Search results for: estimations of probability distributions

Authors: David C. Ni

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In the previous efforts, we constructed N-Body Systems by an extended Blaschke product (EBP), which represents a non-temporal and nonlinear extension of Lorentz transformation. In this construction, we rely only on two parameters, nonlinear degree, and relative momentum to characterize the systems. We further explored root computation via iteration with an algorithm extended from Jenkins-Traub method. The solution sets demonstrate a form of σ+ i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various canonical distributions. In this paper, we correlate the convergent sets in the original domain with solution sets, which demonstrating large-deviation distributions in the codomain. We proceed to compare our approach with the formula or principles, such as Donsker-Varadhan and Wentzell-Freidlin theories. The deterministic model based on this construction allows us to explore applications in the areas of finance and statistical mechanics.

Keywords: nonlinear Lorentz transformation, Blaschke equation, iteration solutions, root computation, large deviation distribution, deterministic model

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Authors: Eke Bala Sophie Michelle

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The renewable resource character of NTFPs is an opportunity to its sustainability, this study analyzed the role of social capital in the adoption of sustainable management practices of NTFPs by households in the community forest (CF) Morikouali-ye. The analysis shows that 67% of households surveyed perceive the level of degradation of NTFPs in their CF as time passes and are close to 74% for adoption of sustainable management practices of NTFPs that are domestication, sustainable management of the CF, the logging ban trees and uprooting plants, etc. 26% refused to adopt these practices estimate that, at 39% it is better to promote logging in the CF. The estimated probit model shows that social capital through trust, solidarity and social inclusion significantly influences the probability of households to adopt sustainable NTFP management practices. In addition, age, education level and income from the sale of NTFPs have a significant impact on the probability of adoption. The probability of adoption increases with the level of education and confidence among households. So should they be animated by a spirit of solidarity and trust and not let a game of competition for sustainable management of NTFPs in their CF.

Keywords: community forest, social capital, NTFP, trust, solidarity, social inclusion, sustainable management

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Authors: Changshan Zhang, Zhijin Yu, Shixing Fan

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A comprehensive hazard evaluation for coal self-heating in composite long-wall gobs is heavily dependent on computational simulation. In this study, the spatial distributions of cracks which caused significant air leakage were simulated by universal distinct element code (UDEC) simulation. Based on the main routes of air leakage and characteristics of coal self-heating, a computational fluid dynamics (CFD) modeling was conducted to model the coal spontaneous combustion dangerous area in composite long-wall gobs. The results included the oxygen concentration distributions and temperature profiles showed that the numerical approach is validated by comparison with the test data. Furthermore, under the conditions of specific engineering, the major locations where some techniques for extinguishing and preventing long-wall gob fires need to be put into practice were also examined.

Keywords: computational simulation, UDEC simulation, coal self-heating, CFD modeling, long-wall gobs

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Authors: Ebissa Gadissa Kedir, C. S. P. Ojha, K. S. Hari Prasad

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In the present study, the depth-averaged velocity and boundary shear stress in non-prismatic compound channels with three different converging floodplain angles ranging from 1.43ᶱ to 7.59ᶱ have been studied. The analytical solutions were derived by considering acting forces on the channel beds and walls. In the present study, five key parameters, i.e., non-dimensional coefficient, secondary flow term, secondary flow coefficient, friction factor, and dimensionless eddy viscosity, were considered and discussed. An expression for non-dimensional coefficient and integration constants was derived based on the boundary conditions. The model was applied to different data sets of the present experiments and experiments from other sources, respectively, to examine and analyse the influence of floodplain converging angles on depth-averaged velocity and boundary shear stress distributions. The results show that the non-dimensional parameter plays important in portraying the variation of depth-averaged velocity and boundary shear stress distributions with different floodplain converging angles. Thus, the variation of the non-dimensional coefficient needs attention since it affects the secondary flow term and secondary flow coefficient in both the main channel and floodplains. The analysis shows that the depth-averaged velocities are sensitive to a shear stress-dependent model parameter non-dimensional coefficient, and the analytical solutions are well agreed with experimental data when five parameters are included. It is inferred that the developed model may facilitate the interest of others in complex flow modeling.

