Search results for: Taylor’s Series Method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21043

Search results for: Taylor’s Series Method

20263 Software Engineering Inspired Cost Estimation for Process Modelling

Authors: Felix Baumann, Aleksandar Milutinovic, Dieter Roller

Abstract:

Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by initial solutions which are discussed in the literature. This article proposes a method of filling this gap by deriving a cost estimation method from available methods in similar domains namely software development or software engineering. Software development is regarded as closely similar to process modelling as we show. After the proposition of this method different ideas for further analysis and validation of the method are proposed. We derive this method from COCOMO II and Function Point which are established methods of effort estimation in the domain of software development. For this we lay out similarities of the software development rocess and the process of process modelling which is a phase of the Business Process Management life-cycle.

Keywords: COCOMO II, busines process modeling, cost estimation method, BPM COCOMO

Procedia PDF Downloads 440
20262 An Investigation of Rainfall Changes in KanganCity During Years 1964 to 2003

Authors: Borzou Faramarzi, Farideh Azimi, Azam Gohardoust, Abbas Ghasemi Ghasemvand, Maryam Mirzaei, Mandana Amani

Abstract:

In this study, attempts were made to examine and analyze the trend for rainfall changes in Kangan City, Booshehr Province, during the time span 1964 to 2003, using seven rainfall threshold indices based on 50 climate extremes indices approved by WMO–CCL/CLIVAR. These indices include days with heavy precipitations, days with rainfalls, frequency of rainfall threshold values, intensity of rainfall threshold values, percentage of rainfall threshold values, successive days of rainfall, and successive days with no precipitation. Results are indicative of the fact that Kangan City climatic conditions have become more dried than before. Indices days with heavy precipitations and days with rainfalls do not show a certain trend in Kangan City. Frequency, intensity, and percentage of rainfall threshold values in the station under investigation do not indicate a certain trend. In analysis of time series of rainfall extreme indices, generally, it was revealed that Kangan City is influenced by general factors of global warming. Calculation of values for the next 10 years based on ARIMA models demonstrates a continuation of warming trends in Kangan City. On the whole, rainfall conditions in Kangan City have experienced more dry periods compared to the past, the trend which is also observable for next 10 years.

Keywords: climatic indices, climate change, extreme temperature and precipitation, time series

Procedia PDF Downloads 272
20261 Selection the Most Suitable Method for DNA Extraction from Muscle of Iran's Canned Tuna by Comparison of Different DNA Extraction Methods

Authors: Marjan Heidarzadeh

Abstract:

High quality and purity of DNA isolated from canned tuna is essential for species identification. In this study, the efficiency of five different methods for DNA extraction was compared. Method of national standard in Iran, the CTAB precipitation method, Wizard DNA Clean Up system, Nucleospin and GenomicPrep were employed. DNA was extracted from two different canned tuna in brine and oil of the same tuna species. Three samples of each type of product were analyzed with the different methods. The quantity and quality of DNA extracted was evaluated using the 260 nm absorbance and ratio A260/A280 by spectrophotometer picodrop. Results showed that the DNA extraction from canned tuna preserved in different liquid media could be optimized by employing a specific DNA extraction method in each case. Best results were obtained with CTAB method for canned tuna in oil and with Wizard method for canned tuna in brine.

Keywords: canned tuna PCR, DNA, DNA extraction methods, species identification

Procedia PDF Downloads 657
20260 Rainfall Analysis in the Contest of Climate Change for Jeddah Area, Western Saudi Arabia

Authors: Ali M. Subyani

Abstract:

