Search results for: Penalized Quasi Likelihood

Authors: Alok Kumar, Raviraj Patil

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The ability to respond to an incident of a disastrous event in a vulnerable area is very crucial an aspect of emergency management. The ability to constantly predict the likelihood of an event along with its severity in an area and react to those significant events which are likely to have a high impact allows the authorities to respond by allocating resources optimally in a timely manner. It provides for measuring, monitoring, and modeling facilities that integrate underlying systems into one solution to improve operational efficiency, planning, and coordination. We were particularly involved in this innovative incubation work on the current state of research and development in collaboration. technologies & systems for a disaster.

Keywords: predictive analytics, advanced analytics, area flood likelihood model, area flood severity model, level of impact model, mortality score, economic loss score, resource allocation, crew allocation

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Authors: S. Joseph Antony, Z. K. Jahanger

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Soils are subjected to cyclic loading in situ in situations such as during earthquakes and in the compaction of pavements. Investigations on the local scale measurement of the displacements of the grain and failure patterns within the soil bed under the cyclic loading conditions are rather limited. In this paper, using the digital particle image velocimetry (DPIV), local scale displacement fields of a dense sand medium interacting with a rigid footing are measured under the plane-strain condition for two commonly used types of cyclic loading, and the quasi-static loading condition for the purposes of comparison. From the displacement measurements of the grains, the failure envelopes of the sand media are also presented. The results show that, the ultimate cyclic bearing capacity (qultcyc) occurred corresponding to a relatively higher settlement value when compared with that of under the quasi-static loading. For the sand media under the cyclic loading conditions considered here, the displacement fields in the soil media occurred more widely in the horizontal direction and less deeper along the vertical direction when compared with that of under the quasi-static loading. The 'dead zone' in the sand grains beneath the footing is identified for all types of the loading conditions studied here. These grain-scale characteristics have implications on the resulting bulk bearing capacity of the sand media in footing-sand interaction problems.

Keywords: cyclic loading, DPIV, settlement, soil-structure interactions, strip footing

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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This study aims to evaluate the effective size and hysteresis characteristics of Circular Hollow Steel (CHS) damper. CHS damper is among steel dampers which are used widely for seismic energy dissipation because they are easy to install, maintain and are low cost. CHS damper dissipates seismic energy through metallic deformation due to the geometrical elasticity of circular shape and fatigue resistance around connection part. After calculating the effective size, which is found to be height to diameter ratio of √ ("3”), nonlinear FE analyses were conducted to evaluate the hysteresis characteristics. To verify the analysis simulation quasi static loading was carried out and the result was compared and satisfactory result was obtained.

Keywords: SS400 steel, circular hollow steel damper, effective size, quasi static loading, FE analysis

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Authors: Liberto Pombal, Christian Dieter Jaekel

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The objective of this work is to establish theoretical and numerical conditions for Solving Extended Linear Complementarity Problems (XLCP), with emphasis on the Horizontal Linear Complementarity Problem (HLCP). Two new strategies for solving complementarity problems are presented, using differentiable and penalized functions, which resulted in a natural formalization for the Linear Horizontal case. The computational results of all suggested strategies are also discussed in depth in this paper. The implication in practice allows solving and optimizing, in an innovative way, the (forestry) problems of the value chain of the industrial wood sector in Angola.

Keywords: complementarity, box constrained, optimality conditions, wood and environment

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Authors: Keunhong Chae, Seokho Yoon

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In this paper, frequency offset (FO) estimation schemes robust to the non-Gaussian noise environments are proposed for orthogonal frequency division multiplexing (OFDM) systems. First, a maximum-likelihood (ML) estimation scheme in non-Gaussian noise environments is proposed, and then, the complexity of the ML estimation scheme is reduced by employing a reduced set of candidate values. In numerical results, it is demonstrated that the proposed schemes provide a significant performance improvement over the conventional estimation scheme in non-Gaussian noise environments while maintaining the performance similar to the estimation performance in Gaussian noise environments.

