Search results for: maximum likelihood

Authors: Sonal Budhiraja, Biswabrata Pradhan

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This work considers statistical inference based on progressive Type-I interval censored data with random removal. The scheme of progressive Type-I interval censoring with random removal can be described as follows. Suppose n identical items are placed on a test at time T0 = 0 under k pre-fixed inspection times at pre-specified times T1 < T2 < . . . < Tk, where Tk is the scheduled termination time of the experiment. At inspection time Ti, Ri of the remaining surviving units Si, are randomly removed from the experiment. The removal follows a binomial distribution with parameters Si and pi for i = 1, . . . , k, with pk = 1. In this censoring scheme, the number of failures in different inspection intervals and the number of randomly removed items at pre-specified inspection times are observed. Asymptotic properties of the maximum likelihood estimators (MLEs) are established under some regularity conditions. A β-content γ-level tolerance interval (TI) is determined for two parameters Weibull lifetime model using the asymptotic properties of MLEs. The minimum sample size required to achieve the desired β-content γ-level TI is determined. The performance of the MLEs and TI is studied via simulation.

Keywords: asymptotic normality, consistency, regularity conditions, simulation study, tolerance interval

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Authors: Z. Adnan, M. M. Habib

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The laboratory tests for measuring the effects of small strain to the shear strength and maximum stiffness development of post-cyclic degradation of hemic peat are reviewed in this paper. A series of laboratory testing has been conducted to fulfil the objective of this research to study the post-cyclic behaviour of peat soil and focuses on the small strain characteristics. For this purpose, a number of strain-controlled static, cyclic and post-cyclic triaxial tests were carried out in undrained condition on hemic peat soil. The shear strength and maximum stiffness of hemic peat are evaluated immediately after post-cyclic monotonic testing. There are two soil samples taken from West Johor and East Malaysia peat soil. Based on these laboratories and field testing data, it was found that the shear strength and maximum stiffness of peat soil decreased in post-cyclic monotonic loading than its initial shear strength and stiffness. In particular, degradation in shear strength and stiffness is more sensitive for peat soil due to fragile and uniform fibre structures. Shear strength of peat soil, τ_max = 12.53 kPa (Beaufort peat, BFpt) and 36.61 kPa (Parit Nipah peat, PNpt) decreased than its initial 58.46 kPa and 91.67 kPa. The maximum stiffness, G_max = 0.23 and 0.25 decreased markedly with post-cyclic, G_max = 0.04 and 0.09. Simple correlations between the G_max and the τ_max effects due to small strain, ε = 0.1, the G_max values for post-cyclic are relatively low compared to its initial G_max. As a consequence, the reported values and patterns of both the West Johor and East Malaysia peat soil are generally the same.

Keywords: post-cyclic, strain, maximum stiffness, shear strength

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Kamaljit Singh Sokhal, Gangacharyulu Dasoraju, Vijaya Kumar Bulasara

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Biopolymers are popular in many areas, like petrochemicals, food industry and agriculture due to their favorable properties like environment-friendly, availability, and cost. In this study, a biopolymer gum Arabic was used to find its effect on the pressure drop at various concentrations (100 ppm – 300 ppm) with various Reynolds numbers (10000 – 45000). A rheological study was also done by using the same concentrations to find the effect of the shear rate on the shear viscosity. Experiments were performed to find the effect of injection of gum Arabic directly near the boundary layer and to investigate its effect on the maximum possible drag reduction. Experiments were performed on a test section having i.d of 19.50 mm and length of 3045 mm. The polymer solution was injected from the top of the test section by using a peristaltic pump. The concentration of the polymer solution and the Reynolds number were used as parameters to get maximum possible drag reduction. Water was circulated through a centrifugal pump having a maximum 3000 rpm and the flow rate was measured by using rotameter. Results were validated by using Virk's maximum drag reduction asymptote. A maximum drag reduction of 62.15% was observed with the maximum concentration of gum Arabic, 300 ppm. The solution was circulated in the closed loop to find the effect of degradation of polymers with a number of cycles on the drag reduction percentage. It was observed that the injection of the polymer solution in the boundary layer was showing better results than premixed solutions.