The increase in the greenhouse gas emission has had a severe impact on global climate change and is bound to affect the weather patterns worldwide. This climate change impacts are among the future significant effects on any society. Rainfall levels are drastically increasing with flash floods in some places and long periods of droughts in others, especially in arid regions. These extreme events are causes of interactions concerning environmental, socio-economic and cultural life and their implementation. This paper presents the detailed features of dry and wet spell durations and rainfall intensity series available (1971-2012) on daily basis for the Jeddah area, Western, Saudi Arabia. It also presents significant articles for combating the climate change impacts on this area. Results show trend changes in dry and wet spell durations and rainfall amount on daily, monthly and annual time series. Three rain seasons were proposed in this investigation: high rain, low rain, and dry seasons. It shows that the overall average dry spell durations is about 80 continuous days while the average wet spell durations is 1.39 days with an average rainfall intensity of 8.2 mm/day. Annual and seasonal autorun analyses confirm that the rainy seasons are tending to have more intense rainfall while the seasons are becoming drier. This study would help decision makers in future for water resources management and flood risk analysis.

Keywords: climate change, daily rainfall, dry and wet spill, Jeddah, Saudi Arabia

Procedia PDF Downloads 338
20259 PM10 Prediction and Forecasting Using CART: A Case Study for Pleven, Bulgaria

Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

Abstract:

Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

Procedia PDF Downloads 194
20258 Damage Localization of Deterministic-Stochastic Systems

Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

Abstract:

A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification

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20257 The Cultural Adaptation of a Social and Emotional Learning Program for an Intervention in Saudi Arabia’s Preschools

Authors: Malak Alqaydhi

Abstract:

A problem in the Saudi Arabia education system is that there is a lack of curriculum- based Social, emotional learning (SEL) teaching practices with the pedagogical concept of SEL yet to be practiced in the Kingdom of Saudi Arabia (KSA). Furthermore, voices of teachers and parents have not been captured regarding the use of SEL, particularly in preschools. The importance of this research is to help determine, with the input of teachers and mothers of preschoolers, the efficacy of a culturally adapted SEL program. The purpose of this research is to determine the most appropriate SEL intervention method to appropriately apply in the cultural context of the Saudi preschool classroom setting. The study will use a mixed method exploratory sequential research design, applying qualitative and quantitative approaches including semi-structured interviews with teachers and parents of preschoolers and an experimental research approach. The research will proceed in four phases beginning with a series of interviews with Saudi preschool teachers and mothers, whose voices and perceptions will help guide the second phase of selection and adaptation of a suitable SEL preschool program. The third phase will be the implementation of the intervention by the researcher in the preschool classroom environment, which will be facilitated by the researcher’s cultural proficiency and practical experience in Saudi Arabia. The fourth and final phase will be an evaluation to assess the effectiveness of the trialled SEL among the preschool student participants. The significance of this research stems from its contribution to knowledge about SEL in culturally appropriate Saudi preschools and the opportunity to support initiatives for Saudi early childhood educators to consider implementing SEL programs. The findings from the study may be useful to inform the Saudi Ministry of Education and its curriculum designers about SEL programs, which could be beneficial to trial more widely in the Saudi preschool curriculum.

Keywords: social emotional learning, preschool children, saudi Arabia, child behavior

Procedia PDF Downloads 157
20256 An Optimized Method for Calculating the Linear and Nonlinear Response of SDOF System Subjected to an Arbitrary Base Excitation

Authors: Hossein Kabir, Mojtaba Sadeghi

Abstract:

Finding the linear and nonlinear responses of a typical single-degree-of-freedom system (SDOF) is always being regarded as a time-consuming process. This study attempts to provide modifications in the renowned Newmark method in order to make it more time efficient than it used to be and make it more accurate by modifying the system in its own non-linear state. The efficacy of the presented method is demonstrated by assigning three base excitations such as Tabas 1978, El Centro 1940, and MEXICO CITY/SCT 1985 earthquakes to a SDOF system, that is, SDOF, to compute the strength reduction factor, yield pseudo acceleration, and ductility factor.