Keywords: frequency offset estimation, maximum-likelihood, non-Gaussian noise environment, OFDM, training symbol

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Authors: Idit Kalisher, Israel Luski

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One result of the growing dynamicity of labor markets in recent decades is a wider scope of employment mobility – i.e., transitions between employers, either within or between careers. Employment mobility decisions are primarily affected by the current employment status of the worker, which is reflected in wage and tenure. Using 34,328 observations from the National Longitudinal Survey of Youth 1979 (NLS79), which were derived from the USA population between 1990 and 2012, this paper aims to investigate the effects of wage and tenure over employment mobility choices, and additionally to examine the effects of other personal characteristics, individual labor market characteristics and macroeconomic factors. The estimation strategy was designed to address two challenges that arise from the combination of the model and the data: (a) endogeneity of the wage and the tenure in the choice equation; and (b) unobserved heterogeneity, as the data of this research is longitudinal. To address (a), estimation was performed using two-stage limited dependent variable procedure (2SLDV); and to address (b), the second stage was estimated using femlogit – an implementation of the multinomial logit model with fixed effects. Among workers who have experienced at least one turnover, the wage was found to have a main effect on career turnover likelihood of all workers, whereas the wage effect on job turnover likelihood was found to be dependent on individual characteristics. The wage was found to negatively affect the turnover likelihood and the effect was found to vary across wage level: high-wage workers were more affected compared to low-wage workers. Tenure was found to have a main positive effect on both turnover types’ likelihoods, though the effect was moderated by the wage. The findings also reveal that as their wage increases, women are more likely to turnover than men, and academically educated workers are more likely to turnover within careers. Minorities were found to be as likely as Caucasians to turnover post wage-increase, but less likely to turnover with each additional tenure year. The wage and the tenure effects were found to vary also between careers. The difference in attitude towards money, labor market opportunities and risk aversion could explain these findings. Additionally, the likelihood of a turnover was found to be affected by previous unemployment spells, age, and other labor market and personal characteristics. The results of this research could assist policymakers as well as business owners and employers. The former may be able to encourage women and older workers’ employment by considering the effects of gender and age on the probability of a turnover, and the latter may be able to assess their employees’ likelihood of a turnover by considering the effects of their personal characteristics.

Keywords: employment mobility, endogeneity, femlogit, turnover

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Authors: Isao Tomita

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Power characteristics are obtained for laser beams of near-infrared and terahertz wavelengths when produced by difference-frequency generation with a quasi-phase-matched (QPM) waveguide made of gallium phosphide (GaP). A refractive-index change of the QPM GaP waveguide is included in computations with Sellmeier’s formula for varying input wavelengths, where optical loss is also included. Although the output power decreases with decreasing photon energy as the beam wavelength changes from near-infrared to terahertz wavelengths, the beam generation with such greatly different wavelengths, which is not achievable with an ordinary laser diode without the replacement of semiconductor material with a different bandgap one, can be made with the same semiconductor (GaP) by changing the QPM period, where a way of changing the period is provided.

Keywords: difference-frequency generation, gallium phosphide, quasi-phase-matching, waveguide

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

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This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

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Authors: Chen Li-Ching

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The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test.

Keywords: case-control studies, goodness-of-fit test, Kolmogorov-Smirnov test, multinomial logistic regression

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Authors: Md. Rezaul Karim, Andreas Thiel

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Bangladesh is known as one of the most climate vulnerable countries in the world. Innovative technologies are always the key responses to the management of climate impacts. The objectives of this study are to determine the farmer’s perception of climate variability, to compare farmers’ perceptions with metrological data, and to explore the determinants that affect the likelihood of adoption of the selected Climate Smart Agricultural (CSA) technologies. Data regarding climate change perception, determinants and adoption were collected based on the household survey from stratified and randomly selected 365 farmers of the Biral sub-district under Dinajpur district in drought-prone northern Bangladesh. The likelihood of adoption of CSA technologies was analyzed following a multivariate probit model. The findings show that about 82.5% of the farmers perceived increasing temperature, and 75.1 % of farmers perceived decreasing dry season rainfall over the years, which is similarly relevant to metrological data. About 76.4.7% and 80.85% of farmers were aware of the drought tolerance crops and vermicompost, respectively; more than half of the farmers adopted these practices. Around 70.7% of farmers were aware of perching for insect control, but 46.3% of farmers adopted this practice. Although two-thirds of farmers were aware of crop diversification and pheromone trap, adoption was lower compared to the other three CSAs. Results also indicate that the likelihood of adoption of the selected CSAs is significantly influenced by different factors such as socio-economic characteristics, institutional factors and perceived technological or innovation attributes. The likelihood of adopting drought tolerance crops is affected by 11, while crop diversification and perching method by 7, pheromone trap by 9 and vermicompost by 8 determining factors. Lack of information and unavailability of input appear to be major obstacles to the non-adoption of CSA technologies. This study suggests that policy implications are necessary to promote extension services and overcome the obstacles to the non-adoption of individual CSA technologies. It further recommends that the research study should be conducted in a diverse context, nationally or globally.

