Search results for: peak estimation

Authors: Hasik Lee, Seung-Young Kho

Abstract:

Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

Procedia PDF Downloads 324

Authors: Zaid Jamal Saeed Almahmoud

Abstract:

Our increasing reliance on electricity, with inefficient consumption trends, has resulted in several economical and environmental threats. These threats include wasting billions of dollars, draining limited resources, and elevating the impact of climate change. As a solution, the smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing the peak power consumption under a fixed delay requirement is a significant problem in the smart grid. In addition, matching demand to supply is a key requirement for the success of the future electricity. In this work, we consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-Hard, we propose two versions of a heuristic algorithm for solving this problem. Our theoretical analysis and experimental results show that our proposed heuristics outperform existing methods by providing a better approximation to the optimal solution. In addition, we consider dynamic pricing methods to minimize the peak load and match demand to supply in the smart grid. Our contribution is the proposal of generic, as well as customized pricing heuristics to minimize the peak demand and match demand with supply. In addition, we propose optimal pricing algorithms that can be used when the maximum deadline period of the power jobs is relatively small. Finally, we provide theoretical analysis and conduct several experiments to evaluate the performance of the proposed algorithms.

Keywords: heuristics, optimization, smart grid, peak demand, power supply

Procedia PDF Downloads 61

Authors: Kalu Ram Meena, Aditi Kar Gangopadhyay, Satrajit Mandal

Abstract:

Two normal populations with different means and same variance are considered, where the variances are known. The population with the smaller sample mean is selected. Various estimators are constructed for the mean of the selected normal population. Finally, they are compared with respect to the bias and MSE risks by the method of Monte-Carlo simulation and their performances are analysed with the help of graphs.

Keywords: estimation after selection, Brewster-Zidek technique, estimators, selected populations

Procedia PDF Downloads 476

Authors: Ludovic Fabre, Paola Melani, Patrick Lemaire

Abstract:

The goal of this study was to test whether and how emotions influence drone operators in estimation skills. The empirical study was run in the context of numerical estimation. Participants saw a two-digit number together with a collection of cars. They had to indicate whether the stimuli collection was larger or smaller than the number. The two-digit numbers ranged from 12 to 27, and collections included 3-36 cars. The presentation of the collections was dynamic (each car moved 30 deg. per second on the right). Half the collections were smaller collections (including fewer than 20 cars), and the other collections were larger collections (i.e., more than 20 cars). Splits between the number of cars in a collection and the two-digit number were either small (± 1 or 2 units; e.g., the collection included 17 cars and the two-digit number was 19) or larger (± 8 or 9 units; e.g., 17 cars and '9'). Half the collections included more items (and half fewer items) than the number indicated by the two-digit number. Before and after each trial, participants saw an image inducing negative emotions (e.g., mutilations) or neutral emotions (e.g., candle) selected from International Affective Picture System (IAPS). At the end of each trial, participants had to say if the second picture was the same as or different from the first. Results showed different effects of emotions on RTs and percent errors. Participants’ performance was modulated by emotions. They were slower on negative trials compared to the neutral trials, especially on the most difficult items. They errored more on small-split than on large-split problems. Moreover, participants highly overestimated the number of cars when in a negative emotional state. These findings suggest that emotions influence numerical estimation, that effects of emotion in estimation interact with stimuli characteristics. They have important implications for understanding the role of emotions on estimation skills, and more generally, on how emotions influence cognition.

Keywords: drone operators, emotion, numerical estimation, arithmetic

Procedia PDF Downloads 87

Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

Abstract:

Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

Procedia PDF Downloads 325

Authors: Mikiyas Adugna

Abstract:

Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

Procedia PDF Downloads 24

Authors: Keunhong Chae, Seokho Yoon

Abstract:

We address the integer frequency offset (IFO) estimation under the influence of the timing offset (TO) in orthogonal frequency division multiplexing (OFDM) systems. Incorporating the IFO and TO into the symbol set used to represent the received OFDM symbol, we investigate the influence of the TO on the IFO, and then, propose a combining method between two consecutive OFDM correlations, reducing the influence. The proposed scheme has almost the same complexity as that of the conventional schemes, whereas it does not need the TO knowledge contrary to the conventional schemes. From numerical results it is confirmed that the proposed scheme is insensitive to the TO, consequently, yielding an improvement of the IFO estimation performance over the conventional schemes when the TO exists.

