Search results for: time series data

Authors: Prashant S. Humnabad

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The objective of this work is to carry out a thermal heat transfer analysis to obtain the time dependent temperature field in welding process friction stir welded dissimilar materials with different preheating temperature. A series of joints were made on four mm thick aluminum and steel plates. The temperature used was 100ºC, 150ºC and 200ºC. The welding operation was performed with different rotational speeds and traverse speed (1000, 1400 and 2000 rmp and 16, 20 and 25 mm/min..). In numerical model, the welded plate was modeled as the weld line is the symmetric line. The work-piece has dimensions of 100x100x4 mm. The obtained result was compared with experimental result, which shows good agreement and within the acceptable limit. The peak temperature at the weld zone increases significantly with respect to increase in process time.

Keywords: FEA, thermal analysis, preheating, friction stir welding

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Authors: Erzen Muharemi, Emmanuel De Jaeger, Jos Knockaert

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The work presented here investigates the modeling of power electronics converters in terms of their harmonic production. Specifically, it addresses high-frequency emissions in the range of 2-150 kHz, referred to as supraharmonics. This paper models a conventional converter, namely the boost converter used as an active power factor corrector (APFC). Furthermore, the modeling is extended to the case of the interleaved boost converter, which offers advantages such as halving the emissions. Finally, a comparison between the theoretical, numerical, and experimental results will be provided.

Keywords: APFC, boost converter, converter modeling, double fourier series, supraharmonics

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Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood

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The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.

Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health

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Authors: Nader Parsazadeh

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The variety of bed sediment load relationships, insufficient information and data, and the influence of river conditions make the selection of an optimum relationship for a given river extremely difficult. Hence, in order to select the best formulae, the bed load equations should be evaluated. The affecting factors need to be scrutinized, and equations should be verified. Also, re-evaluation may be needed. In this research, sediment bed load of Dez Dam at Tal-e Zang Station has been studied. After reviewing the available references, the most common formulae were selected that included Meir-Peter and Muller, using MS Excel to compute and evaluate data. Then, 52 series of already measured data at the station were re-measured, and the sediment bed load was determined. 1. The calculated bed load obtained by different equations showed a great difference with that of measured data. 2. r difference ratio from 0.5 to 2.00 was 0% for all equations except for Nilsson and Shields equations while it was 61.5 and 59.6% for Nilsson and Shields equations, respectively. 3. By reviewing results and discarding probably erroneous measured data measurements (by human or machine), one may use Nilsson Equation due to its r value higher than 1 as an effective equation for estimating bed load at Tal-e Zang Station in order to predict activities that depend upon bed sediment load estimate to be determined. Also, since only few studies have been conducted so far, these results may be of assistance to the operators and consulting companies.

Keywords: bed load, empirical relation ship, sediment, Tale Zang Station

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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Authors: Godwin Chigozie Okpara

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This paper using standard GARCH, EGARCH, and TARCH models on day of the week return series (of 246 days) from the Nigerian Stock market estimated the model variants’ VaR. An asymmetric return distribution and fat-tail phenomenon in financial time series were considered by estimating the models with normal, student t and generalized error distributions. The analysis based on Akaike Information Criterion suggests that the EGARCH model with student t innovation distribution can furnish more accurate estimate of VaR. In the light of this, we apply the likelihood ratio tests of proportional failure rates to VaR derived from EGARCH model in order to determine the short and long positions VaR performances. The result shows that as alpha ranges from 0.05 to 0.005 for short positions, the failure rate significantly exceeds the prescribed quintiles while it however shows no significant difference between the failure rate and the prescribed quantiles for long positions. This suggests that investors and portfolio managers in the Nigeria stock market have long trading position or can buy assets with concern on when the asset prices will fall. Precisely, the VaR estimates for the long position range from -4.7% for 95 percent confidence level to -10.3% for 99.5 percent confidence level.

