Search results for: stochastic covariance process

Authors: Nikolaos Simantiris, Markos Avlonitis

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This work builds a simulation platform, modeling the spatial diffusion of the invasive species Callinectes sapidus (blue crab) as a random walk, incorporating also generation, fatality, and fishing rates modeling the time evolution of its population. Antinioti lagoon in West Greece was used as a testbed for applying the simulation model. Field measurements from June 2020 to June 2021 on the lagoon’s setting, bathymetry, and blue crab juveniles provided the initial population simulation of blue crabs, as well as biological parameters from the current literature were used to calibrate simulation parameters. The scope of this study is to render the authors able to predict the evolution of the blue crab population in confined environments of the Ionian Islands region in West Greece. The first result of the simulation experiments shows the possibility for a robust prediction for blue crab population evolution in the Antinioti lagoon.

Keywords: antinioti lagoon, blue crab, stochastic simulation, random walk

Procedia PDF Downloads 186

Authors: S. Cheragh Dar, M. Saljooghi, A. Babrgir

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In the last couple of decades researchers' attitudes were focused on developing and enhancing heat transfer processes by using new components or cellular solids that divide into stochastic structures and periodic structures. Open-cell metal foams are part of stochastic structures families that they can be considered as an avant-garde technology and they have unique properties, this porous media can have tremendous achievements in thermal processes. This paper argues and surveys postulating possible in industrial thermal issues which include: compact electronic cooling, heat exchanger, aerospace, fines, turbo machinery, automobiles, crygen tanks, biomechanics, high temperature filters and etc. Recently, by surveying exponential rate of publications in thermal open-cell metal foams, all can be demonstrated in a holistic view which can lead researchers to a new level of understanding in different industrial thermal sections.

Keywords: heat transfer, industrial thermal, cellular solids, open cell metal foam

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Authors: Collins Molua

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This paper investigated the effect of Teaching Strategies on Academic Achievement in Secondary Physics Education as a quality assurance process for the teaching and learning of the subject. Teaching strategies investigated were the interactive, independent and dependent strategies. Three null hypotheses were tested at p< 0.05 using one instrument, physics achievement test(PAT).The data were analyzed using analysis of covariance (ANCOVA).Results showed that teaching strategies have significant effect on students achievement; the joint effect of the teaching strategies was also significant on students achievement in Physics. The interactive teaching strategies was recommended for teaching the subject and the students should be exposed to practical, computer literacy to stimulate interest and curiosity to enhance quality.

Keywords: quality, assurance, secondary education, strategies, physics

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Authors: Syaza Isma, Timothy Higgins

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In Malaysia, increased take-up rates of tertiary student borrowing, and reliance on retirement savings to fund children's education show the importance of public higher education financing schemes (PTPTN). PTPTN has been operating for 2 decades now; however, there are some critical issues and challenges that include low loan recovery and loan default that suggest a detailed consideration of student loan/financing scheme alternatives is crucial. In addition, the decline in funding level per student following introduction of the new PTPTN full and partial loan scheme has raised ongoing concerns over the sustainability of the scheme to provide continuous financial assistance to students in tertiary education. This research seeks to assess these issues that put greater efficiency in an effort to ensure equitable access to student funding for current and future generations. We explore the extent of repayment hardship under the current loan arrangements that presumably led to low recovery from the borrowers, particularly low-income graduates. The concept of manageable debt exists in the design of income-contingent repayment schemes, as practiced in Australia, New Zealand, UK, Hungary, USA (in limited form), the Netherlands, and South Korea. Can Income Contingent Loans (ICL) offer the best practice for an education financing scheme, and address the issue of repayment hardship and concurrently, can a properly designed ICL scheme provide a solution to the current issues and challenges facing Malaysia student financing? We examine the different potential ICL models using deterministic and stochastic approach to simulate income of graduates.

Keywords: deterministic, income contingent loan, repayment burden, simulation, stochastic

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Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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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: Abdolsalam Ghaderi

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In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.

