Studies Using Computer Simulation Models to Solve Problems Related to Logistics Terminals

This thesis deals with the use of simulation as a problem-solving tool to solve a few logistic system related problems. More specifically it relates to studies on transport terminals. Transport terminals are key elements in the supply chains of industrial systems. One of the problems related to use of simulation is that of the multiplicity of models needed to study different problems. There is a need for development of methodologies related to conceptual modelling which will help reduce the number of models needed. Three different logistic terminal systems Viz. a railway yard, container terminal of apart and airport terminal were selected as cases for this study. The standard methodology for simulation development consisting of system study and data collection, conceptual model design, detailed model design and development, model verification and validation, experimentation, and analysis of results, reporting of finding were carried out. We found that models could be classified into tightly pre-scheduled, moderately pre-scheduled and unscheduled systems. Three types simulation models( called TYPE 1, TYPE 2 and TYPE 3) of various terminal operations were developed in the simulation package Extend. All models were of the type discrete-event simulation. Simulation models were successfully used to help solve strategic, tactical and operational problems related to three important logistic terminals as set in our objectives. From the point of contribution to conceptual modelling we have demonstrated that clubbing problems into operational, tactical and strategic and matching them with tightly pre-scheduled, moderately pre-scheduled and unscheduled systems is a good workable approach which reduces the number of models needed to study different terminal related problems.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Factorial Hidden Markov Models

We present a framework for learning in hidden Markov models with distributed state representations. Within this framework, we derive a learning algorithm based on the Expectation--Maximization (EM) procedure for maximum likelihood estimation. Analogous to the standard Baum-Welch update rules, the M-step of our algorithm is exact and can be solved analytically. However, due to the combinatorial nature of the hidden state representation, the exact E-step is intractable. A simple and tractable mean field approximation is derived. Empirical results on a set of problems suggest that both the mean field approximation and Gibbs sampling are viable alternatives to the computationally expensive exact algorithm.

Transition between metadata models: approach based on the use open source software

This article shows the work developed for adapting metadata conform to the official Colombian metadata standard NTC 4611 to the international standard ISO 19115. CatMDedit, an open source metadata editor, is used in this task. CatMDedit is able of import variants of CSDGM such as NTC 4611 and export to the stable version of ISO 19139 (the XML implementation model of ISO 19115)

Aspectes metodològics i aplicacions de la modelització del temps de supervivència multivariant mitjançant models mixtes

Els estudis de supervivència s'interessen pel temps que passa des de l'inici de l'estudi (diagnòstic de la malaltia, inici del tractament,...) fins que es produeix l'esdeveniment d'interès (mort, curació, millora,...). No obstant això, moltes vegades aquest esdeveniment s'observa més d'una vegada en un mateix individu durant el període de seguiment (dades de supervivència multivariant). En aquest cas, és necessari utilitzar una metodologia diferent a la utilitzada en l'anàlisi de supervivència estàndard. El principal problema que l'estudi d'aquest tipus de dades comporta és que les observacions poden no ser independents. Fins ara, aquest problema s'ha solucionat de dues maneres diferents en funció de la variable dependent. Si aquesta variable segueix una distribució de la família exponencial s'utilitzen els models lineals generalitzats mixtes (GLMM); i si aquesta variable és el temps, variable amb una distribució de probabilitat no pertanyent a aquesta família, s'utilitza l'anàlisi de supervivència multivariant. El que es pretén en aquesta tesis és unificar aquests dos enfocs, és a dir, utilitzar una variable dependent que sigui el temps amb agrupacions d'individus o d'observacions, a partir d'un GLMM, amb la finalitat d'introduir nous mètodes pel tractament d'aquest tipus de dades.

