Search results for: velocity prediction program

Authors: Yanni Chang, Dezhi Dai, Albert Y. Tong

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Piecewise linear interface calculation (PLIC) schemes are widely used in the volume-of-fluid (VOF) method to capture interfaces in numerical simulations of multiphase flows. Dynamic overset meshes can be especially useful in applications involving component motions and complex geometric shapes. In the present study, the VOF value of an acceptor cell is evaluated in a geometric way that transfers the fraction field between the meshes precisely with reconstructed interfaces from the corresponding donor elements. The acceptor cell value is evaluated by using a weighted average of its donors for most of the overset interpolation schemes for continuous flow variables. The weighting factors are obtained by different algebraic methods. Unlike the continuous flow variables, the VOF equation is a step function near the interfaces, which ranges from zero to unity rapidly. A geometric interpolation scheme of the VOF field in overset meshes for the PLIC-VOF method has been proposed in the paper. It has been tested successfully in quadrilateral/hexahedral overset meshes by employing several VOF advection tests with imposed solenoidal velocity fields. The proposed algorithm has been shown to yield higher accuracy in mass conservation and interface reconstruction compared with three other algebraic ones.

Keywords: interpolation scheme, multiphase flows, overset meshes, PLIC-VOF method

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Authors: Olu Akande

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This study explores the effectiveness of a community-based hand hygiene education and awareness program in reducing community-acquired infections among children with limited access to healthcare services. Utilizing the PICOT framework, this research evaluates the impact of targeted hand hygiene interventions compared to standard care on infection rates, specifically respiratory and gastrointestinal diseases, over a six-month period. The findings aim to inform public health strategies to improve health outcomes in underserved communities. This study highlights the importance of preventative measures in addressing healthcare disparities and enhancing community resilience.

Keywords: community-based education, hand hygiene, infection prevention, underserved communities

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Authors: Valentina Rodas, Luis Almache

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The interaction effects between the existing soil and the substructure of a 5-story building with an underground one were evaluated in such a way that the structural-geotechnical concepts were validated through the method of impedance factors with a program based on the method of the finite elements. The continuous wall-type foundation had a constant thickness and followed inclined and orthogonal directions, while the ground had homogeneous and medium-type characteristics. The soil considered was type C according to the Ecuadorian Construction Standard (NEC) and the corresponding foundation comprised a depth of 4.00 meters and a basement wall thickness of 40 centimeters. This project is part of a mid-rise building in the city of Azogues (Ecuador). The hypotheses raised responded to the objectives in such a way that the model implemented with springs had a variation with respect to the embedded base, obtaining conservative results.

Keywords: interaction, soil, substructure, springs, effects, modeling , embedment

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira

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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.

Keywords: neurology, intracranial pressure, medical education, simulation

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Authors: Hossein Agheshlui, Stephan Matthai

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In fractured rock masses open fractures tend to act as the main pathways of fluid flow. The permeability of a rock fracture depends on its aperture. The change of aperture with stress can cause a many-orders-of-magnitude change in the hydraulic conductivity at moderate compressive stress levels. In this study, the change of aperture in fragmented rocks is investigated using finite element analysis. A full 3D mechanical model of a simplified version of an outcrop analog is created and studied. A constant initial aperture value is applied to all fractures. Different far field stresses are applied and the change of aperture is monitored considering the block to block interaction. The fragmented rock layer is assumed to be sandwiched between softer layers. Frictional contact forces are defined at the layer boundaries as well as among contacting rock blocks. For a given in situ stress, the blocks slide and contact each other, resulting in new aperture distributions. A map of changed aperture is produced after applying the in situ stress and compared to the initial apertures. Subsequently, the permeability of the system before and after the stress application is compared.

Keywords: fractured rocks, mechanical model, aperture change due to stress, frictional interface

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Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

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The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

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Authors: H. E. Budak, B. Arslan-Ilkiz, N. Cakmakci, I. Gocek, U. K. Sahin, H. Acikgoz-Tufan, M. H. Arslan

