3D dose reconstruction for narrow beams using ion chamber array measurements.

3D dose reconstruction is a verification of the delivered absorbed dose. Our aim was to describe and evaluate a 3D dose reconstruction method applied to phantoms in the context of narrow beams. A solid water phantom and a phantom containing a bone-equivalent material were irradiated on a 6 MV linac. The transmitted dose was measured by using one array of a 2D ion chamber detector. The dose reconstruction was obtained by an iterative algorithm. A phantom set-up error and organ interfraction motion were simulated to test the algorithm sensitivity. In all configurations convergence was obtained within three iterations. A local reconstructed dose agreement of at least 3% / 3mm with respect to the planned dose was obtained, except in a few points of the penumbra. The reconstructed primary fluences were consistent with the planned ones, which validates the whole reconstruction process. The results validate our method in a simple geometry and for narrow beams. The method is sensitive to a set-up error of a heterogeneous phantom and interfraction heterogeneous organ motion.

Gorilla genome structural variation reveals evolutionary parallelisms with chimpanzee

Structural variation has played an important role in the evolutionary restructuring of human and great ape genomes. Recent analyses have suggested that the genomes of chimpanzee and human have been particularly enriched for this form of genetic variation. Here, we set out to assess the extent of structural variation in the gorilla lineage by generating 10-fold genomic sequence coverage from a western lowland gorilla and integrating these data into a physical and cytogenetic framework of structural variation. We discovered and validated over 7665 structural changes within the gorilla lineage, including sequence resolution of inversions, deletions, duplications, and mobile element insertions. A comparison with human and other ape genomes shows that the gorilla genome has been subjected to the highest rate of segmental duplication. We show that both the gorilla and chimpanzee genomes have experienced independent yet convergent patterns of structural mutation that have not occurred in humans, including the formation of subtelomeric heterochromatic caps, the hyperexpansion of segmental duplications, and bursts of retroviral integrations. Our analysis suggests that the chimpanzee and gorilla genomes are structurally more derived than either orangutan or human genomes.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

On solving fair exchange and related distributed problems in Byzantine environments

Abstract The solvability of the problem of fair exchange in a synchronous system subject to Byzantine failures is investigated in this work. The fair exchange problem arises when a group of processes are required to exchange digital items in a fair manner, which means that either each process obtains the item it was expecting or no process obtains any information on, the inputs of others. After introducing a novel specification of fair exchange that clearly separates safety and liveness, we give an overview of the difficulty of solving such a problem in the context of a fully-connected topology. On one hand, we show that no solution to fair exchange exists in the absence of an identified process that every process can trust a priori; on the other, a well-known solution to fair exchange relying on a trusted third party is recalled. These two results lead us to complete our system model with a flexible representation of the notion of trust. We then show that fair exchange is solvable if and only if a connectivity condition, named the reachable majority condition, is satisfied. The necessity of the condition is proven by an impossibility result and its sufficiency by presenting a general solution to fair exchange relying on a set of trusted processes. The focus is then turned towards a specific network topology in order to provide a fully decentralized, yet realistic, solution to fair exchange. The general solution mentioned above is optimized by reducing the computational load assumed by trusted processes as far as possible. Accordingly, our fair exchange protocol relies on trusted tamperproof modules that have limited communication abilities and are only required in key steps of the algorithm. This modular solution is then implemented in the context of a pedagogical application developed for illustrating and apprehending the complexity of fair exchange. This application, which also includes the implementation of a wide range of Byzantine behaviors, allows executions of the algorithm to be set up and monitored through a graphical display. Surprisingly, some of our results on fair exchange seem contradictory with those found in the literature of secure multiparty computation, a problem from the field of modern cryptography, although the two problems have much in common. Both problems are closely related to the notion of trusted third party, but their approaches and descriptions differ greatly. By introducing a common specification framework, a comparison is proposed in order to clarify their differences and the possible origins of the confusion between them. This leads us to introduce the problem of generalized fair computation, a generalization of fair exchange. Finally, a solution to this new problem is given by generalizing our modular solution to fair exchange

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Messaging Application Engine for Symbian Platform