Keywords: single-degree-of-freedom system (SDOF), linear acceleration method, nonlinear excited system, equivalent displacement method, equivalent energy method

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20255 Estrogen Controls Hepatitis C Virus Entry and Spread through the GPR30 Pathway

Authors: Laura Ulitzky, Dougbeh-Chris Nyan, Manuel M. Lafer, Erica Silberstein, Nicoleta Cehan, Deborah R. Taylor

Abstract:

Hepatitis C virus (HCV)-associated hepatocellular carcinoma, fibrosis and cirrhosis are more frequent in men and postmenopausal women than in premenopausal women and women receiving hormone replacement therapy, suggesting that β-estradiol (estrogen) plays an innate role in preventing viral infection and liver disease. Estrogen classically acts through nuclear estrogen receptors or, alternatively, through the membrane-bound G-protein-coupled estrogen receptor (GPR30 or GPER). We observed a marked decrease in detectable virus when HCV-infected human hepatoma cells were treated with estrogen. The effect was mimicked by both Tamoxifen (Tam) and G1, a GPR30-specific agonist, and was reversed by the GPR30-specific antagonist, G15. Through GPR30, estrogen-mediated the down-regulation of occludin; a tight junction protein and HCV receptor, by promoting activation of matrix metalloproteinases (MMPs). Activated MMP-9 was secreted in response to estrogen, cleaving occludin in the extracellular Domain D, the motif required for HCV entry and spread. This pathway gives new insight into a novel innate immune pathway and the disparate host-virus responses to HCV demonstrated by the two sexes. Moreover, these data suggest that hormone replacement therapy may have beneficial antiviral properties for HCV-infected postmenopausal women and show promise for new antiviral treatments for both men and women.

Keywords: HCV, estrogen, occludin, MMPs

Procedia PDF Downloads 437
20254 An Equivalent Circuit Model Approach for Battery Pack Simulation in a Hybrid Electric Vehicle System Powertrain

Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

Abstract:

The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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20253 Hybrid GNN Based Machine Learning Forecasting Model For Industrial IoT Applications

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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20252 A Semi-Implicit Phase Field Model for Droplet Evolution

Authors: M. H. Kazemi, D. Salac

Abstract:

A semi-implicit phase field method for droplet evolution is proposed. Using the phase field Cahn-Hilliard equation, we are able to track the interface in multiphase flow. The idea of a semi-implicit finite difference scheme is reviewed and employed to solve two nonlinear equations, including the Navier-Stokes and the Cahn-Hilliard equations. The use of a semi-implicit method allows us to have larger time steps compared to explicit schemes. The governing equations are coupled and then solved by a GMRES solver (generalized minimal residual method) using modified Gram-Schmidt orthogonalization. To show the validity of the method, we apply the method to the simulation of a rising droplet, a leaky dielectric drop and the coalescence of drops. The numerical solutions to the phase field model match well with existing solutions over a defined range of variables.

Keywords: coalescence, leaky dielectric, numerical method, phase field, rising droplet, semi-implicit method

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20251 Deflagration and Detonation Simulation in Hydrogen-Air Mixtures

Authors: Belyayev P. E., Makeyeva I. R., Mastyuk D. A., Pigasov E. E.

Abstract:

Previously, the phrase ”hydrogen safety” was often used in terms of NPP safety. Due to the rise of interest to “green” and, particularly, hydrogen power engineering, the problem of hydrogen safety at industrial facilities has become ever more urgent. In Russia, the industrial production of hydrogen is meant to be performed by placing a chemical engineering plant near NPP, which supplies the plant with the necessary energy. In this approach, the production of hydrogen involves a wide range of combustible gases, such as methane, carbon monoxide, and hydrogen itself. Considering probable incidents, sudden combustible gas outburst into open space with further ignition is less dangerous by itself than ignition of the combustible mixture in the presence of many pipelines, reactor vessels, and any kind of fitting frames. Even ignition of 2100 cubic meters of the hydrogen-air mixture in open space gives velocity and pressure that are much lesser than velocity and pressure in Chapman-Jouguet condition and do not exceed 80 m/s and 6 kPa accordingly. However, the space blockage, the significant change of channel diameter on the way of flame propagation, and the presence of gas suspension lead to significant deflagration acceleration and to its transition into detonation or quasi-detonation. At the same time, process parameters acquired from the experiments at specific experimental facilities are not general, and their application to different facilities can only have a conventional and qualitative character. Yet, conducting deflagration and detonation experimental investigation for each specific industrial facility project in order to determine safe infrastructure unit placement does not seem feasible due to its high cost and hazard, while the conduction of numerical experiments is significantly cheaper and safer. Hence, the development of a numerical method that allows the description of reacting flows in domains with complex geometry seems promising. The base for this method is the modification of Kuropatenko method for calculating shock waves recently developed by authors, which allows using it in Eulerian coordinates. The current work contains the results of the development process. In addition, the comparison of numerical simulation results and experimental series with flame propagation in shock tubes with orifice plates is presented.