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The aim of this study is to design a novel laundry algorithm for colored textiles which have significant decoloring problem. During the experimental work, bleached knitted single jersey fabric made of 100% cotton and dyed with reactive dyestuff was utilized, since according to a conducted survey textiles made of cotton are the most demanded textile products in the textile market by the textile consumers and for coloration of textiles reactive dyestuffs are the ones that are the most commonly used in the textile industry for dyeing cotton-made products. Therefore, the fabric used in this study was selected and purchased in accordance with the survey results. The fabric samples cut out of this fabric were dyed with different dyeing parameters by using Remazol Brilliant Red 3BS dyestuff in Gyrowash machine at laboratory conditions. From the alternative reactive-dyed cotton fabric samples, the ones that have high tendency to color loss were determined and examined. Accordingly, the parameters of the dyeing process used for these fabric samples were evaluated and the dyeing process which was chosen to be used for causing high tendency to color loss for the cotton fabrics was determined in order to reveal the level of improvement in color loss during this study clearly. Afterwards, all of the untreated fabric samples cut out of the fabric purchased were dyed with the dyeing process selected. When dyeing process was completed, an experimental design was created for the laundering process by using Minitab® program considering temperature, time and mechanical action as parameters. All of the washing experiments were performed in domestic washing machine. 16 washing experiments were performed with 8 different experimental conditions and 2 repeats for each condition. After each of the washing experiments, water samples of the main wash of the laundering process were measured with UV spectrophotometer. The values obtained were compared with the calibration curve of the materials used for the dyeing process. The results of the washing experiments were statistically analyzed with Minitab® program. According to the results, the most suitable washing algorithm to be used in terms of the parameters temperature, time and mechanical action for domestic washing machines for minimizing fabric color loss was chosen. The laundry algorithm proposed in this study have the ability of minimalizing the problem of color loss of colored textiles in washing machines by eliminating the negative effects of the parameters of laundering process on color of textiles without compromising the fundamental effects of basic cleaning action being performed properly. Therefore, since fabric color loss is minimized with this washing algorithm, dyestuff residuals will definitely be lower in the grey water released from the laundering process. In addition to this, with this laundry algorithm it is possible to wash and clean other types of textile products with proper cleaning effect and minimized color loss.

Keywords: color loss, laundry algorithm, textiles, domestic washing process

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Authors: Ka Hin Kevin Lee, Jacob Lindh, Yue Qing LI

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The biomechanics of golf swing performance are increasingly being investigated to better understand the relationship between gender and equipment choices. Gender-based variations in swing mechanics, particularly wrist kinematics, are thought to have a substantial influence on performance. While current studies show gender differences in wrist motions and the impact of club selection, there is little study on amateur collegiate golfers. This demography provides a unique perspective, spanning professional and leisure activity and providing significant biomechanical aspects. This study looks into gender differences in wrist kinematics during golf swings, specifically angular velocities (yaw, pitch, and roll) and the impact of club choice. Ten undergraduate golfers (five male and five female) took part in the study, each doing five swings with a 7-iron and a driver. Participants used their own clubs to guarantee familiarity and minimize variation. Xsens MTw Awinda wireless motion sensors were mounted on their forearms and wrists, gathering high-resolution motion data at 100 Hz. A thorough calibration procedure was used to synchronise sensor data with individual stances. The trial replicated real-world playing settings, with players told to take full-power swings. Data were processed and analysed in MATLAB, with angular velocity profiles extracted for each swing.

Keywords: biomechanics, sports, performance, gender, wrist, kinematics

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Authors: Chejarla Raghunathababu, E. Logashanmugam

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An antenna is an assortment of linked devices that function together to transmit and receive radio waves as a single antenna. Antennas occur in a variety of sizes and forms, but the microstrip patch antenna outperforms other types in terms of effectiveness and prediction. These antennas are easy to generate with discreet benefits. Nevertheless, the antenna's effectiveness will be affected because of the patch's shape above a thick dielectric substrate. As a result, a double-pole rectangular microstrip antenna with nanofillers was suggested in this study. By employing nano-composite substances (Fumed Silica and Aluminum Oxide), which are composites of graphene with nanofillers, the physical characteristics of the microstrip antenna, that is, the elevation of the microstrip antenna substrate and the width of the patch microstrip antenna have been improved in this research. The surface conductivity of graphene may be modified to function at specific frequencies. In order to prepare for future wireless communication technologies, a microstrip patch antenna operating at 93 GHz resonant frequency is constructed and investigated. The goal of this study was to reduce VSWR and increase gain. The simulation yielded results for the gain and VSWR, which were 8.26 dBi and 1.01, respectively.