Keywords: depth-average velocity, converging floodplain angles, non-dimensional coefficient, non-prismatic compound channels

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Authors: Ainura Tursunalieva, Irene Hudson

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Continuous improvement of both the quality and safety of health care is an important goal in Australia and internationally. The intensive care unit (ICU) receives patients with a wide variety of and severity of illnesses. Accurately identifying patients at risk of developing complications or dying is crucial to increasing healthcare efficiency. Thus, it is essential for clinicians and researchers to have a robust framework capable of evaluating the risk profile of a patient. ICU scoring systems provide such a framework. The Acute Physiology and Chronic Health Evaluation III and the Simplified Acute Physiology Score II are ICU scoring systems frequently used for assessing the severity of acute illness. These scoring systems collect multiple risk factors for each patient including physiological measurements then render the assessment outcomes of individual risk factors into a single numerical value. A higher score is related to a more severe patient condition. Furthermore, the Mortality Probability Model II uses logistic regression based on independent risk factors to predict a patient’s probability of mortality. An important overlooked limitation of SAPS II and MPM II is that they do not, to date, include interaction terms between a patient’s vital signs. This is a prominent oversight as it is likely there is an interplay among vital signs. The co-existence of certain conditions may pose a greater health risk than when these conditions exist independently. One barrier to including such interaction terms in predictive models is the dimensionality issue as it becomes difficult to use variable selection. We propose an innovative scoring system which takes into account a dependence structure among patient’s vital signs, such as systolic and diastolic blood pressures, heart rate, pulse interval, and peripheral oxygen saturation. Copulas will capture the dependence among normally distributed and skewed variables as some of the vital sign distributions are skewed. The estimated dependence parameter will then be incorporated into the traditional scoring systems to adjust the points allocated for the individual vital sign measurements. The same dependence parameter will also be used to create an alternative copula-based model for predicting a patient’s probability of mortality. The new copula-based approach will accommodate not only a patient’s trajectories of vital signs but also the joint dependence probabilities among the vital signs. We hypothesise that this approach will produce more stable assessments and lead to more time efficient and accurate predictions. We will use two data sets: (1) 250 ICU patients admitted once to the Chui Regional Hospital (Kyrgyzstan) and (2) 37 ICU patients’ agitation-sedation profiles collected by the Hunter Medical Research Institute (Australia). Both the traditional scoring approach and our copula-based approach will be evaluated using the Brier score to indicate overall model performance, the concordance (or c) statistic to indicate the discriminative ability (or area under the receiver operating characteristic (ROC) curve), and goodness-of-fit statistics for calibration. We will also report discrimination and calibration values and establish visualization of the copulas and high dimensional regions of risk interrelating two or three vital signs in so-called higher dimensional ROCs.

Keywords: copula, intensive unit scoring system, ROC curves, vital sign dependence

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Authors: Maria A. Murtiati, Ancella A. Hermawan

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The objective of this study is to examine whether the firm’s eligibility to get a bank loan is influenced by earnings management. The earnings management is distinguished between accruals and real earnings management. Hypothesis testing is carried out with logistic regression model using sample of 285 companies listed at Indonesian Stock Exchange in 2010. The result provides evidence that a greater magnitude in accruals earnings management increases the firm’s probability to be eligible to get bank loan. In contrast, real earnings management through abnormal cash flow and abnormal discretionary expenses decrease firm’s probability to be eligible to get bank loan, while real management through abnormal production cost increases such probability. The result of this study suggests that if the earnings management is assumed to be opportunistic purpose, the accruals based earnings management can distort the banks credit analysis using financial statements. Real earnings management has more impact on the cash flows, and banks are very concerned on the firm’s cash flow ability. Therefore, this study indicates that banks are more able to detect real earnings management, except abnormal production cost in real earning management.

Keywords: discretionary accruals, real earning management, bank loan, credit worthiness

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Authors: Ali Sagiroglu, Sema Noyan Alacali, Guray Arslan

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This paper presents a study on the influence of the safety factor in the concrete contribution to shear strength of high-strength concrete (HSC) beams according to TS500. In TS500, the contribution of concrete to shear strength is obtained by reducing diagonal cracking strength with a safety factor of 0.8. It was investigated that the coefficient of 0.8 considered in determining the contribution of concrete to the shear strength corresponds to which value of failure probability. Also, the changes in the reduction factor depending on different coefficients of variation of concrete were examined.