Keywords: drag reduction, shear viscosity, gum arabic, injection point

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Authors: Enemeri George Uweiyohowo

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Improved achievement with respect to output control of photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident to its low carbon emission and efficiency. Power failure or outage from commercial providers, in general, does not promote development to public and private sector, these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost-effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with MPPT from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0∘N, with a corresponding tilt angle of 36∘, 26∘ and 16∘. Preliminary results include regression analysis (normal probability plot) showing the maximum power point in the system as well the best tilt angle for maximum power point tracking.

Keywords: poly-crystalline PV panels, information technology (IT), maximum power point tracking (MPPT), pulse width modulation (PWM)

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Authors: Piyangkun Kukutapan, Siridech Boonsang

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The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

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Authors: A. Bayaga

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This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

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Authors: Pallavi Moudgil, J. S. Bedi, R. S. Aulakh, J. P. S. Gill

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Mycotoxins in milk are of major public health concern. The present study was envisaged with an aim to monitor the occurrence of aflatoxin M1 and ochratoxin A in raw milk samples collected from individual animals from dairy farms located in Punjab (India). A total of 168 raw milk samples were collected and analysed using competitive ELISA kits. Out of these, 9 (5.4%) samples were found positive for aflatoxin M1 with the mean concentration of 0.006-0.13 ng/ml and 2 (1.2%) samples exceeded the established maximum residue limit of 0.05 ng/ml established by the European Union. For ochratoxin A, 2 (0.1%) samples were found positive with the mean concentration of 0.61-0.83 ng/ml with both the samples below the established maximum residue limit of 2 ng/ml. The results showed that the milk of dairy cattle is safe with respect to ochratoxin A contamination but occurrence of aflatoxin M1 above maximum residue limit suggested that feed contaminated with mycotoxins might have been offered to dairy cattle that can pose serious health risks to consumers.

Keywords: Aflatoxin M1, health risks, maximum residue limit, milk, Ochratoxin A

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Authors: Ghada Shahrour, Nusiebeh Ananbh, Heyam Dalky, Mohammad Rababa, Fatmeh Alzoubi

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Positive teacher-student relationship has been found to affect students’ attitudes towards bullying and, in turn, their engagement in bullying behavior. However, no investigation has been conducted to explore whether teacher-student relationship affects teachers’ attitudes towards bullying. The aim of this study was to examine the role of teacher-student relationship on teachers’ attitudes towards bullying in terms of bullying seriousness, empathic responding, and likelihood to intervene in bullying situation. A cross-sectional, descriptive design was employed among a convenience sample of 173 school teachers (50.9% female) of 12 to 17-year-old students. The teachers were recruited from secondary public schools of three governorates in the Northern district of Jordan. Each group of students has multiple teachers for different subjects. Results showed that teacher-student relationship is partially related to teachers’ attitudes towards bullying. More specifically, having a close teacher-student relationship significantly increased teachers’ perception of bullying seriousness and empathy but not the likelihood to intervene. Research is needed to examine teachers’ obstacles for not providing bullying interventions, as the barriers may be culturally contextualized. Meanwhile, interventions that promote quality teacher-student relationship are necessary to increase teachers’ perception of bullying seriousness and empathy. Students have been found to adopt the values of their teachers, and this may deter them from engaging in bullying behavior.

Keywords: school bullying, teachers’ attitudes, teacher-student relationship, adolescent students

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Authors: Edén Bojórquez, Victor Baca, Alfredo Reyes-Salazar, Jorge González

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In this paper, simplified equations to predict maximum inter-story drift demands of steel framed buildings are proposed in terms of two ground motion intensity measures based on the acceleration spectral shape. For this aim, the maximum inter-story drifts of steel frames with 4, 6, 8 and 10 stories subjected to narrow-band ground motion records are estimated and compared with the spectral acceleration at first mode of vibration Sa(T1) which is commonly used in earthquake engineering and seismology, and with a new parameter related with the structural response known as INp. It is observed that INp is the parameter best related with the structural response of steel frames under narrow-band motions. Finally, equations to compute maximum inter-story drift demands of steel frames as a function of spectral acceleration and INp are proposed.

