Search results for: cumulative distribution function

Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

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Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, road network, selection method, spatial information expression, distribution pattern

Procedia PDF Downloads 381

Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

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Authors: S. Sudhharani

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Energy distribution networks are the main link between the energy industry and consumers and are subject to the most scrutiny and testing of any category. As a result, it is important to monitor energy levels during the distribution phase. Power distribution networks, on the other hand, remain subject to common problems, including voltage breakdown, power outages, harmonics, and capacitor switching, all of which disrupt sinusoidal waveforms and reduce the quality and power of the network. Using power appliances in the form of custom power appliances is one way to deal with energy quality issues. Dynamic Voltage Restorer (DVR), integrated with network and distribution networks, is one of these devices. At the same time, by injecting voltage into the system, it can adjust the voltage amplitude and phase in the network. In the form of injections and three-phase syncing, it is used to compensate for the difficulty of energy quality. This article examines the recent use of DVR for power compensation and provides data on the control of each DVR in distribution networks.

Keywords: dynamic voltage restorer (DVR), power quality, distribution networks, control systems(PWM)

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Authors: Bernardo C. P. Albuquerque, Darym J. F. Campos

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Increasing our ability to solve complex engineering problems is directly related to the processing capacity of computers. By means of such equipments, one is able to fast and accurately run numerical algorithms. Besides the increasing interest in numerical simulations, probabilistic approaches are also of great importance. This way, statistical tools have shown their relevance to the modelling of practical engineering problems. In general, statistical approaches to such problems consider that the random variables involved follow a normal distribution. This assumption tends to provide incorrect results when skew data is present since normal distributions are symmetric about their means. Thus, in order to visualize and quantify this aspect, 9 statistical distributions (symmetric and skew) have been considered to model a hypothetical slope stability problem. The data modeled is the friction angle of a superficial soil in Brasilia, Brazil. Despite the apparent universality, the normal distribution did not qualify as the best fit. In the present effort, data obtained in consolidated-drained triaxial tests and saturated direct shear tests have been modeled and used to analytically derive the probability density function (PDF) of the safety factor of a hypothetical slope based on Mohr-Coulomb rupture criterion. Therefore, based on this analysis, it is possible to explicitly derive the failure probability considering the friction angle as a random variable. Furthermore, it is possible to compare the stability analysis when the friction angle is modelled as a Dagum distribution (distribution that presented the best fit to the histogram) and as a Normal distribution. This comparison leads to relevant differences when analyzed in light of the risk management.

Keywords: statistical slope stability analysis, skew distributions, probability of failure, functions of random variables

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Authors: Tokuei Sako

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The ground and low-lying singly-excited states of He and He-like atomic ions have been studied by the Full Configuration Interaction (FCI) method focusing on the angular correlation between two electrons in the studied systems. The two-electron angle density distribution obtained by integrating the square-modulus of the FCI wave function over the coordinates other than the interelectronic angle shows a distinct trend between the singlet-triplet pair of states for different values of the nuclear charge Zn. Further, both of these singlet and triplet distributions tend to show an increasingly stronger dependence on the interelectronic angle as Zn increases, in contrast to the well-known fact that the correlation energy approaches towards zero for increasing Zn. This controversial observation has been rationalized on the basis of the recently introduced concept of so-called conjugate Fermi holes.

Keywords: He-like systems, angular correlation, configuration interaction wave function, conjugate Fermi hole

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Authors: Bina Kumari, Subir K. Sarkar, Pradipta Bandyopadhyay

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The autocorrelation function of the density fluctuation is studied in each of the two phases in a Gibbs Ensemble Monte Carlo (GEMC) simulation of the problem of phase separation for a square well potential with various values of its range. We find that the normalized autocorrelation function is described very well as a linear combination of an exponential function with a time scale τ₂ and a stretched exponential function with a time scale τ₁ and an exponent α. Dependence of (α, τ₁, τ₂) on the parameters of the GEMC algorithm and the range of the square well potential is investigated and interpreted. We also analyse the issue of how to choose the parameters of the GEMC simulation optimally.

