Prediction of hypertensive crisis based on average, variability and approximate entropy of 24-h ambulatory blood pressure monitoring

Approximate entropy (ApEn) of blood pressure (BP) can be easily measured based on software analysing 24-h ambulatory BP monitoring (ABPM), but the clinical value of this measure is unknown. In a prospective study we investigated whether ApEn of BP predicts, in addition to average and variability of BP, the risk of hypertensive crisis. In 57 patients with known hypertension we measured ApEn, average and variability of systolic and diastolic BP based on 24-h ABPM. Eight of these fifty-seven patients developed hypertensive crisis during follow-up (mean follow-up duration 726 days). In bivariate regression analysis, ApEn of systolic BP (P<0.01), average of systolic BP (P=0.02) and average of diastolic BP (P=0.03) were significant predictors of hypertensive crisis. The incidence rate ratio of hypertensive crisis was 14.0 (95% confidence interval (CI) 1.8, 631.5; P<0.01) for high ApEn of systolic BP as compared to low values. In multivariable regression analysis, ApEn of systolic (P=0.01) and average of diastolic BP (P<0.01) were independent predictors of hypertensive crisis. A combination of these two measures had a positive predictive value of 75%, and a negative predictive value of 91%, respectively. ApEn, combined with other measures of 24-h ABPM, is a potentially powerful predictor of hypertensive crisis. If confirmed in independent samples, these findings have major clinical implications since measures predicting the risk of hypertensive crisis define patients requiring intensive follow-up and intensified therapy.

JExample: Exploiting Dependencies Between Tests to Improve Defect Localization

To quickly localize defects, we want our attention to be focussed on relevant failing tests. We propose to improve defect localization by exploiting dependencies between tests, using a JUnit extension called JExample. In a case study, a monolithic white-box test suite for a complex algorithm is refactored into two traditional JUnit style tests and to JExample. Of the three refactorings, JExample reports five times fewer defect locations and slightly better performance (-8-12\%), while having similar maintenance characteristics. Compared to the original implementation, JExample greatly improves maintainability due the improved factorization following the accepted test quality guidelines. As such, JExample combines the benefits of test chains with test quality aspects of JUnit style testing.

Clinical Validation of a Peritoneal Dialysis Prescription Model in the PatientOnLine Software

Peritoneal transport characteristics and residual renal function require regular control and subsequent adjustment of the peritoneal dialysis (PD) prescription. Prescription models shall facilitate the prediction of the outcome of such adaptations for a given patient. In the present study, the prescription model implemented in the PatientOnLine software was validated in patients requiring a prescription change. This multicenter, international prospective cohort study with the aim to validate a PD prescription model included patients treated with continuous ambulatory peritoneal dialysis. Patients were examined with the peritoneal function test (PFT) to determine the outcome of their current prescription and the necessity for a prescription change. For these patients, a new prescription was modeled using the PatientOnLine software (Fresenius Medical Care, Bad Homburg, Germany). Two to four weeks after implementation of the new PD regimen, a second PFT was performed. The validation of the prescription model included 54 patients. Predicted and measured peritoneal Kt/V were 1.52 ± 0.31 and 1.66 ± 0.35, and total (peritoneal + renal) Kt/V values were 1.96 ± 0.48 and 2.06 ± 0.44, respectively. Predicted and measured peritoneal creatinine clearances were 42.9 ± 8.6 and 43.0 ± 8.8 L/1.73 m2/week and total creatinine clearances were 65.3 ± 26.0 and 63.3 ± 21.8 L/1.73 m2/week, respectively. The analysis revealed a Pearson's correlation coefficient for peritoneal Kt/V of 0.911 and Lin's concordance coefficient of 0.829. The value of both coefficients was 0.853 for peritoneal creatinine clearance. Predicted and measured daily net ultrafiltration was 0.77 ± 0.49 and 1.16 ± 0.63 L/24 h, respectively. Pearson's correlation and Lin's concordance coefficient were 0.518 and 0.402, respectively. Predicted and measured peritoneal glucose absorption was 125.8 ± 38.8 and 79.9 ± 30.7 g/24 h, respectively, and Pearson's correlation and Lin's concordance coefficient were 0.914 and 0.477, respectively. With good predictability of peritoneal Kt/V and creatinine clearance, the present model provides support for individual dialysis prescription in clinical practice. Peritoneal glucose absorption and ultrafiltration are less predictable and are likely to be influenced by additional clinical factors to be taken into consideration.

Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Estudio de la fiabilidad software, según defectos, en controladores de velocidad para robots autónomos móviles

Tanto los robots autónomos móviles como los robots móviles remotamente operados se utilizan con éxito actualmente en un gran número de ámbitos, algunos de los cuales son tan dispares como la limpieza en el hogar, movimiento de productos en almacenes o la exploración espacial. Sin embargo, es difícil garantizar la ausencia de defectos en los programas que controlan dichos dispositivos, al igual que ocurre en otros sectores informáticos. Existen diferentes alternativas para medir la calidad de un sistema en el desempeño de las funciones para las que fue diseñado, siendo una de ellas la fiabilidad. En el caso de la mayoría de los sistemas físicos se detecta una degradación en la fiabilidad a medida que el sistema envejece. Esto es debido generalmente a efectos de desgaste. En el caso de los sistemas software esto no suele ocurrir, ya que los defectos que existen en ellos generalmente no han sido adquiridos con el paso del tiempo, sino que han sido insertados en el proceso de desarrollo de los mismos. Si dentro del proceso de generación de un sistema software se focaliza la atención en la etapa de codificación, podría plantearse un estudio que tratara de determinar la fiabilidad de distintos algoritmos, válidos para desempeñar el mismo cometido, según los posibles defectos que pudieran introducir los programadores. Este estudio básico podría tener diferentes aplicaciones, como por ejemplo elegir el algoritmo menos sensible a los defectos, para el desarrollo de un sistema crítico o establecer procedimientos de verificación y validación, más exigentes, si existe la necesidad de utilizar un algoritmo que tenga una alta sensibilidad a los defectos. En el presente trabajo de investigación se ha estudiado la influencia que tienen determinados tipos de defectos software en la fiabilidad de tres controladores de velocidad multivariable (PID, Fuzzy y LQR) al actuar en un robot móvil específico. La hipótesis planteada es que los controladores estudiados ofrecen distinta fiabilidad al verse afectados por similares patrones de defectos, lo cual ha sido confirmado por los resultados obtenidos. Desde el punto de vista de la planificación experimental, en primer lugar se realizaron los ensayos necesarios para determinar si los controladores de una misma familia (PID, Fuzzy o LQR) ofrecían una fiabilidad similar, bajo las mismas condiciones experimentales. Una vez confirmado este extremo, se eligió de forma aleatoria un representante de clase de cada familia de controladores, para efectuar una batería de pruebas más exhaustiva, con el objeto de obtener datos que permitieran comparar de una forma más completa la fiabilidad de los controladores bajo estudio. Ante la imposibilidad de realizar un elevado número de pruebas con un robot real, así como para evitar daños en un dispositivo que generalmente tiene un coste significativo, ha sido necesario construir un simulador multicomputador del robot. Dicho simulador ha sido utilizado tanto en las actividades de obtención de controladores bien ajustados, como en la realización de los diferentes ensayos necesarios para el experimento de fiabilidad. ABSTRACT Autonomous mobile robots and remotely operated robots are used successfully in very diverse scenarios, such as home cleaning, movement of goods in warehouses or space exploration. However, it is difficult to ensure the absence of defects in programs controlling these devices, as it happens in most computer sectors. There exist different quality measures of a system when performing the functions for which it was designed, among them, reliability. For most physical systems, a degradation occurs as the system ages. This is generally due to the wear effect. In software systems, this does not usually happen, and defects often come from system development and not from use. Let us assume that we focus on the coding stage in the software development pro¬cess. We could consider a study to find out the reliability of different and equally valid algorithms, taking into account any flaws that programmers may introduce. This basic study may have several applications, such as choosing the algorithm less sensitive to pro¬gramming defects for the development of a critical system. We could also establish more demanding procedures for verification and validation if we need an algorithm with high sensitivity to programming defects. In this thesis, we studied the influence of certain types of software defects in the reliability of three multivariable speed controllers (PID, Fuzzy and LQR) designed to work in a specific mobile robot. The hypothesis is that similar defect patterns affect differently the reliability of controllers, and it has been confirmed by the results. From the viewpoint of experimental planning, we followed these steps. First, we conducted the necessary test to determine if controllers of the same family (PID, Fuzzy or LQR) offered a similar reliability under the same experimental conditions. Then, a class representative was chosen at ramdom within each controller family to perform a more comprehensive test set, with the purpose of getting data to compare more extensively the reliability of the controllers under study. The impossibility of performing a large number of tests with a real robot and the need to prevent the damage of a device with a significant cost, lead us to construct a multicomputer robot simulator. This simulator has been used to obtain well adjusted controllers and to carry out the required reliability experiments.