Keywords: reinforced concrete, beam, shear strength, failure probability, safety factor

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Authors: Kamyar Maleki Bagherabadi, Torstein Aarseth Bø, Truls Flatberg, Olve Mo

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Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy, and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishery vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a PEM fuel cell, a diesel genset, and a battery. The methodologies used are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed, and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider time variation of the load provide more realistic estimations of energy and fuel consumption regarding hydrogen tank and battery size, still within low computational time.

Keywords: fuel cell, battery, hydrogen, hybrid power system, power management system

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Authors: H. Moalla, A. Frikha

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Multi-criteria decision aid methods consider decision problems where numerous alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too much strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE method. On the base of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE’s net flows and then calculates weights. Subsequently, it aggregates the distribution masses associated to each criterion using Murphy’s modified combination rule in order to infer a global belief structure. The final action ranking is obtained via pignistic probability transformation. A case study of real-world application concerning the location of a waste treatment center from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the BELIEF-PROMETHEE approach.

Keywords: belief function theory, incomplete information, multiple criteria analysis, PROMETHEE method

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Authors: Matthew Morey, Aron Gottesman

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This paper examines the relationship between mutual fund governance and the activeness of equity mutual funds. Using a fund’s corporate culture as a proxy for its governance and controlling for other variables, we find that funds with the better governance are significantly more active than other funds. Further, we find the probability of finding a highly active fund increases significantly as the governance of the fund improves. We also find some evidence that the probability of finding a closet index fund increases as the governance of the fund declines. These results demonstrate that mutual fund governance should be considered carefully when making mutual fund investment decisions.

Keywords: active, share, mutual funds, economics

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Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

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In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

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Authors: Chun-Qing Li, Guoyang Fu, Wei Yang

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A significant portion of current water networks is made of cast iron pipes. Due to aging and deterioration with corrosion being the most predominant mechanism, the failure rate of cast iron pipes is very high. Although considerable research has been carried out in the past few decades, most are on the effect of corrosion on the structural capacity of pipes using strength theory as the failure criterion. This paper presents a reliability-based methodology for the assessment of corrosion affected cast iron pipe cracking failures. A nonlinear limit state function taking into account all three fracture modes is proposed for brittle metal pipes with mixed mode fracture. A stochastic model of the load effect is developed, and time-dependent reliability method is employed to quantify the probability of failure and predict the remaining service life. A case study is carried out using the proposed methodology, followed by sensitivity analysis to investigate the effects of the random variables on the probability of failure. It has been found that the larger the inclination angle or the Mode I fracture toughness is, the smaller the probability of pipe failure is. It has also been found that the multiplying and exponential coefficients k and n in the power law corrosion model and the internal pressure have the most influence on the probability of failure for cast iron pipes. The methodology presented in this paper can assist pipe engineers and asset managers in developing a risk-informed and cost-effective strategy for better management of corrosion-affected pipelines.

Keywords: corrosion, inclined surface cracks, pressurized cast iron pipes, stress intensity

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Authors: Benmansour Nassima, Benmansour Souheyla

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The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

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Authors: Ranjan Banerjee, W. D. Gunawardana

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The free vibration and flutter analysis plays a major part in aircraft design which is indeed, a mandatory requirement. In particular, high aspect ratio transport airliner wings are prone to free vibration and flutter problems that must be addressed during the design process as demanded by the airworthiness authorities. The purpose of this paper is to carry out a detailed free vibration and flutter analysis for a wide range of high aspect ratio aircraft wings and generate design curves to provide useful visions and understandings of aircraft design from an aeroelastic perspective. In the initial stage of the investigation, the bending and torsional stiffnesses of a number of transport aircraft wings are looked at and critically examined to see whether it is possible to express the stiffness distributions in polynomial form, but in a sufficiently accurate manner. A similar attempt is made for mass and mass moment of inertia distributions of the wing. Once the choice of stiffness and mass distributions in polynomial form is made, the high aspect ratio wing is idealised by a series of bending-torsion coupled beams from a structural standpoint. Then the dynamic stiffness method is applied to compute the natural frequencies and mode shape of the wing. Next the wing is idealised aerodynamically and to this end, unsteady aerodynamic of Theodorsen type is employed to represent the harmonically oscillating wing. Following this step, a normal mode method through the use of generalised coordinates is applied to formulate the flutter problem. In essence, the generalised mass, stiffness and aerodynamic matrices are combined to obtain the flutter matrix which is subsequently solved in the complex domain to determine the flutter speed and flutter frequency. In the final stage of the investigation, an exhaustive parametric study is carried out by varying significant wing parameters to generate design curves which help to predict the free vibration and flutter behaviour of high aspect ratio transport aircraft wings in a generic manner. It is in the aeroelastic context of aircraft design where the results are expected to be most useful.

