Probability Theory. Stochastic Processes And Their Applications Probabilistic Analysis Of Some Queueing And Inventory Models

In this thesis we attempt to make a probabilistic analysis of some physically realizable, though complex, storage and queueing models. It is essentially a mathematical study of the stochastic processes underlying these models. Our aim is to have an improved understanding of the behaviour of such models, that may widen their applicability. Different inventory systems with randon1 lead times, vacation to the server, bulk demands, varying ordering levels, etc. are considered. Also we study some finite and infinite capacity queueing systems with bulk service and vacation to the server and obtain the transient solution in certain cases. Each chapter in the thesis is provided with self introduction and some important references

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Planning and Scheduling Decisions in Supply Chains with Multiple Supply Modes: An Integrated Approach

We address the problem of jointly determining shipment planning and scheduling decisions with the presence of multiple shipment modes. We consider long lead time, less expensive sea shipment mode, and short lead time but expensive air shipment modes. Existing research on multiple shipment modes largely address the short term scheduling decisions only. Motivated by an industrial problem where planning decisions are independent of the scheduling decisions, we investigate the benefits of integrating the two sets of decisions. We develop sequence of mathematical models to address the planning and scheduling decisions. Preliminary computational results indicate improved performance of the integrated approach over some of the existing policies used in real-life situations.

Applying the Lessons of “Lean Now” to Transform the US Aerospace Enterprise

Lean is common sense and good business sense. As organizations grow and become more successful, they begin to lose insight into the basic truths of what made them successful. Organizations have to deal with more and more issues that may not have anything to do with directly providing products or services to their customers. Lean is a holistic management approach that brings the focus of the organization back to providing value to the customer. In August 2002, Mrs. Darleen Druyun, the Principal Deputy to the Assistant Secretary of the Air Force for Acquisition and government co-chairperson of the Lean Aerospace Initiative (LAI), decided it was time for Air Force acquisitions to embrace the concepts of lean. At her request, the LAI Executive Board developed a concept and methodology to employ lean into the Air Force’s acquisition culture and processes. This was the birth of the “Lean Now” initiative. An enterprise-wide approach was used, involving Air Force System Program Offices (SPOs), aerospace industry, and several Department of Defense agencies. The aim of Lean Now was to focus on the process interfaces between these “enterprise” stakeholders to eliminate barriers that impede progress. Any best practices developed would be institutionalized throughout the Air Force and the Department of Defense (DoD). The industry members of LAI agreed to help accelerate the government-industry transformation by donating lean Subject Matter Experts (SMEs) to mentor, train, and facilitate the lean events of each enterprise. Currently, the industry SMEs and the Massachusetts Institute of Technology are working together to help the Air Force develop its own lean infrastructure of training courses and Air Force lean SMEs. The first Lean Now programs were the F/A-22, Global Hawk, and F-16. Each program focused on specific acquisition processes. The F/A-22 focused on the Test and Evaluation process; the Global Hawk focused on Evolutionary Acquisitions; and the F-16 focused on improving the Contract Closeout process. Through lean, each enterprise made many significant improvements. The F/A-22 was able to reduce its Operational Flight Plan (OFP) Preparation and Load process time of 2 to 3 months down to 7 hours. The Global Hawk developed a new production plan that increases the annual production of its Integrated Sensor Suite from 3 per year to 6 per year. The F-16 enterprise generated and is working 12 initiatives that could result in a contract closeout cycle time reduction of 3 to 7 years. Each enterprise continues to generate more lean initiatives that focus on other areas and processes within their respective enterprises.

Sugammadex: su eficacia y seguridad en la reversión selectiva del vecuronio

Introducción: En 1979, con la monitorización del uso rutinario de los relajantes neuromusculares, se determinó incidencia en la relajación neuromuscular residual del 45%, con múltiples complicaciones respiratorias que incrementan la estancia hospitalaria. No es conocida la eficacia y seguridad del manejo del vecuronio y su reversión con el uso del sugammadex dentro del manejo rutinario de anestesia. Métodos: Revisión sistemática de artículos sobre el comportamiento del sugammadex cuando se realiza reversión para el efecto del vecuronio, por ser la primera droga que ha demostrado eficacia y seguridad frente a relajantes musculares no despolarizantes esteroideos, que ayuda a prevenir bloqueo residual en el posoperatorio. Resultados: Búsqueda en las bases de datos de EMBASE, EBSCO y MEDLINE y Pubmed (desde enero 2000-diciembre 2012), con palabras MeSH, sugammadex, vecuronium, binding reversal agents, neuromuscular blocking agents; artículos en idioma inglés de estudios clínicos controlados en pacientes humanos adultos en los cuales el sugammadex fue comparado con placebo u otro medicamento. Se aprecia disminución del tiempo de recuperación de la relajación neuromuscular en el bloqueo moderado con un rango de 1,5 a 2,3min con el sugammadex vs 18,9 a 66,2min con la neostigmine y en un bloqueo profundo desde 35,5-68,4min, con dosis de 0,5mgrs/kg de sugammadex hasta 1,4-1,7min con 8mgrs/kg. Discusión: Resultados favorables en el suministro de dosis mayores a 2mgrs/kg en pacientes que presentaban bloqueo neuromuscular moderado y mayores de 4mgrs/kg en bloqueo neuromuscular profundo. Existe necesidad de nuevos estudios clínicos que soporten estos hallazgos. Conclusión: La evidencia sugiere que sí existe una adecuada reversión de la relajación neuromuscular del vecuronio con el uso de sugammadex a 2mgrs/kg, con disminución importante del tiempo y mayor recuperación del paciente sin presencia de relajación residual.