Keywords: location-routing problem, robust optimization, stochastic programming, variable neighborhood search

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Authors: Seon Soon Choi

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The fatigue crack growth is stochastic because of the fatigue behavior having an uncertainty and a randomness. Therefore, it is necessary to determine the probability distribution of a grown crack size at a specific fatigue crack propagation life for maintenance of structure as well as reliability estimation. The essential purpose of this study is to present the good probability distribution fit for the grown crack size at a specified fatigue life in a rolled magnesium alloy under different specimen thickness conditions. Fatigue crack propagation experiments are carried out in laboratory air under three conditions of specimen thickness using AZ31 to investigate a stochastic crack growth behavior. The goodness-of-fit test for probability distribution of a grown crack size under different specimen thickness conditions is performed by Anderson-Darling test. The effect of a specimen thickness on variability of a grown crack size is also investigated.

Keywords: crack size, fatigue crack propagation, magnesium alloys, probability distribution, specimen thickness

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Authors: Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst

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Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. Process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. Process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches.

Keywords: multidimensional process mining, mMulti-perspective business processes, OLAP, process cubes, process discovery, process mining

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Authors: Amer Ait Sidhoum

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Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

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Authors: S. Dey, T. Mukhopadhyay, S. Adhikari

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This paper presents an exhaustive comparative investigation on sampling techniques of polynomial regression model based stochastic natural frequency of composite plates. Both individual and combined variations of input parameters are considered to map the computational time and accuracy of each modelling techniques. The finite element formulation of composites is capable to deal with both correlated and uncorrelated random input variables such as fibre parameters and material properties. The results obtained by Polynomial regression (PR) using different sampling techniques are compared. Depending on the suitability of sampling techniques such as 2k Factorial designs, Central composite design, A-Optimal design, I-Optimal, D-Optimal, Taguchi’s orthogonal array design, Box-Behnken design, Latin hypercube sampling, sobol sequence are illustrated. Statistical analysis of the first three natural frequencies is presented to compare the results and its performance.

Keywords: composite plate, natural frequency, polynomial regression model, sampling technique, uncertainty quantification

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Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

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Authors: Wannee Sutthachaidee

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The study of the production process of coconut-shell product in Amphawa, Samutsongkram Province is objected to study the pattern of the process of coconut-shell product by focusing in the 3 main processes which are inbound logistics process, production process and outbound process. The result of the research: There were 4 main results from the study. Firstly, most of the manufacturer of coconut-shell product is usually owned by a single owner and the quantity of the finished product is quite low and the main labor group is local people. Secondly, the production process can be divided into 4 stages which are pre-production process, production process, packaging process and distribution process. Thirdly, each 3 of the logistics process of coconut shell will find process which may cause the problem to the business but the process which finds the most problem is the production process because the production process needs the skilled labor and the quantity of the labor does not match with the demand from the customers. Lastly, the factors which affect the production process of the coconut shell can be founded in almost every process of the process such as production design, packaging design, sourcing supply and distribution management.

Keywords: production process, coconut-shell product, Amphawa District, inbound logistics process

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Authors: Mariusz Hofman

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The paper ‘Theoretical framework for value creation in Project-Oriented Companies’ is designed to determine, how organisations create value and whether this allows them to achieve market success. An assumption has been made that there are two routes to achieving this value. The first one is to create intangible assets (i.e. the resources of human, structural and relational capital), while the other one is to create added value (understood as the surplus of revenue over costs). It has also been assumed that the combination of the achieved added value and unique intangible assets translates to the success of a project-oriented company. The purpose of the paper is to present hypothetical and deductive model which describing the modus operandi of such companies and approach to model operationalisation. All the latent variables included in the model are theoretical constructs with observational indicators (measures). The existence of a latent variable (construct) and also submodels will be confirmed based on a covariance matrix which in turn is based on empirical data, being a set of observational indicators (measures). This will be achieved with a confirmatory factor analysis (CFA). Due to this statistical procedure, it will be verified whether the matrix arising from the adopted theoretical model differs statistically from the empirical matrix of covariance arising from the system of equations. The fit of the model with the empirical data will be evaluated using χ2, RMSEA and CFI (Comparative Fit Index). How well the theoretical model fits the empirical data is assessed through a number of indicators. If the theoretical conjectures are confirmed, an interesting development path can be defined for project-oriented companies. This will let such organisations perform efficiently in the face of the growing competition and pressure on innovation.

