Search results for: double robust estimation

Authors: Belkacem Soundes, Guezouli Larbi

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This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time.

Keywords: text detection, text localization, lecture videos, pseudo zernike moments

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

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Authors: Mohammad Shoraka, Francesco Preti, Karen Angeles, Raulina Wojtkiewicz, Karthik Ramanathan

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Catastrophe modeling has evolved significantly over the last four decades. Verisk introduced its pioneering comprehensive inland flood model tailored for the U.K. in 2008. Over the course of the last 15 years, Verisk has built a suite of physically driven flood models for several countries and regions across the globe. This paper aims to spotlight a selection of these advancements tailored to the development of vulnerability estimation, which forms an integral part of a forthcoming update to Verisk’s U.K. inland flood model. Vulnerability functions are critical to evaluating and robust modeling flood-induced damage to buildings and contents. The subsequent damage assessments then allow for direct quantification of losses for entire building portfolios. Notably, today’s flood loss models more often prioritize enhanced development of hazard characterization, while vulnerability functions often lack sufficient granularity for a robust assessment. This study proposes a novel, engineering-driven, physically based component-level flood vulnerability framework for the U.K. Various aspects of the framework, including component classification and comprehensive cost analysis, meticulously tailored to capture the distinct building characteristics unique to the U.K., will be discussed. This analysis will elucidate how the cost distribution across individual components contributes to translating component-level damage functions into building-level damage functions. Furthermore, a succinct overview of essential datasets employed to gauge building regional vulnerability will be highlighted.

Keywords: catastrophe modeling, inland flood, vulnerability, cost analysis

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Authors: Quan Li, Dongcai Shen, Zhengting Xiao, Xin Liu Mingrui Wu, Licheng Liu, Qin Li, Xianguo Li, Wentai Wang

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Direct electrocatalytic nitrogen oxidation (NOR) provides a promising alternative strategy for synthesizing high-value-added nitric acid from widespread N₂, which overcomes the disadvantages of the Haber-Bosch-Ostwald process. However, the NOR process suffers from the limitation of high N≡N bonding energy (941 kJ mol− ¹), sluggish kinetics, low efficiency and yield. It is a prerequisite to develop more efficient electrocatalysts for NOR. Herein, we synthesized double-shelled CeO₂ hollow spheres (D-CeO₂) and further modified with Ti₃C₂ MXene quantum dots (MQDs) for electrocatalytic N₂ oxidation, which exhibited a NO₃− yield of 71.25 μg h− ¹ mgcat− ¹ and FE of 31.80% at 1.7 V. The unique quantum size effect and abundant edge active sites lead to a more effective capture of nitrogen. Moreover, the double-shelled hollow structure is favorable for N₂ fixation and gathers intermediate products in the interlayer of the core-shell. The in-situ infrared Fourier transform spectroscopy confirmed the formation of *NO and NO₃− species during the NOR reaction, and the kinetics and possible pathways of NOR were calculated by density functional theory (DFT). In addition, a Zn-N₂ reaction device was assembled with D-CeO₂/MQDs as anode and Zn plate as cathode, obtaining an extremely high NO₃− yield of 104.57 μg h− ¹ mgcat− ¹ at 1 mA cm− ².

Keywords: electrocatalytic N₂ oxidation, nitrate production, CeO₂, MXene quantum dots, double-shelled hollow spheres

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Authors: Mohamed Habila, Ahmed Mohamed El-Toni, Mohamed Sheikh Moshab, Abdulrhman Al-Awadi, Zeid AL Othman

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Water pollution with dyes is a critical environmental issue because off the huge amount of dyes disbarred annually, which cause severe damage for the ecosystem and human life. The main raison for this severs pollution is the rapid industrial development which led to more production of harmful pollutants. on the other hand, the core shell based magnetic materials have showed amazing character for controlling the material synthesis with the targeted structure to enhance the adsorptive removal of pollutants. Herein, the Fe3O4core-meso SiO2/TiO2 double shell have been prepared for methylene blue dye adsorption. the preparation procedure is controlled to prepare the magnetic core with further coating layers from silica and titania. The prepared Fe3O4core-meso SiO2/TiO2 double shell showed adsorption capacity for methylene blue removal about 50 mg/g at pH 6 after 80 min contact time form 50 ppm methylene blue solution. The adsorption process of methylene blue onto Fe3O4core-meso SiO2/TiO2 double shell was well fitted with the pseudo-second-order kinetic model and freundlish isotherm, indicating a quick and multilayer adsorption mechanism.