Keywords: downside risk, value-at-risk, failure rate, kupiec LR tests, GARCH models

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Authors: S. Pirrello

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Sydney’s booming real estate market has pushed property developers to invest in historically “no-go” areas, which were previously too expensive to develop. These areas are usually near rivers where the sites are underlain by deep alluvial and estuarine sediments. In these ground conditions, conventional bored pile techniques are often not competitive. Contiguous Flight Auger (CFA) and Drilled Displacement (DD) Piles techniques are on the other hand suitable for these ground conditions. This paper deals with the design and construction challenges encountered with these piling techniques for a series of high-rise towers in Sydney’s West. The advantages of DD over CFA piles such as reduced overall spoil with substantial cost savings and achievable rock sockets in medium strength bedrock are discussed. Design performances were assessed with PIGLET. Pile performances are validated in two stages, during constructions with the interpretation of real-time data from the piling rigs’ on-board computer data, and after construction with analyses of results from high strain pile dynamic testing (PDA). Results are then presented and discussed. High Strain testing data are presented as Case Pile Wave Analysis Program (CAPWAP) analyses.

Keywords: contiguous flight auger (CFA) , DEFPIG, case pile wave analysis program (CAPWAP), drilled displacement piles (DD), pile dynamic testing (PDA), PIGLET, PLAXIS, repute, pile performance

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Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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Authors: Manana Chumburidze

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We have considered a non-classical model of dynamical problems for a conjugated system of differential equations arising in thermo-piezoelectricity, which was formulated by Toupin – Mindlin. The basic concepts and the general theory of solvability for isotropic homogeneous elastic media is considered. They are worked by using the methods the Laplace integral transform, potential method and singular integral equations. Approximate solutions of mixed boundary value problems for finite domain, bounded by the some closed surface are constructed. They are solved in explicitly by using the generalized Fourier's series method.

Keywords: thermo-piezoelectricity, boundary value problems, Fourier's series, isotropic homogeneous elastic media

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Authors: Mahmoud Reza Hosseini

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The universe is in a continuous expansion process, resulting in the reduction of its density and temperature. Also, by extrapolating back from its current state, the universe at its early times is studied, known as the big bang theory. According to this theory, moments after creation, the universe was an extremely hot and dense environment. However, its rapid expansion due to nuclear fusion led to a reduction in its temperature and density. This is evidenced through the cosmic microwave background and the universe structure at a large scale. However, extrapolating back further from this early state reaches singularity, which cannot be explained by modern physics, and the big bang theory is no longer valid. In addition, one can expect a nonuniform energy distribution across the universe from a sudden expansion. However, highly accurate measurements reveal an equal temperature mapping across the universe, which is contradictory to the big bang principles. To resolve this issue, it is believed that cosmic inflation occurred at the very early stages of the birth of the universe. According to the cosmic inflation theory, the elements which formed the universe underwent a phase of exponential growth due to the existence of a large cosmological constant. The inflation phase allows the uniform distribution of energy so that an equal maximum temperature can be achieved across the early universe. Also, the evidence of quantum fluctuations of this stage provides a means for studying the types of imperfections the universe would begin with. Although well-established theories such as cosmic inflation and the big bang together provide a comprehensive picture of the early universe and how it evolved into its current state, they are unable to address the singularity paradox at the time of universe creation. Therefore, a practical model capable of describing how the universe was initiated is needed. This research series aims at addressing the singularity issue by introducing a state of energy called a "neutral state," possessing an energy level that is referred to as the "base energy." The governing principles of base energy are discussed in detail in our second paper in the series "A Conceptual Study for Addressing the Singularity of the Emerging Universe," which is discussed in detail. To establish a complete picture, the origin of the base energy should be identified and studied. In this research paper, the mechanism which led to the emergence of this natural state and its corresponding base energy is proposed. In addition, the effect of the base energy in the space-time fabric is discussed. Finally, the possible role of the base energy in quantization and energy exchange is investigated. Therefore, the proposed concept in this research series provides a road map for enhancing our understating of the universe's creation from nothing and its evolution and discusses the possibility of base energy as one of the main building blocks of this universe.

