Search results for: moving average model

Authors: Hossein Hassani, Ali Rezaei

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Heavy metals are naturally occurring elements that have a high atomic weight and a density at least five times greater than that of water. Their multiple industrial, domestic, agricultural, medical, and technological applications have led to their wide distribution in the environment, raising concerns over their potential effects on human health and the environment. Environmental protection against various pollutants, such as heavy metals formed by industries, mines and modern technologies, is a concern for researchers and industry. In order to assess the contamination of soils the distribution and environmental behavior have been investigated. Jajarm bauxite mine, the most important deposits have been discovered in Iran, which is about 22 million tons of reserve, and is the main mineral of the Diaspora. With a view to estimate the heavy metals ratio of the Jajarm bauxite mine area and to evaluate the pollution level, 50 samples have been collected and have been analyzed for the heavy metals of As, Cd, Cu, Hg, Ni and Pb with the help of Inductively Coupled Plasma-Mass Spectrometer (ICP- MS). In this study, we have dealt with determining evaluation criteria including contamination factor (CF), average concentration (AV), enrichment factor (EF) and geoaccumulation index (GI) to assess the risk of pollution from heavy metals(As, Cd, Cu, Hg, Ni and Pb) in Jajarm bauxite mine. In the samples of the studied, the average of recorded concentration of elements for Arsenic, Cadmium, Copper, Mercury, Nickel and Lead are 18, 0.11, 12, 0.07, 58 and 51 (mg/kg) respectively. The comparison of the heavy metals concentration average and the toxic potential in the samples has shown that an average with respect to the world average of the uncontaminated soil amounts. The average of Pb and As elements shows a higher quantity with respect to the world average quantity. The pollution factor for the study elements has been calculated on the basis of the soil background concentration and has been categorized on the basis of the uncontaminated world soil average with respect to the Hakanson classification. The calculation of the corrected pollutant degree shows the degree of the bulk intermediate pollutant (1.55-2.0) for the average soil sampling of the study area which is on the basis of the background quantity and the world average quantity of the uncontaminated soils. The provided conclusion from calculation of the concentrated factor, for some of the samples show that the average of the lead and arsenic elements stations are more than the background values and the unnatural metal concentration are covered under the study area, That's because the process of mining and mineral extraction. Given conclusion from the calculation of Geoaccumulation index of the soil sampling can explain that the copper, nickel, cadmium, arsenic, lead and mercury elements are Uncontamination. In general, the results indicate that the Jajarm bauxite mine of heavy metal pollution is uncontaminated area and extract the mineral from the mine, not create environmental hazards in the region.

Keywords: enrichment factor, geoaccumulation index, heavy metals, Jajarm bauxite mine, pollution

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Authors: M. T. Alodat

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In this paper, we propose a generalization to the Gaussian process regression(GPR) model called the extended skew Gaussian process for regression(ESGPr) model. The ESGPR model works better than the GPR model when the errors are skewed. We derive the predictive distribution for the ESGPR model at a new input. Also we apply the ESGPR model to FOREX data and we find that it fits the Forex data better than the GPR model.

Keywords: extended skew normal distribution, Gaussian process for regression, predictive distribution, ESGPr model

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Heng Han, Zhilei Liang, Xiangong Zhou

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In this paper, the finite element method is used to study the temperature field of the main cable of the suspension bridge, and the calculation method of the average temperature of the cross-section of the main cable suitable for the construction control of the cable system is proposed; By comparing and analyzing the temperature field of the main cable with five diameters, a reasonable diameter limit for calculating the average temperature of the cross section of the main cable by finite element method is proposed. The results show that the maximum error of this method is less than 1℃, which meets the requirements of construction control accuracy; For the main cable with a diameter greater than 400mm, the surface temperature measuring points combined with the finite element method shall be used to calculate the average cross-section temperature.