Keywords: graphene, microstrip patch antenna, substrate material, wireless communication, nanocomposite material

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Authors: Ehsan Gholamalizadeh, Jae Dong Chung

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Solar chimney power plant is a feasible solar thermal system which produces electricity from the Sun. The objective of this study is to investigate buoyancy-driven flow and heat transfer through a built pilot solar chimney system called 'Kerman Project'. The system has a chimney with the height and diameter of 60 m and 3 m, respectively, and the average radius of its solar collector is about 20 m, and also its average collector height is about 2 m. A three-dimensional simulation was conducted to analyze the system, using computational fluid dynamics (CFD). In this model, radiative transfer equation was solved using the discrete ordinates (DO) radiation model taking into account a non-gray radiation behavior. In order to modelling solar irradiation from the sun’s rays, the solar ray tracing algorithm was coupled to the computation via a source term in the energy equation. The model was validated with comparing to the experimental data of the Manzanares prototype and also the performance of the built pilot system. Then, based on the numerical simulations, velocity and temperature distributions through the system, the temperature profile of the ground surface and the system performance were presented. The analysis accurately shows the flow and heat transfer characteristics through the pilot system and predicts its performance.

Keywords: buoyancy-driven flow, computational fluid dynamics, heat transfer, renewable energy, solar chimney power plant

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Authors: Adel M. Mahmoud

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This Investigation was conducted to determine the productivity and water use efficiency for new sunflower genotypes. Ten sunflower genotypes were evaluated under drip irrigation using two treatments of. Results indicate that decreasing the amount of irrigation water from 1500 to 1130 mm/hectar significantly reduced all studied traits. Mutation (M1-63) surpassed all the other one genotypes in seed yield and WUE. Lines which gave the highest yield of the seed have water use efficiency under drought conditions higher than water use efficiency under normal irrigation. The lowest depression in seed yield due to drought conditions has been registered for Line 20, Line M1-63 and Sakha 53 genotypes (11 , 18 and 16 %, respectively). Genotypes (Line 20 , Line M1-63 and Sakha 53) are more tolerant to drought than others and we can used its in breeding program to develop sunflower hybrids suitable for cultivation under drought condition.

Keywords: sunflower genotypes, water use efficiency, mutation, inbred lines

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Authors: Sebwato Nasurudiin, Akimasa Yoshikawa, Ahmed Elsaid, Ayman Mahrous

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This study examines the correlation between the amplitude of Forbush Decreases (FDs) detected by the Mountain Chacaltaya neutron monitor and the solar wind electric field (E). Forbush Decreases, characterized by sudden drops in cosmic ray intensity, are typically associated with interplanetary coronal mass ejections (ICMEs) and high-speed solar wind streams. The Mountain Chacaltaya neutron monitor, located at a high altitude in Bolivia, offers an optimal setting for observing cosmic ray variations. The solar wind electric field, influenced by the solar wind velocity and interplanetary magnetic field, significantly impacts cosmic ray transport in the heliosphere. By analyzing neutron monitor data alongside solar wind parameters, we found a high correlation between E and FD amplitudes with a correlation factor of nearly 87%. The findings enhance our understanding of space weather processes, cosmic ray modulation, and solar-terrestrial interactions, providing valuable insights for predicting space weather events and mitigating their technological impacts. This study contributes to the broader astrophysics field by offering empirical data on cosmic ray modulation mechanisms.

Keywords: cosmic rays, Forbush decrease, solar wind, neutron monitor

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Authors: Muhammad Kamran, Xue Pu, Naveed Ahmed

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Sandwich foam structures are efficient in impact energy absorption and making components lightweight; however their efficient use require a detailed understanding of its mechanical response. In this study, the foam core, laminated facings’ sandwich panel with internal triangular rib configuration is impacted by a spherical steel projectile at different angles using ABAQUS finite element package and damage mechanics is studied. Laminated ribs’ structure is sub-divided into three formations; all zeros, all 45 and optimized combination of zeros and 45 degrees. Impact velocity is varied from 250 m/s to 500 m/s with an increment of 50 m/s. The impact damage can significantly demolish the structural integrity and energy absorption due to fiber breakage, matrix cracking, and de-bonding. Macroscopic fracture study of the panel and core along with load-displacement responses and failure modes are the key parameters in the design of smart ballistic resistant structures. Ballistic impact characteristics of panels are studied on different speed, different inclination angles and its dependency on the base, and core materials, ribs formation, and cross-sectional spaces among them are determined. Impact momentum, penetration and kinetic energy absorption data and curves are compiled to predict the first and proximity impact in an effort to enhance the dynamic energy absorption.

Keywords: dynamic energy absorption, proximity impact, sandwich panels, impact momentum

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Ashkan Shafee, Ahamd Fahimifar, Sajjad V. Maghvan

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Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.