Software tool for simulation of aircraft trajectories

New concepts in air navigation have been introduced recently. Among others, are the concepts of trajectory optimization, 4D trajectories, RBT (Reference Business Trajectory), TBO (trajectory based operations), CDA (Continuous Descent Approach) and ACDA (Advanced CDA), conflict resolution, arrival time (AMAN), introduction of new aircraft (UAVs, UASs) in air space, etc. Although some of these concepts are new, the future Air Traffic Management will maintain the four ATM key performance areas such as Safety, Capacity, Efficiency, and Environmental impact. So much, the performance of the ATM system is directly related to the accuracy with which the future evolution of the traffic can be predicted. In this sense, future air traffic management will require a variety of support tools to provide suitable help to users and engineers involved in the air space management. Most of these tools are based on an appropriate trajectory prediction module as main component. Therefore, the purposes of these tools are related with testing and evaluation of any air navigation concept before they become fully operative. The aim of this paper is to provide an overview to the design of a software tool useful to estimate aircraft trajectories adapted to air navigation concepts. Other usage of the tool, like controller design, vertical navigation assessment, procedures validation and hardware and software in the loop are available in the software tool. The paper will show the process followed to design the tool, the software modules needed to perform accurately and the process followed to validate the output data.

Estudio de una metodología de software para la predicción y análisis del balance paramétrico de buques para su aplicación en los criterios de estabilidad de segunda generación

El objetivo de ésta tesis es estudiar cómo desarrollar una aplicación informática que implemente algoritmos numéricos de evaluación de características hidrodinámicas de modelos geométricos representativos de carenas de buques. Se trata de especificar los requisitos necesarios que debe cumplir un programa para informático orientado a dar solución a un determinado problema hidródinámico, como es simular el comportamiento en balance de un buque sometido a oleaje, de popa o proa. una vez especificada la aplicación se realizará un diseño del programa; se estudiarán alternativas para implementar la aplicación; se explicará el proceso que ha de seguirse para obtener la aplicación en funcionamiento y se contrastarán los resultados obtenidos en la medida que sea posible. Se pretende sistematizar y sintetizar todo el proceso de desarrollo de software, orientado a la simulación del comportamiento hidrodinámico de un buque, en una metodología que se pondrá a disposición de la comunidad académica y científica en la forma que se considere más adecuada. Se trata, por tanto, de proponer una metodología de desarrollo de software para obetener una aplicación que facilite la evaluación de diferentes alternativas de estudio variando parámetros relativos al problema en estudio y que sea capaz de proporcionar resultados para su análisis. Así mismo se incide en cómo ha de conducirse en el proceso para que dicha aplicación pueda crecer, incorporando soluciones existentes no implementadas o nuevas soluciones que aparezcan en este ámbito de conocimiento. Como aplicación concreta de la aplicación se ha elegido implementar los algoritmos necesarios para evaluar la aparición del balance paramétrico en un buque. En el análisis de éste problema se considera de interés la representación geométrica que se hace de la carena del buque. Además de la carena aparecen otros elementos que tienen influencia determinante en éste estudio, como son las situación de mar y las situaciones de carga. Idealmente, el problema sería resuelto si se consiguiera determinar el ángulo de balance que se produce al enfrentar un buque a las diferentes condiciones de mar. Se pretende preparar un programa utilizando el paradigma de la orientación a objetos. Considero que es la más adecuada forma de modularizar el programa para poder utilizar diferentes modelos de una misma carena y así comparar los resultados de la evaluación del balance paramétrico entre sí. En una etapa posterior se podrían comparar los resultados con otros obtenidos empíricamente. Hablo de una nueva metodología porque pretendo indicar cómo se ha de construir una aplicación de software que sea usable y sobre la que se pueda seguir desarrollando. Esto justifica la selección del lenguaje de programación C++. Se seleccionará un núcleo geométrico de software que permita acoplar de forma versátil los distintos componentes de software que van a construir el programa. Este trabajo pretende aplicar el desarrollo de software a un aspecto concreto del área de conocimiento de la hidrodinámica. No se pretende aportar nuevos algoritmos para resolver problemas de hidrodinámica, sino diseñar un conjunto de objetos de software que implementen soluciones existentes a conocidas soluciones numéricas a dichos problemas. Se trata fundamentalmente de un trabajo de software, más que de hidrodinámica. Lo que aporta de novedad es una nueva forma de realizar un programa aplicado a los cálculos hidrodinámicos relativos a la determinación del balance paramétrico, que pueda crecer e incorporar cualquier novedad que pueda surgir más adelante. Esto será posible por la programación modular utilizada y los objetos que representan cada uno de los elementos que intervienen en la determinación del balance paramétrico. La elección de aplicar la metodología a la predicción del balance paramétrico se debe a que este concepto es uno de los elementos que intervienen en la evaluación de criterios de estabilidad de segunda generación que estan en estudio para su futura aplicación en el ámbito de la construcción naval. Es por tanto un estudio que despierta interés por su próxima utilidad. ABSTRACT The aim of this thesis is to study how to develop a computer application implementing numerical algorithms to assess hydrodynamic features of geometrical models of vessels. It is therefore to propose a methodology for software development applied to an hydrodynamic problem, in order to evaluate different study alternatives by varying different parameters related to the problem and to be capable of providing results for analysis. As a concrete application of the program it has been chosen to implement the algorithms necessary for evaluating the appearance of parametric rolling in a vessel. In the analysis of this problem it is considered of interest the geometrical representation of the hull of the ship and other elements which have decisive influence in this phenomena, such as the sea situation and the loading condition. Ideally, the application would determine the roll angle that occurs when a ship is on waves of different characteristics. It aims to prepare a program by using the paradigm of object oriented programming. I think it is the best methodology to modularize the program. My intention is to show how face the global process of developing an application from the initial specification until the final release of the program. The process will keep in mind the spefici objetives of usability and the possibility of growing in the scope of the software. This work intends to apply software development to a particular aspect the area of knowledge of hydrodynamics. It is not intended to provide new algorithms for solving problems of hydrodynamics, but designing a set of software objects that implement existing solutions to these problems. This is essentially a job software rather than hydrodynamic. The novelty of this thesis stands in this work focuses in describing how to apply the whole proccess of software engineering to hydrodinamics problems. The choice of the prediction of parametric balance as the main objetive to be applied to is because this concept is one of the elements involved in the evaluation of the intact stability criteria of second generation. Therefore, I consider this study as relevant usefull for the future application in the field of shipbuilding.

Building intuition of iron evolution during solar cell processing through analysis of different process models

An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe-i]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetically limited and bulk [Fe-i] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.

The prediction and representation of phase equilibria and physicochemical properties in complex slag systems

The development of new experimental techniques for the determination of phase equilibria in complex slag systems, chemical thermodynamic, and viscosity models is reported. The new experimental data, and new thermodynamic and viscosity models, have been combined in a custom-designed computer software package to produce limiting operability diagrams for slag systems. These diagrams are used to describe phase equilibria and physicochemical properties in complex slag systems. The approach is illustrated with calculations on the system FeO-Fe2O3-CaO-SiO-Al2O3 at metallic iron saturation, slags produced in coal slagging gasifiers, and in the reprocessing of nonferrous smelting slags. This article was presented at the Mills Symposium Molten Metals, Slags and Glasses-Characterisation of Properties and Phenomena held in London in August 2000.

Prediction of subcellular localization using sequence-biased recurrent networks

Motivation: Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging. Results: We contrast the use of feed forward models as employed by the popular TargetP/SignalP predictors with a sequence-biased recurrent network model. The models are evaluated in terms of performance at the residue level and at the sequence level, and demonstrate that recurrent networks improve the overall prediction performance. Compared to the original results reported for TargetP, an ensemble of the tested models increases the accuracy by 6 and 5% on non-plant and plant data, respectively.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^