Avaluació de la toxicitat de metalls pesants i arsènic en diferents models biològics

En aquest estudi, la toxicitat de diversos metalls pesants i l'arsènic va ser analitzada utilitzant diferents models biològics. En la primera part d'aquest treball, el bioassaig de toxicitat Microtox, el qual està basat en la variació de l'emissió lumínica del bacteri luminiscent Vibrio fischeri, va ser utilitzat per establir les corbes dosi-resposta de diferents elements tòxics com el Zn(II), Pb(II), Cu(II), Hg(II), Ag(I), Co(II), Cd(II), Cr(VI), As(V) i As(III) en solucions aquoses. Els experiments es varen portar a terme a pH 6.0 i 7.0 per tal de mostrar que el pH pot influir en la toxicitat final mesurada d'alguns metalls degut als canvis relacionats amb la seva especiació química. Es varen trobar diferents tipus de corbes dosi-resposta depenent del metall analitzat i el pH del medi. En el cas de l'arsènic, l'efecte del pH en la toxicitat de l'arsenat i l'arsenit es va investigar utilitzant l'assaig Microtox en un rang de pHs comprès entre pH 5.0 i 9.0. Els valors d'EC50 determinats per l'As(V) disminueixen, reflectint un augment de la toxicitat, a mesura que el pH de la solució augmenta mentre que, en el cas de l'As(III), els valors d'EC50 quasi bé no varien entre pH 6.0 i 8.0 i només disminueixen a pH 9.0. HAsO42- i H2AsO3- es varen definir com les espècies més tòxiques. Així mateix, una anàlisi estadística va revelar un efecte antagònic entre les espècies químiques d'arsenat que es troben conjuntament a pH 6.0 i 7.0. D'altra banda, els resultats de dos mètodes estadístics per predir la toxicitat i les possibles interaccions entre el Co(II), Cd(II), Cu(II), Zn(II) i Pb(II) en mescles binàries equitòxiques es varen comparar amb la toxicitat observada sobre el bacteri Vibrio fischeri. L'efecte combinat d'aquests metalls va resultar ser antagònic per les mescles de Co(II)-Cd(II), Cd(II)-Zn(II), Cd(II)-Pb(II) i Cu(II)-Pb(II), sinèrgic per Co(II)-Cu(II) i Zn(II)-Pb(II) i additiu en els altres casos, revelant un patró complex de possibles interaccions. L'efecte sinèrgic de la combinació Co(II)-Cu(II) i la forta disminució de la toxicitat del Pb(II) quan es troba en presència de Cd(II) hauria de merèixer més atenció quan s'estableixen les normatives de seguretat ambiental. La sensibilitat de l'assaig Microtox també va ser determinada. Els valors d'EC20, els quals representen la toxicitat llindar mesurable, varen ser determinats per cada element individualment i es va veure que augmenten de la següent manera: Pb(II) < Ag(I) < Hg(II)  Cu(II) < Zn(II) < As(V) < Cd(II)  Co(II) < As(III) < Cr(VI). Aquests valors es varen comparar amb les concentracions permeses en aigues residuals industrials establertes per la normativa oficial de Catalunya (Espanya). L'assaig Microtox va resultar ser suficientment sensible per detectar els elements assajats respecte a les normes oficials referents al control de la contaminació, excepte en el cas del cadmi, mercuri, arsenat, arsenit i cromat. En la segona part d'aquest treball, com a resultats complementaris dels resultats previs obtinguts utilitzant l'assaig de toxicitat aguda Microtox, els efectes crònics del Cd(II), Cr(VI) i As(V) es varen analitzar sobre la taxa de creixement i la viabilitat en el mateix model biològic. Sorprenentment, aquests productes químics nocius varen resultar ser poc tòxics per aquest bacteri quan es mesura el seu efecte després de temps d'exposició llargs. Tot i això, en el cas del Cr(VI), l'assaig d'inhibició de la viabilitat va resultar ser més sensible que l'assaig de toxicitat aguda Microtox. Així mateix, també va ser possible observar un clar fenomen d'hormesis, especialment en el cas del Cd(II), quan s'utilitza l'assaig d'inhibició de la viabilitat. A més a més, diversos experiments es varen portar a terme per intentar explicar la manca de toxicitat de Cr(VI) mostrada pel bacteri Vibrio fischeri. La resistència mostrada per aquest bacteri podria ser atribuïda a la capacitat d'aquest bacteri de convertir el Cr(VI) a la forma menys tòxica de Cr(III). Es va trobar que aquesta capacitat de reducció depèn de la composició del medi de cultiu, de la concentració inicial de Cr(VI), del temps d'incubació i de la presència d'una font de carboni. En la tercera part d'aquest treball, la línia cel·lular humana HT29 i cultius primaris de cèl·lules sanguínies de Sparus sarba es varen utilitzar in vitro per detectar la toxicitat llindar de metalls mesurant la sobreexpressió de proteines d'estrès. Extractes de fangs precedents de diverses plantes de tractament d'aigues residuals i diferents metalls, individualment o en combinació, es varen analitzar sobre cultius cel·lulars humans per avaluar el seu efecte sobre la taxa de creixement i la capacitat d'induir la síntesi de les proteïnes Hsp72 relacionades amb l'estrès cel·lular. No es varen trobar efectes adversos significatius quan els components s'analitzen individualment. Nogensmenys, quan es troben conjuntament, es produeix un afecte advers sobre tan la taxa de creixement com en l'expressió de proteins d'estrès. D'altra banda, cèl·lules sanguínies procedents de Sparus sarba es varen exposar in vitro a diferents concentracions de cadmi, plom i crom. La proteïna d'estrès HSP70 es va sobreexpressar significativament després de l'exposició a concentracions tan febles com 0.1 M. Sota les nostres condicions de treball, no es va evidenciar una sobreexpressió de metal·lotioneïnes. Nogensmenys, les cèl·lules sanguínies de peix varen resultar ser un model biològic interessant per a ser utilitzat en anàlisis de toxicitat. Ambdós models biològics varen resultar ser molt adequats per a detectar acuradament la toxicitat produïda per metalls. En general, l'avaluació de la toxicitat basada en l'anàlisi de la sobreexpressió de proteïnes d'estrès és més sensible que l'avaluació de la toxicitat realitzada a nivell d'organisme. A partir dels resultats obtinguts, podem concloure que una bateria de bioassaigs és realment necessària per avaluar acuradament la toxicitat de metalls ja que existeixen grans variacions entre els valors de toxicitat obtinguts emprant diferents organismes i molts factors ambientals poden influir i modificar els resultats obtinguts.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