Keywords: magnetic core, silica shell, titania shell, water treatment, methylene blue, solvo-thermal process, adsorption

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Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

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The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

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Authors: C. H. Chang, R. Z. Qiu, C. W. Tsao, Y. H. Cheng, C. H. Chen, W. J. Hsueh

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Characteristics of photoluminescence (PL) in a resonant quasi-periodic double-period quantum wells (DPQW) are demonstrated. The maximum PL intensity in the DPQW is remarkably greater than that in a traditional periodic QW (PQW) under the Bragg or anti-Bragg conditions. The optimal PL spectrum in the DPQW has an asymmetrical form instead of the symmetrical form in the PQW. Moreover, there are two large values of PL intensity in the DPQW, which also differs from the PQW.

Keywords: Photoluminescence, quantum wells, quasiperiodic structure

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Authors: Minh Tu Le, Quang Huy Nguyen, Mai Lan Nguyen

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Bonding characteristics between pavement layers have an important influence on responses of pavement structures. This paper deals with analytical solution for the stresses, strains, and deflections of double-layered asphalt pavement structure. This solution is based on the homogeneous half-space of layered theory developed by Burmister (1943). The partial interaction between the layers is taken into account by considering an interface bonding behavior which is obtained by push-out shear test. Numerical applications considering three cases of bonding (unbonded, partially bonded, and fully bonded overlays) are carried out to the influence of the interface bonding on the structural behavior of asphalt pavement under static loading. Further, it was observed that numerical results indicate that the horizontal shear reaction modulus at the interface (Ks) will significantly affect pavement structure behavior.

Keywords: analytical solution, interface bonding, shear test keyword, double-layered asphalt, shear reaction modulus

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Authors: Jiajia Yao, Guanlin Wu, Fang Liu, Junshuai Xue, Yue Hao

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This study reports on the epitaxial growth of a GaN-based resonant tunneling diode (RTD) structure with stable and repeatable double negative differential resistance (NDR) characteristics at room temperature on a c-plane GaN-on-sapphire template using plasma-assisted molecular beam epitaxy (PA-MBE) technology. In this structure, two independent AlN/GaN RTDs are epitaxially connected in series in the vertical growth direction through a silicon-doped GaN layer. As the collector electrode bias voltage increases, the two RTDs respectively align the ground state energy level in the quantum well with the 2DEG energy level in the emitter accumulation well to achieve quantum resonant tunneling and then reach the negative differential resistance (NDR) region. The two NDR regions exhibit similar peak current densities and peak-to-valley current ratios, which are 230 kA/cm² and 249 kA/cm², 1.33 and 1.38, respectively, for a device with a collector electrode mesa diameter of 1 µm. The consistency of the NDR is much higher than the results of on-chip discrete RTD device interconnection, resulting from the smaller chip area, fewer interconnect parasitic parameters, and less process complexity. The methods and results presented in this paper show the brilliant prospects of GaN RTDs in the development of multi-value logic digital circuits.

Keywords: MBE, AlN/GaN, RTDs, double NDR

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Authors: Meng H. Lean, Wei-Ping L. Chu