Keywords: autocorrelation function, density fluctuation, GEMC, simulation

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Authors: Ehan Sabah Shukri, Wirachman Wisnoe

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Numerical study is performed to investigate the temperature distribution in an annular diffuser fitted with helical tape hub. Different pitches (Y = 20 mm, and Y = 30 mm) for the helical tape are studied with different heights (H = 20 mm, 22 mm, and 24 mm) to be compared. The geometry of the annular diffuser and the inlet condition for both hub arrangements are kept constant. The result obtains that using helical tape insert with different pitches and different heights will force the temperature to distribute in a helical direction; however the use of helical tape hub with height (H = 22 mm) for both pitches enhance the temperature distribution in a good manner.

Keywords: helical tape, divergent fluid flow, temperature distribution, swirl flow, CFD

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Authors: Sunantha Teyarachakul

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We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems.

Keywords: inventory management, Newsvendor model, order policy, worker learning

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Authors: Atefeh Pourshafie, Homayoun Bakhtiari

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The main task of power distribution companies is to supply the power required by customers in an acceptable level of quality and reliability. Some key performance indicators for electric power distribution companies are those evaluating the continuity of supply within the network. More than other problems, power outages (due to lightning, flood, fire, earthquake, etc.) challenge economy and business. In addition, end users expect a reliable power supply. Reliability indices are evaluated on an annual basis by the specialized holding company of Tavanir (Power Produce, Transmission& distribution company of Iran) . Evaluation of reliability indices is essential for distribution companies, and with regard to the privatization of distribution companies, it will be of particular importance to evaluate these indices and to plan for their improvement in a not too distant future. According to IEEE-1366 standard, there are too many indices; however, the most common reliability indices include SAIFI, SAIDI and CAIDI. These indices describe the period and frequency of blackouts in the reporting period (annual or any desired timeframe). This paper calculates reliability indices for three sample feeders in Lorestan Electric Power Distribution Company and defines the threshold values in a ten-month period. At the end, strategies are introduced to reach the threshold values in order to increase customers' satisfaction.

Keywords: power, distribution network, reliability, outage

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Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

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Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

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Authors: Muhammad Farooq, Ahtasham Gul

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To meet the desired standard, it is important to monitor and analyze different engineering processes to get desired output. The bivariate distributions got a lot of attention in recent years to describe the randomness of natural as well as artificial mechanisms. In this article, a bivariate model is constructed using two independent models developed by the nesting approach to study the effect of each component on reliability for better understanding. Further, the Bayes analysis of system availability is studied by considering prior parametric variations in the failure time and repair time distributions. Basic statistical characteristics of marginal distribution, like mean median and quantile function, are discussed. We use inverse Gamma prior to study its frequentist properties by conducting Monte Carlo Markov Chain (MCMC) sampling scheme.

Keywords: reliability, system availability Weibull, inverse Lomax, Monte Carlo Markov Chain, Bayesian

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Authors: Yuan Zheng

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3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information

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Authors: S. B. Provost, Susan Sheng

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An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

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Authors: Alexander Norbach

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The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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Authors: Ehan Sabah Shukri, Wirachman Wisnoe

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The influence of twist arrangement on the temperature distribution in an annular diffuser fitted with twisted rectangular hub is investigated. Different pitches (Y = 120 mm, 100 mm, 80 mm, and 60 mm) for the twist arrangements are simulated to be compared. The geometry of the annular diffuser and the inlet condition for the hub arrangements are kept constant. The result reveals that using twisted rectangular hub insert with different pitches will force the temperature to distribute in a circular direction. However, temperature distribution will be enhanced with the length pitch increases.

Keywords: numerical simulation, twist arrangement, annular diffuser, temperature distribution, swirl flow, pitches

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Authors: Autcha Araveeporn

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This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20.

Keywords: Bayes method, Markov chain Monte Carlo method, maximum likelihood method, normal distribution

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Authors: Natalia Bustos Sierra, Katrien Tersago