Las TIC en la administración de la cadena de suministro y su incidencia en el desempeño operacional

Las tecnologías de la información han empezado a ser un factor importante a tener en cuenta en cada uno de los procesos que se llevan a cabo en la cadena de suministro. Su implementación y correcto uso otorgan a las empresas ventajas que favorecen el desempeño operacional a lo largo de la cadena. El desarrollo y aplicación de software han contribuido a la integración de los diferentes miembros de la cadena, de tal forma que desde los proveedores hasta el cliente final, perciben beneficios en las variables de desempeño operacional y nivel de satisfacción respectivamente. Por otra parte es importante considerar que su implementación no siempre presenta resultados positivos, por el contrario dicho proceso de implementación puede verse afectado seriamente por barreras que impiden maximizar los beneficios que otorgan las TIC.

Business cycle asymmentries: An investment cost approach

In this paper, investment cost asymmetry is introduced in order to test wheter this kind of asymmetry can account for asymmetries in business cycles. By using a smooth transition function, asymmetric investment cost is modeled and introduced in a canonical RBC model. Simulations of the model with Perturbations Method (PM) are very close to simulations through Parameterized Expectations Algorithm (PEA), which allows the use of the former for the sake of time reduction and computational costs. Both symmetric and asymmetric models were simulated and compared. Deterministic and stochastic impulse-response excersices revealed that it is possible to adequately reproduce asymmetric business cycles by modeling asymmetric investment costs. Simulations also showed that higher order moments are insu_cient to detect asymmetries. Instead, methods such as Generalized Impulse Response Analysis (GIRA) and Nonlinear Econometrics prove to be more e_cient diagnostic tools.

The predictability of extratropical storm tracks and the sensitivity of their prediction to the observing system

A new method for assessing forecast skill and predictability that involves the identification and tracking of extratropical cyclones has been developed and implemented to obtain detailed information about the prediction of cyclones that cannot be obtained from more conventional analysis methodologies. The cyclones were identified and tracked along the forecast trajectories, and statistics were generated to determine the rate at which the position and intensity of the forecasted storms diverge from the analyzed tracks as a function of forecast lead time. The results show a higher level of skill in predicting the position of extratropical cyclones than the intensity. They also show that there is potential to improve the skill in predicting the position by 1 - 1.5 days and the intensity by 2 - 3 days, via improvements to the forecast model. Further analysis shows that forecasted storms move at a slower speed than analyzed storms on average and that there is a larger error in the predicted amplitudes of intense storms than the weaker storms. The results also show that some storms can be predicted up to 3 days before they are identified as an 850-hPa vorticity center in the analyses. In general, the results show a higher level of skill in the Northern Hemisphere (NH) than the Southern Hemisphere (SH); however, the rapid growth of NH winter storms is not very well predicted. The impact that observations of different types have on the prediction of the extratropical cyclones has also been explored, using forecasts integrated from analyses that were constructed from reduced observing systems. A terrestrial, satellite, and surface-based system were investigated and the results showed that the predictive skill of the terrestrial system was superior to the satellite system in the NH. Further analysis showed that the satellite system was not very good at predicting the growth of the storms. In the SH the terrestrial system has significantly less skill than the satellite system, highlighting the dominance of satellite observations in this hemisphere. The surface system has very poor predictive skill in both hemispheres.

