Search results for: Monte Carlo Markov Chain

Authors: H. M. Alfrihidi, H.A. Albarakaty

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Flattening filter-free (FFF) photon beam radiotherapy has increased in the last decade, which is enabled by advancements in treatment planning systems and radiation delivery techniques like multi-leave collimators. FFF beams have higher dose rates, which reduces treatment time. On the other hand, FFF beams have a higher surface dose, which is due to the loss of beam hardening effect caused by the presence of the flatting filter (FF). The possibility of improving FFF beam quality using filters from low-z materials such as steel and aluminium (Al) was investigated using Monte Carlo (MC) simulations. The attenuation coefficient of low-z materials for low-energy photons is higher than that of high-energy photons, which leads to the hardening of the FFF beam and, consequently, a reduction in the surface dose. BEAMnrc user code, based on Electron Gamma Shower (EGSnrc) MC code, is used to simulate the beam of a 6 MV True-Beam linac. A phase-space (phosphor) file provided by Varian Medical Systems was used as a radiation source in the simulation. This phosphor file was scored just above the jaws at 27.88 cm from the target. The linac from the jaw downward was constructed, and radiation passing was simulated and scored at 100 cm from the target. To study the effect of low-z filters, steel and Al filters with a thickness of 1 cm were added below the jaws, and the phosphor file was scored at 100 cm from the target. For comparison, the FF beam was simulated using a similar setup. (BEAM Data Processor (BEAMdp) is used to analyse the energy spectrum in the phosphorus files. Then, the dose distribution resulting from these beams was simulated in a homogeneous water phantom using DOSXYZnrc. The dose profile was evaluated according to the surface dose, the lateral dose distribution, and the percentage depth dose (PDD). The energy spectra of the beams show that the FFF beam is softer than the FF beam. The energy peaks for the FFF and FF beams are 0.525 MeV and 1.52 MeV, respectively. The FFF beam's energy peak becomes 1.1 MeV using a steel filter, while the Al filter does not affect the peak position. Steel and Al's filters reduced the surface dose by 5% and 1.7%, respectively. The dose at a depth of 10 cm (D10) rises by around 2% and 0.5% due to using a steel and Al filter, respectively. On the other hand, steel and Al filters reduce the dose rate of the FFF beam by 34% and 14%, respectively. However, their effect on the dose rate is less than that of the tungsten FF, which reduces the dose rate by about 60%. In conclusion, filters from low-z material decrease the surface dose and increase the D10 dose, allowing for a high-dose delivery to deep tumors with a low skin dose. Although using these filters affects the dose rate, this effect is much lower than the effect of the FF.

Keywords: flattening filter free, monte carlo, radiotherapy, surface dose

Procedia PDF Downloads 48

Authors: Ethan Nikookar, Yalda Boroushaki, Larissa Statsenko, Jorge Ochoa Paniagua

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Given the serious impact that supply chain disruptions can have on a firm's bottom-line performance, both industry and academia are interested in supply chain resilience, a capability of the supply chain that enables it to cope with disruptions. To date, much of the research has focused on the antecedents of supply chain resilience. This line of research has suggested various firm-level capabilities that are associated with greater supply chain resilience. A consensus has emerged among researchers that supply chain flexibility holds the greatest potential to create resilience. Supply chain flexibility achieves resilience by creating readiness to respond to disruptions with little cost and time by means of reconfiguring supply chain resources to mitigate the impacts of the disruption. Decisions related to supply chain disruptions are made by supply chain managers; however, the role played by supply chain managers' reference networks has been overlooked in the supply chain resilience literature. This study aims to understand the impact of supply chain managers on their firms' supply chain resilience. Drawing on social capital theory and social network theory, this paper proposes a conceptual model to explore the role of supply chain managers in developing the resilience of supply chains. Our model posits that higher level of supply chain managers' embeddedness in their reference network is associated with increased resilience of their firms' supply chain. A reference network includes individuals from whom supply chain managers seek advice on supply chain related matters. The relationships between supply chain managers' embeddedness in reference network and supply chain resilience are mediated by supply chain flexibility.