Keywords: big bang, cosmic inflation, birth of universe, energy creation, universe evolution

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Authors: Chernet Mulugeta, Girma Seyoum, Yeshineh Demrew, Kehabtimer Shiferaw

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Background: Obstetric fistula (OF) is a serious medical condition that includes an abnormal opening between the vagina and bladder (vesico-vaginal fistula) or the vagina and rectum (recto-vaginal fistula). It is usually caused by prolonged obstructed labour. Despite its serious health and psychosocial consequences, there is a paucity of evidence regarding the time it takes to heal from OF. Objective: The aim of this study was to assess the time to cure from obstetric fistula and its predictors among women admitted to Addis Ababa Hamlin Fistula Hospital, Addis Ababa, Ethiopia. Methodology: An institution-based retrospective cohort study was conducted from January 2015 to December 2020 among a randomly selected 434 women with OF in Addis Ababa Hamlin Fistula Hospital. Data was collected using a structured checklist adapted from a similar study. The open data kit (ODK) collected data was exported and analyzed by using STATA (14.2). Kaplan Meir was used to compare the recovery time from OF. To identify the predictors of OF, a Cox regression model was fitted, and an adjusted hazard ratio with a 95% confidence interval was used to estimate the strength of the associations. Results: The average time to recover from obstetric fistula was 3.95 (95% CI: 3.0-4.6) weeks. About ¾ of the women [72.8% (95% CI - 0.65-1.2)] were physically cured of obstetric fistula. Having secondary education and above [AHR=3.52; 95% CI (1.98, 6.25)] compared to no formal education, having a live birth [AHR=1.64; 95% CI (1.22, 2.21)], having an intact bladder [AHR=2.47; 95% CI (1.1, 5.54)] compared to totally destructed, and having a grade 1 fistula [AHR=1.98; 95% CI (1.19, 3.31)] compared to grade 3 were the significant predictors of shorter time to cure from an obstetric fistula. Conclusion and recommendation: Overall, the proportion of women with OF who were not being cured was unacceptably high. The time it takes for them to recover from the fistula was also extended. It connotes us to work on the identified predictors to improve the time to recovery from OF.

Keywords: time to recovery, obstetric fistula, predictors, Ethiopia

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Authors: Michael Granado

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The French philosopher Gaston Bachelard’s philosophy of time is articulated in his two works on the subject, the Intuition of the Instant (1932) and his The Dialectic of Duration (1936). Both works present a systematic methodology predicated upon the assumption that our understanding of time has radically changed as a result of Einstein and subsequently needs to be reimagined. Bachelard makes a major distinction in his discussion of time: 1. Time as it is (physical time), 2. Time as we experience it (phenomenological time). This paper will focus on the second distinction, phenomenological time, and explore the connections between Bachelard’s work and contemporary psychology. Several aspects of Bachelard’s philosophy of time nicely complement our current understanding of memory and self and clarify how the self relates to experienced time. Two points, in particular, stand out; the first is the relative nature of subjective time, and the second is the implications of subjective time in the formation of the narrative self. Bachelard introduces two philosophical concepts to explain these points: rhythmanalysis and reverie. By exploring these concepts, it will become apparent that there is an undeniable link between memory, self, and time. Through the use of narrative self, the individual connects and links memories and time together to form a sense of personal identity.

Keywords: Gaston Bachelard, memory, self, time

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Authors: James Adewale, Joshua Sunday

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In this paper, we developed a linear multistep method, which is implemented in predictor corrector-method. The corrector is developed by method of collocation and interpretation of power series approximate solutions at some selected grid points, to give a continuous linear multistep method, which is evaluated at some selected grid points to give a discrete linear multistep method. The predictors were also developed by method of collocation and interpolation of power series approximate solution, to give a continuous linear multistep method. The continuous linear multistep method is then solved for the independent solution to give a continuous block formula, which is evaluated at some selected grid point to give discrete block method. Basic properties of the corrector were investigated and found to be zero stable, consistent and convergent. The efficiency of the method was tested on some linear, non-learn, oscillatory and stiff problems of first order, initial value problems of ordinary differential equations. The results were found to be better in terms of computer time and error bound when compared with the existing methods.