Keywords: high-aspect ratio wing, flutter, dynamic stiffness method, free vibration, aeroelasticity

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Garry A. Einicke, Langford B. White

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This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost.

Keywords: optimal filtering, smoothing, Markov chains

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Authors: Gubhinder Kundhi, Paul Rilstone

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Refined procedures for higher-order asymptotic theory for non-linear models are developed. These include a new method for deriving stochastic expansions of arbitrary order, new methods for evaluating the moments of polynomials of sample averages, a new method for deriving the approximate moments of the stochastic expansions; an application of these techniques to gather improved inferences with the weak instruments problem is considered. It is well established that Instrumental Variable (IV) estimators in the presence of weak instruments can be poorly behaved, in particular, be quite biased in finite samples. In our application, finite sample approximations to the distributions of these estimators are obtained using Edgeworth and Saddlepoint expansions. Departures from normality of the distributions of these estimators are analyzed using higher order analytical corrections in these expansions. In a Monte-Carlo experiment, the performance of these expansions is compared to the first order approximation and other methods commonly used in finite samples such as the bootstrap.

Keywords: edgeworth expansions, higher order asymptotics, saddlepoint expansions, weak instruments

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Authors: Leizhang Wang, Baocang Wang

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General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

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Authors: V. S. S. Kumar, V. Ramya

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In the modern electronic warfare, the signal scenario is changing at a rapid pace with the introduction of Low Probability of Intercept (LPI) radars. In the modern battlefield, radar system faces serious threats from passive intercept receivers such as Electronic Attack (EA) and Anti-Radiation Missiles (ARMs). To perform necessary target detection and tracking and simultaneously hide themselves from enemy attack, radar systems should be LPI. These LPI radars use a variety of complex signal modulation schemes together with pulse compression with the aid of advancement in signal processing capabilities of the radar such that the radar performs target detection and tracking while simultaneously hiding enemy from attack such as EA etc., thus posing a major challenge to the ES/ELINT receivers. Today an increasing number of LPI radars are being introduced into the modern platforms and weapon systems so these LPI radars created a requirement for the armed forces to develop new techniques, strategies and equipment to counter them. This paper presents various modulation techniques used in generation of LPI signals and development of Time Frequency Algorithms to analyse those signals.

Keywords: anti-radiation missiles, cross terms, electronic attack, electronic intelligence, electronic warfare, intercept receiver, low probability of intercept

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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: Gabriel I. Loaiza Ossa, Carlos A. Cadavid Moreno, Juan C. Arango Parra

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It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ= -1/2, as does the family of usual Gaussian distributions. In the present paper, firstly, we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ₁, θ₂; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the inverse q-Gaussian distribution family (q < 3) as the family obtained by replacing the usual exponential function with the Tsallis q-exponential function in the expression for the inverse Gaussian distribution and observe that it supports two possible geometries, the Fisher and the q-Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q-Fisher geometry of the inverse q-Gaussian distribution family, similar to the ones obtained in the case of the inverse Gaussian distribution family.

Keywords: base of changes, information geometry, inverse Gaussian distribution, inverse q-Gaussian distribution, statistical manifolds

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Authors: Olawale Babatunde Olatinsu, Deborah Oluwaseun Olorode

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Industrial rocks were collected from a quarry site at Ewekoro in south-western Nigeria and analysed using Nuclear Magnetic Resonance (NMR) technique. NMR measurement was conducted on the samples in partial water-saturated and full brine-saturated conditions. Raw NMR data were analysed with the aid of T2 curves and T2 spectra generated by inversion of raw NMR data using conventional regularized least-squares inversion routine. Results show that NMR transverse relaxation (T2) signatures fairly adequately distinguish between the rock types. Similar T2 curve trend and rates at partial saturation suggests that the relaxation is mainly due to adsorption of water on micropores of similar sizes while T2 curves at full saturation depict relaxation decay rate as: 1/T2(shale)>1/ T2(glauconite)>1/ T2(limestone) and 1/T2(sandstone). NMR T2 distributions at full brine-saturation show: unimodal distribution in shale; bimodal distribution in sandstone and glauconite; and trimodal distribution in limestone. Full saturation T2 distributions revealed the presence of well-developed and more abundant micropores in all the samples with T2 in the range, 402-504 μs. Mesopores with amplitudes much lower than those of micropores are present in limestone, sandstone and glauconite with T2 range: 8.45-26.10 ms, 6.02-10.55 ms, and 9.45-13.26 ms respectively. Very low amplitude macropores of T2 values, 90.26-312.16 ms, are only recognizable in limestone samples. Samples with multiple peaks showed well-connected pore systems with sandstone having the highest degree of connectivity. The difference in T2 curves and distributions for the rocks at full saturation can be utilised as a potent diagnostic tool for discrimination of these rock types found at Ewekoro.