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The effects of ferroelectric nanofiller size, shape, loading, and polarization, on bipolar charge injection, transport, and recombination through amorphous and semicrystalline polymers are studied. A 3D particle-in-cell model extends the classical electrical double layer representation to treat ferroelectric nanoparticles. Metal-polymer charge injection assumes Schottky emission and Fowler-Nordheim tunneling, migration through field-dependent Poole-Frenkel mobility, and recombination with Monte Carlo selection based on collision probability. A boundary integral equation method is used for solution of the Poisson equation coupled with a second-order predictor-corrector scheme for robust time integration of the equations of motion. The stability criterion of the explicit algorithm conforms to the Courant-Friedrichs-Levy limit. Trajectories for charge that make it through the film are curvilinear paths that meander through the interspaces. Results indicate that charge transport behavior depends on nanoparticle polarization with anti-parallel orientation showing the highest leakage conduction and lowest level of charge trapping in the interaction zone. Simulation prediction of a size range of 80 to 100 nm to minimize attachment and maximize conduction is validated by theory. Attached charge fractions go from 2.2% to 97% as nanofiller size is decreased from 150 nm to 60 nm. Computed conductivity of 0.4 x 1014 S/cm is in agreement with published data for plastics. Charge attachment is increased with spheroids due to the increase in surface area, and especially so for oblate spheroids showing the influence of larger cross-sections. Charge attachment to nanofillers and nanocrystallites increase with vol.% loading or degree of crystallinity, and saturate at about 40 vol.%.

Keywords: nanocomposites, nanofillers, electrical double layer, bipolar charge transport

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Authors: Abdulrahman S. Alturki, John S. Loomis

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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

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Authors: Shimeles Terefe Mengistue, Paola Marziani, Ascensióndel Olmo, Jaime Perea, Mirjana Pović

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The theory that rotating accretion disks are responsible for the broad emission-line profiles in quasars is frequently put forth; however, the presence of accretion disk (AD) in active galactic nuclei (AGN) had limited and indirect observational support. In order to evaluate the extent to which the AD is a source of the broad Balmer lines and high ionization UV lines in radio-loud (RL) AGN, we focused on an extremely jetted RL quasar, 3C 47 that clearly shows a double peaked profile. This work presents its optical spectra and UV observations from the HST/FOS covering the rest-frame spectral range from 2000 to 7000 \AA. The fit of the low ionization lines, Hbeta, Halpha and MgII2800 show profiles that are in very good agreement with a relativistic Keplerian AD model. The profile of the prototypical high ionization lines can also be modeled by the contribution of the AD, with additional components due to outflows and emissions from the innermost part of the narrow line regions (NLRs). A prominent fit of the resulting double peaked profiles were found and very important disk parameters of the disk have been determined using the Hbeta, Halpha and MgII2800 lines: the inner and outer radii (both in units of G/mbh, where mbh is the supermassive black hole), an inclination to the line of sight, the emissivity index and the local broadening parameter. In addition, the accretion parameters, /mbh and /lledd are also determined. This work indicates that the line profile of 3C 47 shows the most convincing direct evidence for the presence of a rotating AD in AGN and the broad, double-peaked profiles originate from this AD that surrounds an /mbh.

Keywords: active galactic nuclei, quasars, emission lines, Double-peaked, supermassive black hole

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Authors: B. Rakjarit, S. Athichanagorn

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Double displacement process is a method in which gas is injected at an updip well to displace the oil bypassed by waterflooding operation from downdip water injector. As gas injection is costly and a large amount of gas is needed, gas dump-flood from multiple gas reservoirs is an attractive alternative. The objective of this paper is to demonstrate the benefits of the novel approach of double displacement process via gas dump-flood from multiple gas reservoirs. A reservoir simulation model consisting of a dipping oil reservoir and several underlying layered gas reservoirs was constructed in order to investigate the performance of the proposed method. Initially, water was injected via the downdip well to displace oil towards the producer located updip. When the water cut at the producer became high, the updip well was shut in and perforated in the gas zones in order to dump gas into the oil reservoir. At this point, the downdip well was open for production. In order to optimize oil recovery, oil production and water injection rates and perforation strategy on the gas reservoirs were investigated for different numbers of gas reservoirs having various depths and thicknesses. Gas dump-flood from multiple gas reservoirs can help increase the oil recovery after implementation of waterflooding upto 10%. Although the amount of additional oil recovery is slightly lower than the one obtained in conventional double displacement process, the proposed process requires a small completion cost of the gas zones and no operating cost while the conventional method incurs high capital investment in gas compression facility and high-pressure gas pipeline and additional operating cost. From the simulation study, oil recovery can be optimized by producing oil at a suitable rate and perforating the gas zones with the right strategy which depends on depths, thicknesses and number of the gas reservoirs. Conventional double displacement process has been studied and successfully implemented in many fields around the world. However, the method of dumping gas into the oil reservoir instead of injecting it from surface during the second displacement process has never been studied. The study of this novel approach will help a practicing engineer to understand the benefits of such method and can implement it with minimum cost.