Past, present and future precipitation in the Middle East: insights from models and observations

Anthropogenic changes in precipitation pose a serious threat to society—particularly in regions such as the Middle East that already face serious water shortages. However, climate model projections of regional precipitation remain highly uncertain. Moreover, standard resolution climate models have particular difficulty representing precipitation in the Middle East, which is modulated by complex topography, inland water bodies and proximity to the Mediterranean Sea. Here we compare precipitation changes over the twenty-first century against both millennial variability during the Holocene and interannual variability in the present day. In order to assess the climate model and to make consistent comparisons, this study uses new regional climate model simulations of the past, present and future in conjunction with proxy and historical observations. We show that the pattern of precipitation change within Europe and the Middle East projected by the end of the twenty-first century has some similarities to that which occurred during the Holocene. In both cases, a poleward shift of the North Atlantic storm track and a weakening of the Mediterranean storm track appear to cause decreased winter rainfall in southern Europe and the Middle East and increased rainfall further north. In contrast, on an interannual time scale, anomalously dry seasons in the Middle East are associated with a strengthening and focusing of the storm track in the north Mediterranean and hence wet conditions throughout southern Europe.

A comparison of three canopy interception models for a leafless mixed deciduous forest stand in the eastern United States

Canopy interception of incident precipitation is a critical component of the forest water balance during each of the four seasons. Models have been developed to predict precipitation interception from standard meteorological variables because of acknowledged difficulty in extrapolating direct measurements of interception loss from forest to forest. No known study has compared and validated canopy interception models for a leafless deciduous forest stand in the eastern United States. Interception measurements from an experimental plot in a leafless deciduous forest in northeastern Maryland (39°42'N, 75°5'W) for 11 rainstorms in winter and early spring 2004/05 were compared to predictions from three models. The Mulder model maintains a moist canopy between storms. The Gash model requires few input variables and is formulated for a sparse canopy. The WiMo model optimizes the canopy storage capacity for the maximum wind speed during each storm. All models showed marked underestimates and overestimates for individual storms when the measured ratio of interception to gross precipitation was far more or less, respectively, than the specified fraction of canopy cover. The models predicted the percentage of total gross precipitation (PG) intercepted to within the probable standard error (8.1%) of the measured value: the Mulder model overestimated the measured value by 0.1% of PG; the WiMo model underestimated by 0.6% of PG; and the Gash model underestimated by 1.1% of PG. The WiMo model’s advantage over the Gash model indicates that the canopy storage capacity increases logarithmically with the maximum wind speed. This study has demonstrated that dormant-season precipitation interception in a leafless deciduous forest may be satisfactorily predicted by existing canopy interception models.