Potential predictability of rapid changes in the Atlantic meridional overturning circulation

We explore the potential predictability of rapid changes in the Atlantic meridional overturning circulation (MOC) using a coupled global climate model (HadCM3). Rapid changes in the temperature and salinity of surface water in the Nordic Seas, and the flow of dense water through Denmark Strait, are found to be precursors to rapid changes in the model's MOC, with a lead time of around 10 years. The mechanism proposed to explain this potential predictability relies on the development of density anomalies in the Nordic Seas which propagate through Denmark Strait and along the deep western boundary current, affecting the overturning. These rapid changes in the MOC have significant, and widespread, climate impacts which are potentially predictable a few years ahead. Whilst the flow through Denmark Strait is too strong in HadCM3, the presence of such potential predictability motivates the monitoring of water properties in the Nordic Seas and Denmark Strait.

Coupled simulations of the Indian monsoon intraseasonal oscillation using a fine-resolution mixed-layer ocean model

The intraseasonal variability (ISV) of the Indian summer monsoon is dominated by a 30–50 day oscillation between “active” and “break” events of enhanced and reduced rainfall over the subcontinent, respectively. These organized convective events form in the equatorial Indian Ocean and propagate north to India. Atmosphere–ocean coupled processes are thought to play a key role the intensity and propagation of these events. A high-resolution, coupled atmosphere–mixed-layer-oceanmodel is assembled: HadKPP. HadKPP comprises the Hadley Centre Atmospheric Model (HadAM3) and the K Profile Parameterization (KPP) mixed-layer ocean model. Following studies that upper-ocean vertical resolution and sub-diurnal coupling frequencies improve the simulation of ISV in SSTs, KPP is run at 1 m vertical resolution near the surface; the atmosphere and ocean are coupled every three hours. HadKPP accurately simulates the 30–50 day ISV in rainfall and SSTs over India and the Bay of Bengal, respectively, but suffers from low ISV on the equator. This is due to the HadAM3 convection scheme producing limited ISV in surface fluxes. HadKPP demonstrates little of the observed northward propagation of intraseasonal events, producing instead a standing oscillation. The lack of equatorial ISV in convection in HadAM3 constrains the ability of KPP to produce equatorial SST anomalies, which further weakens the ISV of convection. It is concluded that while atmosphere–ocean interactions are undoubtedly essential to an accurate simulation of ISV, they are not a panacea for model deficiencies. In regions where the atmospheric forcing is adequate, such as the Bay of Bengal, KPP produces SST anomalies that are comparable to the Tropical Rainfall Measuring Mission Microwave Imager (TMI) SST analyses in both their magnitude and their timing with respect to rainfall anomalies over India. HadKPP also displays a much-improved phase relationship between rainfall and SSTs over a HadAM3 ensemble forced by observed SSTs, when both are compared to observations. Coupling to mixed-layer models such as KPP has the potential to improve operational predictions of ISV, particularly when the persistence time of SST anomalies is shorter than the forecast lead time.

How well does the ECMWF Ensemble Prediction System predict blocking?

Forecasting atmospheric blocking is one of the main problems facing medium-range weather forecasters in the extratropics. The European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) provides an excellent basis for medium-range forecasting as it provides a number of different possible realizations of the meteorological future. This ensemble of forecasts attempts to account for uncertainties in both the initial conditions and the model formulation. Since 18 July 2000, routine output from the EPS has included the field of potential temperature on the potential vorticity (PV) D 2 PV units (PVU) surface, the dynamical tropopause. This has enabled the objective identification of blocking using an index based on the reversal of the meridional potential-temperature gradient. A year of EPS probability forecasts of Euro-Atlantic and Pacific blocking have been produced and are assessed in this paper, concentrating on the Euro-Atlantic sector. Standard verification techniques such as Brier scores, Relative Operating Characteristic (ROC) curves and reliability diagrams are used. It is shown that Euro-Atlantic sector-blocking forecasts are skilful relative to climatology out to 10 days, and are more skilful than the deterministic control forecast at all lead times. The EPS is also more skilful than a probabilistic version of this deterministic forecast, though the difference is smaller. In addition, it is shown that the onset of a sector-blocking episode is less well predicted than its decay. As the lead time increases, the probability forecasts tend towards a model climatology with slightly less blocking than is seen in the real atmosphere. This small under-forecasting bias in the blocking forecasts is possibly related to a westerly bias in the ECMWF model. Copyright © 2003 Royal Meteorological Society

An event-based approach to validating solar wind speed predictions: high-speed enhancements in the Wang-Sheeley-Arge model