Keywords: gas dump-flood, multi-gas layers, double displacement process, reservoir simulation

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

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Authors: Ahmed Salam, Haithem Benkahla

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Recently, an efficient backward-stable algorithm for computing eigenvalues and vectors of a symmetric and Hamiltonian matrix has been proposed. The method preserves the symmetric and Hamiltonian structures of the original matrix, during the whole process. In this paper, we revisit the method. We derive a way for implementing the reduction of the matrix to the appropriate condensed form. Then, we construct a novel version of the implicit QR-algorithm for computing the eigenvalues and vectors.

Keywords: block implicit QR algorithm, preservation of a double structure, QR algorithm, symmetric and Hamiltonian structures

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Authors: T. Sanches, K. Bousson

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As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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Authors: Mohamed Belhorma, Aboubakar S. Bouchikhi, Belkacem Bounab

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This paper addresses modeling a Double A-Arm suspension, a three-dimensional nonlinear model has been developed using the multibody systems formalism. Dynamical study of the different components responses was done, particularly for the wheel assembly. To validate those results, the system was constructed and simulated by RecurDyn, a professional multibody dynamics simulation software. The model has been used as the Objectif function in an optimization algorithm for ride quality improvement.

Keywords: double A-Arm suspension, multibody systems, ride quality optimization, dynamic simulation

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Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

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The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate

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Authors: Abbaas I. Kareem, H. Nikraz

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The use of recycled concrete aggregates (RCAs) in hot-mix asphalt (HMA) production could ease natural aggregate shortage and maintain sustainability in modern societies. However, it was the attached cement mortar and other impurities that make the RCAs behave differently than high-quality aggregates. Therefore, different upgrading treatments were suggested to enhance its properties before being used in HMA production. Disappointedly, some of these treatments had caused degradation to some RCA properties. In order to avoid degradation, a coating technique is developed. This technique is based on combining of two main treatments, so it is named as double coating technique (DCT). Dosages of 0%, 20%, 40% and 60% uncoated RCA, RCA coated with Cement Slag Paste (CSP), and Double Coated Recycled Concrete Aggregates (DCRCAs) in place of granite aggregates were evaluated. The results indicated that the DCT improves strength and reduces water absorption of the DCRCAs compared with uncoated RCAs and RCA coated with CSP. In addition, the DCRCA asphalt mixtures exhibit stability values higher than those obtained for mixes made with granite aggregates, uncoated RCAs and RCAs coated with CSP. Also, the DCRCA asphalt mixtures require less bitumen to achieve the optimum bitumen content (OBC) than those manufactured with uncoated RCA and RCA-coated with CSP. Although the results obtained were encouraging, more testing is required in order to examine the effect of the DCT on performance properties of DCRCA- asphalt mixtures such as rutting and fatigue.

Keywords: aggregate crashed value, double coating technique, hot mix asphalt, Marshall parameters, recycled concrete aggregates

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Authors: Hatice Boyacioglu, Nursel Akkaya, Humeyra Ozge Yilanci, Hilmi Kansu, Nihal Avcu

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The strong relationship between the reduction in the size of the pulp cavity and increasing age has been reported in the literature. This relationship can be utilized to estimate the age of an individual by measuring the pulp cavity size using dental radiographs as a non-destructive method. The purpose of this study is to develop a population specific regression model for age estimation in a sample of Turkish adults by applying Cameriere’s method on panoramic radiographs. The sample consisted of 100 panoramic radiographs of Turkish patients (40 men, 60 women) aged between 20 and 70 years. Pulp and tooth area ratios (AR) of the maxilla¬¬ry canines were measured by two maxillofacial radiologists and then the results were subjected to regression analysis. There were no statistically significant intra-observer and inter-observer differences. The correlation coefficient between age and the AR of the maxillary canines was -0.71 and the following regression equation was derived: Estimated Age = 77,365 – ( 351,193 × AR ). The mean prediction error was 4 years which is within acceptable errors limits for age estimation. This shows that the pulp/tooth area ratio is a useful variable for assessing age with reasonable accuracy. Based on the results of this research, it was concluded that Cameriere’s method is suitable for dental age estimation and it can be used for forensic procedures in Turkish adults. These instructions give you guidelines for preparing papers for conferences or journals.