Keywords: estimation, integer frequency offset, OFDM, timing offset

Procedia PDF Downloads 441

Authors: Mohammad Hedar

Abstract:

This paper presents selected topics from the area of high-speed electrical machine control with a focus on loss minimization. It focuses on pulse amplitude modulation (PAM) set-up in order to minimize the inrush current peak. An overview of these machines and the control topologies that have been used with these machines are reported. The critical problem that happens when controlling a high-speed electrical motor is the high current peak in the start-up process, which will cause high power-losses. The main goal of this paper is to clarify how the inrush current peak can be minimized in the start-up process. PAM control method is proposed to use in the frequency inverter, simulation results for PAM & PWM control method, and steps to improve the PAM control are reported. The simulations were performed with data for PMSM (nominal speed: 25 000 min-1, power: 3.1 kW, load: 1.2 Nm).

Keywords: control topology, frequency inverter, high-speed electrical machines, PAM, power losses, PWM

Procedia PDF Downloads 88

Authors: P. S. Jain, K. D. Bobade, S. J. Surana

Abstract:

A simple, selective, precise and Stability-indicating High-performance thin-layer chromatographic method for analysis of Naftopidil both in a bulk and in pharmaceutical formulation has been developed and validated. The method employed, HPTLC aluminium plates precoated with silica gel as the stationary phase. The solvent system consisted of hexane: ethyl acetate: glacial acetic acid (4:4:2 v/v). The system was found to give compact spot for Naftopidil (Rf value of 0.43±0.02). Densitometric analysis of Naftopidil was carried out in the absorbance mode at 253 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.999±0.0001 with respect to peak area in the concentration range 200-1200 ng per spot. The method was validated for precision, recovery and robustness. The limits of detection and quantification were 20.35 and 61.68 ng per spot, respectively. Naftopidil was subjected to acid and alkali hydrolysis, oxidation and thermal degradation. The drug undergoes degradation under acidic, basic, oxidation and thermal conditions. This indicates that the drug is susceptible to acid, base, oxidation and thermal conditions. The degraded product was well resolved from the pure drug with significantly different Rf value. Statistical analysis proves that the method is repeatable, selective and accurate for the estimation of investigated drug. The proposed developed HPTLC method can be applied for identification and quantitative determination of Naftopidil in bulk drug and pharmaceutical formulation.

Keywords: naftopidil, HPTLC, validation, stability, degradation

Procedia PDF Downloads 377

Authors: K. Kouzi

Abstract:

In order to have stable and high performance of direct torque and flux control (DTFC) of double star induction motor drive (DSIM), proper on-line adaptation of the stator resistance is very important. This is inevitably due to the variation of the stator resistance during operating conditions, which introduces error in estimated flux position and the magnitude of the stator flux. Error in the estimated stator flux deteriorates the performance of the DTFC drive. Also, the effect of error in estimation is very important especially at low speed. Due to this, our aim is to overcome the sensitivity of the DTFC to the stator resistance variation by proposing on-line fuzzy estimation stator resistance. The fuzzy estimation method is based on an on-line stator resistance correction through the variations of the stator current estimation error and its variations. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of the suggested algorithm control is to avoid the drive instability that may occur in certain situations and ensure the tracking of the actual stator resistance. The validity of the technique and the improvement of the whole system performance are proved by the results.

Keywords: direct torque control, dual stator induction motor, Fuzzy Logic estimation, stator resistance adaptation

Procedia PDF Downloads 296

Authors: K. Ebrahimi, Sh. Shahid, M. Mohammadi Ghaleni, M. H. Omid

Abstract:

The longitudinal dispersion coefficient is a crucial parameter for 1-D water quality analysis of riverine flows. So far, different types of empirical equations for estimation of the coefficient have been developed, based on various case studies. The main objective of this paper is to develop an empirical equation for estimation of the coefficient for a riverine flow. For this purpose, a set of tracer experiments was conducted, involving salt tracer, at three sections located in downstream of a lengthy canal. Tracer data were measured in three mixing lengths along the canal including; 45, 75 and 100m. According to the results, the obtained coefficients from new developed empirical equation gave an encouraging level of agreement with the theoretical values.

