Tunnel engineering – influence of the type and the quantity of measurements in the back analysis of geomechanical parameters

The monitoring data collected during tunnel excavation can be used in inverse analysis procedures in order to identify more realistic geomechanical parameters that can increase the knowledge about the interested formations. These more realistic parameters can be used in real time to adapt the project to the real structure in situ behaviour. However, monitoring plans are normally designed for safety assessment and not especially for the purpose of inverse analysis. In fact, there is a lack of knowledge about what types and quantity of measurements are needed to succeed in identifying the parameters of interest. Also, the optimisation algorithm chosen for the identification procedure may be important for this matter. In this work, this problem is addressed using a theoretical case with which a thorough parametric study was carried out using two optimisation algorithms based on different calculation paradigms, namely a conventional gradient-based algorithm and an evolution strategy algorithm. Calculations were carried for different sets of parameters to identify several combinations of types and amount of monitoring data. The results clearly show the high importance of the available monitoring data and the chosen algorithm for the success rate of the inverse analysis process.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

An immunity based configuration for multilayer single featured biometric authentication algorithms

Immune systems have been used in the last years to inspire approaches for several computational problems. This paper focus on behavioural biometric authentication algorithms’ accuracy enhancement by using them more than once and with different thresholds in order to first simulate the protection provided by the skin and then look for known outside entities, like lymphocytes do. The paper describes the principles that support the application of this approach to Keystroke Dynamics, an authentication biometric technology that decides on the legitimacy of a user based on his typing pattern captured on he enters the username and/or the password and, as a proof of concept, the accuracy levels of one keystroke dynamics algorithm when applied to five legitimate users of a system both in the traditional and in the immune inspired approaches are calculated and the obtained results are compared.

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Bootstrap performance profiles in stochastic algorithms assessment

Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

Biosynthesis, detection and toxicology of ochratoxins - optimisation of production

Ochratoxin A (OTA) is a very well known mycotoxin found in several food commodities for which maximum limits are being discussed in EC in other to produce appropriate regulations. OTA is one of several ochratoxins produced by Aspergillus and Penicillium species. All the compounds in this group have a molecular structure very similar to OTA and some were already isolated from natural substrates. Several of these compounds such as ochratoxin , methyl and ethyl ester of ochratoxin A, 4-R and S-hydroxyochratoxin A, 10-hydroxyochratoxin A and ochratoxin A open lactone are commercially unavailable. However, they can be easily synthesized through OTA modification. With the main objective of its application on further research works, OTA production, isolation and purification has been optimised from an A. alliaceus strain grown on wheat medium. Synthesis and purification of some OTA derivatives has been achieved and an HPLC method for their detection was optimised. Data about their production by several species of Aspergillus will be presented. The toxicological properties of ochratoxins are still not very clear and a future EC safety limit for OTA will depend on e.g., a better clarification of its carcinogenity. Could OTA derivatives play a role here?