One of the primary goals of the Center for Integrated Space Weather Modeling (CISM) effort is to assess and improve prediction of the solar wind conditions in near‐Earth space, arising from both quasi‐steady and transient structures. We compare 8 years of L1 in situ observations to predictions of the solar wind speed made by the Wang‐Sheeley‐Arge (WSA) empirical model. The mean‐square error (MSE) between the observed and model predictions is used to reach a number of useful conclusions: there is no systematic lag in the WSA predictions, the MSE is found to be highest at solar minimum and lowest during the rise to solar maximum, and the optimal lead time for 1 AU solar wind speed predictions is found to be 3 days. However, MSE is shown to frequently be an inadequate “figure of merit” for assessing solar wind speed predictions. A complementary, event‐based analysis technique is developed in which high‐speed enhancements (HSEs) are systematically selected and associated from observed and model time series. WSA model is validated using comparisons of the number of hit, missed, and false HSEs, along with the timing and speed magnitude errors between the forecasted and observed events. Morphological differences between the different HSE populations are investigated to aid interpretation of the results and improvements to the model. Finally, by defining discrete events in the time series, model predictions from above and below the ecliptic plane can be used to estimate an uncertainty in the predicted HSE arrival times.

Northern hemisphere snow: measurement, modelling and predictability

Northern hemisphere snow water equivalent (SWE) distribution from remote sensing (SSM/I), the ERA40 reanalysis product and the HadCM3 general circulation model are compared. Large differences are seen in the February climatologies, particularly over Siberia. The SSM/I retrieval algorithm may be overestimating SWE in this region, while comparison with independent runoff estimates suggest that HadCM3 is underestimating SWE. Treatment of snow grain size and vegetation parameterizations are concerns with the remotely sensed data. For this reason, ERA40 is used as `truth' for the following experiments. Despite the climatology differences, HadCM3 is able to reproduce the distribution of ERA40 SWE anomalies when assimilating ERA40 anomaly fields of temperature, sea level pressure, atmospheric winds and ocean temperature and salinity. However when forecasts are released from these assimilated initial states, the SWE anomaly distribution diverges rapidly from that of ERA40. No predictability is seen from one season to another. Strong links between European SWE distribution and the North Atlantic Oscillation (NAO) are seen, but forecasts of this index by the assimilation scheme are poor. Longer term relationships between SWE and the NAO, and SWE and the El Ni\~no-Southern Oscillation (ENSO) are also investigated in a multi-century run of HadCM3. SWE is impacted by ENSO in the Himalayas and North America, while the NAO affects SWE in North America and Europe. While significant connections with the NAO index were only present in DJF (and to an extent SON), the link between ENSO and February SWE distribution was seen to exist from the previous JJA ENSO index onwards. This represents a long lead time for SWE prediction for hydrological applications such as flood and wildfire forecasting. Further work is required to develop reliable large scale observation-based SWE datasets with which to test these model-derived connections.

Forecast calibration and combination: a simple Bayesian approach for ENSO

This study presents a new simple approach for combining empirical with raw (i.e., not bias corrected) coupled model ensemble forecasts in order to make more skillful interval forecasts of ENSO. A Bayesian normal model has been used to combine empirical and raw coupled model December SST Niño-3.4 index forecasts started at the end of the preceding July (5-month lead time). The empirical forecasts were obtained by linear regression between December and the preceding July Niño-3.4 index values over the period 1950–2001. Coupled model ensemble forecasts for the period 1987–99 were provided by ECMWF, as part of the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction (DEMETER) project. Empirical and raw coupled model ensemble forecasts alone have similar mean absolute error forecast skill score, compared to climatological forecasts, of around 50% over the period 1987–99. The combined forecast gives an increased skill score of 74% and provides a well-calibrated and reliable estimate of forecast uncertainty.

Verification of cloud-fraction forecasts

Cloud radar and lidar can be used to evaluate the skill of numerical weather prediction models in forecasting the timing and placement of clouds, but care must be taken in choosing the appropriate metric of skill to use due to the non- Gaussian nature of cloud-fraction distributions. We compare the properties of a number of different verification measures and conclude that of existing measures the Log of Odds Ratio is the most suitable for cloud fraction. We also propose a new measure, the Symmetric Extreme Dependency Score, which has very attractive properties, being equitable (for large samples), difficult to hedge and independent of the frequency of occurrence of the quantity being verified. We then use data from five European ground-based sites and seven forecast models, processed using the ‘Cloudnet’ analysis system, to investigate the dependence of forecast skill on cloud fraction threshold (for binary skill scores), height, horizontal scale and (for the Met Office and German Weather Service models) forecast lead time. The models are found to be least skillful at predicting the timing and placement of boundary-layer clouds and most skilful at predicting mid-level clouds, although in the latter case they tend to underestimate mean cloud fraction when cloud is present. It is found that skill decreases approximately inverse-exponentially with forecast lead time, enabling a forecast ‘half-life’ to be estimated. When considering the skill of instantaneous model snapshots, we find typical values ranging between 2.5 and 4.5 days. Copyright c 2009 Royal Meteorological Society