Keywords: determinants, adoption, climate smart agriculture, northern Bangladesh

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Authors: G. Minak, D. Ghelli, A. Zucchelli

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This paper presents the results of an experimental characterization of a glass fibre-epoxy composite. The behavior of the traditional two-phase composite has been compared with the one of a new three-phase composite where the epoxy matrix was modified by addition of a 3% weight fraction of montmorillonite nano-particles. Two different types of nano-clays, Cloisite® 30B and RXG7000, produced by Southern Clay Products Inc., have been considered. Three-point bending tests, both monotonic and cyclic, were carried out. A strong reduction of the ultimate flexural strength upon nano-modification has been observed in quasi-static tests. Fatigue tests yielded a smaller strength loss. In both quasi-static and fatigue tests a more pronounced tendency to delamination has been noticed in three-phase composites, especially in the case of 30B nano-clay, with respect to the standard two-phase glass fiber composite.

Keywords: bending fatigue, epoxy resin, glass fiber, montmorillonite

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Authors: Rana Rimawi, Ayman Baklizi

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Skewed distributions are important models that are frequently used in applications. Generalized distributions form a class of skewed distributions and gain widespread use in applications because of their flexibility in data analysis. More specifically, the Generalized Logistic Distribution with its different types has received considerable attention recently. In this study, based on progressively type-II censored data, we will consider point estimation in type II Generalized Logistic Distribution (Type II GLD). We will develop several estimators for its unknown parameters, including maximum likelihood estimators (MLE), Bayes estimators and linear estimators (BLUE). The estimators will be compared using simulation based on the criteria of bias and Mean square error (MSE). An illustrative example of a real data set will be given.

Keywords: point estimation, type II generalized logistic distribution, progressive censoring, maximum likelihood estimation

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Authors: Hyun-Woo Cho

Abstract:

For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: David Ompong, Jai Singh

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A better understanding of the open-circuit voltage (Voc) related losses in organic solar cells (OSCs) is desirable in order to assess the photovoltaic performance of these devices. We have derived Voc as a function of charge carrier mobilities (μe and μh) for organic and hybrid solar cells by optimizing the drift-diffusion current density. The optimum Voc thus obtained depends on the energy difference between the highest occupied molecular orbital (HOMO) level and the quasi-Fermi level of holes of the donor material. We have found that the Voc depends on the ratio of the electron (μe) and hole (μh) mobilities and when μh > μe the Voc increases. The most important loss term in the Voc arises from the energetics of the donor and acceptor materials, which will be discussed in detail in this paper.

Keywords: charge carrier mobility, open-circuit voltage, organic solar cells, quasi-fermi levels

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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

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

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

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Authors: Safeer Hussain Khan, H. Fukhar-ud-Din

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The concept of quasi-contractive type operators was given by Berinde and extended by Imoru and Olatinwo. They named this new type as contractive-like operators. On the other hand, Xu and Noo introduced a three-step-one-mappings iterative process which can be seen as a generalization of Mann and Ishikawa iterative processes. Approximating common fixed points has its own importance as it has a direct link with minimization problem. Motivated by this, in this paper, we first extend the iterative process of Xu and Noor to the case of three-step-three-mappings and then prove a strong convergence result using contractive-like operators for this iterative process. In general, this generalizes corresponding results using Mann, Ishikawa and Xu-Noor iterative processes with quasi-contractive type operators. It is to be pointed out that our results can also be proved with iterative process involving error terms.

Keywords: contractive-like operator, iterative process, common fixed point, strong convergence

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Authors: Hyeon-Kyo Lim, Sang-Hun Byun

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Risk assessment is carried out in most industrial plants for accident prevention, but there exists insufficient data for statistical decision making. It is commonly said that risk can be expressed as a product of consequence and likelihood of a corresponding hazard factor. Eventually, therefore, risk assessment involves human decision making which cannot be objective per se. This study was carried out to comprehend perceptive characteristics of human beings in industrial plants. Subjects were shown a set of illustrations describing scenes of industrial plants, and were asked to assess the risk of each scene with not only linguistic variables but also numeric scores in the aspect of consequence and likelihood. After that, their responses were formulated as fuzzy membership functions, and compared with those of university students who had no experience of industrial works. The results showed that risk level of industrial workers were lower than those of any other groups, which implied that the workers might generally have a tendency to neglect more hazard factors in their work fields.

Keywords: fuzzy, hazard, linguistic variable, risk assessment

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Authors: A. Mourtzikou, D. Sygkridou, T. Georgakopoulos, G. Katsagounos, E. Stathatos

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Over 60% highly transparent quasi-solid-state dye-sensitized solar cells (DSSCs) with dimension of 50x50 cm² were fabricated via inkjet printing process using nanocomposite inks as raw materials and tested under outdoor illumination conditions. The cells were electrically characterized, and their possible application to the shell of greenhouses was also examined. The panel design was in Z-interconnection, where the working electrode was inkjet printed on one conductive glass and the counter electrode on a second glass in a sandwich configuration. Silver current collective fingers were printed on the glasses to make the internal electrical connections. In that case, the adjacent cells were connected in series via silver fingers and finally insulated using a UV curing resin to protect them from the corrosive (I^-/I₃^-) redox couple of the electrolyte.

Keywords: Dye-sensitized solar panels, inkjet printing, quasi-solid state electrolyte, semi-transparency, scale up

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Authors: A. M. Abd-Elfattah, M. H. Abu-Moussa

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In this paper, the estimation of stress-strength parameter R = P(Y < X) is considered when X; Y the strength and stress respectively are two independent random variables of Burr Type XII distribution. The samples taken for X and Y are progressively censoring of type II. The maximum likelihood estimator (MLE) of R is obtained when the common parameter is unknown. But when the common parameter is known the MLE, uniformly minimum variance unbiased estimator (UMVUE) and the Bayes estimator of R = P(Y < X) are obtained. The exact condence interval of R based on MLE is obtained. The performance of the proposed estimators is compared using the computer simulation.

Keywords: Burr Type XII distribution, progressive type-II censoring, stress-strength model, unbiased estimator, maximum-likelihood estimator, uniformly minimum variance unbiased estimator, confidence intervals, Bayes estimator

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Authors: Eda Orhun

Abstract:

Purpose: This paper analyzes a target firm’s decision to voluntarily disclose information during a takeover event and the effect of such disclosures on the outcome of the takeover. Such voluntary disclosures especially in the form of earnings forecasts made around takeover events may affect shareholders’ decisions about the target firm’s value and in return takeover result. This study aims to shed light on this question. Design/methodology/approach: The paper tries to understand the role of voluntary disclosures by target firms during a takeover event in the likelihood of takeover success both theoretically and empirically. A game-theoretical model is set up to analyze the voluntary disclosure decision of a target firm to inform the shareholders about its real worth. The empirical implication of model is tested by employing binary outcome models where the disclosure variable is obtained by identifying the target firms in the sample that provide positive news by issuing increasing management earnings forecasts. Findings: The model predicts that a voluntary disclosure of positive information by the target decreases the likelihood that the takeover succeeds. The empirical analysis confirms this prediction by showing that positive earnings forecasts by target firms during takeover events increase the probability of takeover failure. Overall, it is shown that information dissemination through voluntary disclosures by target firms is an important factor affecting takeover outcomes. Originality/Value: This study is the first to the author's knowledge that studies the impact of voluntary disclosures by the target firm during a takeover event on the likelihood of takeover success. The results contribute to information economics, corporate finance and M&As literatures.

Keywords: takeovers, target firm, voluntary disclosures, earnings forecasts, takeover success

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.

Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers

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Authors: Hussein Shaman, Faris Almansour

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This paper proposes a modified optimum bandstop filter with ultra-wideband stopband. The filter consists of three shunt open-circuited stubs and two non-redundant unit elements. The proposed bandstop filter is designed with unequal electrical lengths of the open-circuited stubs at the mid-stopband. Therefore, the filter can exhibit a quasi-elliptic function response that improves the selectivity and enhances the rejection bandwidth. The filter is designed to exhibit a fractional bandwidth of about 114% at a mid-stopband frequency of 3.0 GHz. The filter is successfully realized in theory, simulated, fabricated and measured. An excellent agreement is obtained between calculated, simulated and measured. The fabricated filter has a compact size with a low insertion loss in the passbands, high selectivity and good attenuation level inside the desired stopband

Keywords: microstrip filter, bandstop filter, UWB filter, transmission line filter

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Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: Santu Dey, Arindam Bhattacharyya

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The object of the present paper is to study a quarter-symmetric metric connection in a Lorentzian α-Sasakian manifold. We study some curvature properties of Lorentzian α-Sasakian manifold with respect to quarter-symmetric metric connection. We investigate quasi-projectively at, Φ-symmetric, Φ-projectively at Lorentzian α-Sasakian manifolds with respect to quarter-symmetric metric connection. We also discuss Lorentzian α-Sasakian manifold admitting quartersymmetric metric connection satisfying P.S = 0, where P denote the projective curvature tensor with respect to quarter-symmetric metric connection.

Keywords: quarter-symmetric metric connection, Lorentzian alpha-Sasakian manifold, quasi-projectively flat Lorentzian alpha-Sasakian manifold, phi-symmetric manifold

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Authors: Aamir Mubashar, Ibrahim Fiaz

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This research presents a three-dimensional finite element modelling strategy to simulate damage in a quasi-static three-point bending analysis of woven twill 2/2 type carbon fibre reinforced plastic (CFRP) composite on a micro-meso level using cohesive zone modelling technique. A meso scale finite element model comprised of a number of plies was developed in the commercial finite element code Abaqus/explicit. The interfaces between the plies were explicitly modelled using cohesive zone elements to allow for debonding by crack initiation and propagation. Load-deflection response of the CRFP within the quasi-static range was obtained and compared with the data existing in the literature. This provided validation of the model at the global scale. The outputs resulting from the global model were then used to develop a simulation model capturing the micro-meso scale material features. The sub-model consisted of a refined mesh representative volume element (RVE) modelled in texgen software, which was later embedded with cohesive elements in the finite element software environment. The results obtained from the developed strategy were successful in predicting the overall load-deflection response and the damage in global and sub-model at the flexure limit of the specimen. Detailed analysis of the effects of the micro-scale features was carried out.

Keywords: woven composites, multi-scale modelling, cohesive zone, finite element model

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Authors: Sharmistha Chowdhury, Shuva Chowdhury

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Buying-selling new as well as second-hand goods like tools, furniture, household, electronics, clothing, baby stuff, vehicles, and hobbies through the Facebook marketplace has become a new paradigm for c2c sellers. This phenomenon encourages and empowers decentralised home-oriented sellers. This study adopts Elaboration Likelihood Model (ELM) to explain consumer behaviour on Facebook Marketplace (FM). ELM suggests that consumers process information through the central and peripheral routes, which eventually shape their attitudes towards posts. The central route focuses on information quality, and the peripheral route focuses on cues. Sellers’ FM posts usually include product features, prices, conditions, pictures, and pick-up location. This study uses information relevance and accuracy as central route factors. The post’s attractiveness represents cues and creates positive or negative associations with the product. A post with remarkable pictures increases the attractiveness of the post. So, post aesthetics is used as a peripheral route factor. People influenced via the central or peripheral route forms an attitude that includes multiple processes – response and purchase intention. People respond to FM posts through save, share and chat. Purchase intention reflects a positive image of the product and higher purchase intention. This study proposes trust on sellers as a moderator to test the strength of its influence on consumer attitudes and behaviour. Trust on sellers is assessed whether sellers have badges or not. A sample questionnaire will be developed and distributed among a group of random FM sellers who are selling vehicles on this platform to conduct the study. The chosen product of this study is the vehicle, a high-value purchase item. High-value purchase requires consumers to consider forming their attitude without any sign of impulsiveness seriously. Hence, vehicles are the perfect choice to test the strength of consumers attitudes and behaviour. The findings of the study add to the elaboration likelihood model and online second-hand marketplace literature.

Keywords: consumer behaviour, elaboration likelihood model, facebook marketplace, c2c marketing

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: A. M. Tahsini, S. Tadayon Mousavi

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The purpose of this paper is to elucidate the flow unsteady behavior for moving plug in convergent-divergent variable thrust nozzle. Compressible axisymmetric Navier-Stokes equations are used to study this physical phenomenon. Different velocities are set for plug to investigate the effect of plug movement on flow unsteadiness. Variation of mass flow rate and thrust are compared under two conditions: First, the plug is placed at different positions and flow is simulated to reach the steady state (quasi steady simulation) and second, the plug is moved with assigned velocity and flow simulation is coupled with plug movement (unsteady simulation). If plug speed is high enough and its movement time scale is at the same order of the flow time scale, variation of the mass flow rate and thrust level versus plug position demonstrate a vital discrepancy under the quasi steady and unsteady conditions. This phenomenon should be considered especially from response time viewpoints in thrusters design.

Keywords: nozzle, numerical study, unsteady, variable thrust

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Authors: Willy Mbenza, Sho Kenjiro

Abstract:

Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

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