Keywords: coefficients, dispersion, river, tracer, water quality

Procedia PDF Downloads 362

Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

Abstract:

The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

Procedia PDF Downloads 455

Authors: O. Moussous, T. Medjadj

Abstract:

The suitability of a Fricke dosimeter for the measurement of a relative depth dose profile and the peak scatter factors was studied. The measurements were carried out in the secondary standard dosimetry laboratory at CRNA Algiers using a collimated 60Co gamma source teletherapy machine. The measurements were performed for different field sizes at the phantom front face, at a fixed source-to-phantom distance of 80 cm. The dose measurements were performed by first placing the dosimeters free-in-air at the distance-source-detector (DSD) of 80.5 cm from the source. Additional measurements were made with the phantom in place. The water phantom type Med-Tec 40x40x40 cm for vertical beam was used in this work as scattering martial. The phantom was placed on the irradiation bench of the cobalt unit at the SSD of 80 cm from the beam focus and the centre of the field coincided with the geometric centre of the dosimeters placed at the depth in water of 5 mm Relative depth dose profile and Peak scatter factors measurements were carried out using our Fricke system. This was intercompared with similar measurements by ionization chamber under identical conditions. There is a good agreement between the relative percentage depth–dose profiles and the PSF values measured by both systems using a water phantom.

Keywords: Fricke dosimeter, depth–dose profiles, peak scatter factors, DSD

Procedia PDF Downloads 228

Authors: Yi Tse Wang, Che Hsiu Chen, Zih Jian Huang, Hon Wen Cheng

Abstract:

Stretching treatments enhanced flexibility. On the other hand, decreases in hamstrings strength have been reported after stretching, especially with static stretching or passive stretching. Stretching has been shown to be more effective than static stretching to improve muscle performance, but a clear consensus for the effect of dynamic stretching on muscle performance has not been achieved. The purpose of this study was to compare the acute effect of a dynamic stretching, static stretching and eccentric exercise protocol on hamstrings stiffness, flexibility and muscle strength. Forty-five healthy active men (height 179.9 cm; weight 71.5 kg; age 22.5 years) were participated in 3 randomly ordered testing sessions: dynamic stretching (DS), active static stretching (ASS), and passive static stretching (PSS). All the stretch were performed 30 seconds and repeated 6 times. There was a 30-second interval between repetitions. The outcome measures were isokinetic concentric contraction (60°/s), eccentric contraction (30°/s) peak torque, muscle flexibility after stretching. The results showed that the muscle flexibility (3.6%, 3.9% and 1.59%, respectively) increased significantly after DS, PSS and ASS. Hamstring isokinetic concentric peak torque (-6.4%, -8.0% and -5.8%, respectively) and eccentric peak torque (-5.8%, -4.5% and -5.4%, respectively) decreased significantly after DS, PSS and ASS. Hence, although the stretching protocols improve hamstrings flexibility immediately, reduced hamstring muscle eccentric and concentric peak torque.

Keywords: hamstrings injury, warm-up, muscle performance, muscle stretching

Procedia PDF Downloads 349

Authors: Felix Aberu

Abstract:

The high rate of greenhouse gas (CO₂) emission and increased concentration of Carbon Dioxide in the atmosphere are not unconnected to both human and natural activities. This has caused climate change and global warming in the world. The adverse effect of these climatic changes has no doubt threatened human existence. Hence, this study examined the effects of environmental and climate influence on mortality and morbidity rates, with particular reference to the world’s leading CO₂ emission countries, using both the pre-estimation, estimation, and post-estimation techniques for more dependable outcomes. Hence, the System Generalized Method of Moments (SGMM) was adopted as the main estimation technique for the data analysis from 1996 to 2023. The coefficient of carbon emissions confirmed a positive and significant relationship among CO₂ emission, mortality, and morbidity rates in the world’s leading CO₂ emissions countries, which implies that carbon emission has contributed to mortality and morbidity rates in the world. Therefore, significant action should be taken to facilitate the expansion of environmental protection and sustainability initiatives in any CO₂ emissions nations of the world.