Keywords: value creation, project-oriented company, structural equation modelling

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Authors: Nisith K. Datta, Rakesh Bharti

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The purpose of the study was to find out the effects of Aquatic and Land plyometric training on selected physical variables in intercollegiate male handball players. To achieve this purpose of the study, forty five handball players of Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat were selected as players at random and their age ranged between 18 to 21 years. The selected players were divided into three equal groups of fifteen players each. Group I underwent Aquatic plyometric training, Group II underwent Land plyometric training and Group III Control group for three days per week for twelve weeks. Control Group did not participate in any special training programme apart from their regular activities as per their curriculum. The following physical fitness variables namely speed; leg explosive power and agility were selected as dependent variables. All the players of three groups were tested on selected dependent variables prior to and immediately after the training programme. The analysis of covariance was used to analyze the significant difference, if any among the groups. Since, three groups were compared, whenever the obtained ‘F’ ratio for adjusted post test was found to be significant, the Scheffe’s test to find out the paired mean differences, if any. The 0.05 level of confidence was fixed as the level of significance to test the ‘F’ ratio obtained by the analysis of covariance, which was considered as an appropriate. The result of the study indicates due to Aquatic and Land plyometric training on speed, explosive power, and agility has been improved significantly.

Keywords: aquatic training, explosive power, plyometric training, speed

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Authors: Seon Soon Choi

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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.

Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution

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Authors: Imen Boudali, Marwa Ragmoun

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

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

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Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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Authors: Ping Tan, Xiaomeng Su, Yi Shen

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The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

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Authors: Arnold Missiame

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In Ghana, rural dwellers who depend primarily on agriculture for their livelihood constitute about 60% of the country’s population. This shows the critical role and potentials of the agricultural sector in helping to achieve Ghana’s vision 2030. With the current threat of climate change and advancements in technology, agricultural extension is not just about technology transfer and improvements in productivity, but it is also about improving the managerial and technical skills of farmers. In Ghana, the government of Ghana as well as other players in the sector like; non-governmental organizations, NGOs, local and international funding agencies, for decades now, have made capacity-building-investments in smallholder farmers by way of extension services delivery. This study sought to compare the technical efficiency of farmers who have access to agricultural extension and farmers who do not in Ghana. The study employed the stochastic meta-frontier model to analyze household survey data comprising 300 smallholder cassava farmers from the Fanteakwa district of Ghana. The farmers were selected through a two-stage sampling technique where 5 communities were purposively selected in the first stage and then 60 smallholder cassava farmers were randomly selected from each of the 5 communities. Semi-structured questionnaires were used to collect data on farmers’ socioeconomic and farm-level characteristics. The results showed that farmers who have access to agricultural extensions services have higher technical efficiencies (TE) and produce much closer to their meta-production frontiers (higher technology gap ratios (TGR) than farmers who do not have access to such extension services. Furthermore, experience in cassava cultivation and formal education significantly improves the technical efficiencies of farmers. The study recommends that the mode and scope of agricultural extension service delivery in the country should be enhanced to ensure that smallholder farmers have easy access to extension agents.

Keywords: agricultural extension, Ghana, smallholder farmers, stochastic meta-frontier model, technical efficiency

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Authors: Guo Haonan, Chen Peiyu, Zhao Hanyu, Burra Venkata Durga Kumar

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Unix and Unix-like operating systems are widely used due to their high stability but are limited by the parent-child process structure, and the child process depends on the parent process, so the crash of a single process may cause the entire process group or even the entire system to fail. Another possibility of unexpected process termination is that the system administrator inadvertently closed the terminal or pseudo-terminal where the application was launched, causing the application process to terminate unexpectedly. This paper mainly analyzes the reasons for the problems and proposes two solutions.