Keywords: predictor, corrector, collocation, interpolation, approximate solution, independent solution, zero stable, consistent, convergent

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Authors: Abdullah Arafat, Ali Al-Farhan, Amir Omair

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Objectives: To review and assess the effectiveness of the implemented modified five-levels triage and acuity scale triage system in AL-Yarmook Urgent Care Center (UCC), King Abdulaziz Residential city, Riyadh, Saudi Arabia. Method: The applied study design was an observational cross sectional design. A data collection sheet was designed and distributed to triage nurses; the data collection was done during triage process and was directly observed by the co-investigator. Triage system was reviewed by measuring three time intervals as quality indicators: time before triage (TBT), time before being seen by physician (TBP) and total length of stay (TLS) taking in consideration timing of presentation and level of triage. Results: During the study period, a total of 187 patients were included in our study. 118 visits were at weekdays and 68 visits at weekends. Overall, 173 patients (92.5%) were seen by the physician in timely manner according to triage guidelines while 14 patients (7.5%) were not seen at appropriate time.Overall, The mean time before seen the triage nurse (TBT) was 5.36 minutes, the mean time to be seen by physician (TBP) was 22.6 minutes and the mean length of stay (TLS) was 59 minutes. The data didn’t showed significant increase in TBT, TBP, and number of patients not seen at the proper time, referral rate and admission rate during weekend. Conclusion: The CTAS is adaptable to countries beyond Canada and worked properly. The applied CTAS triage system in Al-Yarmook UCC is considered to be effective and well applied. Overall, urgent cases have been seen by physician in timely manner according to triage system and there was no delay in the management of urgent cases.

Keywords: CTAS, emergency, Saudi Arabia, triage, urgent care

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Authors: Salwa Abdelbaki

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This research investigated how leaders develop, asking whether they have been leaders due to their innate abilities or they gain leadership characteristics through interactions based on requirements of a situation. If the first is true, then a leader should be successful in any situation. Otherwise, a leader may succeed only in a specific situation. A series of experiments were carried out on three groups including of males and females. First; a group of 148 students with different specializations had to select a leader. Another group of 51 students had to recall their previous experiences and their knowledge of each other to identify who were leaders in different situations. Then a series of analytic tools were applied to the identified leaders and to the whole groups to find out how leaders were developed. A group of 40 young children was also experimented with to find young leaders among them and to analyze their characteristics.

Keywords: leadership, innate characteristics, situation, leadership theories

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: Farrukh Javed, Krzysztof Podgórski

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We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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Authors: Ian Walmsley

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The aim of this paper is to explore the influence of time and temporality on the experience of coming off heroin in prison. The presentation draws on qualitative data collected during a small-scale pilot study of the role of self-care in the process of coming off drugs in prison. Time and temporality emerged as a key theme in the interview transcripts. Drug dependent prisoners experience of time in prison has not been recognized in the research literature. Instead, the literature on prison time typically views prisoners as a homogenous group or tends to focus on the influence of aging and gender on prison time. Furthermore, there is a tendency in the literature on prison drug treatment and recovery to conceptualize drug dependent prisoners as passive recipients of prison healthcare, rather than active agents. In building on these gaps, this paper argues that drug dependent prisoners experience multiple temporalities which involve an interaction between the body-times of the drug dependent prisoner and the economy of time in prison. One consequence of this interaction is the feeling that they are doing, at this point in their prison sentence, double prison time. The second part of the argument is that time and temporality were a means through which they governed their withdrawing bodies. In addition, this paper will comment on the challenges of prison research in England.