Keywords: environmental, mortality, morbidity, health outcomes, carbon emissions

Procedia PDF Downloads 18

Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

Abstract:

Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

Procedia PDF Downloads 427

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

Abstract:

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

Procedia PDF Downloads 579

Authors: Amir A. Beltagi, Ahmed R. Abdelbaki

Abstract:

Background: Core stability training has recently attracted attention for optimizing performance and improving muscle balance for healthy and unhealthy individuals. The purpose of this study was to investigate the effect of beginner’s core stability exercises on the trunk flexors’/extensors’ peak torque ratio and trunk flexors’ and extensors’ peak torques. Methods: Thirty five healthy individuals, randomly assigned into two groups; experimental (group I) and control (group II), participated in the study. Group I involved 20 participants (10 male & 10 female) with mean ±SD age, weight, and height of 20.7±2.4 years, 66.5±12.1 kg and 166.7±7.8 cm respectively. Group II involved 15 participants (6 male & 9 female) with mean ±SD age, weight, and height of 20.3±0.61 years, 68.57±12.2 kg and 164.28 ±7.59 cm respectively. Data were collected using the Biodex Isokinetic system. The participants were tested twice; before and after a 6-week period during which the experimental group performed a core stability training program. Findings: Statistical analysis using the 2x2 Mixed Design ANOVA revealed that there were no significant differences in the trunk flexors’/extensors’ peak torque ratio between the ‘pre’ and ‘post’ tests for either group (p > 0.025). Moreover, there were no significant differences in the trunk flexors’/extensors’ ratios between both groups at either test (p > 0.025). Meanwhile, the 2x2 Mixed Design MANOVA revealed that there were significant differences in the trunk flexors’ and extensors’ peak torques between the ‘pre’ and ‘post’ tests for group I (p < 0.025), while there were no significant differences inbetween for group II (p > 0.025). Moreover, there were no significant differences between both groups for the tested muscles’ peak torques at either test except for that of the trunk flexors at the ‘post’ test only (p < 0.025). Interpretation: The improvement in muscle performance indicated by the increase in the trunk flexors’ and extensors’ peak torques in the experimental group recommends including core stability training in the exercise programs that aim to improve muscle performance.

Keywords: core stability, isokinetic, trunk muscles, muscle balance

Procedia PDF Downloads 275

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

Abstract:

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

Procedia PDF Downloads 116

Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

Abstract:

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

Procedia PDF Downloads 285

Authors: Alcardo Alex Barakabitze, Saddam Aziz, Muhammad Zubair

Abstract:

The Orthogonal Frequency Division Multiplexing (OFDM) is a special form of multicarrier transmission that splits the total transmission bandwidth into a number of orthogonal and non-overlapping subcarriers and transmit the collection of bits called symbols in parallel using these subcarriers. In this paper, we explore the Peak to Average Power Reduction (PAPR) problem in OFDM systems. We provide the performance analysis of CCDF and BER through MATLAB simulations.

Keywords: bit error ratio (BER), OFDM, peak to average power reduction (PAPR), sub-carriers

Procedia PDF Downloads 509

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

Abstract:

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

Procedia PDF Downloads 422

Authors: Vikram Saini, Lillie Dewan

Abstract:

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

Procedia PDF Downloads 366

Authors: Ashwani Kumar

Abstract:

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

Procedia PDF Downloads 260

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

Abstract:

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

Procedia PDF Downloads 307

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 378

Authors: Nicholas Bayfield, Liam Bibo, Charley Budgeon, Robert Larbalestier, Tom Briffa

Abstract:

