ELISA) applications. The most common protein arrays are produced by using multiple monoclonal antibodies, since they are robust molecules which can be easily handled and immobilized by standard procedures without loss of activity. Protein expression profiling with protein array technology allows simultaneous analysis of the protein expression pattern of a large number of proteins. Trabectedin, a tetrahydroisoquinoline alkaloid derived from a Caribbean tunicate, Ecteinascidia turbinata, has been shown to have antitumor effects. Here, we used a novel proteomic approach to explore the mechanism of action of trabectedin in prostate cancer cell line PC-3 by apoptosis antibody microarray. XTT cell proliferation kit and Cell Death Detection Elisa Plus Kit (Roche) was used for measuring cytotoxicity and apoptosis. Human Apoptosis Protein Array (R&D Systems) which consists of 35 apoptosis related proteins was used to assess the omic protein expression pattern. Trabectedin induced cytotoxicity and apoptosis in prostate cancer cells in a time and concentration-dependent manner. The expression levels of the death receptor pathway molecules, TRAIL-R1/DR4, TRAIL R2/DR5, TNF R1/TNFRSF1A, FADD were significantly increased by 4.0-, 21.0-, 4.20- and 11.5-fold by trabectedin treatment in PC-3 cells. Moreover, mitochondrial pathway related pro-apoptotic proteins Bax, Bad, Cytochrome c, and Cleaved Caspase-3 expressions were induced by 2.68-, 2.07-, 2.8-, and 4.5-fold and the expression levels of anti-apoptotic proteins Bcl-2 and Bcl-XL were reduced by 3.5- and 5.2-fold in PC-3 cells. Proteomic (antibody microarray) analysis suggests that the mechanism of action of trabectedin may be exerted via the induction of both intrinsic and extrinsic apoptotic pathways. The antibody microarray platform can be utilised to explore the molecular mechanism of action of novel anticancer agents.

Keywords: trabectedin, prostate cancer, omic protein expression profile, apoptosis

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Authors: Yu Zhang, Il Kim

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Polypeptides with defined peptide sequences illustrate the power of remarkable applications in drug delivery, tissue engineering, sensing and catalysis. Especially the cyclic polypeptides, the distinctive topological architecture imparts many characteristic properties comparing to linear polypeptides. Here, a facile and highly efficient strategy for the synthesis of linear and cyclic polypeptides is reported using N-heterocyclic carbenes (NHCs)-mediated ring-opening polymerization (ROP) of α-amino acid N-carboxyanhydrides (NCA) in the presence or absence of primary amine initiator. The polymerization proceeds rapidly in a quasi-living manner, allowing access to linear and cyclic polypeptides of well-defined chain length and narrow polydispersity, as evidenced by nuclear magnetic resonance spectrum (1H NMR and 13C NMR spectra) and size exclusion chromatography (SEC) analysis. The cyclic architecture of the polypeptides was further verified by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectra (MALDI-TOF MS) and electrospray ionization (ESI) mass spectra, as well as viscosity studies. This approach can also simplify workup procedures and make bulk scale synthesis possible, which thereby opens avenues for practical uses in diverse areas, opening up the new generation of polypeptide synthesis.

Keywords: α-amino acid N-carboxyanhydrides, living polymerization, polypeptides, N-heterocyclic carbenes, ring-opening polymerization

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Authors: C. Gebauer, C. Henke, R. Vossen

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Within the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020, a team of unmanned aerial vehicles (UAV) is used to capture intruder drones by physical interaction. The challenge is motivated by UAV safety. The purpose of this work is to investigate the agility of a quadcopter being controlled visually. The aim is to track and follow a highly dynamic target, e.g., an intruder quadcopter. The following is realized in close range and the opponent has a velocity of up to 10 m/s. Additional limitations are given by the hardware itself, where only monocular vision is present, and no additional knowledge about the targets state is available. An image based visual servoing (IBVS) approach is applied in combination with a Linear Quadratic Regulator (LQR). The IBVS is integrated into the LQR and an optimal trajectory is computed within the projected three-dimensional image-space. The approach has been evaluated on real quadcopter systems in different flight scenarios to demonstrate the system's stability.