Tämä diplomityö kuvaa viestintä sovelluksen ytimen kehitystyön Symbian-alustalle. Koko sovelluksen vaatimuksena oli vastaamattomiin puheluihin vastaaminen ennalta määritellyillä tekstiviesteillä käyttäjän määrittelemien sääntöjen mukaisesti. Ei-toiminnallisia vaatimuksia olivat resurssien käytön vähentäminen ja uudelleenkäytön mahdollistaminen. Täten tämän työn tavoitteena oli kehittää ydin, joka kapseloi sovelluksen sellaisen toiminnallisuuden, joka on käyttöliittymästä riippumatonta ja uudelleenkäytettävää. Kehitystyössä ohjasi Unified Process, joka on iteroiva, käyttötapauksien ohjaama ja arkkitehtuurikeskeinen ohjelmistoprosessi. Se kannusti käyttämään myös muita teollisuudenalan vakiintuneita menetelmiä, kuten suunnittelumalleja ja visuaalista mallintamista käyttäen Unified Modelling Languagea. Suunnittelumalleja käytettiin kehitystyön aikana ja ohjelmisto mallinnettiin visuaalisesti suunnittelun edistämiseksi ja selkiyttämiseksi. Alustan palveluita käytettiin hyväksi kehitysajan ja resurssien käytön minimoimiseksi. Ytimen päätehtäviksi määrättiin viestien lähettäminen sekä sääntöjen talletus ja tarkistaminen. Sovelluksen eri alueet, eli sovelluspalvelin ja käyttöliittymää, pystyivät käyttämään ydintä ja sillä ei ollut riippuvuuksia käyttöliittymätasolle. Täten resurssien käyttö väheni ja uudelleenkäytettävyys lisääntyi. Viestien lähettäminen toteutettiin Symbian-alustan menetelmin. Sääntöjen tallettamiseen tehtiin tallennuskehys, joka eristää sääntöjen sisäisen ja ulkoisen muodon. Tässä tapauksessa ulkoiseksi tallennustavaksi valittiin relaatiotietokanta. Sääntöjen tarkastaminen toteutettiin tavanomaisella olioiden yhteistoiminnalla. Päätavoite saavutettiin. tämä ja muut hyviksi arvioidut lopputulokset, kuten uudelleenkäytettävyys ja vähentynyt resurssien käyttö, arveltiin juontuvan suunnittelumallien ja Unified Processin käytöstä. Kyseiset menetelmät osoittivat mukautuvansa pieniinkin projekteihin. Menetelmien todettiin myös tukevan ja kannustavan kehitystyön aikaista oppimista, mikä oli välttämätöntä tässä tapauksessa.

Evolutionary computing in search-based software engineering

This master’s thesis aims to study and represent from literature how evolutionary algorithms are used to solve different search and optimisation problems in the area of software engineering. Evolutionary algorithms are methods, which imitate the natural evolution process. An artificial evolution process evaluates fitness of each individual, which are solution candidates. The next population of candidate solutions is formed by using the good properties of the current population by applying different mutation and crossover operations. Different kinds of evolutionary algorithm applications related to software engineering were searched in the literature. Applications were classified and represented. Also the necessary basics about evolutionary algorithms were presented. It was concluded, that majority of evolutionary algorithm applications related to software engineering were about software design or testing. For example, there were applications about classifying software production data, project scheduling, static task scheduling related to parallel computing, allocating modules to subsystems, N-version programming, test data generation and generating an integration test order. Many applications were experimental testing rather than ready for real production use. There were also some Computer Aided Software Engineering tools based on evolutionary algorithms.

Optimización y aproximación al problema de la regresión simbólica a través de Straight Line Programs (SLP's) y algoritmos genéticos : Entrenamiento genético de SLP's

El problema de la regresión simbólica consiste en el aprendizaje, a partir de un conjunto muestra de datos obtenidos experimentalmente, de una función desconocida. Los métodos evolutivos han demostrado su eficiencia en la resolución de instancias de dicho problema. En este proyecto se propone una nueva estrategia evolutiva, a través de algoritmos genéticos, basada en una nueva estructura de datos denominada Straight Line Program (SLP) y que representa en este caso expresiones simbólicas. A partir de un SLP universal, que depende de una serie de parámetros cuya especialización proporciona SLP's concretos del espacio de búsqueda, la estrategia trata de encontrar los parámetros óptimos para que el SLP universal represente la función que mejor se aproxime al conjunto de puntos muestra. De manera conceptual, este proyecto consiste en un entrenamiento genético del SLP universal, utilizando los puntos muestra como conjunto de entrenamiento, para resolver el problema de la regresión simbólica.