Keywords: Ewekoro, NMR techniques, industrial rocks, characterization, relaxation

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Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

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Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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Authors: Roberta Martino, Viviana Ventre

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From a theoretical point of view, the relationship between the risk associated with an investment and the expected value are directly proportional, in the sense that the market allows a greater result to those who are willing to take a greater risk. However, empirical evidence proves that this relationship is distorted in the minds of investors and is perceived exactly the opposite. To deepen and understand the discrepancy between the actual actions of the investor and the theoretical predictions, this paper analyzes the essential parameters used for the valuation of financial assets with greater attention to two elements: probability and the passage of time. Although these may seem at first glance to be two distinct elements, they are closely related. In particular, the error in the theoretical description of the relationship between risk and return lies in the failure to consider the impatience that is generated in the decision-maker when events that have not yet happened occur in the decision-making context. In this context, probability loses its objective meaning and in relation to the psychological aspects of the investor, it can only be understood as the degree of confidence that the investor has in the occurrence or non-occurrence of an event. Moreover, the concept of objective probability does not consider the inter-temporality that characterizes financial activities and does not consider the condition of limited cognitive capacity of the decision maker. Cognitive psychology has made it possible to understand that the mind acts with a compromise between quality and effort when faced with very complex choices. To evaluate an event that has not yet happened, it is necessary to imagine that it happens in your head. This projection into the future requires a cognitive effort and is what differentiates choices under conditions of risk and choices under conditions of uncertainty. In fact, since the receipt of the outcome in choices under risk conditions is imminent, the mechanism of self-projection into the future is not necessary to imagine the consequence of the choice and the decision makers dwell on the objective analysis of possibilities. Financial activities, on the other hand, develop over time and the objective probability is too static to consider the anticipatory emotions that the self-projection mechanism generates in the investor. Assuming that uncertainty is inherent in valuations of events that have not yet occurred, the focus must shift from risk management to uncertainty management. Only in this way the intertemporal dimension of the decision-making environment and the haste generated by the financial market can be cautioned and considered. The work considers an extension of the prospectus theory with the temporal component with the aim of providing a description of the attitude towards risk with respect to the passage of time.

Keywords: impatience, risk aversion, subjective probability, uncertainty

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Authors: Rahul Kumar

Abstract:

Background: Under-FiveMortality Rate(U5MR)ofanationiswidelyacceptedandlong-standing indicators of well-beingofherchildren.They measuredtheprobability of dying before theageoffive(expressedper1000livebirths).TheU5MRisanappropriate indicator of the cumulative exposure totheriskofdeathduringthefirstfiveyearsoflife, and accepted globalindicator ofthehealthandsocioeconomicstatusofagiven population.Itisalsousefulforassessing theimpactofvariousintervention programmes aimed at improving child survival.Under-fivemortalitytrendsconstitutealeadingindicatorofthelevel ofchildhealthandoveralldevelopmentincountries. Objectives: The first aim of our research is to study the level, trends, and Pattern of Under-five mortality using different sources of data. The second objective is to examine the survival pattern of Under-five mortality by different background characteristics. Data Source and Methodology: SRS and NFHS data have been used forobservingthelevelandtrendofUnder-Five mortality rate. Kaplan Meier Estimate has been used to understand the survival Pattern of Under-five mortality. Result: WefindthatallmostallthestatesmadesomeprogressbyreducingU5MRin recent decades.During1992-93highestU5MR(per thousand live birth) was observed in Assam(142)followed by up(141),Odisha(131),MP(130),andBihar(127.5).While the least U5MR(perthousandlive birth)wasobservedinRajasthan(102). The highestU5MR(per thousandlive birth)isobservedinUP(78.1), followed by MP(64.9)and Chhattisgarh(63.7)which are far away from the national level(50). Among them, Uttarakhand(46.7)hadleastU5MR(perthousandlivebirth), followed by Odisha(48.6). TheU5MR(perthousandlivebirth)ofcombinedhighfocusstateis63.7whichisfar away fromthenationallevel(50). Weidentified thatthesurvivalprobability ofunder-fivechildrenfromadolescentmotherislessin comparisontootherchildrenbornby differentagegroupofmothers. thatduringneonatalperiodusually male mortality exceedsthefemale mortality butthisdifferentialreversedinthepostneonatalperiod. Astheirageincreasesand approachingtofiveyears,weidentifiedthatthesurvivalprobability ofbothsexdecreasesbut female’s survival probabilitydecrement is more than male as their ageincreases. The poorer children’s survival probability is minimum. Children using improved toilet facility has more survival probability throughout thefiveyearsthan who uses unimproved. The survival probability of children under five who got Full ANCis more than the survival probability of children under five who doesn’t get any ANC. Conclusions: Improvement of maternal education is an urgent need to improve their health seeking behavior and thus the health of their children. Awareness on reproductive health and environmental sanitation should be strengthened.