Keywords: CFD, reacting flow, DDT, gas explosion

Procedia PDF Downloads 90
20250 Imputation of Incomplete Large-Scale Monitoring Count Data via Penalized Estimation

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

Abstract:

In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

Procedia PDF Downloads 156
20249 Teenage Pregnancy: The Unmet Needs of Female Adolescents in Uganda

Authors: M. Weller Jones, J. Moffat, J. Taylor, J. Hartland, M. Natarajan

Abstract:

Background: Uganda’s teenage pregnancy rate remains a significant problem for female and maternal health in the country. Teenage pregnancy is linked to higher rates of maternal and neonatal mortality and morbidity, including preterm labour, obstructed labour, vesicovaginal fistulae, infections, and maternal mental health morbidity. In 2015, the National Strategy to End Child Marriage and Teenage Pregnancy was launched in Uganda. Research is needed so that the interventions in this Strategy can be effectively applied at a local level. This study at Kitovu and Villa Maria Hospitals, two local community hospitals near Masaka, Uganda, aimed to measure change in the local teenage pregnancy rate over the past 5 years; and to explore the awareness and attitudes of teenagers and healthcare professionals towards 1) teenage pregnancy and, 2) the challenges female adolescents still currently face. Method: Teenage delivery rate, type of delivery, incidence of complications in labour and neonatal and maternal outcomes were collected from the labour ward admission books, at both hospitals, for a six month time period in 2011 and 2016. At Kitovu Hospital, qualitative data regarding the experience of, and attitudes towards teenage pregnancy was collected from interviews conducted with 12 maternity staff members and with eight female teenagers, aged 16-19, who were pregnant or post-partum. Results: The proportion of total births to teenage mothers fell from 14% in 2011 to 7% in 2016 (Kitovu), but it remains higher in rural locations (19%, Villa Maria). Beliefs about exacerbating factors included: poor access to contraception; misconceptions that contraception is damaging to women’s health; failing sex education in schools; and poor awareness of national campaigns to reduce teenage pregnancy. Staff felt that the best way to tackle teenage pregnancy was to improve sex education in schools and to sensitise families to these issues. Six of the eight teenagers wanted more frequent sex education and easier, cheap access to contraception. Only one teenager saw positive consequences stating that teenage pregnancy would ‘avoid operations later in life.’ Discussion: Teenage pregnancy is a recognised problem and strategies in the Masaka region should focus on improving sex education in schools and initiating an organisation that educates and supplies free contraception to teenagers.

Keywords: adolescents, attitudes, teenage pregnancy, Uganda

Procedia PDF Downloads 186
20248 Teacher’s Perception of Dalcroze Method Course as Teacher’s Enhancement Course: A Case Study in Hong Kong

Authors: Ka Lei Au

Abstract:

The Dalcroze method has been emerging in music classrooms, and music teachers are encouraged to integrate music and movement in their teaching. Music programs in colleges in Hong Kong have been introducing method courses such as Orff and Dalcroze method in music teaching as teacher’s education program. Since the targeted students of the course are music teachers who are making the decision of what approach to use in their classroom, their perception is significantly valued to identify how this approach is applicable in their teaching in regards to the teaching and learning culture and environment. This qualitative study aims to explore how the Dalcroze method as a teacher’s education course is perceived by music teachers from three aspects: 1) application in music teaching, 2) self-enhancement, 3) expectation. Through the lens of music teachers, data were collected from 30 music teachers who are taking the Dalcroze method course in music teaching in Hong Kong by the survey. The findings reveal the value and their intention of the Dalcroze method in Hong Kong. It also provides a significant reference for better development of such courses in the future in adaption to the culture, teaching and learning environment and teacher’s, student’s and parent’s perception of this approach.