Keywords: supply chain resilience, embeddedness, reference networks, social capitals

Procedia PDF Downloads 182

Authors: Otman Jai, Otman Elhajjaji, Jaouad Tajmouati

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Several neutronic calculation codes must be used to solve the equation for different levels of discretization which all necessitate a specific modelisation. This chain of such models, known as a calculation scheme, leads to the knowledge of the neutron flux in a reactor from its own geometry, its isotopic compositions and a cross-section library. Being small in size, the 'Slowpoke-2' reactor is difficult to model due to the importance of the leaking neutrons. In the paper, the simulation model is presented (geometry, cross section library, assumption, etc.), and the results obtained by DRAGON4/DONJON4 codes were compared to the calculations performed with Monte Carlo code MCNP using detailed geometrical model of the reactor and the experimental data. Criticality calculations have been performed to verify and validate the model. Since created model properly describes the reactor core, it can be used for calculations of reactor core parameters and for optimization of research reactor application.

Keywords: transport equation, Dragon4, Donjon4, neutron flux, effective multiplication factor

Procedia PDF Downloads 444

Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)

Procedia PDF Downloads 130

Authors: Kalu Ram Meena, Aditi Kar Gangopadhyay, Satrajit Mandal

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Two normal populations with different means and same variance are considered, where the variances are known. The population with the smaller sample mean is selected. Various estimators are constructed for the mean of the selected normal population. Finally, they are compared with respect to the bias and MSE risks by the method of Monte-Carlo simulation and their performances are analysed with the help of graphs.

Keywords: estimation after selection, Brewster-Zidek technique, estimators, selected populations

Procedia PDF Downloads 476

Authors: Farouk Metiri, Halim Zeghdoudi, Mohamed Riad Remita

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Credibility theory is an experience rating technique in actuarial science which can be seen as one of quantitative tools that allows the insurers to perform experience rating, that is, to adjust future premiums based on past experiences. It is used usually in automobile insurance, worker's compensation premium, and IBNR (incurred but not reported claims to the insurer) where credibility theory can be used to estimate the claim size amount. In this study, we focused on a popular tool in credibility theory which is the Bayesian premium estimator, considering Lindley distribution as a claim distribution. We derive this estimator under entropy loss which is asymmetric and squared error loss which is a symmetric loss function with informative and non-informative priors. In a purely Bayesian setting, the prior distribution represents the insurer’s prior belief about the insured’s risk level after collection of the insured’s data at the end of the period. However, the explicit form of the Bayesian premium in the case when the prior is not a member of the exponential family could be quite difficult to obtain as it involves a number of integrations which are not analytically solvable. The paper finds a solution to this problem by deriving this estimator using numerical approximation (Lindley approximation) which is one of the suitable approximation methods for solving such problems, it approaches the ratio of the integrals as a whole and produces a single numerical result. Simulation study using Monte Carlo method is then performed to evaluate this estimator and mean squared error technique is made to compare the Bayesian premium estimator under the above loss functions.

Keywords: bayesian estimator, credibility theory, entropy loss, monte carlo simulation

Procedia PDF Downloads 298

Authors: Alfred L. Guiffrida

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A review of the literature on supply chain delivery models which use delivery windows to measure delivery performance is presented. The review herein serves to meet the following objectives: (i) provide a synthesis of previously published literature on supply chain delivery performance models, (ii) provide in one paper a consolidation of research that can serve as a single source to keep researchers up to date with the research developments in supply chain delivery models, and (iii) identify gaps in the modeling of supply chain delivery performance which could stimulate new research agendas.

Keywords: delivery performance, delivery window, supply chain delivery models, supply chain performance

Procedia PDF Downloads 387

Authors: David Gligor

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The purpose of this study was to build on Fisher's (1997) seminal article. First, it sought to determine how companies can achieve supply chain fit (i.e., match between the products' characteristics and the underlying supply chain design). Second, it attempted to develop a better understanding of how environmental conditions impact the relationship between supply chain fit and performance. The findings indicate that firm supply chain agility allows organizations to quickly adjust the structure of their supply chains and therefore, achieve supply chain fit. In addition, archival and survey data were used to explore the moderating effects of six environmental uncertainty dimensions: munificence, market dynamism, technological dynamism, technical complexity, product diversity, and geographic dispersion. All environmental variables, except technological dynamism, were found to impact the relationship between supply chain fit and firm performance.