Keywords: under-five mortality, survival pattern, ANC, trend

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Authors: Yu Song, Yuefei Jin

Abstract:

Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

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Authors: A. GuhaRay, C. V. S. P. Kiranmayi, S. Rudraraju

Abstract:

The present study considers the effect of variation of different geotechnical random variables in the design of stone column-foundation systems for assessing the bearing capacity and consolidation settlement of highly compressible soil. The soil and stone column properties, spacing, diameter and arrangement of stone columns are considered as the random variables. Probability of failure (P_f) is computed for a target degree of consolidation and a target safe load by Monte Carlo Simulation (MCS). The study shows that the variation in coefficient of radial consolidation (c_r) and cohesion of soil (c_s) are two most important factors influencing Pf. If the coefficient of variation (COV) of c_r exceeds 20%, P_f exceeds 0.001, which is unsafe following the guidelines of US Army Corps of Engineers. The bearing capacity also exceeds its safe value for COV of c_s > 30%. It is also observed that as the spacing between the stone column increases, the probability of reaching a target degree of consolidation decreases. Accordingly, design guidelines, considering both consolidation and bearing capacity of improved ground, are proposed for different spacing and diameter of stone columns and geotechnical random variables.

Keywords: bearing capacity, consolidation, geotechnical random variables, probability of failure, stone columns

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Authors: Nitaya Buntao

Abstract:

This paper considers the problems of interval estimation for rainfall mean of the lognormal distribution and the delta-lognormal distribution in Northeastern Thailand. We present here the modified generalized pivotal approach (MGPA) compared to the modified method of variance estimates recovery (MMOVER). The performance of each method is examined in term of coverage probabilities and average lengths by Monte Carlo simulation. An extensive simulation study indicates that the MMOVER performs better than the MGPA approach in terms of the coverage probability; it results in highly accurate coverage probability.

Keywords: rainfall mean, interval estimation, lognormal distribution, delta-lognormal distribution

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Authors: Sayed A. Elsayed, Emad Z. Ibrahim, Osama M. Mesalhy, Mohamed A. Abdelatief

Abstract:

An experimental and numerical study has been conducted to clarify fluid flow characteristics and pressure drop distributions of a cross-flow heat exchanger employing staggered wing-shaped tubes at different angels of attack. The water-side Rew and the air-side Rea were at 5 x 102 and at from 1.8 x 103 to 9.7 x 103, respectively. Three cases of the tubes arrangements with various angles of attack, row angles of attack and 90° cone angles were employed at the considered Rea range. Correlation of pressure drop coefficient Pdc in terms of Rea, design parameters for the studied cases were presented. The flow pattern around the staggered wing-shaped tubes bundle were predicted by using commercial CFD FLUENT 6.3.26 software package. Results indicated that the values of Pdc were increased by increasing the angle of attack from 0° to 45°, while the opposite was true for angles of attack from 135° to 180°. Comparisons between the experimental and numerical results of the present study and those, previously, obtained for similar available studies showed good agreements.

Keywords: wing-shaped tubes, cross-flow cooling, staggered arrangement, CFD

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Authors: Syed Ahzam Tariq, Atharva Modi

Abstract:

This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

Procedia PDF Downloads 127