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It is currently proven that both extremes of temperature are associated with increased mortality and that air pollution is associated with temperature. This relationship is complex, and in countries with important seasonal variations in weather such as Belgium, some effects can appear as non-significant when the analysis is done over the entire year. We, therefore, analyzed the effect of short-term outdoor air pollution exposure on cardiovascular mortality during the warmer and colder months separately. We used daily cardiovascular deaths from acute cardiovascular diagnostics according to the International Classification of Diseases, 10th Revision (ICD-10: I20-I24, I44-I49, I50, I60-I66) during the period 2008-2013. The environmental data were population-weighted concentrations of particulates with an aerodynamic diameter less than 10 µm (PM₁₀) and less than 2.5 µm (PM₂.₅) (daily average), nitrogen dioxide (NO₂) (daily maximum of the hourly average) and ozone (O₃) (daily maximum of the 8-hour running mean). A Generalized linear model was applied adjusting for the confounding effect of season, temperature, dew point temperature, the day of the week, public holidays and the incidence of influenza-like illness (ILI) per 100,000 inhabitants. The relative risks (RR) were calculated for an increase of one interquartile range (IQR) of the air pollutant (μg/m³). These were presented for the four hottest months (June, July, August, September) and coldest months (November, December, January, February) in Belgium. We applied both individual lag model and unconstrained distributed lag model methods. The cumulative effect of a four-day exposure (day of exposure and three consecutive days) was calculated from the unconstrained distributed lag model. The IQR for PM₁₀, PM₂.₅, NO₂, and O₃ were respectively 8.2, 6.9, 12.9 and 25.5 µg/m³ during warm months and 18.8, 17.6, 18.4 and 27.8 µg/m³ during cold months. The association with CV mortality was statistically significant for the four pollutants during warm months and only for NO₂ during cold months. During the warm months, the cumulative effect of an IQR increase of ozone for the age groups 25-64, 65-84 and 85+ was 1.066 (95%CI: 1.002-1.135), 1.041 (1.008-1.075) and 1.036 (1.013-1.058) respectively. The cumulative effect of an IQR increase of NO₂ for the age group 65-84 was 1.066 (1.020-1.114) during warm months and 1.096 (1.030-1.166) during cold months. The cumulative effect of an IQR increase of PM₁₀ during warm months reached 1.046 (1.011-1.082) and 1.038 (1.015-1.063) for the age groups 65-84 and 85+ respectively. Similar results were observed for PM₂.₅. The short-term effect of air pollution on cardiovascular mortality is greater during warm months for lower pollutant concentrations compared to cold months. Spending more time outside during warm months increases population exposure to air pollution and can, therefore, be a confounding factor for this association. Age can also affect the length of time spent outdoors and the type of physical activity exercised. This study supports the deleterious effect of air pollution on cardiovascular mortality (CV) which varies according to season and age groups in Belgium. Public health measures should, therefore, be adapted to seasonality.

Keywords: air pollution, cardiovascular, mortality, season

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Authors: Ali Razmi, Saeed Golian

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Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.

Keywords: climate change, climate variables, copula, joint probability

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Authors: W. Widhiada, D. N. K. P. Negara, P. A. Suryawan

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The technological advances in the field of health to be very important, especially on the safety of the baby. In this case a lot of premature infants death caused by poorly managed health facilities. Mostly the death of premature baby caused by bacteria since the temperature around the baby is not normal. Related to this, the incubator equipment needs to be important, especially in how to control the temperature in incubator. On/Off controls is used to regulate the temperature distribution in the incubator so that the desired temperature is 36 °C to stay awake and stable. The authors have been observed and analyzed the data to determine the temperature distribution in the incubator using program of MATLAB/Simulink. The output temperature distribution is obtained at 36 °C in 400 seconds using an Arduino AT 2560. This incubator is able to maintain an ambient temperature and maintain the baby's body temperature within normal limits and keep the moisture in the air in accordance with the limit values required in infant incubator.

Keywords: on/off control, distribution temperature, Arduino AT 2560, baby incubator

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Authors: Harjot Singh Gill, Neelkanth Grover, Jwala Parshad Singla

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The main aim of this research work is to present the effect of coating on two different grades of grey cast iron using detonation spray method. Ni20Cr and Al2O3-13TiO2 powders were sprayed using detonation gun onto GI250 and GIHC substrates and the results as well as coating surface morphology of the coating is studied by XRD and SEM/EDAX analysis. The wear resistance of Ni20Cr and Al2O3-13TiO2 has been investigated on pin-on-disc tribometer using ASTM G99 standards. Cumulative wear rate and coefficient of friction (µ) were calculated under three normal load of 30N, 40N, 50N at constant sliding velocity of 1m/s. Worn out surfaces were analyzed by SEM/EDAX. The results show significant resistance to wear with Al2O3-13TiO2 coating as compared to Ni20Cr and bare substrates. SEM/EDAX analysis and cumulative wear loss bar charts clearly explain the wear behavior of coated as well as bare sample of GI250 and GIHC.