Keywords: intensity measures, spectral shape, steel frames, peak demands

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Authors: Hailemariam Gebremichael Gebretsadik, Abrham Hagos Tesfaslasea

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To satisfy the high need for ICT entrepreneurship and rectify the weak entrepreneurial culture in Ethiopia, the country has established ICT Business incubation centers with the intention of preventing business failures, promoting innovation, and accelerating the growth and success of firms. This study investigates the role of business incubators and social capital on the innovation and growth of firms in Ethiopia. In this research, innovation and growth of firms were considered as dependent variables, whereas business incubation and social capital were treated as independent variables. The researcher employed an e-mail survey among 137 tenant Firms (Firms that joined and/or graduated to/from the Business incubation centers available in Ethiopia) to collect the data and obtained 113 responses that were appropriate for this research. The result of this study reveals that the dimensions of business incubation (physical resource, business support, and networking) have a significant effect on the innovation of Firms, but these dimensions of business incubation do not show a significant effect on the growth of firms. On the other hand, the dimensions of social capital (structural, cognitive, and relational) show a significant positive impact on the likelihood of Firms' growth but not on the innovation of firms. Moreover, the result of this study indicates that the dimensions of business incubation and social capital together have a significant effect on the likelihood of tenant firms innovating and growing.

Keywords: business incubation, innovation, social capital, tenant firms

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Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.

Keywords: association rules, FP-growth, multiple minimum supports, Weka tool

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

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Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: interconnection network, augmented cube, induced subgraph, bisection width

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

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Authors: Augustine Okolie, Johannes Müller, Mirjam Kretzchmar

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We adopt a maximum-likelihood framework to estimate parameters of a stochastic susceptible-infected-recovered (SIR) model with contact tracing on a rooted random tree. Given the number of detectees per index case, our estimator allows to determine the degree distribution of the random tree as well as the tracing probability. Since we do not discover all infectees via contact tracing, this estimation is non-trivial. To keep things simple and stable, we develop an approximation suited for realistic situations (contract tracing probability small, or the probability for the detection of index cases small). In this approximation, the only epidemiological parameter entering the estimator is the basic reproduction number R0. The estimator is tested in a simulation study and applied to covid-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical covid-19 data, we are able to compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution meet the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency on the reproduction number.

Keywords: stochastic SIR model on graph, contact tracing, branching process, parameter inference

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Authors: Ariful Islam, Showkat Ahmad Lone

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Statistical distributions have long been employed in the assessment of semiconductor devices and product reliability. The power function-distribution is one of the most important distributions in the modern reliability practice and can be frequently preferred over mathematically more complex distributions, such as the Weibull and the lognormal, because of its simplicity. Moreover, it may exhibit a better fit for failure data and provide more appropriate information about reliability and hazard rates in some circumstances. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests for competing risk based on adoptive type-I progressive hybrid censoring criteria. The life data of the units under test is assumed to follow Mukherjee-Islam distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameters and tampering coefficient. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: adoptive progressive hybrid censoring, competing risk, mukherjee-islam distribution, partially accelerated life testing, simulation study

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Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda

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The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, the maximum gross weight of the train, the maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of the train consisting of a new type of wagons.

Keywords: loading units, theoretical capacity model, train capacity, wagon for intermodal transport

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Authors: Keven A. Prusak, William F. Christensen, Zack Beddoes

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Background: For more than a decade, the Sport Motivation Scale (SMS) has been used to measure contextual motivation across a variety of sporting and physical education (PE) settings but not without criticism as to its tenability. Consequently, a new version of the sport motivation scale (SMS-II) was created to address certain weakness of the original SMS. Purpose: The purpose of this study is to assess the suitability of the SMS-II in the secondary PE setting. Methods: Three hundred and twenty (204 females, and 116 males; grades 7-9) completed the 18-item, six-subscale SMS-II at the end of a required PE class. Factor means, standard deviations, and correlations were calculated and further examined via confirmatory factor analysis (CFA). Model parameters were estimated maximum likelihood function. Results: Results indicate that participants held generally positive perceptions toward PE as a context (more so for males than females). Reliability analysis yielded adequate alphas (rα = 0.71 to 0.87, Mα = 0.78) with the exception of the AM subscale (αAM = .64). Correlation analysis indicated some support for the SIMPLEX pattern, but distal ends of the motivation continuum displayed no relationship. CFA yielded robust fit indices to the proposed structure of the SMS-II for PE. A small but significant variance across genders was noted and discussed. Conclusions: In all, the SMS-II suitably accesses PE context-specific motivational indices within Jr. High PE.