Introduction: Stress hyperglycaemia is common following cardiac surgery. Its optimal management is uncertain and may differ by diabetic status. This study assesses the in-hospital glycaemic management of cardiac surgery patients and associated postoperative outcomes. Methods: A retrospective cohort analysis of all patients undergoing cardiac surgery at Fiona Stanley Hospital from February 2015 to May 2019 was undertaken. Management and outcomes of hyperglycaemia following cardiac surgery were assessed. Follow-up was assessed to 1 year postoperatively. Multivariate regression modelling was utilised. Results: 1050 non-diabetic patients and 689 diabetic patients were included. In the non-diabetic cohort, patients with mild (peak blood sugar level [BSL] < 14.3), transient stress hyperglycaemia managed without insulin were not at an increased risk of wound-related morbidity (P=0.899) or mortality at 1 year (P=0.483). Insulin management was associated with wound-related readmission to hospital (P=0.004) and superficial sternal wound infection (P=0.047). Prolonged or severe stress hyperglycaemia was predictive of hospital re-admission (P=0.050) but not morbidity or mortality (P=0.546). Diabetes mellitus was an independent risk factor 1-year mortality (OR; 1.972 [1.041–3.736], P=0.037), graft harvest site wound infection (OR; 1.810 [1.134–2.889], P=0.013) and wound-related readmission (OR; 1.866 [1.076–3.236], P=0.026). In diabetics, postoperative peak BSL > 13.9mmol/L was predictive of graft harvest site infections (OR; 3.528 [1.724-7.217], P=0.001) and wound-related readmission OR; 3.462 [1.540-7.783], P=0.003) regardless of modality of management. A peak BSL of 10.0-13.9 did not increase the risk of morbidity/mortality compared to a peak BSL of < 10.0 (P=0.557). Diabetics with a peak BSL of 13.9 or less did not have significantly increased morbidity/mortality outcomes compared to non-diabetics (P=0.418). Conclusion: In non-diabetic patients, transient mild stress hyperglycaemia following cardiac surgery does not uniformly require treatment. In diabetic patients, postoperative hyperglycaemia with peak BSL exceeding 13.9mmol/L was associated with wound-related morbidity and hospital readmission following cardiac surgery.

Keywords: cardiac surgery, pulmonary embolism, pulmonary embolectomy, cardiopulmonary bypass

Procedia PDF Downloads 135

Authors: Srutirekha Giri, Manoranjan Sahoo, Anuradha Das, Pravanjan Mallick, Biswajit Mallick

Abstract:

Ion Beam (IB) technique is a very powerful experimental technique for both material synthesis and material modifications. In this work, 3MeV proton beam was generated using the 3MV Tandem machine of the Institute of Physics, Bhubaneswar and extracted into air for the irradiation-induced modification purpose[1]. The polymeric material can be modeled for a three-phase system viz. crystalline(I), amorphous(II) and mesomorphic(III). So far, our knowledge is concerned. There are only few techniques reported for the synthesis of this third-phase(III) of polymer. The IB induced technique is one of them and has been reported very recently [2-4]. It was observed that by irradiating polyethylene terephthalate (PET) fiber at very low proton fluence, 10¹⁰ - 10¹² p/s, possess 2D mesophase structure. This was confirmed using X-ray diffraction technique. A low-intensity broad peak was observed at small angle of about 2θ =6º, when the fiber axis was mounted parallel to the X-ray direction. Such peak vanished in the diffraction spectrum when the fiber axis was mounted perpendicular to the beam direction. The appearance of this extra peak in a particular orientation confirms that the phase is 2-dimensionally oriented (mesophase). It is well known that the mesophase is a 2-dimensionally ordered structure but 3-dimensionally disordered. Again, the crystallite of the mesophase peak particle was measured about 3nm. The MeV proton-induced 2D mesophase patterning of nanocrystallites (3nm) of PET due to irradiation was observed within the above low fluence range and failed in high proton fluence. This is mainly due to the breaking of crystallites, radiation-induced thermal degradation, etc.

Keywords: Ion irradiation, mesophase, nanocrystallites, polymer

Procedia PDF Downloads 170

Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

Abstract:

Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

Procedia PDF Downloads 297

Authors: Qiang Wang, Hongyang Yu

Abstract:

Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

Procedia PDF Downloads 46