Keywords: concrete damaged plasticity, fiber reinforced concrete, finite element modeling, macro-synthetic fibers, uniaxial tensile test

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Authors: Wahab Ali Shah, Junjia He

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In this work, we performed a large-scale investigation into leader development in a 10 m rod-plane gap under a long front positive impulse. To describe the leader propagation under slow front impulse voltages, we recorded the leader propagation with a high-speed charge coupled device (CCD) camera. It is important to figure out this phenomenon to deepen our understanding of leader discharge. The observation results showed that the leader mechanism is a very complex physical phenomenon; it could be categorized into two types of leader process, namely, continuous and the discontinuous leader streamer-leader propagation. Furthermore, we studied the continuous leader development parameters, including two-dimensional (2-D) leader length, injected charge, and final jump stage, as well as leader velocity for rod–plane configuration. We observed that the discontinuous leader makes an important contribution to the appearance of channel re-illuminations of the positive leader. The comparative study shows better results in terms of standard switch impulse and long front positive impulse. Finally, the results are presented with a view toward improving our understanding of propagation mechanisms related to restrike phenomena, which are rarely reported. To clarify the above doubts under long front cases, we carried out extensive experiments in this study.

Keywords: continuous and discontinuous leader, high-speed photographs, long air gap, positive long front impulse, restrike phenomena

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: S. K. Ashiquer Rahman

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This paper presents a knowledge mediation platform, “ePLANETe Blue” that addresses the challenge of building knowledge partnerships for higher education. The purpose is to present, as an institutional perception, the ‘ePLANETe' idea and functionalities as a practical and pedagogical innovation program contributing to the collaborative learning goals in higher education. In consequence, the set of functionalities now amalgamated in ‘ePLANETe’ can be seen as an investigation of the challenges of “Collaborative Learning Digital Process.” It can exploit the system to facilitate collaborative education, research and student learning in higher education. Moreover, the platform is projected to support the identification of best practices at explicit levels of action and to inspire knowledge interactions in a “virtual community” and thus to advance in deliberation and learning evaluation of higher education through the engagement of collaborative activities of different sorts.

Keywords: mediation, collaboration, deliberation, evaluation

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Authors: Sajjad Negahban, Ruihe Wang, Baojiang Sun

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Gas-lift dual gradient drilling is a solution for deepwater drilling challenges. As well, Continuous development of drilling technology leads to increase employment of mineral oil based drilling fluids and synthetic-based drilling fluids, which have adequate characteristics such as: high rate of penetration, lubricity, shale inhibition and low toxicity. The paper discusses utilization of nitrified mineral oil base drilling for deepwater drilling and for more accurate prediction of pressure in DGD at marine riser, solubility and bubble pressure were considered in steady state hydraulic model. The Standing bubble pressure and solubility correlations, and two models which were acquired from experimental determination were applied in hydraulic model. The effect of the black oil correlations, and new solubility and bubble pressure models was evaluated on the PVT parameters such as oil formation volume factor, density, viscosity, volumetric flow rate. Eventually, the consequent simulated pressure profile due to these models was presented.

Keywords: solubility, bubble pressure, gas-lift dual gradient drilling, steady state hydraulic model

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Authors: Gajaanuja Megalathan, Banuka Athuraliya

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Crime is one of our society's most intimidating and threatening challenges. With the majority of the population residing in cities, many experts and data provided by local authorities suggest a rapid increase in the number of crimes committed in these cities in recent years. There has been an increasing graph in the crime rates. People living in Sri Lanka have the right to know the exact crime rates and the crime rates in the future of the place they are living in. Due to the current economic crisis, crime rates have spiked. There have been so many thefts and murders recorded within the last 6-10 months. Although there are many sources to find out, there is no solid way of searching and finding out the safety of the place. Due to all these reasons, there is a need for the public to feel safe when they are introduced to new places. Through this research, the author aims to develop a mobile application that will be a solution to this problem. It is mainly targeted at tourists, and people who recently relocated will gain advantage of this application. Moreover, the Arima Model combined with ANN is to be used to predict crime rates. From the past researchers' works, it is evidently clear that they haven’t used the Arima model combined with Artificial Neural Networks to forecast crimes.