Keywords: detonation spray, grey cast iron, wear rate, coefficient of friction

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Authors: Boukhris Lahouari, Bouchetara Mostefa

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The active safety of a vehicle is mainly influenced by the properties of the installed braking system. With the increase in road traffic density and travel speeds, increasingly stringent requirements are placed on the vehicle's behaviour during braking. The achievable decelerations are limited by the physical aspect characterized by the coefficient of friction between the tires and the ground. As a result, it follows that an optimized distribution of braking forces becomes necessary for a better use of friction coefficients. This objective could only be achieved if sufficient knowledge is available on the theory of vehicle dynamics during braking and on current standards for the approval of braking systems. These will facilitate the development of a braking force calculation algorithm that will enable an optimized distribution of braking forces to be achieved. Operating safety is conditioned by the requirements of efficiency, progressiveness, regularity or fidelity of a braking system without obviously neglecting the recommendations imposed by the legislator.

Keywords: brake force distribution, distribution diagram, friction coefficient, brake by wire

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Authors: Eseldin Keleb

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In the pharmaceutical industry particle size distribution is an important parameter for the characterization of pharmaceutical powders. The powder flowability, reactivity and compatibility, which have a decisive impact on the final product, are determined by particle size and size distribution. Therefore, the aim of this study was to evaluate the influence of processing parameters on the particle size distribution measurements. Different Size fractions of α-lactose monohydrate and 5% polyvinylpyrrolidone were prepared by wet granulation and were used for the preparation of samples. The influence of sieve load (50, 100, 150, 200, 250, 300, and 350 g), processing time (5, 10, and 15 min), sample size ratios (high percentage of small and large particles), type of disturbances (vibration and shaking) and process reproducibility have been investigated. Results obtained showed that a sieve load of 50 g produce the best separation, a further increase in sample weight resulted in incomplete separation even after the extension of the processing time for 15 min. Performing sieving using vibration was rapider and more efficient than shaking. Meanwhile between day reproducibility showed that particle size distribution measurements are reproducible. However, for samples containing 70% fines or 70% large particles, which processed at optimized parameters, the incomplete separation was always observed. These results indicated that sieving reliability is highly influenced by the particle size distribution of the sample and care must be taken for samples with particle size distribution skewness.

Keywords: sieving, reliability, particle size distribution, processing parameters

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Authors: Mohammedi Ferhate

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This paper deals with the generalized the notion of the function of wave a micro particle moving free, the concept of the linear operator in the representation function delta of Dirac which is a generalization of the symbol of Kronecker to the case of a continuous variation of the sizes concerned with the condition of orthonormation of the Eigen functions the use of linear operators and their Eigen functions in connection with the solution of given differential equations, it is of interest to study the properties of the operators themselves and determine which of them follow purely from the nature of the operators, without reference to specific forms of Eigen functions. The models simulation examples are also presented.

Keywords: function, operator, simulation, wave

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Authors: Rafida M. Elobaid

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Most of the literature on goodness-of-fit test try to provide a theoretical basis for studying empirical distribution functions. Such goodness-of-fit tests are Kolmogorove-Simirnov and Crumer-Von Mises Type tests. However, it is likely that most of literature has not focused in details on the relationship of the values of the test statistics and skewness or kurtosis. The aim of this study is to investigate the behavior of the values of the χ2 test statistic with the variation of the skewness of right skewed distribution. A simulation study is conducted to generate random numbers from Weibull distribution. For a fixed sample sizes, different levels of skewness are considered, and the corresponding values of the χ2 test statistic are calculated. Using different sample sizes, the results show an inverse relationship between the value of χ2 test and the level of skewness for Wiebull distribution, i.e the value of χ2 test statistic decreases as the value of skewness increases. The research results also show that with large values of skewness we are more confident that the data follows the assumed distribution. Nonparametric Kendall τ test is used to confirm these results.