Keywords: image based visual servoing, quadcopter, dynamic object tracking, linear-quadratic regulator

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Authors: Deepak K. Gupta, T. R. Ravindran

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Holographic Optical Tweezers (HOTs) in general use iterative algorithms such as weighted Gerchberg-Saxton (WGS) to generate multiple traps, which produce traps with 99% uniformity theoretically. But in experiments, it is the phase response of the spatial light modulator (SLM) which ultimately determines the efficiency, uniformity, and quality of the trap spots. In general, SLMs show a nonlinear phase response behavior, and they may even have asymmetric phase modulation depth before and after π. This affects the resolution with which the gray levels are addressed before and after π, leading to a degraded trap performance. We present a method to optimize the SLM for a linear phase response behavior along with a symmetric phase modulation depth around π. Further, we optimize the SLM for its varying phase response over different spatial regions by optimizing the brightness/contrast and gamma of the hologram in different subsections. We show the effect of the optimization on an array of trap spots resulting in improved efficiency and uniformity. We also calculate the spot sharpness metric and trap performance metric and show a tightly focused spot with reduced aberration. The trap performance is compared by calculating the trap stiffness of a trapped particle in a given trap spot before and after aberration correction. The trap stiffness is found to improve by 200% after the optimization.

Keywords: spatial light modulator, optical trapping, aberration, phase modulation

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Authors: Soltani Amir, Hu Jiaxin

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Determination of optimal parameters of a passive control system device is the primary objective of this study. Expanding upon the use of control devices in wind and earthquake hazard reduction has led to development of various control systems. The advantage of non-linearity characteristics in a passive control device and the optimal control method using LQR algorithm are explained in this study. Finally, this paper introduces a simple approach to determine optimum parameters of a nonlinear viscous damper for vibration control of structures. A MATLAB program is used to produce the dynamic motion of the structure considering the stiffness matrix of the SDOF frame and the non-linear damping effect. This study concluded that the proposed system (variable damping system) has better performance in system response control than a linear damping system. Also, according to the energy dissipation graph, the total energy loss is greater in non-linear damping system than other systems.

Keywords: passive control system, damping devices, viscous dampers, control algorithm

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Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)

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Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

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This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

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Authors: Sabiha Shahid Antora, Young Ki Chang

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Along with various farm management technologies, imagery is an important tool that facilitates crop assessment, monitoring, and management. As a consequence, drone imaging technology is playing a vital role to capture the state of the entire field for yield mapping, crop scouting, weed detection, and so on. Although it is essential to inspect the cultivable lands in real-time for making rapid decisions regarding field variable inputs to combat stresses and diseases, drone imagery is still evolving in this area of interest. Cost margin and post-processing complexions of the image stream are the main challenges of imaging technology. Therefore, this proposed project involves the cost-effective field programmable gate array (FPGA) based image processing device that would process the image stream in real-time as well as providing the processed output to support on-the-spot decisions in the crop field. As a result, the real-time FPGA-based image processing system would reduce operating costs while minimizing a few intermediate steps to deliver scalable field decisions.

Keywords: real-time, FPGA, drone imagery, image processing, crop monitoring

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Authors: Mannika Garg, N. Srinivas Murthy, Sunish Nair

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TeamIndus is only Indian team participated in the Google Lunar X Prize (GLXP). GLXP is an incentive prize space competition which is organized by the XPrize Foundation and sponsored by Google. The main objective of the mission is to soft land a rover on the moon surface, travel minimum displacement of 500 meters and transmit HD and NRT videos and images to the Earth. Team Indus is designing a Lunar Lander which carries Rover with it and deliver onto the surface of the moon with a soft landing. For lander to survive throughout the mission, energy is required to operate all attitude control sensors, actuators, heaters and other necessary components. Photovoltaic solar array systems are the most common and primary source of power generation for any spacecraft. The scope of this paper is to provide a system-level approach for designing the solar array systems of the lander to generate required power to accomplish the mission. For this mission, the direction of design effort is to higher efficiency, high reliability and high specific power. Towards this approach, highly efficient multi-junction cells have been considered. The design is influenced by other constraints also like; mission profile, chosen spacecraft attitude, overall lander configuration, cost effectiveness and sizing requirements. This paper also addresses the various solar array design challenges such as operating temperature, shadowing, radiation environment and mission life and strategy of supporting required power levels (peak and average). The challenge to generate sufficient power at the time of surface touchdown, due to low sun elevation (El) and azimuth (Az) angle which depends on Lunar landing site, has also been showcased in this paper. To achieve this goal, energy balance analysis has been carried out to study the impact of the above-mentioned factors and to meet the requirements and has been discussed in this paper.