Keywords: supply chain fit, environmental uncertainty, supply chain agility, management engineering

Procedia PDF Downloads 563

Authors: Amira Kaddour

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To curb the problem of liquidity in times of financial crises, two cases arise; the Bailout or Bailin, two opposite choices that elicit the analysis of their effect on moral hazard. This paper attempts to empirically analyze the effect of these two types of events on the behavior of investors. For this end, we use the Emerging Market Bonds Index (EMBI-JP Morgan), and its excess of return, to detect the change in the risk premia through a Markov switching model. The results showed the transition to two types of regime and an effect on moral hazard; Bailout is an incentive of moral hazard, Bailin effectiveness remains subject of credibility.

Keywords: Bailout, Bailin, Moral hazard, financial crisis, Markov switching

Procedia PDF Downloads 441

Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Nop Sopipan

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In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.

Keywords: volatility, Markov Regime Switching, forecasting, Baht/USD

Procedia PDF Downloads 266

Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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

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

Procedia PDF Downloads 166

Authors: Asavasereerat K., Teacharsripaitoon T., Tungyingyong P., Charupongrat S., Noppiboon S. Hochareon L., Kitsuban P.

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Third generation of vaccines is based on gene therapy where DNA is introduced into patients. The antigenic or therapeutic proteins encoded from transgenes DNA triggers an immune-response to counteract various diseases. Moreover, DNA vaccine offers the customization of its ability on protection and treatment with high stability. The production of DNA vaccines become of interest. According to USFDA guidance for industry, the recommended limits for impurities from host cell are lower than 1%, and the active conformation homogeneity supercoiled DNA, is more than 80%. Thus, the purification strategy using two-steps chromatography has been established and verified for its robustness. Herein, pVax1/lacZ, a pre-approved USFDA DNA vaccine backbone, was used and transformed into E. coli strain DH5α. Three purification process parameters including sample-loading flow rate, the salt concentration in washing and eluting buffer, were studied and the experiment was designed using response surface method with central composite face-centered (CCF) as a model. The designed range of selected parameters was 10% variation from the optimized set point as a safety factor. The purity in the percentage of supercoiled conformation obtained from each chromatography step, AIEX and HIC, were analyzed by HPLC. The response data were used to establish regression model and statistically analyzed followed by Monte Carlo simulation using SAS JMP. The results on the purity of the product obtained from AIEX and HIC are between 89.4 to 92.5% and 88.3 to 100.0%, respectively. Monte Carlo simulation showed that the pVAX1/lacZ purification process is robust with confidence intervals of 0.90 in range of 90.18-91.00% and 95.88-100.00%, for AIEX and HIC respectively.

Keywords: AIEX, DNA vaccine, HIC, puification, response surface method, robustness

Procedia PDF Downloads 183

Authors: Yiqi Wu, Simon Tait, Andrew Nichols

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Management of UK railway drainage assets is challenging due to the large amounts of historical assets with long asset life cycles. A major concern for asset managers is to maintain the required performance economically and efficiently while complying with the relevant regulation and legislation. As the majority of the drainage assets are buried underground and are often difficult or costly to examine, it is important for asset managers to understand and model the degradation process in order to foresee the upcoming reduction in asset performance and conduct proactive maintenance accordingly. In this research, a Markov chain approach is used to model the deterioration process of rail drainage assets. The study is based on historical condition scores and characteristics of drainage assets across the whole railway network in England, Scotland, and Wales. The model is used to examine the effect of various characteristics on the probabilities of degradation, for example, the regional difference in probabilities of degradation, and how material and shape can influence the deterioration process for chambers, channels, and pipes.

Keywords: deterioration, degradation, markov models, probability, railway drainage

Procedia PDF Downloads 191

Authors: Yo Fukutani, Shuji Moriguchi, Takuma Kotani, Terada Kenjiro

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If risk management of the assets owned by companies, risk assessment of real estate portfolio, and risk identification of the entire region are to be implemented, it is necessary to consider simultaneous damage to multiple buildings. In this research, the Sagami Trough earthquake tsunami that could have a significant effect on the Japanese capital region is focused on, and a method is proposed for simultaneous damage assessment using copulas that can take into consideration the correlation of tsunami depths and building damage between two sites. First, the tsunami inundation depths at two sites were simulated by using a nonlinear long-wave equation. The tsunamis were simulated by varying the slip amount (five cases) and the depths (five cases) for each of 10 sources of the Sagami Trough. For each source, the frequency distributions of the tsunami inundation depth were evaluated by using the response surface method. Then, Monte-Carlo simulation was conducted, and frequency distributions of tsunami inundation depth were evaluated at the target sites for all sources of the Sagami Trough. These are marginal distributions. Kendall’s tau for the tsunami inundation simulation at two sites was 0.83. Based on this value, the Gaussian copula, t-copula, Clayton copula, and Gumbel copula (n = 10,000) were generated. Then, the simultaneous distributions of the damage rate were evaluated using the marginal distributions and the copulas. For the correlation of the tsunami inundation depth at the two sites, the expected value hardly changed compared with the case of no correlation, but the damage rate of the ninety-ninth percentile value was approximately 2%, and the maximum value was approximately 6% when using the Gumbel copula.

Keywords: copulas, Monte-Carlo simulation, probabilistic risk assessment, tsunamis

Procedia PDF Downloads 114

Authors: Josip Arneric, Blanka Skrabic Peric

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Forecasting of volatility, i.e. returns fluctuations, has been a topic of interest to portfolio managers, option traders and market makers in order to get higher profits or less risky positions. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most common used models are GARCH type models. As standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance, it is difficult the predict volatility using standard GARCH models. Due to practical limitations of these models different approaches have been proposed in the literature, based on Markov switching models. In such situations models in which the parameters are allowed to change over time are more appropriate because they allow some part of the model to depend on the state of the economy. The empirical analysis demonstrates that Markov switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility for selected emerging markets.

Keywords: emerging markets, Markov switching, GARCH model, transition probabilities

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Authors: Juliza Hidayati, Sawarni Hasibuan

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PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

Procedia PDF Downloads 334

Authors: Chigozirim N. Onwusiribe, Jude A. Mbanasor

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The potato value chain when harnessed can engage numerous youths and aid in the fight against poverty, malnutrition and unemployment. This study seeks to evaluate the level of youth participation in the potato value chain in Nigeria. Specifically, this study will examine the extent of youth participation in potato value chain, analyze the cost, benefits and sustainability of youth participation in the potato value chain, identify the factors that can propel or hinder youth participation in the potato value chain and make recommendations that will result in the increase in youth employment in the potato value chain. This study was conducted in the North Central and South East geopolitical zones of Nigeria. A multi stage sampling procedure was used to select 540 youths from the study areas. Focused group discussions and survey approach was used to elicit the required data. The data were analyzed using statistical and econometric tools. The study revealed that the potato value chain is very profitable.

Keywords: value, chain, potato, youth, enterprise

Procedia PDF Downloads 114

Authors: Khenfer Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

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This paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a human-machine interface with a voice recognition system that allows the operator to teleoperate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands pronounced in two languages: French and Arabic. The obtained recognition rate is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equals 30 dB, in this case; the Arabic speech recognition rate is 69%, and the French speech recognition rate is 80%. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: Arabic speech recognition, Hidden Markov Model (HMM), HTK, noise, TIMIT, voice command

Procedia PDF Downloads 338

Authors: Jaime A. Palma-Mendoza

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A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

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Authors: Sameer Jung Karki, Gokhan Saygili

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The allowable bearing capacity of foundation systems is determined by applying a factor of safety to the ultimate bearing capacity. Conventional ultimate bearing capacity calculations routines are based on deterministic input parameters where the nonuniformity and inhomogeneity of soil and site properties are not accounted for. Hence, the laws of mathematics like probability calculus and statistical analysis cannot be directly applied to foundation engineering. It’s assumed that the Factor of Safety, typically as high as 3.0, incorporates the uncertainty of the input parameters. This factor of safety is estimated based on subjective judgement rather than objective facts. It is an ambiguous term. Hence, a probabilistic analysis of the bearing capacity of an isolated footing on a clayey soil is carried out by using the Monte Carlo Simulation method. This simulated model was compared with the traditional discrete model. It was found out that the bearing capacity of soil was found higher for the simulated model compared with the discrete model. This was verified by doing the sensitivity analysis. As the number of simulations was increased, there was a significant % increase of the bearing capacity compared with discrete bearing capacity. The bearing capacity values obtained by simulation was found to follow a normal distribution. While using the traditional value of Factor of safety 3, the allowable bearing capacity had lower probability (0.03717) of occurring in the field compared to a higher probability (0.15866), while using the simulation derived factor of safety of 1.5. This means the traditional factor of safety is giving us bearing capacity that is less likely occurring/available in the field. This shows the subjective nature of factor of safety, and hence probability method is suggested to address the variability of the input parameters in bearing capacity equations.