Keywords: arima model, ANN, crime prediction, data analysis

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Authors: Rozelle Labuschagne, Ronel Roos

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Individuals often experience a reduction in physical function, quality of life and basic activities of daily living after surgery. This is exponentially true for high-risk patients, especially the elderly and frail individuals. Not much is known about the physical function, physical activity preferences and factors associated with the six-minute walk test of elderly individuals who would undergo elective abdominal surgery in South Africa. Such information is important to design effective prehabilitation physiotherapy programs prior to elective surgery. The purpose of the study was to describe the demographic profile and physical function of elderly patients who would undergo elective surgery and to determine factors associated with their six-minute walk test distance findings. A cross-sectional descriptive study in elderly patients older than 60 years of age who would undergo elective abdominal surgery were consecutively sampled at a private hospital in Pretoria, South Africa. Participants’ demographics were collected and physical function assessed with the Functional Comorbidity Index (FCI), DeMorton Mobility Index (DEMMI), Lawton-Brody Instrumental Activities of Daily Living Scale (IADL) and six-minute walk test (6MWT). Descriptive and inferential statistics were used for data analysis with IBM SPSS 25. A p-value ≤ 0.05 were deemed statistically significant. The pilot study consisted of 12 participants (female (n=11, 91.7%), male (n=1, 8.3%) with a mean age of 65.8 (±4.5) years, body mass index of 28 (±4.2) kg.m2 with one (8.3%) participant being a current smoker and four (33.3%) participants having a smoking history. Nine (75%) participants lived independently at home and three (25%) had caregivers. Participants reported walking (n=6, 50%), stretching exercises (n=1, 8.3%), household chores & gardening (n=2, 16.7%), biking/swimming/running (n=1, 8.3%) as physical activity preferences. Physical function findings of the sample were: mean FCI score 3 (±1.1), DEMMI score 81.1 (±14.9), IADL 95 (±17.3), 6MWT 435.50 (IQR 364.75-458.50) with percentage 6MWT distance achieved 81.8% (IQR 64.4%-87.5%). A strong negative correlation was observed between 6MWT distance walked and FCI (r = -0.729, p=0.007). The majority of study participants reported incorporating some form of physical activity into their daily life as form of exercise. Most participants did not achieve their predicted 6MWT distance indicating less than optimal levels of physical function capacity. The number of comorbidities as determined by the FCI was associated with the distance that participants could walk with the 6MWT. The results of this pilot study could be used to indicate which elderly individuals would benefit most from a pre-surgical rehabilitation program. The main goal of such a program would be to improve physical function capacity as measured by the 6MWT. Surgeons could refer patients based on age and number of comorbidities, as determined by the FCI, to potentially improve surgical outcomes.

Keywords: abdominal surgery, elderly, physical function, six-minute walk test

Procedia PDF Downloads 203

Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

Abstract:

Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

Procedia PDF Downloads 505

Authors: Ramin Mansouri

Abstract:

The manhole is one of the types of structures that are installed at the site of change direction or change in the pipe diameter or sewage pipes as well as in step slope areas to reduce the flow velocity. In this study, the flow characteristics of hydraulic structures in a manhole structure have been investigated with a numerical model. In this research, the types of computational grid coarse, medium, and fines have been used for simulation. In order to simulate flow, k-ε model (standard, RNG, Realizable) and k-w model (standard SST) are used. Also, in order to find the best wall conditions, two types of standard and non-equilibrium wall functions were investigated. The turbulent model k-ε has the highest correlation with experimental results or all models. In terms of boundary conditions, constant speed is set for the flow input boundary, the output pressure is set in the boundaries which are in contact with the air, and the standard wall function is used for the effect of the wall function. In the numerical model, the depth at the output of the second manhole is estimated to be less than that of the laboratory and the output jet from the span. In the second regime, the jet flow collides with the manhole wall and divides into two parts, so hydraulic characteristics are the same as large vertical shaft hydraulic characteristics. In this situation, the turbulence is in a high range since it can be seen more energy loss in it. According to the results, energy loss in numerical is estimated at 9.359%, which is more than experimental data.

Keywords: manhole, energy, depreciation, turbulence model, wall function, flow

Procedia PDF Downloads 89

Authors: V. Villa-Cruz, H. Pérez-Ladron de Guevara, J. E. Diaz-Díaz

Abstract:

Static Light Scattering (SLS) was used as a method to analyse cow's milk raw, coming from the town of Lagos de Moreno, Jalisco, Mexico. This method is based on the analysis of the dispersion of light laser produced by a set of particles in solution. Based on the above, raw milk, which contains particles of fat globules, with a diameter of 2000 nm and particles of micelles of protein with 300 nm in diameter were analyzed. For this, dilutions of commercial milk were made (1.0%, 2.0% and 3.3%) to obtain a pattern of laser light scattering and also made measurements of raw cow's milk. Readings were taken in a sweep initial angle 10° to 170°, results were analyzed with the program OriginPro 7. The SLS method gives us an estimate of the percentage of fat content in milk samples. It can be concluded that the SLS method, is a quick method of analysis to detect adulteration in raw cow's milk.

Keywords: light scattering, milk analysis, adulteration in milk, micelles, OriginPro

Procedia PDF Downloads 378