Algoritmo genético em química

Genetic algorithm is an optimization technique based on Darwin evolution theory. In last years its application in chemistry is increasing significantly due the special characteristics for optimization of complex systems. The basic principles and some further modifications implemented to improve its performance are presented, as well as a historical development. A numerical example of a function optimization is also shown to demonstrate how the algorithm works in an optimization process. Finally several chemistry applications realized until now is commented to serve as parameter to future applications in this field.

Aplicação de algoritmos genéticos na seleção de variáveis em espectroscopia no infravermelho médio: determinação simultânea de glicose, maltose e frutose

Genetic algorithm was used for variable selection in simultaneous determination of mixtures of glucose, maltose and fructose by mid infrared spectroscopy. Different models, using partial least squares (PLS) and multiple linear regression (MLR) with and without data pre-processing, were used. Based on the results obtained, it was verified that a simpler model (multiple linear regression with variable selection by genetic algorithm) produces results comparable to more complex methods (partial least squares). The relative errors obtained for the best model was around 3% for the sugar determination, which is acceptable for this kind of determination.

Seleção de variáveis em QSAR

The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.

Estudo do estado fundamental de aglomerados de silício via redes neurais

We introduce a global optimization method based on the cooperation between an Artificial Neural Net (ANN) and Genetic Algorithm (GA). We have used ANN to select the initial population for the GA. We have tested the new method to predict the ground-state geometry of silicon clusters. We have described the clusters as a piling of plane structures. We have trained three ANN architectures and compared their results with those of pure GA. ANN strongly reduces the total computational time. For Si10, it gained a factor of 5 in search speed. This method can be easily extended to other optimization problems.

Niche Differentiation and Fine-Scale Projections for Argentine Ants Based on Remotely Sensed Data

Modeling ecological niches of species is a promising approach for predicting the geographic potential of invasive species in new environments. Argentine ants (Linepithema humile) rank among the most successful invasive species: native to South America, they have invaded broad areas worldwide. Despite their widespread success, little is known about what makes an area susceptible - or not - to invasion. Here, we use a genetic algorithm approach to ecological niche modeling based on high-resolution remote-sensing data to examine the roles of niche similarity and difference in predicting invasions by this species. Our comparisons support a picture of general conservatism of the species' ecological characteristics, in spite of distinct geographic and community contexts

Lautanauhaohjeen muodostus tavoitekuviosta geneettisellä algoritmilla

Lautanauhatekniikka on monipuolinen menetelmä esimerkiksi kuvioitujen nauhojen kutomiseen, mutta uusien kuvioaiheiden suunnittelu, tai aloittelijalle jo valmiiden ohjeettomien kuviomallien jäljittely, voi helposti käydä työlääksi menetelmän ominaispiirteiden johdosta. Tämän työn tavoitteena oli kehittää ohjelmallinen työkalu auttamaan näissä ongelmissa automatisoimalla kudontaohjeen etsintä käyttäjän laatimalle tavoitekuviolle. Ratkaisumenetelmän perustaksi valittiin geneettinen algoritmi, minkä johdosta työn keskeisintutkimusongelma oli kartoittaa algoritmin perusoperaatioiden parametrien ja tavoitekuvion kompleksisuuden keskinäisiä riippuvuuksia riittävästi toimivien arvosuositusten antamiseen ohjelman tulevassa käytännön käytössä. Työssä ei kehitetty sovellusalueeseen mukautettuja evoluutiooperaatioita, vaan keskityttiin luomaan hyvin tunnetuista elementeistä perusta, jota voi myöhemmin kehittää eteenpäin.

Testing Platform Development for Large Scale Solar Integration

Currently, a high penetration level of Distributed Generations (DGs) has been observed in the Danish distribution systems, and even more DGs are foreseen to be present in the upcoming years. How to utilize them for maintaining the security of the power supply under the emergency situations, has been of great interest for study. This master project is intended to develop a control architecture for studying purposes of distribution systems with large scale integration of solar power. As part of the EcoGrid EU Smart Grid project, it focuses on the system modelling and simulation of a Danish representative LV network located in Bornholm island. Regarding the control architecture, two types of reactive control techniques are implemented and compare. In addition, a network voltage control based on a tap changer transformer is tested. The optimized results after applying a genetic algorithm to five typical Danish domestic loads are lower power losses and voltage deviation using Q(U) control, specially with large consumptions. Finally, a communication and information exchange system is developed with the objective of regulating the reactive power and thereby, the network voltage remotely and real-time. Validation test of the simulated parameters are performed as well.