Keywords: bearing capacity, factor of safety, isolated footing, montecarlo simulation

Procedia PDF Downloads 155

Authors: Navid Mohammadzadeh, Huy Truong-Ba, Michael Cholette

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The solar tower (ST) plant is a promising technology to exploit large-scale solar irradiation. With thermal energy storage, ST plant has the potential to shift generation to high electricity price periods. However, the size of storage limits the dispatchability of the plant, particularly when it should compete with uncertainty in forecasts of solar irradiation and electricity prices. The purpose of this study is to explore the size of storage when Rolling Horizon Control (RHC) is employed for dispatch scheduling. To this end, RHC is benchmarked against perfect knowledge (PK) forecast and two day-ahead dispatching policies. With optimisation of dispatch planning using PK policy, the optimal achievable profit for a specific size of the storage is determined. A sensitivity analysis using Monte-Carlo simulation is conducted, and the size of storage for RHC and day-ahead policies is determined with the objective of reaching the profit obtained from the PK policy. A case study is conducted for a hypothetical ST plant with thermal storage located in South Australia and intends to dispatch under two market scenarios: 1) fixed price and 2) wholesale spot price. The impact of each individual source of uncertainty on storage size is examined for January and August. The exploration of results shows that dispatching with RH controller reaches optimal achievable profit with ~15% smaller storage compared to that in day-ahead policies. The results of this study may be applied to the CSP plant design procedure.

Keywords: solar tower plant, spot market, thermal storage system, optimized dispatch planning, sensitivity analysis, Monte Carlo simulation

Procedia PDF Downloads 97

Authors: Luis Lara-Valencia, Mateo Ramirez-Acevedo, Daniel Caicedo, Jose Brito, Yosef Farbiarz

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Controlling wind-induced vibrations as well as aerodynamic forces, is an essential part of the structural design of tall buildings in order to guarantee the serviceability limit state of the structure. This paper presents a numerical investigation on the optimal design parameters of a Tuned Inerter Damper (TID) based system for the control of wind-induced vibration in tall buildings. The control system is based on the conventional TID, with the main difference that its location is changed from the ground level to the last two story-levels of the structural system. The TID tuning procedure is based on an evolutionary cultural algorithm in which the optimum design variables defined as the frequency and damping ratios were searched according to the optimization criteria of minimizing the root mean square (RMS) response of displacements at the nth story of the structure. A Monte Carlo simulation was used to represent the dynamic action of the wind in the time domain in which a time-series derived from the Davenport spectrum using eleven harmonic functions with randomly chosen phase angles was reproduced. The above-mentioned methodology was applied on a case-study derived from a 37-story prestressed concrete building with 144 m height, in which the wind action overcomes the seismic action. The results showed that the optimally tuned TID is effective to reduce the RMS response of displacements up to 25%, which demonstrates the feasibility of the system for the control of wind-induced vibrations in tall buildings.

Keywords: evolutionary cultural algorithm, Monte Carlo simulation, tuned inerter damper, wind-induced vibrations

Procedia PDF Downloads 113

Authors: Tiantian Ma

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The district of Doumen, Zhuhai has a sophisticated seabass value chain. However, unlike typical Global Value Chain (GVC) industries, the seabass value chain in Doumen is highly domestic both in terms of production and consumption. Still, since the highly-industrialized and capital-intensive industry involves many off-farm segments in both upstream and downstream, this paper will be utilizing the method of value chain analysis. To be specific, the paper will concentrate on two research goals: 1) the value chain mapping of the seabass industry, such as identifying actors in the hatchery, fish feed, fishponds, processing, logistics, and distribution, 2) the SWOT analysis of the seabass industry in Doumen, including incompetence of the waste disposal, the strategy of marketing, and the supportive role of the government, etc. In general, the seabass industry in Doumen is a sophisticated but not yet comprehensive value chain. It has achieved a lot in industrializing aqua-food products and fostering development, but there are still improvements that could be carried out, such as upholding environmental sustainability and promoting the brand better.