Keywords: age estimation by teeth, forensic dentistry, panoramic radiograph, Cameriere's method

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Authors: Vikram Saini, Lillie Dewan

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This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: Samriti Wadhwa, Beena Kumari

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Background and Significance: Residue levels of ready mix (chlorpyriphos 50% and cypermethrin 5%), cypermethrin and chlorpyriphos individually in sandy loam soil under okra fruits (Variety, Varsha Uphar) were determined; a field experiment was conducted at Research Farm of Department of Entomology of Chaudhary Charan Singh Haryana Agriculture University, Hisar, Haryana, India. Persistence behavior of cypermethrin and chlorpyriphos was studied following application of a pre-mix formulation of insecticides viz. Action-505EC, chlorpyriphos (Radar 20 EC) and cypermethrin (Cyperkill 10 EC) at the recommended dose and double the recommended dose along with control at fruiting stage. Pesticide application also leads to decline in soil acarine fauna which is instrumental in the breakdown of the litter because of which minerals are released into the soil. So, by this study, one can evaluate the safety of pesticides for the soil health. Methodology: Action-505EC (chlorpyriphos 50% and cypermethrin 5%) at 275 g a .i. ha⁻¹ (single dose) and 550 g a. i. ha⁻¹ (double dose), chlorpyriphos (Radar 20 EC) at 200 g a. i. ha⁻¹ (single dose) and 400 g a. i. ha⁻¹ (double dose) and cypermethrin (Cyperkill 10 EC) at 50 g a. i. ha⁻¹ (single dose) and 100 g a. i. ha⁻¹ (double dose) were applied at the fruiting stage on okra crop. Samples of soils from okra field were collected periodically at 0 (1h after spray), 1, 3, 5, 7, 10, 15 days and at harvest after application as well of control soil sample. After air drying, adsorbing through Florisil and activated charcoal and eluting with hexane: acetone (9:1) then residues in soils were estimated by a gas chromatograph equipped with a capillary column and electron capture detector. Results: No persistence of cypermethrin in ready-mix in soil under okra fruits at single and double dose was observed. In case of chlorpyriphos in ready-mix, average initial deposits on 0 (1 h after treatment) day was 0.015 mg kg⁻¹ and 0.036 mg kg⁻¹ which persisted up to 5 days and up to 7 days for single and double dose, respectively. After that residues reached below a detectable level of 0.010 mg kg⁻¹. Experimental studies on cypermethrin individually revealed that average initial deposits on 0 (1 h after treatment) were 0.008 mg kg⁻¹ and 0.012 mg kg⁻¹ which persisted up to 3 days and 5 days for single and double dose, respectively after that residues reached to below detectable level. The initial deposits of chlorpyriphos individually in soil were found to be 0.055 mg kg⁻¹ and 0.113 mg kg⁻¹ which persisted up to 7 days and 10 days at a lower dose and higher dose, respectively after that residues reached to below determination level. Conclusion: In soil under okra crop, only individual cypermethrin in both the doses persisted whereas no persistence of cypermethrin in ready-mix was observed. Persistence of chlorpyriphos individually is more as compared to chlorpyriphos in ready-mix in both the doses. Overall, the persistence of chlorpyriphos in soil under okra crop is more than cypermethrin.

Keywords: chlorpyriphos, cypermethrin, okra, ready mix, soil

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Authors: Ashwani Kumar

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GPS plays an important role in everyday life for safe and convenient transportation. While pedestrians use hand held devices to know their position in a city, vehicles in intelligent transport systems use relatively sophisticated GPS receivers for estimating their current position. However, in urban areas where the GPS satellites are occluded by tall buildings, trees and reflections of GPS signals from nearby vehicles, GPS position estimation becomes poor. In this work, an exhaustive GPS data is collected at a single point in urban area under different times of day and under dynamic environmental conditions. The data is analyzed and statistical refinement methods are used to obtain optimal position estimate among all the measured positions. The results obtained are compared with publically available datasets and obtained position estimation refinement results are promising.