Keywords: energy balance analysis, multi junction solar cells, photovoltaic, reliability, spacecraft attitude

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete frames

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Authors: Amina Sultan, Mohamed Ghonim, Eman Oweida, Aya Abdelaziz

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Objective: To assess the diagnostic reliability of multi-detector CT in pre and post-operative evaluation of cochlear implant candidates. Material and Methods: The study includes 40 patients (18 males and 22 females); mean age 5.6 years. They were classified into two groups: Group A (20 patients): cochlear implant device was Nucleus-22 and Group B (20 patients): the device was MED-EL. Cochlear length (CL) and cochlear height (CH) were measured pre-operatively by 128-multidetector CT. Electrode length (EL) and insertion depth angle (α) were measured post-operatively by MDCT. Results: For Group A mean CL was 9.1 mm ± 0.4 SD; mean CH was 4.1 ± 0.3 SD; mean EL was 18 ± 2.7 SD; mean α angle was 299.05 ± 37 SD. Significant statistical correlation (P < 0.05) was found between preoperative CL and post-operative EL (r²=0.6); as well as EL and α angle (r²=0.7). Group B's mean CL was 9.1 mm ± 0.3 SD; mean CH was 4.1 ± 0.4 SD; mean EL was 27 ± 2.1 SD; mean α angle was 287.6 ± 41.7 SD. Significant statistical correlation was found between CL and EL (r²= 0.6) and α angle (r²=0.5). Also, a strong correlation was found between EL and α angle (r²=0.8). Significant statistical difference was detected between the two devices as regards to the electrode length. Conclusion: Multidetector CT is a reliable tool for preoperative planning and post-operative evaluation of the outcomes of cochlear implant operations. Cochlear length is a valuable prognostic parameter for prediction of the depth of electrode array insertion which can influence criteria of device selection.

Keywords: angle of insertion (α angle), cochlear implant (CI), cochlear length (CL), Multidetector Computed Tomography (MDCT)

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, we introduce a mathematical algorithm which is used for estimating the states in the bilinear systems. This algorithm uses a special linearization of the second-order term by using the best available information about the state of the system. This technique makes our algorithm generalizes the well-known Kalman estimators. The system which is used here is of the bilinear class, the evolution of this model is linear-bilinear in the state of the system. Our algorithm can be used with linear and bilinear systems. We also here introduced a real application for the new algorithm to prove the feasibility and the efficiency for it.

Keywords: estimation algorithm, bilinear systems, Kakman filter, second order linearization

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Authors: Zahra Kouzehgari

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Since the early emergence of chaos theory in the 1970s in mathematics and physical science, it has increasingly been developed and adapted in social sciences as well. The non-linear and dynamic characteristics of the theory make it a useful conceptual framework to interpret the complex social systems behavior. Regarding chaotic approach principals, sensitivity to initial conditions, dynamic adoption, strange attractors and unpredictability this paper aims to examine whether chaos approach could interpret the ancient social changes. To do this, at first, a brief history of the chaos theory, its development and application in social science as well as the principals making the theory, then its application in archaeological since has been reviewed. The study demonstrates that although based on existing archaeological records reconstruct the whole social system of the human past, the non-linear approaches in studying social complex systems would be of a great help in finding general order of the ancient societies and would enable us to shed light on some of the social phenomena in the human history or to make sense of them.

Keywords: archaeology, non-linear approach, chaos theory, ancient social systems

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Authors: Bello Yusuf Idi

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The Gongola arm of the Upper Banue Trough, Northeastern Nigeria is predominantly covered by the outcrops of Limestone-bearing rocks in form of Sandstone with intercalation of carbonate clay, shale, basaltic, felsphatic and migmatide rocks at subpixel dimension. In this work, subpixel classification algorithm was used to classify the data acquired from landsat 7 Enhance Thematic Mapper (ETM+) satellite system with the aim of producing fractional distribution image for three most economically important solid minerals of the area: Limestone, Basalt and Migmatide. Linear Spectral Unmixing (LSU) algorithm was used to produce fractional distribution image of abundance of the three mineral resources within a 100Km2 portion of the area. The results show that the minerals occur at different proportion all over the area. The fractional map could therefore serve as a guide to the ongoing reconnaissance for the economic potentiality of the formation.

Keywords: linear spectral un-mixing, upper benue trough, gongola arm, geological engineering

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

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In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

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Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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Authors: Hande Sezgin, Senem Kursun Bahadır, Yakup Erhan Boke, Fatma Kalaoğlu

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Electronic textiles (e-textiles) are fabrics that contain electronics and interconnections with them. In this study, two types of base yarns (cotton and acrylic) and three conductive steel yarns with different linear resistance values (14Ω/m, 30Ω/m, 70Ω/m) were used to investigate the effect of base yarn type and linear resistance of conductive yarns on thermal behavior of e-textile structures. Thermal behavior of samples were examined by thermal camera.