Keywords: agricultural value chain, fish farming, regional development, SWOT analysis, value chain mapping

Procedia PDF Downloads 116

Authors: Ozan Yavuz Baytemir, Ender Cigeroglu, Gokhan Osman Ozgen

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Vibration is an important issue in the design of various components of aerospace, marine and vehicular applications. In order not to lose the components’ function and operational performance, vibration isolation design involving the optimum isolator properties selection and isolator positioning processes appear to be a critical study. Knowing the growing need for the vibration isolation system design, this paper aims to present two types of software capable of implementing modal analysis, response analysis for both random and harmonic types of excitations, static deflection analysis, Monte Carlo simulations in addition to study of parameter and location optimization for different types of isolation problem scenarios. Investigating the literature, there is no such study developing a software-based tool that is capable of implementing all those analysis, simulation and optimization studies in one platform simultaneously. In this paper, the theoretical system model is generated for a 6-DOF rigid body. The vibration isolation system of any mechanical structure is able to be optimized using hybrid method involving both global search and gradient-based methods. Defining the optimization design variables, different types of optimization scenarios are listed in detail. Being aware of the need for a user friendly vibration isolation problem solver, two types of graphical user interfaces (GUIs) are prepared and verified using a commercial finite element analysis program, Ansys Workbench 14.0. Using the analysis and optimization capabilities of those GUIs, a real application used in an air-platform is also presented as a case study at the end of the paper.

Keywords: hybrid optimization, Monte Carlo simulation, multi-degree-of-freedom system, parameter optimization, location optimization, passive vibration isolation analysis

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Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

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In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control

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Authors: Lie-Fen Lin, Tzu-Hsuan Lin, Ching-Heng Lin

Abstract:

Hospice care for terminally ill patients provides not only a better quality of life but also cost-saving benefits. However, the utilization of home-based hospice care (HBH care) remains low even for countries covered by National Health Insurance (NHI) programs in Taiwan. In the current commercial insurance policy, only hospital-based hospice benefits were covered. It may have an influence on the insureds chosen to receive end-of-life care in a hospitalized manner. Thus, how to propose a feasible method to advocate HBH care utilization rate of public health policies is an important issue. A total of 130,219 cancer decedents in the year 2011-2013 from the National Health Insurance Research Database (NHIRD) in Taiwan were included in this study. By adding a day volume pays benefits of HBH care as a commercial insurance rider, will provide alternative benefits for the insureds. A multiple-state Markov chain model was incorporated to estimate the transition intensities of patients in different states at the end of their lives (Non-hospice, HBH, hospital-based hospice), and the premiums were estimated. HBH care insurance benefits provide financial support and reduce the burden of care for patients. The rate-making of this product is very sensitive while the utilization rate is rising, especially for high ages. The proposed HBH care insurance is a feasible way to reduce the financial burden, enhance the care quality and family satisfaction of insureds. Meanwhile, insurance companies can participate in advocating a good medical policy to enhance the social image. In addition, the medical costs of NHI can reduce effectively.

Keywords: home-based hospice care, commercial insurance, Markov chain model, the day volume pays

Procedia PDF Downloads 186

Authors: Kittipong Tissayakorn, Fumio Akagi, Yu Song

Abstract:

Manufacturers have been exploring innovative strategies to achieve and sustain competitive advantages as they face a new era of intensive global competition. Such strategy is known as Supply Chain Management (SCM), which has gained a tremendous amount of attention from both researchers and practitioners over the last decade. Supply chain management (SCM) is considered as the most popular operating strategy for improving organizational competitiveness in the twenty-first century. It has attracted a lot of attention recently due to its role involving all of the activities in industrial organizations, ranging from raw material procurement to final product delivery to customers. Well-designed supply chain systems can substantially improve efficiency and product quality, and eventually enhance customer satisfaction and profitability. In this paper, a manufacturing engineering perspective on supply chain integration is presented. Research issues discussed include the product and process design for the supply chain, design evaluation of manufacturing in the supply chain, agent-based techniques for supply chain integration, intelligent information for sharing across the supply chain, and a development of standards for product, process, and production data exchange to facilitate electronic commerce. The objective is to provide guidelines and references for manufacturing engineers and researchers interested in supply chain integration.

Keywords: supply chain, supply chain management, supply chain integration, manufacturing industries

Procedia PDF Downloads 315

Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

Abstract:

In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

Procedia PDF Downloads 323