Keywords: motivation, self-determination theory, physical education, confirmatory factor analysis

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Authors: Sajjad Seifoori

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Impact behavior of striker on graphene sheet and carbon nanotube is investigated based on molecular dynamics (MD) simulations. A MD simulation is conducted to obtain the maximum dynamic deflections of a square and rectangular single-layered graphene sheets (SLGSs) with various values of side-length and striker parameter. Effect of (i) chirality, (ii) graphene side-length and nanotube length, (iii) striker mass on the maximum dynamic deflections of graphene and nanotube are investigated. The effect of different types of boundary condition on the maximum dynamic deflections is studied for zigzag and armchair SWCNTs with various aspect ratios (Length/Diameter).

Keywords: impact, molecular dynamic, graphene, spring mass

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Ali Akber Jaffri, Asad Naseem, Javeria Khan, Zubair Hamza, Ishtiaq

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The purpose of this study is to determine safety stock, maximum inventory level, reordering point, and reordering quantity by rearranging lot sizes for supplier and customer in MRO (maintenance repair operations) warehouse of Engro Polymers & Chemicals. To achieve the aim, physical analysis method and excel commands were carried out to elicit the customer and supplier data provided by the company. Initially, we rearranged the current lot sizes and MOUs (measure of units) in SAP software. Due to change in lot sizes, we have to determine the new quantities for safety stock, maximum inventory, reordering point and reordering quantity as per company's demand. By proposed system, we saved extra cost in terms of reducing time of receiving from vendor and in issuance to customer, ease of material handling in MRO warehouse and also reduce human efforts.

Keywords: maintenance repair operation, maximum inventory, reorder quantity, safety stock

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Authors: David Carvalho

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Future changes in the mean, maximum and minimum temperature in continental Portugal were investigated using high-resolution future climate projections based on the latest IPCC AR6 CMIP6 climate scenarios. The results show that the mean, maximum and minimum temperatures are projected to increase substantially in all of continental Portugal, particularly in the south-central inland regions. For the near-term future (2046-2065 period), SSP3-7.0 is the future climate scenario that projects higher increases of around 1 ºC, 1.5 ºC and 2 ºC for the daily mean, maximum and minimum temperatures, respectively. For the long-term future (2081-2100 period), the projected warming is higher, particularly under the SSP5-8.5 future climate scenario with projected warmings of 3 ºC, 3.5 ºC and 2.5 ºC for the daily mean, maximum and minimum temperatures, respectively. Occurrences of hot days (mean temperature above 30 ºC), very hot days (maximum temperature above 40 ºC) and tropical nights (minimum temperature above 20 ºC) are all projected to increase up to 35-40, 12-15 and 50 more days per year, respectively, mainly in the interior areas of Portugal. Oppositely, the occurrence of frost days is projected to decrease in practically all mountainous areas in Portugal. These results show a clear tendency of a significant increase in the surface temperatures and frequency of occurrence of extreme temperature episodes in continental Portugal, which can have severe impacts on the population, environment, economy and vital human activities such as agriculture.

Keywords: climate change, global warming, CMIP6, Portugal

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Authors: Qurrat Ul Ain Farooq, Misha Arshad, Malik Abid Mehmood

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The experiment under discussion was carried out to check the effect of different concentrations of sucrose (2%, 4%, 6%), CuSO4 (200ppm, 300ppm, 400 ppm), GA3 (25ppm, 50ppm, 75 ppm), and combinations of sucrose and GA3 (2% +25 ppm), (4%+50 ppm), (6%+75 ppm) on the carnation cut flower. Visual symptoms of flower senescence, changes in weight (g) of a flower was observed and recorded by using weight balance. The experiment was laid out according to CRD (Complete Randomized Design) it was two-factor factorial, the software used for the analysis was Statistix. Maximum TSS were found in 6% sucrose + 75 ppm GA3 (8.3 %) followed by CuSO4 400 ppm, 4% sucrose + 50 ppm GA3 and 6% sucrose + 75 ppm GA3. Maximum vase life in term of days was recorded in treatment. CuSO4 400 ppm and 6% sucrose + 75 ppm GA3 (8 days) followed by CuSO4 200 ppm (7.7 days). CuSO4 300 ppm & 6% sucrose + 75 ppm GA3 were at par (7 days). Maximum water uptake was also observed in 6% sucrose + 75 ppm GA3 (56.7 ml) followed by CuSO4 400 ppm (49.7 ml) and 50 ppm GA3 (45 ml). Hence, CuSO4 400 ppm found best in all aspects.