Keywords: Dalcroze method, music teaching, perception, self-enhancement, teacher’s education

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20247 Exploring an Exome Target Capture Method for Cross-Species Population Genetic Studies

Authors: Benjamin A. Ha, Marco Morselli, Xinhui Paige Zhang, Elizabeth A. C. Heath-Heckman, Jonathan B. Puritz, David K. Jacobs

Abstract:

Next-generation sequencing has enhanced the ability to acquire massive amounts of sequence data to address classic population genetic questions for non-model organisms. Targeted approaches allow for cost effective or more precise analyses of relevant sequences; although, many such techniques require a known genome and it can be costly to purchase probes from a company. This is challenging for non-model organisms with no published genome and can be expensive for large population genetic studies. Expressed exome capture sequencing (EecSeq) synthesizes probes in the lab from expressed mRNA, which is used to capture and sequence the coding regions of genomic DNA from a pooled suite of samples. A normalization step produces probes to recover transcripts from a wide range of expression levels. This approach offers low cost recovery of a broad range of genes in the genome. This research project expands on EecSeq to investigate if mRNA from one taxon may be used to capture relevant sequences from a series of increasingly less closely related taxa. For this purpose, we propose to use the endangered Northern Tidewater goby, Eucyclogobius newberryi, a non-model organism that inhabits California coastal lagoons. mRNA will be extracted from E. newberryi to create probes and capture exomes from eight other taxa, including the more at-risk Southern Tidewater goby, E. kristinae, and more divergent species. Captured exomes will be sequenced, analyzed bioinformatically and phylogenetically, then compared to previously generated phylogenies across this group of gobies. This will provide an assessment of the utility of the technique in cross-species studies and for analyzing low genetic variation within species as is the case for E. kristinae. This method has potential applications to provide economical ways to expand population genetic and evolutionary biology studies for non-model organisms.

Keywords: coastal lagoons, endangered species, non-model organism, target capture method

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20246 Cycads Bark Harvest in Limpopo Province in South Africa: A Negative Practice Contributing to Biodiversity Loss

Authors: S. O. Bamigboye, P. M. Tshisikhawe, P. J. Taylor

Abstract:

Cycads are the most threatened plant species in the world. In South Africa over 70% of cycads are threatened with extinction with 60% of them as a result of bark harvest of these highly endangered species for medicinal purposes. 3 cycads species in South Africa have gone extinct due to bark harvest for medicinal purpose. This practice keeps increasing biodiversity loss within the nation and this has generated concern for conservationists on different way to discover how people go about this practices and how it can be discouraged. Studies have revealed this practice to be common practice in provinces like Kwazulu natal, Eastern cape, Gauteng, Mpumalanga, but studies in the past have not really focused on cycads bark harvest in Limpopo province. In this study we use the indigenous knowledge to discover a particular location within the Soutpansberg Montane (a major biodiversity hotspot in Limpopo Province in South Africa) in Vhembe district in Limpopo province not yet conserved where we have a highly disturbed population of cycads. Several individuals of cycads species have been highly damaged due to bark harvest in this location. We are about proposing that such areas needs attention for conservation to prevent the loss of these species endemic to this particular location. Our study hereby reveals that cycads bark harvest which is a major threat to African cycads is also a common practice in Limpopo Province in South Africa. Rigorous conservation action is required to discourage this practice in order to prevent further biodiversity loss in this region.