Keywords: global positioning system, statistical approach, intelligent transport systems, least squares estimation

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Authors: Dong-Ho Kim, Zheng-Xun Jin, Yong-Woon Cha, Su-Sang Lim, Sang-Won Han, Chang-Taek Hyun

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As construction is a labor-intensive industry, it is important to identify and manage labor quantities for accurate progress management of the construction project. However, the progress management that focuses on construction cost calculated based on materials rather than labor quantities has led to a difference in the implementation of cost and progress of the actual construction. In addition, since it is not easy to predict accurate labor quantities in the estimation of labor quantity-based progress rate, there have been limited researches into the progress rate estimation based on labor quantity. Accordingly, this study proposed a process for labor quantity-based progress rate estimation using a standard of estimate to predict accurate progress rate of the construction project in Republic Korea. It is expected that the utilization of the proposed process will help to identify the progress rate closer to that of the actual site management and adjust the workforce in each construction type, thereby contributing to improving construction efficiency.

Keywords: labor based, labor cost, progress management, progress rate, progress payment

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Authors: E. H. N. Gashti, M. Malaska, K. Kujala

Abstract:

The thermo-mechanical behaviour of concrete energy pile foundations with different single and double U-tube shapes incorporated was analysed using the Comsol Multi-physics package. For the analysis, a 3D numerical model in real scale of the concrete pile and surrounding soil was simulated regarding actual operation of ground heat exchangers (GHE) and the surrounding ambient temperature. Based on initial ground temperature profile measured in situ, tube inlet temperature was considered to range from 6°C to 0°C (during the contraction process) over a 30-day period. Extra thermal stresses and deformations were calculated during the simulations and differences arising from the use of two different systems (single-tube and double-tube) were analysed. The results revealed no significant difference for extra thermal stresses at the centre of the pile in either system. However, displacements over the pile length were found to be up to 1.5-fold higher in the double-tube system than the single-tube system.

Keywords: concrete energy piles, stresses, displacements, thermo-mechanical behaviour, soil-structure interactions

Procedia PDF Downloads 189

Authors: Yulong Wang, Yuan Yan Tang, Cuiming Zou, Lina Yang

Abstract:

This paper presents a novel sparse representation method for robust pattern classification. Generalized orthogonal matching pursuit (GOMP) is a recently proposed efficient sparse representation technique. However, GOMP adopts the mean square error (MSE) criterion and assign the same weights to all measurements, including both severely and slightly corrupted ones. To reduce the limitation, we propose an information-theoretic GOMP (ITGOMP) method by exploiting the correntropy induced metric. The results show that ITGOMP can adaptively assign small weights on severely contaminated measurements and large weights on clean ones, respectively. An ITGOMP based classifier is further developed for robust pattern classification. The experiments on public real datasets demonstrate the efficacy of the proposed approach.

Keywords: correntropy induced metric, matching pursuit, pattern classification, sparse representation

Procedia PDF Downloads 332

Authors: Savita, Anurag Sharma, Harsukhpreet Singh

Abstract:

Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

Procedia PDF Downloads 380

Authors: Matjaž Divjak, Simon Zelič, Aleš Holobar

Abstract:

We present a dedicated video-based monitoring system for quantification of patient’s attention to visual feedback during robot assisted gait rehabilitation. Two different approaches for eye gaze and head pose tracking are tested and compared. Several metrics for assessment of patient’s attention are also presented. Experimental results with healthy volunteers demonstrate that unobtrusive video-based gaze tracking during the robot-assisted gait rehabilitation is possible and is sufficiently robust for quantification of patient’s attention and assessment of compliance with the rehabilitation therapy.

Keywords: video-based attention monitoring, gaze estimation, stroke rehabilitation, user compliance

Procedia PDF Downloads 397