Keywords: conductive yarn, e-textiles, smart textiles, thermal analysis

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Authors: F. Rahimi Dehgolan, S. E. Khadem, S. Bab, M. Najafee

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Nowadays, using rotating systems like shafts and disks in industrial machines have been increased constantly. Dynamic stability is one of the most important factors in designing rotating systems. In this study, linear frequencies and stability of a coupled continuous flexible rotor-disk-blades system are studied. The Euler-Bernoulli beam theory is utilized to model the blade and shaft. The equations of motion are extracted using the extended Hamilton principle. The equations of motion have been simplified using the Coleman and complex transformations method. The natural frequencies of the linear part of the system are extracted, and the effects of various system parameters on the natural frequencies and decay rates (stability condition) are clarified. It can be seen that the centrifugal stiffening effect applied to the blades is the most important parameter for stability of the considered rotating system. This result highlights the importance of considering this stiffing effect in blades equation.

Keywords: rotating shaft, flexible blades, centrifugal stiffness, stability

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Authors: Kuniyoshi Abe

Abstract:

Bi-conjugate gradient (Bi-CG) is a well-known method for solving linear equations Ax = b, for x, where A is a given n-by-n matrix, and b is a given n-vector. Typically, the dimension of the linear equation is high and the matrix is sparse. A number of hybrid Bi-CG methods such as conjugate gradient squared (CGS), Bi-CG stabilized (Bi-CGSTAB), BiCGStab2, and BiCGstab(l) have been developed to improve the convergence of Bi-CG. Bi-CGSTAB has been most often used for efficiently solving the linear equation, but we have seen the convergence behavior with a long stagnation phase. In such cases, it is important to have Bi-CG coefficients that are as accurate as possible, and the stabilization strategy, which stabilizes the computation of the Bi-CG coefficients, has been proposed. It may avoid stagnation and lead to faster computation. Motivated by a large number of processors in present petascale high-performance computing hardware, the scalability of Krylov subspace methods on parallel computers has recently become increasingly prominent. The main bottleneck for efficient parallelization is the inner products which require a global reduction. The resulting global synchronization phases cause communication overhead on parallel computers. The parallel variants of Krylov subspace methods reducing the number of global communication phases and hiding the communication latency have been proposed. However, the numerical stability, specifically, the convergence speed of the parallel variants of Bi-CGSTAB may become worse than that of the standard Bi-CGSTAB. In this paper, therefore, we compare the convergence speed between the standard Bi-CGSTAB and the parallel variants by numerical experiments and show that the convergence speed of the standard Bi-CGSTAB is faster than the parallel variants. Moreover, we propose the stabilization strategy for the parallel variants.

Keywords: bi-conjugate gradient stabilized method, convergence speed, Krylov subspace methods, linear equations, parallel variant

Procedia PDF Downloads 163

Authors: Ruyang Ren, Yaohua Zhao, Yanhua Diao

Abstract:

The intermittent and unstable characteristics of renewable energy such as solar energy can be effectively solved through battery energy storage system. Lithium-ion battery is widely used in battery energy storage system because of its advantages of high energy density, small internal resistance, low self-discharge rate, no memory effect and long service life. However, the performance and service life of lithium-ion battery is seriously affected by its operating temperature. Thus, the safety operation of the lithium-ion battery module is inseparable from an effective thermal management system (TMS). In this study, a new type of TMS based on micro heat pipe array (MHPA) for lithium-ion battery is established, and the TMS is applied to a battery energy storage box that needs to operate at a high temperature environment of 40 °C all year round. MHPA is a flat shape metal body with high thermal conductivity and excellent temperature uniformity. The battery energy storage box is composed of four battery modules, with a nominal voltage of 51.2 V, a nominal capacity of 400 Ah. Through the excellent heat transfer characteristics of the MHPA, the heat generated by the charge and discharge process can be quickly transferred out of the battery module. In addition, if only the MHPA cannot meet the heat dissipation requirements of the battery module, the TMS can automatically control the opening of the external fan outside the battery module according to the temperature of the battery, so as to further enhance the heat dissipation of the battery module. The thermal management performance of lithium-ion battery TMS based on MHPA is studied experimentally under different ambient temperatures and the condition to turn on the fan or not. Results show that when the ambient temperature is 40 °C and the fan is not turned on in the whole charge and discharge process, the maximum temperature of the battery in the energy storage box is 53.1 °C and the maximum temperature difference in the battery module is 2.4 °C. After the fan is turned on in the whole charge and discharge process, the maximum temperature is reduced to 50.1 °C, and the maximum temperature difference is reduced to 1.7 °C. Obviously, the lithium-ion battery TMS based on MHPA not only could control the maximum temperature of the battery below 55 °C, but also ensure the excellent temperature uniformity of the battery module. In conclusion, the lithium-ion battery TMS based on MHPA can ensure the safe and stable operation of the battery energy storage box in high temperature environment.

Keywords: heat dissipation, lithium-ion battery thermal management, micro heat pipe array, temperature uniformity

Procedia PDF Downloads 181