Keywords: goodness-of-fit test, chi-square test, simulation, continuous right skewed distributions

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Authors: Bouchou Aïssa, Mohamed Akbi

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Contact materials used for electrical breakers are often made with silver alloys. Mechanical and thermo dynamical properties as well as electron emission of such complicated alloys present a lack of reliable and accurate experimental data. This paper deals mainly with electron work function (EWF) measurements about silver-metal oxide (Ag-MeO) electrical contacts (Ag-ZnO (92/8), before and after surface heat treatments at 296 K  813 K, under UHV conditions (residual gas pressure of 1.4 x 10-7 mbar). The electron work function (EWF) of silver zinc oxide materials was measured photoelectrically, using both Fowler’s method of isothermal curves and linearized Fowler plots. In this paper, we present the development of a method for measuring photoelectric work function of contact materials. Also reported in this manuscript are the results of experimental work whose purpose has been the buildup of a reliable photoelectric system and associated monochromatic ultra-violet radiations source, and the photoelectric measurement of the electron work functions (EWF) of contact materials. In order to study the influence of annealing temperature on the EWF, a vacuum furnace was used for heating the metallic samples up to 800 K. The EWF of the silver – zinc oxide materials were investigated to study the influence of annealing temperature on the EWF. In the present study, the photoelectric measurements about Ag-ZnO(92/8) contacts have shown a linear decrease of the EWF with increasing temperature, i.e. the temperature coefficient is constant and negative: for the first annealing # 1, in the temperature range [299 K  823 K]. On the contrary, a linear increase was observed with increasing temperature (i.e. , being constant and positive), for the next annealing # 2, in the temperature range [296 K  813 K]. The EWFs obtained for silver-zinc oxide Ag-ZnO(92/8) show an obvious dependence on the annealing temperature which is strongly associated with the evolution of the arrangement on ZnO nano particles on the Ag-ZnO contact surface as well as surface charge distribution.

Keywords: Photoemission, Electron work function, Fowler methods, Ag-ZnO contact materials, Vacuum heat treatment

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Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

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Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

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Authors: Boukhris Lahouari, Bouchetara Mostefa

Abstract:

The active safety of a vehicle is mainly influenced by the properties of the installed braking system. With the increase in road traffic density and travel speeds, increasingly stringent requirements are placed on the vehicle's behaviour during braking. The achievable decelerations are limited by the physical aspect characterized by the coefficient of friction between the tires and the ground. As a result, it follows that an optimized distribution of braking forces becomes necessary for a better use of friction coefficients. This objective could only be achieved if sufficient knowledge is available on the theory of vehicle dynamics during braking and on current standards for the approval of braking systems. This will facilitate the development of a braking force calculation algorithm that will enable an optimized distribution of braking forces to be achieved. Operating safety is conditioned by the requirements of efficiency, progressiveness, regularity or fidelity of a braking system without obviously neglecting the recommendations imposed by the legislator.

Keywords: brake force distribution, distribution diagram, friction coefficient, brake by wire

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

Abstract:

Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

Procedia PDF Downloads 326

Authors: Samuel Hyellamada Jerry

Abstract:

This study focused on assessing conservation priorities within the Karlahi Forest Reserve of Fufore Local Government in Adamawa State. The main objective was to identify specific areas within the forest reserve that require immediate conservation attention. The research employed remote sensing and GIS techniques to achieve this goal. By overlaying the IDRIS Silva module results, a spatial distribution map was generated, highlighting the cumulative priority areas within and outside the forest. Among the total vegetated area of 26.38 km² in the Karlahi Forest Reserve, the analysis revealed that 16.16 km² were classified as high-priority conservation zones. Additionally, 4.59 km² and 5.63 km² were identified as medium and low-priority areas, respectively. In light of these findings, it is recommended that conservation efforts incorporate detailed land cover information and regular assessments of species diversity. Furthermore, strict adherence to national and state policies regarding forest reserves and parks is crucial for effective conservation management.

Keywords: priority, Karlahi, forest, reserve, IDRISI Silva, species diversity

Procedia PDF Downloads 121

Authors: Y. N. Phang, E. F. Loh

Abstract:

Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling over-dispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling over-dispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling over-dispersed medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling over-dispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian, and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling over-dispersed medical count data when ZIP and ZINB are inadequate.

Keywords: zero inflated, inverse trinomial distribution, Poisson inverse Gaussian distribution, strict arcsine distribution, Pearson’s goodness of fit

Procedia PDF Downloads 511