Keywords: carnation, vaselife, GA3, CuSO4, sucrose

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Authors: Zhiqiang Cheng, Qingliang He, Lu Li, Jie Ren

Abstract:

The safety of pipelines in the condition of frost heave or thaw settlement is necessarily evaluated. A full-scale experiment pipe with the typical structure configuration in station pipeline is constructed, the residual stress is tested with X-ray residual stress device, and the residual stress field of pipe is analyzed. The evolution of pipe strain with pressure in the scope of maximum allowable operation pressure (MAOP) is investigated by both strain gauge and X-ray methods. Load caused by frost heave or thaw settlement is simulated by two ways of lifting jack. The relation of maximum stress of pipe and clearances between supporter and pipe is studied in case of frost heave. The relation of maximum stress of pipe and maximum deformation of pipe on the ground is studied in case of thaw settlement. The study methods and results are valuable for safety assessment of station pipeline according to clearances or deformation in the condition of frost heave or thaw settlement.

Keywords: frost heave, pipeline, stress analysis, thaw settlement

Procedia PDF Downloads 187

Authors: Ghulam Hasan Abbasi, Moazzam Jamil, M. Anwar-Ul-Haq

Abstract:

Heavy metals are significant pollutants in environment and their toxicity is a problem for survival of living things while Silicon (Si) is one of the most ubiquitous macroelements, performing an essential function in healing plants in response to environmental stresses. A hydroponic experiment was conducted to investigate the role of exogenous application of silicon under cadmium stress in six different maize hybrids with five treatments comprising of control, 7.5 µM Cd + 5 mM Si, 7.5 µM Cd + 10 mM Si, 15 µM Cd + 5 mM Si and 15 µM Cd + 10 mM Si. Results revealed that treatments of plants with 10mM Si application under both 7.5µM Cd and 15 µM Cd stress resulted in maximum improvement in plant morphological attributes (root and shoot length, root and shoot fresh and dry weight, leaf area and relative water contents) and antioxidant enzymes (POD and CAT) relative to 5 mM Si application in all maize hybrids. Results regarding Cd concentrations showed that Cd was more retained in roots followed by shoots and then leaves and maximum reduction in Cd uptake was observed at 10mM Si application. Maize hybrid 6525 showed maximum growth and least concentration of Cd whereas maize hybrid 1543 showed the minimum growth and maximum Cd concentration among all maize hybrids.

Keywords: antioxidant, cadmium, maize, silicon

Procedia PDF Downloads 520

Authors: Ziyu Diao, Yanyan Zhang, Zhentao Liu, Ruidong Yan

Abstract:

The update frequency of wear profile in main bearing wear prognosis of internal combustion engine plays an important role in the calculation efficiency and accuracy. In order to investigate the appropriate cycle index of the simplified working condition of wear simulation, the main bearing-crankshaft journal friction pair of a diesel engine in service was studied in this paper. The method of multi-body dynamics simulation was used, and the wear prognosis model of the main bearing was established. Several groups of cycle indexes were set up for the wear calculation, and the maximum wear depth and wear profile were compared and analyzed. The results showed that when the cycle index reaches 3, the maximum deviation rate of the maximum wear depth is about 2.8%, and the maximum deviation rate comes to 1.6% when the cycle index reaches 5. This study provides guidance and suggestions for the optimization of wear prognosis by selecting appropriate value of cycle index according to the requirement of calculation cost and accuracy of the simulation work.

Keywords: cycle index, deviation rate, wear calculation, wear profile

Procedia PDF Downloads 170

Authors: Yogita Mishra, Arijit Roy, Dhruval Bhavsar

Abstract:

The study estimates the nitrogen concentration in selected vegetation community’s i.e. chir pine (pinusroxburghii) by using hyperspectral satellite data and also identified the appropriate spectral bands and nitrogen indices. The Short Wave InfraRed reflectance spectrum at 1790 nm and 1680 nm shows the maximum possible absorption by nitrogen in selected species. Among the nitrogen indices, log normalized nitrogen index performed positively and negatively too. The strong positive correlation is taken out from 1510 nm and 760 nm for the pinusroxburghii for leaf nitrogen concentration and leaf nitrogen mass while using NDNI. The regression value of R² developed by using linear equation achieved maximum at 0.7525 for the analysis of satellite image data and R² is maximum at 0.547 for ground truth data for pinusroxburghii respectively.

Keywords: hyperspectral, NDNI, nitrogen concentration, regression value

Procedia PDF Downloads 295