Keywords: suspension bridge, main cable, temperature field, finite element

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Authors: Jose Melena, Rosa Santander, Tanya Gonzalez, Richard Duque, Juan Illanes

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Ecuador is one of the countries with the greatest aquatic biodiversity worldwide. In particular, there are at least a dozen native marine species with great aquaculture potential locally. This research concerns one of those species. It has proposed to implement experimental protocols in order to induce spawning and to generate the early larval development of the penshell Atrina maura under controlled conditions. Bioassays were carried out with one adult batch (n= 26) with an average valvar length of 307,6 ± 9,4 mm, which were collected in the Puerto El Morro Mangrove (2° 42' 33'' S, 80° 14' 28'' W), Guayas Province. During a short acclimation stage, five adults of penshell A. maura were sacrificed in order to determine their sexual maturity degree and to estimate their sex ratio. Dissection showed that three were ripe females (60%) and two were ripe males (40%). Later, three groups (n= 7 by each) were tested with two treatments in order to induce the broodstock spawning: thermal stress, osmotic shock, and one control. Spawning induction was achieved by the immersion in water to 0 g L⁻¹ per 1 h and immersion in sea water to 34 g L⁻¹ per 1 h. After the delivery of gametes, it was achieved 1,35 × 10⁶ viable zygotes. As results, fertilized eggs had 60 µm diameter; while first and second cell divisions were observed to 1 h post-fertilization, with individual average length of 65 ± 4 µm and polar body. Latter cell divisions, including gastrula stage, appeared at 9 h post-fertilization, with individual average length of 71 ± 4 µm; and trochophore stage at 16 h post-fertilization with individual average length of 75 ± 5 µm. In addition, veliger stage was registered at 20 h post-fertilization with individual average length of 81 ± 5 µm. Umboned larvae appeared at day 8 post-fertilization, with individual average length of 145 ± 6 µm. These pioneering results in Ecuador can strengthen the local conservation process of the overexploited A. maura and to encourage its production for commercial purposes.

Keywords: Atrina maura, Ecuador, larval development, spawning induction

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Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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Authors: Rachel Karasenty Saltoun, Charlotte Roddick, Chelsea D. Christie, Frances Chen

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Moving has become an integral part of many people’s lives. This research explores whether relocating to a new city is associated with an increase in loneliness and cardiovascular disease risk and if this increased risk diminishes with continued residency. To test this, various psychosocial variables and three cardiovascular disease risk markers (C-reactive protein, albumin, blood pressure) were assessed on two groups of individuals: those who have moved to Vancouver, Canada in the previous 6 weeks (‘Movers’) and those who have lived in Vancouver for at least five years (‘Non-Movers’). It was hypothesized that individuals who had recently relocated would have heightened levels of loneliness, blood pressure (BP), albumin, and C-reactive protein (CRP) compared to those who had not recently relocated. Length of residency was hypothesized to moderate these effects, such that after a few months, loneliness levels and cardiovascular disease risk would decrease among those who had recently relocated. Correlational analysis indicated a trend between the change in CRP and albumin levels and loneliness overtime on an individual level. However, these results must be interpreted with caution due to the small sample size. As Vancouver’s immigration rates continue to grow, this study has important implications regarding the social support resources offered to new immigrants, as well as bringing awareness at the healthcare level of the potential increase in cardiovascular disease risk among those who have recently relocated.

Keywords: cardiovascular disease risk, loneliness, moving, residential mobility

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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: Sung-Pill Kim, Dae-Gyu Sung, Hee-Sung Shin, Jong-Chun Park

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When a sloshing tank filled partially with liquid is excited with the motion of platform, it can be observed that the center of mass inside the tank is changed and impact loads is instantaneously applied to the wall, which causes dynamic loads additionally to the supporting links of platform. In this case, therefore, the dynamic behavior of platform associated with fluid motion should be considered in the early stage of design for safety and economics of the system. In this paper, the dynamic loads due to liquid sloshing motion in a rectangular tank which is loaded up on the upper deck of a Stewart platform are simulated using a coupled analysis of Moving Particle Simulation (MPS) and Flexible Multi-Body Dynamics (FMBD). The co-simulation is performed using two commercial softwares, Recurdyn for solving FMBD and Particleworks for analyzing fluid motion based on MPS method. For validating the present coupled system, a rectangular sloshing tank being enforced with inline sway motion by 1-DOF motion platform is assumed, and time-varied free-surface elevation and reaction force at a fixed joint are compared with experiments.

Keywords: dynamic loads, liquid sloshing tank, Stewart platform, moving particle semi-implicit (MPS) method, flexible multi-body dynamics (FMBD)

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Authors: Ramkumar R., Gaurav Shinde, Pratik Shroff, Sachin Kumar Jain, Nagesh Walke

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Advancements in electric vehicles have significantly reduced the powertrain noise and moving components of vehicles. As a result, in-cab noises have become more noticeable to passengers inside the car. To ensure a comfortable ride for drivers and other passengers, it has become crucial to eliminate undesirable component noises during the development phase. Standard practices are followed to identify the severity of noises based on subjective ratings, but it can be a tedious process to identify the severity of each development sample and make changes to reduce it. Additionally, the severity rating can vary from jury to jury, making it challenging to arrive at a definitive conclusion. To address this, an automotive component was identified to evaluate squeak and rattle noise issue. Physical tests were carried out for random and sine excitation profiles. Aim was to subjectively assess the noise using jury rating method and objectively evaluate the same by measuring the noise. Suitable jury evaluation method was selected for the said activity, and recorded sounds were replayed for jury rating. Objective data sound quality metrics viz., loudness, sharpness, roughness, fluctuation strength and overall Sound Pressure Level (SPL) were measured. Based on this, correlation co-efficients was established to identify the most relevant sound quality metrics that are contributing to particular identified noise issue. Regression analysis was then performed to establish the correlation between subjective and objective data. Mathematical model was prepared using artificial intelligence and machine learning algorithm. The developed model was able to predict the subjective rating with good accuracy.

Keywords: BSR, noise, correlation, regression

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Authors: Alcardo Alex Barakabitze, Saddam Aziz, Muhammad Zubair

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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

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Authors: Hai Nguyen Tien

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On the basis of the structure of alluvial sediments explained by echo sounding data and remote sensing images, the following results can be given: The estuary of Lam river (from Ben Thuy bridge to Cua Hoi) is divided into 3 channel (location is calculated according to the river bank on the Nghe An province) : i) channel I (from Ben Thuy bridge to Hung Hoa) is the branching river; ii) channel II (from Hung Hoa to Nghi Thai is a channel develops in a meandering direction with a concave side toward Ha Tinh province; iii) channel III, from Nghi Thai to Cua Hoi is a channel develops in a meandering direction with a concave side toward Nghe An province. This estuary area is formed in the period from after the sea level dropped below 0m (current water level) to the present: i) Chanel II developed moving towards Ha Tinh provnce; ii) Chanel III developed moving towards Nghe An province; iii) In chanel I, a second river branch is formed because the flow of river cuts through the Hong Lam- Hong Nhat mudflat, at the same time creating an island. Morphological characteristics of the estuary area of Lam River are the main result of erosion and deposition activities corresponding to two water levels: low water level below 0 m and water level 0 m (current water level). Characteristics of the sediment layers on the riverbed in the estuary can be used to determine the sea levels in Late Holocene–Present.

Keywords: Lam River, development, Cua Hoi, river morphology

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Authors: Aude Pérard Lecomte, Georges Fokoua, Amine Mehel, Anne Tanière

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Air quality in urban areas is deteriorated by pollution, mainly due to the constant increase of the traffic of different types of ground vehicles. In particular, particulate matter pollution with important concentrations in urban areas can cause serious health issues. Characterizing and understanding particle dynamics is therefore essential to establish recommendations to improve air quality in urban areas. To analyze the effects of turbulence on particulate pollutants dispersion, the first step is to focus on the single-phase flow structure and turbulence characteristics in the wake of a heavy truck model. To achieve this, Computational Fluid Dynamics (CFD) simulations were conducted with the aim of modeling the wake airflow of a full- and reduced-scale heavy truck. The Reynolds Average Navier-Stokes (RANS) approach with the Reynolds Stress Model (RSM)as the turbulence model closure was used. The simulations highlight the apparition of a large vortex coming from the under trailer. This vortex belongs to the recirculation region, located in the near-wake of the heavy truck. These vortical structures are expected to have a strong influence on particle dynamics that are emitted by the truck.

Keywords: CDF, heavy truck, recirculation region, reduced scale

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Hsin Lee, Hsuan Lee

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Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.

Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases

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Authors: Le Kang

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According to the nature of the university, as a free and responsible academic community, USR is based on a different foundation —academic responsibility, so the Pyramid and the IC Model of CSR could not fully explain the most distinguished feature of USR. This paper sought to put forward a new model— Ferris Wheel Model, to illustrate the nature of USR and the process of achievement. The Ferris Wheel Model of USR shows the university creates a balanced, fairness and neutrality systemic structure to afford social responsibilities; that makes the organization could obtain a synergistic effect to achieve more extensive interests of stakeholders and wider social responsibilities.

Keywords: USR, achievement model, ferris wheel model, social responsibilities

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Authors: Dianelys Vega, Carlos Magluta, Ney Roitman

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The simulation of loads induced by walking people in civil engineering structures is still challenging It has been the focus of considerable research worldwide in the recent decades due to increasing number of reported vibration problems in pedestrian structures. One of the most important key in the designing of slender structures is the Human-Structure Interaction (HSI). How moving people interact with structures and the effect it has on their dynamic responses is still not well understood. To rely on calibrated pedestrian models that accurately estimate the structural response becomes extremely important. However, because of the complexity of the pedestrian mechanisms, there are still some gaps in knowledge and more reliable models need to be investigated. On this topic several authors have proposed biodynamic models to represent the pedestrian, whether these models provide a consistent approximation to physical reality still needs to be studied. Therefore, this work comes to contribute to a better understanding of this phenomenon bringing an experimental validation of a pedestrian walking model and a Human-Structure Interaction model. In this study, a bi-dimensional bipedal walking model was used to represent the pedestrians along with an interaction model which was applied to a prototype footbridge. Numerical models were implemented in MATLAB. In parallel, experimental tests were conducted in the Structures Laboratory of COPPE (LabEst), at Federal University of Rio de Janeiro. Different test subjects were asked to walk at different walking speeds over instrumented force platforms to measure the walking force and an accelerometer was placed at the waist of each subject to measure the acceleration of the center of mass at the same time. By fitting the step force and the center of mass acceleration through successive numerical simulations, the model parameters are estimated. In addition, experimental data of a walking pedestrian on a flexible structure was used to validate the interaction model presented, through the comparison of the measured and simulated structural response at mid span. It was found that the pedestrian model was able to adequately reproduce the ground reaction force and the center of mass acceleration for normal and slow walking speeds, being less efficient for faster speeds. Numerical simulations showed that biomechanical parameters such as leg stiffness and damping affect the ground reaction force, and the higher the walking speed the greater the leg length of the model. Besides, the interaction model was also capable to estimate with good approximation the structural response, that remained in the same order of magnitude as the measured response. Some differences in frequency spectra were observed, which are presumed to be due to the perfectly periodic loading representation, neglecting intra-subject variabilities. In conclusion, this work showed that the bipedal walking model could be used to represent walking pedestrians since it was efficient to reproduce the center of mass movement and ground reaction forces produced by humans. Furthermore, although more experimental validations are required, the interaction model also seems to be a useful framework to estimate the dynamic response of structures under loads induced by walking pedestrians.

Keywords: biodynamic models, bipedal walking models, human induced loads, human structure interaction

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a three leg voltage source inverter (VSI). Operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation and results show simplicity and accuracy, as well as reliability of the model.

Keywords: model predictive control, three phase voltage source inverter, PV system, Matlab/simulink

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Authors: Nirali Shukla, Neel Shah

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The World Bank Institute (WBI) is undertaking a review of government interventions aimed at facilitating sustainable investment in public private partnerships (PPPs) in various under developed countries. The study presents best practice for applying financial model to make PPPs financially viable. The lessons presented here, if properly implemented, can help countries use limited funds to attract more private investment, get more infrastructure built and, as a result, achieve greater economic growth. The four countries Brazil, Colombia, Mexico, and India in total develop an average of nearly US$50 billion in PPPs per year. There are a range of policies and institutional arrangements governments use to provide subsidies to PPPs. For example, some countries have created dedicated agencies, or ‘funds’, capitalized with money from the national budget to manage and allocate subsidies. Other countries have established well-defined policies for appropriating subsidies on an ad hoc basis through an annual budget process. In this context, subsidies are direct fiscal contributions or grants paid by the government to a project when revenues from user fees are insufficient to cover all capital and operating costs while still providing private investors with a reasonable rate of return. Without subsidies, some infrastructure projects that would provide economic or social gains, but are not financially viable, would go undeveloped. But the Financial model of BOLT (PPP) model described in this study suggests that it is most feasible option rather than going for subsidy schemes for making infrastructure projects financially viable. The major advantage for implementing this model is the government money is saved and can be used for other projects as well as the private investors are getting better rate of return than subsidized schemes.

Keywords: PPP, BOLT, subsidy schemes, financial model

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Authors: Zahra Shakoori, Farid Salmanpour

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Pollination services are a vital service for the ecosystem to maintain environmental stability. The decline of pollinators can disrupt the ecological balance by affecting components of biodiversity. Bumble bees are crucial pollinators, playing a vital role in maintaining plant diversity. This study investigated the temporal patterns of their visitation to flowers in Kiasar National Park, Iran. Observations were conducted in Jun 2024, totaling 442 person-minutes of observation. Five species of bumble bees were identified. The study revealed that they consistently visited an average of 12-15 flowers per minute, regardless of species. The findings highlight the importance of protecting natural habitats, where their populations are thriving in the absence of human-induced stressors. This study was conducted in Kiasar National Park, located in the southeast of Mazandaran, northern Iran. The surveyed area, at an altitude of 1800-2200 meters, includes both forest and pasture. Bumble bee surveys were carried out on sunny days from June 2024, starting at dawn and ending at sunset. To avoid double-counting, we systematically searched for foraging habitats on low-sloping ridges with high mud density, frequently moving between patches. We recorded bumble bee visits to flowers and plant species per minute using direct observation, a stopwatch, and a pre-prepared form. We used statistical analysis of variance (ANOVA) with a confidence level of 95% to examine potential differences in foraging rates across different bumble bee species, flowers, plant bases, and plant species visited. Bumble bee identification relied on morphological indicators. A total of 442 person-minutes of bumble bee observations were recorded. Five species of bumble bees (Bombus fragrans, Bombus haematurus, Bombus lucorum, Bombus melanurus, Bombus terrestris) were identified during the study. The results of this study showed that the visits of bumble bees to flower sources were not different from each other. In general, bumble bees visit an average of 12-15 flowers every 60 seconds. In addition, at the same time they visit between 3-5 plant bases. Finally, they visit an average of 1 to 3 plant species per minute. While many taxa contribute to pollination, insects—especially bees—are crucial for maintaining plant diversity and ecosystem functions. As plant diversity increases, the stopping rate of pollinating insects rises, which reduces their foraging activity. Bumble bees, therefore, stop more frequently in natural areas than in agricultural fields due to higher plant diversity. Our findings emphasize the need to protect natural habitats like Kiasar National Park, where bumble bees thrive without human-induced stressors like pesticides, livestock grazing, and pollution. With bumble bee populations declining globally, further research is essential to understand their behavior in different environments and develop effective conservation strategies to protect them.

Keywords: bumble bees, pollination, pollinator, plant diversity, Iran

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Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

Procedia PDF Downloads 605

Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

Procedia PDF Downloads 112

Authors: Authors: A. Lakhal, M. Bahalou, A. Khattabi

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Introduction: Tuberculosis is one of the world's deadliest infectious diseases. In Morocco, a total of 30,636 cases of Tuberculosis, all forms combined, were reported in 2015, representing an incidence of 89 cases per 100,000 population. The number of deaths from tuberculosis (TB) was 656 cases. In the prefecture of Meknes, its incidence remains high compared to the national level. The objective of this work is to describe the epidemiological profile of tuberculosis in the prefecture of Meknes. Methods: It is a descriptive analysis of TB cases reported between 2016 and 2020 at the regional diagnostic center of tuberculosis and respiratory diseases. We performed analysis by using Microsoft Excel and EpiInfo 7. Results: Epidemiological data from 2016 to 2020 report a total of 4100 new cases of all forms of tuberculosis, with an average of 820 new cases per year. The median age is 32 years. There is a clear male predominance, on average 58% of cases are male and 42% female. The incidence rate of bacteriologically confirmed tuberculosis per 100,000 inhabitants has increased from 35 cases per 100,000 inhabitants in 2016 to 39.4 cases per 100,000 inhabitants in 2020. The confirmation rate for pulmonary tuberculosis decreased from 84% in 2016 to 75% in 2020. Pulmonary involvement predominates by an average of 46%, followed by lymph node involvement 29%and pleural involvement by an average of 10%. Digestive, osteoarticular, genitourinary, and meningeal involvement occurs in 8% of cases. Primary tuberculosis infection occurs in an average of 0.5% of cases. The proportion of HIV-TB co-infections was 2.8 in 2020. Conclusion: The incidence of tuberculosis in Meknes remains high compared to the national level. Thus, it is imperative to reinforce the earlier detection; improve the contact tracing, detection methods of cases for their confirmation and treatment, and to reduce the proportion of the lost to follow up as well.

Keywords: tuberculosis, epidemiological profile, meknes, morocco

Procedia PDF Downloads 157

Authors: Ivan Balachin, Geanette Polanco, Jiang Xingliang, Hu Qin

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The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified.

Keywords: field data processing, regression determination, wind turbine performance, wind turbine placing, yaw system losses

Procedia PDF Downloads 390

Authors: Jamal Fayazi, Farhad Anoosheh, Mohammad R. Ghorbani, Ali R. Paydar

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In this study, to determine the best non-linear regression model describing the growth curve of native poultry, 9657 chicks of generations 18, 19, and 20 raised in Mazandaran breeding center were used. Fowls and roosters of this center distributed in south of Caspian Sea region. To estimate the genetic variability of none linear regression parameter of growth traits, a Gibbs sampling of Bayesian analysis was used. The average body weight traits in the first day (BW1), eighth week (BW8) and twelfth week (BW12) were respectively estimated as 36.05, 763.03, and 1194.98 grams. Based on the coefficient of determination, mean squares of error and Akaike information criteria, Gompertz model was selected as the best growth descriptive function. In Gompertz model, the estimated values for the parameters of maturity weight (A), integration constant (B) and maturity rate (K) were estimated to be 1734.4, 3.986, and 0.282, respectively. The direct heritability of BW1, BW8 and BW12 were respectively reported to be as 0.378, 0.3709, 0.316, 0.389, 0.43, 0.09 and 0.07. With regard to estimated parameters, the results of this study indicated that there is a possibility to improve some property of growth curve using appropriate selection programs.