Keywords: process management, daemon, login-bash and non-login bash, process group

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Authors: Bahram Fathi, Karim Alizadeh, Azam Mohammadbagheri

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The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model’s robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory.

Keywords: oil price, shocks, dynamic stochastic general equilibrium, Iran

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Authors: Zeyu Zhou, Xiaojun Bi

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Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

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An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

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Authors: Sai Hung Cheung, Zhe Shao

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It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

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Authors: Rebecca Owusu Coffie, Atakelty Hailu

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Variants of production frontier models have emerged, however, only a limited number of them are applied in empirical research. Hence the effects of these alternative frontier models are not well understood, particularly within sub-Saharan Africa. In this paper, we apply recent advances in the production frontier to examine levels of technical efficiency and efficiency drivers. Specifically, we compare the heteroscedastic parametric and the semiparametric stochastic smooth coefficient (SPSC) models. Using rice production data from Ghana, our empirical estimates reveal that alternative specification of efficiency estimators results in either downward or upward bias in the technical efficiency estimates. Methodologically, we find that the SPSC model is more suitable and generates high-efficiency estimates. Within the parametric framework, we find that parameterization of both the mean and variance of the pre-truncated function is the best model. For the drivers of technical efficiency, we observed that longer farm distances increase inefficiency through a reduction in labor productivity. High soil quality, however, increases productivity through increased land productivity.

Keywords: pre-truncated, rice production, smooth coefficient, technical efficiency

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Authors: Nkwenti Mbelli Njah

Abstract:

This research was motivated by a project requested by AXA on the topic of pensions payable under the workers compensation (WC) line of business. There are two types of pensions: the compulsorily recoverable and the not compulsorily recoverable. A pension is compulsorily recoverable for a victim when there is less than 30% of disability and the pension amount per year is less than six times the minimal national salary. The law defines that the mathematical provisions for compulsory recoverable pensions must be calculated by applying the following bases: mortality table TD88/90 and rate of interest 5.25% (maybe with rate of management). To manage pensions which are not compulsorily recoverable is a more complex task because technical bases are not defined by law and much more complex computations are required. In particular, companies have to predict the amount of payments discounted reflecting the mortality effect for all pensioners (this task is monitored monthly in AXA). The purpose of this research was thus to develop a stochastic model for the future mortality of the worker’s compensation pensioners of both the Portuguese market workers and AXA portfolio. Not only is past mortality modeled, also projections about future mortality are made for the general population of Portugal as well as for the two portfolios mentioned earlier. The global model was split in two parts: a stochastic model for population mortality which allows for forecasts, combined with a point estimate from a portfolio mortality model obtained through three different relational models (Cox Proportional, Brass Linear and Workgroup PLT). The one-year death probabilities for ages 0-110 for the period 2013-2113 are obtained for the general population and the portfolios. These probabilities are used to compute different life table functions as well as the not compulsorily recoverable reserves for each of the models required for the pensioners, their spouses and children under 21. The results obtained are compared with the not compulsory recoverable reserves computed using the static mortality table (TD 73/77) that is currently being used by AXA, to see the impact on this reserve if AXA adopted the dynamic tables.

Keywords: compulsorily recoverable, life table functions, relational models, worker’s compensation pensioners

Procedia PDF Downloads 141

Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

Abstract:

Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

Procedia PDF Downloads 115

Authors: Sohail Imran, Tariq Mahmood

Abstract:

In complex healthcare diagnostic investigation process, medical practitioners have to focus on ways to standardize their processes to perform high quality care and optimize the time and costs. Process mining techniques can be applied to extract process related knowledge from data without considering causal and dynamic dependencies in business domain and processes. The application of process mining is effective in diagnostic investigation. It is very helpful where a treatment gives no dispositive evidence favoring it. In this paper, we applied process mining to discover important process flow of diagnostic investigation for hepatitis patients. This approach has some benefits which can enhance the quality and efficiency of diagnostic investigation processes.

Keywords: process mining, healthcare, diagnostic investigation process, process flow

Procedia PDF Downloads 490

Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

Procedia PDF Downloads 108