Keywords: heroin withdrawal, time and temporality, prison, body

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Authors: Ricardo Daziano

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In the analysis and planning of the mobility ecosystem, preferences for ride-hailing over incumbent street-hailing services need better understanding. In this paper, a seminonparametric discrete choice model that allows for flexible preference heterogeneity is fitted with data from a discrete choice experiment among adult commuters in Montreal, Canada (N=760). Participants chose among Uber, Teo (a local electric ride-hailing service that was in operation when data was collected in 2018), and a standard taxi when presented with information about cost, time (on-trip, waiting, walking), powertrain of the car (gasoline/hybrid) for Uber and taxi, and whether the available electric Teo was a Tesla (which was one of the actual features of the Teo fleet). The fitted flexible model offers several behavioral insights. Waiting time for ride-hailing services is associated with a statistically significant but low marginal disutility. For other time components, including on-ride, and street-hailing waiting and walking the estimates of the value of time show an interesting pattern: whereas in a conditional logit on-ride time reductions are valued higher, in the flexible LML specification means of the value of time follow the expected pattern of waiting and walking creating a higher disutility. At the same time, the LML estimates show the presence of important, multimodal unobserved preference heterogeneity.

Keywords: discrete choice, electric taxis, ridehailing, semiparametrics

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Authors: Elias K. Maragos, Petros E. Maravelakis

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In Dynamic Data Envelopment Analysis (DDEA), which is a subfield of Data Envelopment Analysis (DEA), the productivity of Decision Making Units (DMUs) is considered in relation to time. In this case, as it is accepted by the most of the researchers, there are outputs, which are produced by a DMU to be used as inputs in a future time. Those outputs are known as intermediates. The common models, in DDEA, do not take into account the shape of the distribution of those inputs, outputs or intermediates data, assuming that the distribution of the virtual value of them does not deviate from linearity. This weakness causes the limitation of the accuracy of the analytical power of the traditional DDEA models. In this paper, the authors, using the concept of piecewise linear inputs and outputs, propose an extended DDEA model. The proposed model increases the flexibility of the traditional DDEA models and improves the measurement of the dynamic performance of DMUs.

Keywords: Dynamic Data Envelopment Analysis, DDEA, piecewise linear inputs, piecewise linear outputs

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Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

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The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

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Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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Authors: Hiroki Takiguchi, Masahiro Furuya, Takahiro Arai

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In order to quantitatively comprehend thermal flow for some industrial applications such as nuclear and chemical reactors, detailed measurements for temperature and abundance (concentration) of materials at high temporal and spatial resolution are required. Additionally, rigorous evaluation of the size effect is also important for practical realization. This paper introduces a real-time spectroscopic imaging method in micro scale field, which visualizes temperature and concentration distribution of a liquid or mix liquids with near-infrared (NIR) wavelength region. This imaging principle is based on absorption of pre-selected narrow band from absorption spectrum peak or its dependence property of target liquid in NIR region. For example, water has a positive temperature sensitivity in the wavelength at 1905 nm, therefore the temperature of water can be measured using the wavelength band. In the experiment, the real-time imaging observation of concentration distribution in micro channel was demonstrated to investigate the applicability of micro-scale diffusion coefficient and temperature measurement technique using this proposed method. The effect of thermal diffusion and binary mutual diffusion was evaluated with the time-series visualizations of concentration distribution.