Keywords: bark harvest, Cycads, conservation, extinction, Limpopo

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20245 Computation of Stress Intensity Factor Using Extended Finite Element Method

Authors: Mahmoudi Noureddine, Bouregba Rachid

Abstract:

In this paper the stress intensity factors of a slant-cracked plate of AISI 304 stainless steel, have been calculated using extended finite element method and finite element method (FEM) in ABAQUS software, the results were compared with theoretical values.

Keywords: stress intensity factors, extended finite element method, stainless steel, abaqus

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20244 Spectrophotometric Methods for Simultaneous Determination of Binary Mixture of Amlodipine Besylate and Atenolol Based on Dual Wavelength

Authors: Nesrine T. Lamie

Abstract:

Four, accurate, precise, and sensitive spectrophotometric methods are developed for the simultaneous determination of a binary mixture containing amlodipine besylate (AM) and atenolol (AT) where AM is determined at its λmax 360 nm (0D), while atenolol can be determined by different methods. Method (A) is absorpotion factor (AFM). Method (B) is the new Ratio Difference method(RD) which measures the difference in amplitudes between 210 and 226 nm of ratio spectrum., Method (C) is novel constant center spectrophotometric method (CC) Method (D) is mean centering of the ratio spectra (MCR) at 284 nm. The calibration curve is linear over the concentration range of 10–80 and 4–40 μg/ml for AM and AT, respectively. These methods are tested by analyzing synthetic mixtures of the cited drugs and they are applied to their commercial pharmaceutical preparation. The validity of results was assessed by applying standard addition technique. The results obtained were found to agree statistically with those obtained by a reported method, showing no significant difference with respect to accuracy and precision.

Keywords: amlodipine, atenolol, absorption factor, constant center, mean centering, ratio difference

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20243 Despiking of Turbulent Flow Data in Gravel Bed Stream

Authors: Ratul Das

Abstract:

The present experimental study insights the decontamination of instantaneous velocity fluctuations captured by Acoustic Doppler Velocimeter (ADV) in gravel-bed streams to ascertain near-bed turbulence for low Reynolds number. The interference between incidental and reflected pulses produce spikes in the ADV data especially in the near-bed flow zone and therefore filtering the data are very essential. Nortek’s Vectrino four-receiver ADV probe was used to capture the instantaneous three-dimensional velocity fluctuations over a non-cohesive bed. A spike removal algorithm based on the acceleration threshold method was applied to note the bed roughness and its influence on velocity fluctuations and velocity power spectra in the carrier fluid. The velocity power spectra of despiked signals with a best combination of velocity threshold (VT) and acceleration threshold (AT) are proposed which ascertained velocity power spectra a satisfactory fit with the Kolmogorov “–5/3 scaling-law” in the inertial sub-range. Also, velocity distributions below the roughness crest level fairly follows a third-degree polynomial series.

Keywords: acoustic doppler velocimeter, gravel-bed, spike removal, reynolds shear stress, near-bed turbulence, velocity power spectra

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20242 Mapping Method to Solve a Nonlinear Schrodinger Type Equation

Authors: Edamana Vasudevan Krishnan

Abstract:

This paper studies solitons in optical materials with the help of Mapping Method. Two types of nonlinear media have been investigated, namely, the cubic nonlinearity and the quintic nonlinearity. The soliton solutions, shock wave solutions and singular solutions have been derives with certain constraint conditions.

Keywords: solitons, integrability, metamaterials, mapping method

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20241 A General Variable Neighborhood Search Algorithm to Minimize Makespan of the Distributed Permutation Flowshop Scheduling Problem

Authors: G. M. Komaki, S. Mobin, E. Teymourian, S. Sheikh

Abstract:

This paper addresses minimizing the makespan of the distributed permutation flow shop scheduling problem. In this problem, there are several parallel identical factories or flowshops each with series of similar machines. Each job should be allocated to one of the factories and all of the operations of the jobs should be performed in the allocated factory. This problem has recently gained attention and due to NP-Hard nature of the problem, metaheuristic algorithms have been proposed to tackle it. Majority of the proposed algorithms require large computational time which is the main drawback. In this study, a general variable neighborhood search algorithm (GVNS) is proposed where several time-saving schemes have been incorporated into it. Also, the GVNS uses the sophisticated method to change the shaking procedure or perturbation depending on the progress of the incumbent solution to prevent stagnation of the search. The performance of the proposed algorithm is compared to the state-of-the-art algorithms based on standard benchmark instances.

Keywords: distributed permutation flow shop, scheduling, makespan, general variable neighborhood search algorithm

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20240 Performance Evaluation of Refinement Method for Wideband Two-Beams Formation

Authors: C. Bunsanit

Abstract:

This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband

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20239 A Novel Method for Solving Nonlinear Whitham–Broer–Kaup Equation System

Authors: Ayda Nikkar, Roghayye Ahmadiasl

Abstract:

In this letter, a new analytical method called homotopy perturbation method, which does not need small parameter in the equation is implemented for solving the nonlinear Whitham–Broer–Kaup (WBK) partial differential equation. In this method, a homotopy is introduced to be constructed for the equation. The initial approximations can be freely chosen with possible unknown constants which can be determined by imposing the boundary and initial conditions. Comparison of the results with those of exact solution has led us to significant consequences. The results reveal that the HPM is very effective, convenient and quite accurate to systems of nonlinear equations. It is predicted that the HPM can be found widely applicable in engineering.

Keywords: homotopy perturbation method, Whitham–Broer–Kaup (WBK) equation, Modified Boussinesq, Approximate Long Wave

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20238 Automatic Detection and Update of Region of Interest in Vehicular Traffic Surveillance Videos

Authors: Naydelis Brito Suárez, Deni Librado Torres Román, Fernando Hermosillo Reynoso

Abstract:

Automatic detection and generation of a dynamic ROI (Region of Interest) in vehicle traffic surveillance videos based on a static camera in Intelligent Transportation Systems is challenging for computer vision-based systems. The dynamic ROI, being a changing ROI, should capture any other moving object located outside of a static ROI. In this work, the video is represented by a Tensor model composed of a Background and a Foreground Tensor, which contains all moving vehicles or objects. The values of each pixel over a time interval are represented by time series, and some pixel rows were selected. This paper proposes a pixel entropy-based algorithm for automatic detection and generation of a dynamic ROI in traffic videos under the assumption of two types of theoretical pixel entropy behaviors: (1) a pixel located at the road shows a high entropy value due to disturbances in this zone by vehicle traffic, (2) a pixel located outside the road shows a relatively low entropy value. To study the statistical behavior of the selected pixels, detecting the entropy changes and consequently moving objects, Shannon, Tsallis, and Approximate entropies were employed. Although Tsallis entropy achieved very high results in real-time, Approximate entropy showed results slightly better but in greater time.

Keywords: convex hull, dynamic ROI detection, pixel entropy, time series, moving objects

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20237 Reduced Differential Transform Methods for Solving the Fractional Diffusion Equations

Authors: Yildiray Keskin, Omer Acan, Murat Akkus

Abstract:

In this paper, the solution of fractional diffusion equations is presented by means of the reduced differential transform method. Fractional partial differential equations have special importance in engineering and sciences. Application of reduced differential transform method to this problem shows the rapid convergence of the sequence constructed by this method to the exact solution. The numerical results show that the approach is easy to implement and accurate when applied to fractional diffusion equations. The method introduces a promising tool for solving many fractional partial differential equations.

Keywords: fractional diffusion equations, Caputo fractional derivative, reduced differential transform method, partial

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20236 The Construction of Exact Solutions for the Nonlinear Lattice Equation via Coth and Csch Functions Method

Authors: A. Zerarka, W. Djoudi

Abstract:

The method developed in this work uses a generalised coth and csch funtions method to construct new exact travelling solutions to the nonlinear lattice equation. The technique of the homogeneous balance method is used to handle the appropriated solutions.

Keywords: coth functions, csch functions, nonlinear partial differential equation, travelling wave solutions

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20235 Parental Diet Effects on Offspring Body Size and Pathogen Resistance in Bactrocera tryoni

Authors: Hue Dinh, Binh Nguyen, Vivian Mendez, Phillip W. Taylor, Fleur Ponton

Abstract:

Better understanding of how parental diet affects offspring traits is an important ecological and evolutionary question. In this study, we explored how maternal diet influences offspring physiology and resistance to infection using Bactrocera tryoni (Q-fly) as a system model. Female Q-flies were fed one of six single diets varying in their yeast-to-sugar ratio yielding six protein-to-carbohydrate ratios. As controls, we used females that were given a choice between yeast and sugar. Males were reared on a choice diet and allowed to mate with females 14 days post-emergence. Results showed that while maternal diet does not influence offspring developmental time, it has a strong effect on larval body weight. Mother fed either high-protein or high-sugar diet produced larger progeny. By challenging offspring with the bacterium Serratia marcescens, we found that female offspring from mothers fed high-sugar diet survived better the infection compared to those from mothers fed low-sugar diet. In contrast, male offspring produced by mother fed high-protein diet showed better resistance to the infection compared to those produced by mother fed low-protein diet. These results suggested sex-dependent transgenerational effects of maternal nutrition on offspring physiology and immunity.

Keywords: bacterial infection, Bactrocera tryoni, maternal diet, offspring, Serretia marcescens

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20234 Antenatal Monitoring of Pre-Eclampsia in a Low Resource Setting

Authors: Alina Rahim, Joanne Moffatt, Jessica Taylor, Joseph Hartland, Tamer Abdelrazik

Abstract:

Background: In 2011, 15% of maternal deaths in Uganda were due to hypertensive disorders (pre-eclampsia and eclampsia). The majority of these deaths are avoidable with optimum antenatal care. The aim of the study was to evaluate how antenatal monitoring of pre-eclampsia was carried out in a low resource setting and to identify barriers to best practice as recommended by the World Health Organisation (WHO) as part of a 4th year medical student External Student Selected component field trip. Method: Women admitted to hospital with pre-eclampsia in rural Uganda (Villa Maria and Kitovu Hospitals) over a year-long period were identified using the maternity register and antenatal record book. It was not possible to obtain notes for all cases identified on the maternity register. Therefore a total of thirty sets of notes were reviewed. The management was recorded and compared to Ugandan National Guidelines and WHO recommendations. Additional qualitative information on routine practice was established by interviewing staff members from the obstetric and midwifery teams. Results: From the records available, all patients in this sample were managed according to WHO recommendations during labour. The rate of Caesarean section as a mode of delivery was noted to be high in this group of patients; 56% at Villa Maria and 46% at Kitovu. Antenatally two WHO recommendations were not routinely met: aspirin prophylaxis and calcium supplementation. This was due to lack of resources, and lack of attendance at antenatal clinic leading to poor detection of high-risk patients. Medical management of pre-eclampsia varied between individual patients, overall 93.3% complied with Ugandan national guidelines. Two patients were treated with diuretics, which is against WHO guidance. Discussion: Antenatal monitoring of pre-eclampsia is important in reducing severe morbidity, long-term disability and mortality amongst mothers and their babies 2 . Poor attendance at antenatal clinic is a barrier to healthcare in low-income countries. Increasing awareness of the importance of these visits for women should be encouraged. The majority of cases reviewed in this sample of women were treated according to Ugandan National Guidelines. It is recommended to commence the use of aspirin prophylaxis for women at high-risk of developing pre-eclampsia and the creation of detailed guidelines for Uganda which would allow for standardisation of care county-wide.

Keywords: antenatal monitoring, low resource setting, pre-eclampsia, Uganda

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