Keywords: direct heritability, Gompertz, growth traits, maturity weight, native poultry

Procedia PDF Downloads 264

Authors: S. A. Sadegh Zadeh, C. Kambhampati

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Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.

Keywords: all-or-none, computational modelling, mathematical model, transmembrane voltage, action potential

Procedia PDF Downloads 617

Authors: Brianna M. Soule, Jesslyn A. Bryk-Lucy, Linda M. Ritchie

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Colic, defined as abdominal pain in the horse, has several known predisposing factors. Decreased water intake has been shown to predispose equines to impaction colic. The objective of this study was to determine if offering flavored water (sweet feed or banana extract) would increase voluntary water intake in horses to serve as an assessable, noninvasive method for farm managers, veterinarians, or owners to decrease the risk of impaction colic. An a priori power analysis, which was conducted using G*Power version 3.1.9.7, indicated that the minimum sample size required to achieve 80% power for detecting a large effect at a significance level of α = .05 was 19 horses for a one-way repeated measures ANOVA with three treatment levels and assuming a non-sphericity correction of ε=0.5. After a three-day control period, 21 horses were randomly divided into two sequences and offered either banana or sweet feed flavored water. Horses always had a bucket of unflavored water available. A repeated measure study design was used to measure water consumption of each horse over a 62-hour period. A one-way repeated measures ANOVA was conducted to determine whether there were statistically significant differences among the means for the three-day average water intake (ml/kg). Although not statistically significant (F(2, 38) = 1.28, p = .290, partial η2 = .063), the three-day average water intake was largest for banana flavored water (M = 53.51, SD = 9.25 ml/kg), followed by sweet feed (M = 52.93, SD = 11.99 ml/kg), and, finally, unflavored water (M = 50.40, SD = 10.82 ml/kg). Paired-samples t-tests were used to determine whether there was a statistically significant difference between the three-day average water intake (ml/kg) for flavored versus unflavored water. The average unflavored water intake (M = 29.3 ml/kg, SD = 8.9) over the measurement period was greater than the banana flavored water (M = 27.7 ml/kg, SD = 9.8), but the average consumption of the sweet feed flavored water (M = 30.4 ml/kg, SD = 14.6) was greater than unflavored water (M = 24.3 ml/kg, SD = 11.4). None of these differences in average intake were statistically significant (p > .244). Future research is warranted to determine if other flavors significantly increase voluntary water intake in horses.

Keywords: colic, equine, equine science, water intake, flavored water, horses, equine management, equine health, horse health, horse health care management, colic prevention

Procedia PDF Downloads 148

Authors: A. J. Julius, E. Imoagene, O. A. Ganiyu

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The purpose of this study is to estimate the economic value of the services and functions rendered by the forest landscape using a conditional logit model. For this study, attributes and levels of forest landscape were chosen; specifically, attributes include topographical forest type, forest type, forest density, recreational factor (side trip, accessibility of valley), and willingness to participate (WTP). Based on these factors, 48 choices sets with balanced and orthogonal form using statistical analysis system (SAS) 9.1 was adopted. The efficiency of the questionnaire was 6.02 (D-Error. 0.1), and choice set and socio-economic variables were analyzed. To reduce the cognitive load of respondents, the 48 choice sets were divided into 4 types in the questionnaire, so that respondents could respond to 12 choice sets, respectively. The study populations were citizens from seven metropolitan cities including Ibadan, Ilorin, Osogbo, etc. and annual WTP per household was asked by using the interview questionnaire, a total of 267 copies were recovered. As a result, Oshogbo had 0.45, and the statistical similarities could not be found except for urban forests, forest density, recreational factor, and level of WTP. Average annual WTP per household for forest landscape was 104,758 Naira (Nigerian currency) based on the outcome from this model, total economic value of the services and functions enjoyed from Nigerian forest landscape has reached approximately 1.6 trillion Naira.

Keywords: economic valuation, urban cities, services, forest landscape, logit model, nigeria

Procedia PDF Downloads 132