Keywords: near-infrared spectroscopic imaging, micro fluid channel, concentration distribution, diffusion phenomenon

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Authors: Yiyuan Tao

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Under the impact of global warming together with the intensification of human activities, the hydrological regimes may be altered, and the traditional stationary assumption was no longer satisfied. However, most of the current design standards of water infrastructures were still based on the hypothesis of stationarity, which may inevitably result in severe biases. Many critical impacts of climate on ecosystems, society, and the economy are controlled by extreme events rather than mean values. Therefore, it is of great significance to identify the non-stationarity of precipitation extremes and model the precipitation extremes in a nonstationary framework. The Wei River Basin (WRB), located in a continental monsoon climate zone in China, is selected as a case study in this study. Six extreme precipitation indices were employed to investigate the changing patterns and stationarity of precipitation extremes in the WRB. To identify if precipitation extremes are stationary, the Mann-Kendall trend test and the Pettitt test, which is used to examine the occurrence of abrupt changes are adopted in this study. Extreme precipitation indices series are fitted with non-stationary distributions that selected from six widely used distribution functions: Gumbel, lognormal, Weibull, gamma, generalized gamma and exponential distributions by means of the time-varying moments model generalized additive models for location, scale and shape (GAMLSS), where the distribution parameters are defined as a function of time. The results indicate that: (1) the trends were not significant for the whole WRB, but significant positive/negative trends were still observed in some stations, abrupt changes for consecutive wet days (CWD) mainly occurred in 1985, and the assumption of stationarity is invalid for some stations; (2) for these nonstationary extreme precipitation indices series with significant positive/negative trends, the GAMLSS models are able to capture well the temporal variations of the indices, and perform better than the stationary model. Finally, the differences between the quantiles of nonstationary and stationary models are analyzed, which highlight the importance of nonstationary modeling of precipitation extremes in the WRB.

Keywords: extreme precipitation, GAMLSSS, non-stationary, Wei River Basin

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Authors: Inkyu Kim, SangMan Moon

Abstract:

This IEEE 802.11b protocol provides up to 11Mbps data rate, whereas aerospace industry wants to seek higher data rate COTS data link system in the UAV. The Total Maximum Throughput (TMT) and delay time are studied on many researchers in the past years This paper provides theoretical data throughput performance of UAV formation flight data link using the existing 802.11b performance theory. We operate the UAV formation flight with more than 30 quad copters with 802.11b protocol. We may be predicting that UAV formation flight numbers have to bound data link protocol performance limitations.

Keywords: UAV datalink, UAV formation flight datalink, UAV WLAN datalink application, UAV IEEE 802.11b datalink application

Procedia PDF Downloads 391

Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

Abstract:

Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

Procedia PDF Downloads 431

Authors: Gayani K. Nandasiri, Tilak Dias, William Hurley

Abstract:

Venous disease of human lower limb could range from minor asymptomatic incompetence of venous valves to chronic venous ulceration. The sheer prevalence of varicose veins and its associated significant costs of treating late complications such as chronic ulcers contribute to a higher burden on health care resources. In most of western countries with developed health care systems, treatment costs associated with Venous disease accounts for a considerable portion of their total health care budget, and it has become a high-cost burden to National Health Service (NHS), UK. The established gold standard of treatment for the venous disease is the graduated compression, where the pressure at the ankle being highest and decreasing towards the knee and thigh. Currently, medical practitioners use two main methods to treat venous disease; i.e. compression bandaging and compression stockings. Both these systems have their own disadvantages which lead to the current programme of research. The aim of the present study is to revolutionize the compression therapy by using a novel active compression system to deliver a controllable and more accurate pressure profiles using a series of inflatable mini bladders. Two types of commercially available silicones were tested for the application. The mini bladders were designed with a special fabrication procedure to provide required pressure profiles, and a series of experiments were conducted to characterise the mini bladders. The inflation/deflation heights of these mini bladders were investigated experimentally and using a finite element model (FEM), and the experimental data were compared to the results obtained from FEM simulations, which showed 70-80% agreement. Finally, the mini bladders were tested for its pressure transmittance characteristics, and the results showed a 70-80% of inlet air pressure transmitted onto the treated surface.

Keywords: finite element analysis, graduated compression, inflatable bladders, venous disease

Procedia PDF Downloads 183

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

Abstract:

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

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

Procedia PDF Downloads 388

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

Procedia PDF Downloads 523