Parametric accelerated failure time models with random effects and an application to kidney transplant survival

Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data. Copyright (C) 2004 John Wiley Sons, Ltd.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.

Ocean acoustic models for low frequency propagation in 2D and 3D environments

In this paper we are mainly concerned with the development of efficient computer models capable of accurately predicting the propagation of low-to-middle frequency sound in the sea, in axially symmetric (2D) and in fully 3D environments. The major physical features of the problem, i.e. a variable bottom topography, elastic properties of the subbottom structure, volume attenuation and other range inhomogeneities are efficiently treated. The computer models presented are based on normal mode solutions of the Helmholtz equation on the one hand, and on various types of numerical schemes for parabolic approximations of the Helmholtz equation on the other. A new coupled mode code is introduced to model sound propagation in range-dependent ocean environments with variable bottom topography, where the effects of an elastic bottom, of volume attenuation, surface and bottom roughness are taken into account. New computer models based on finite difference and finite element techniques for the numerical solution of parabolic approximations are also presented. They include an efficient modeling of the bottom influence via impedance boundary conditions, they cover wide angle propagation, elastic bottom effects, variable bottom topography and reverberation effects. All the models are validated on several benchmark problems and versus experimental data. Results thus obtained were compared with analogous results from standard codes in the literature.

Linear-wavelet models for system identification

A model structure comprising a wavelet network and a linear term is proposed for nonlinear system identification. It is shown that under certain conditions wavelets are orthogonal to linear functions and, as a result, the two parts of the model can be identified separately. The linear-wavelet model is compared to a standard wavelet network using data from a simulated fermentation process. The results show that the linear-wavelet model yields a smaller modelling error when compared to a wavelet network using the same number of regressors.

Testing isotherm models and recovering empirical relationships for adsorption in microporous carbons using virtual carbon models and grand canonical Monte Carlo simulations

Using the plausible model of activated carbon proposed by Harris and co-workers and grand canonical Monte Carlo simulations, we study the applicability of standard methods for describing adsorption data on microporous carbons widely used in adsorption science. Two carbon structures are studied, one with a small distribution of micropores in the range up to 1 nm, and the other with micropores covering a wide range of porosity. For both structures, adsorption isotherms of noble gases (from Ne to Xe), carbon tetrachloride and benzene are simulated. The data obtained are considered in terms of Dubinin-Radushkevich plots. Moreover, for benzene and carbon tetrachloride the temperature invariance of the characteristic curve is also studied. We show that using simulated data some empirical relationships obtained from experiment can be successfully recovered. Next we test the applicability of Dubinin's related models including the Dubinin-Izotova, Dubinin-Radushkevich-Stoeckli, and Jaroniec-Choma equations. The results obtained demonstrate the limits and applications of the models studied in the field of carbon porosity characterization.

The METAFOR project: preserving data through metadata standards for climate models and simulations

Climate modeling is a complex process, requiring accurate and complete metadata in order to identify, assess and use climate data stored in digital repositories. The preservation of such data is increasingly important given the development of ever-increasingly complex models to predict the effects of global climate change. The EU METAFOR project has developed a Common Information Model (CIM) to describe climate data and the models and modelling environments that produce this data. There is a wide degree of variability between different climate models and modelling groups. To accommodate this, the CIM has been designed to be highly generic and flexible, with extensibility built in. METAFOR describes the climate modelling process simply as "an activity undertaken using software on computers to produce data." This process has been described as separate UML packages (and, ultimately, XML schemas). This fairly generic structure canbe paired with more specific "controlled vocabularies" in order to restrict the range of valid CIM instances. The CIM will aid digital preservation of climate models as it will provide an accepted standard structure for the model metadata. Tools to write and manage CIM instances, and to allow convenient and powerful searches of CIM databases,. Are also under development. Community buy-in of the CIM has been achieved through a continual process of consultation with the climate modelling community, and through the METAFOR team’s development of a questionnaire that will be used to collect the metadata for the Intergovernmental Panel on Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs.