Computational Intelligence has found a challenging testbed for various paradigms in the financial sector. Extensive research has resulted in numerous financial applications using neural networks and evolutionary computation, mainly genetic algorithms and genetic programming. More recent advances in the field of computational intelligence have not yet been applied as extensively or have not become available in the public domain, due to the confidentiality requirements of financial institutions. This study investigates how co-evolution together with the combination of par- ticle swarm optimisation and neural networks could be used to discover competitive security trading agents that could enable the timing of buying and selling securities to maximise net profit and minimise risk over time. The investigated model attempts to identify security trend reversals with the help of technical analysis methodologies. Technical market indicators provide the necessary market data to the agents and reflect information such as supply, demand, momentum, volatility, trend, sentiment and retracement. All this is derived from the security price alone, which is one of the strengths of technical analysis and the reason for its use in this study. The model proposed in this thesis evolves trading strategies within a single pop- ulation of competing agents, where each agent is represented by a neural network. The population is governed by a competitive co-evolutionary particle swarm optimi- sation algorithm, with the objective of optimising the weights of the neural networks. A standard feed forward neural network architecture is used, which functions as a market trend reversal confidence. Ultimately, the neural network becomes an amal- gamation of the technical market indicators used as inputs, and hence is capable of detecting trend reversals. Timely trading actions are derived from the confidence output, by buying and short selling securities when the price is expected to rise or fall respectively. No expert trading knowledge is presented to the model, only the technical market indicator data. The co-evolutionary particle swarm optimisation model facilitates the discovery of favourable technical market indicator interpretations, starting with zero knowledge. A competitive fitness function is defined that allows the evaluation of each solution relative to other solutions, based on predefined performance metric objectives. The relative fitness function in this study considers net profit and the Sharpe ratio as a risk measure. For the purposes of this study, the stock prices of eight large market capitalisation companies were chosen. Two benchmarks were used to evaluate the discovered trading agents, consisting of a Bollinger Bands/Relative Strength Index rule-based strategy and the popular buy-and-hold strategy. The agents that were discovered from the proposed hybrid computational intelligence model outperformed both benchmarks by producing higher returns for in-sample and out-sample data at a low risk. This indicates that the introduced model is effective in finding favourable strategies, based on observed historical security price data. Transaction costs were considered in the evaluation of the computational intelligent agents, making this a feasible model for a real-world application. Copyright / Dissertation (MSc)--University of Pretoria, 2010. / Computer Science / unrestricted

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Cette thèse s'est déroulée dans le cadre du projet ANR FOSTER, "FOuille de données Spatio-Temporelles : application à la compréhension et à la surveillance de l'ERosion" (ANR-2010-COSI-012-02, 2011-2014). Dans ce contexte, nous nous sommes intéressés à la modélisation de données spatio-temporelles dans des graphes enrichis de sorte que des calculs de motifs sur de telles données permettent de formuler des hypothèses intéressantes sur les phénomènes à comprendre. Plus précisément, nous travaillons sur la fouille de motifs dans des graphes relationnels (chaque noeud est identifié de fa\c con unique), attribués (chaque noeud du graphe est décrit par des attributs qui sont ici numériques), et dynamiques (les valeurs des attributs et les relations entre les noeuds peuvent évoluer dans le temps). Nous proposons un nouveau domaine de motifs nommé motifs de co-évolution. Ce sont des triplets d'ensembles de noeuds, d'ensembles de pas de temps et d'ensembles d'attributs signés, c'est à dire des attributs associés à une tendance (croissance,décroissance). L'intérêt de ces motifs est de décrire un sous-ensemble des données qui possède un comportement spécifique et a priori intéressant pour conduire des analyses non triviales. Dans ce but, nous définissons deux types de contraintes, une contrainte sur la structure du graphe et une contrainte sur la co-évolution de la valeur des attributs portés par les noeuds. Pour confirmer la spécificité du motif par rapport au reste des données, nous définissons trois mesures de densité qui tendent à répondre à trois questions. À quel point le comportement des noeuds en dehors du motif est similaire à celui des noeuds du motif ? Quel est le comportement du motif dans le temps, est-ce qu'il apparaît soudainement ? Est-ce que les noeuds du motif ont un comportement similaire seulement sur les attributs du motif ou aussi en dehors ? Nous proposons l'utilisation d'une hiérarchie sur les attributs comme connaissance à priori de l'utilisateur afin d'obtenir des motifs plus généraux et adaptons l'ensemble des contraintes à l'utilisation de cette hiérarchie. Finalement, pour simplifier l'utilisation de l'algorithme par l'utilisateur en réduisant le nombre de seuils à fixer et pour extraire uniquement l'ensemble des motifs les plus intéressants, nous utilisons le concept de ``skyline'' réintroduit récemment dans le domaine de la fouille de données. Nous proposons ainsi trois algorithmes MINTAG, H-MINTAG et Sky-H-MINTAG qui sont complets pour extraire l'ensemble de tous les motifs qui respectent les différentes contraintes. L'étude des propriétés des contraintes (anti-monotonie, monotonie/anti-monotonie par parties) nous permet de les pousser efficacement dans les algorithmes proposés et d'obtenir ainsi des extractions sur des données réelles dans des temps raisonnables. / This thesis was conducted within the project ANR FOSTER, ``Spatio-Temporal Data Mining: application to the understanding and monitoring of erosion'' (ANR-2010-COSI-012-02, 2011-2014). In this context, we are interested in the modeling of spatio- temporal data in enriched graphs so that computation of patterns on such data can be used to formulate interesting hypotheses about phenomena to understand. Specifically, we are working on pattern mining in relational graphs (each vertex is uniquely identified), attributed (each vertex of the graph is described by numerical attributes) and dynamic (attribute values and relations between vertices may change over time). We propose a new pattern domain that has been called co-evolution patterns. These are trisets of vertices, times and signed attributes, i.e., attributes associated with a trend (increasing or decreasing). The interest of these patterns is to describe a subset of the data that has a specific behaviour and a priori interesting to conduct non-trivial analysis. For this purpose, we define two types of constraints, a constraint on the structure of the graph and a constraint on the co-evolution of the value worn by vertices attributes. To confirm the specificity of the pattern with regard to the rest of the data, we define three measures of density that tend to answer to three questions. How similar is the behaviour of the vertices outside the co-evolution pattern to the ones inside it? What is the behaviour of the pattern over time, does it appear suddenly? Does the vertices of the pattern behave similarly only on the attributes of the pattern or even outside? We propose the use of a hierarchy of attributes as an a priori knowledge of the user to obtain more general patterns and we adapt the set of constraints to the use of this hierarchy. Finally, to simplify the use of the algorithm by the user by reducing the number of thresholds to be set and to extract only all the most interesting patterns, we use the concept of ``skyline'' reintroduced recently in the domain of data mining. We propose three constraint-based algorithms, called MINTAG, H-MINTAG and Sky-H-MINTAG, that are complete to extract the set of all patterns that meet the different constraints. These algorithms are based on constraints, i.e., they use the anti-monotonicity and piecewise monotonicity/anti-monotonicity properties to prune the search space and make the computation feasible in practical contexts. To validate our method, we experiment on several sets of data (graphs) created from real-world data.

由於資訊科技的發展，提供顧客商品與服務的溝通等價值觀也隨之改變，新興服務業是依賴網際網路和資訊技術所發展而來的，全球產業結構呈現出“工業型經濟”向“服務型經濟”轉型的總趨勢，服務逐步被重視。人類社會第四次的革命“服務革命”，就是服務科學，社會和技術共同演進的科學，以資訊科技為基礎改革服務整體。加上網路效應，讓人們可以透過共同設計思考，為世界帶來創意及新事物的催化劑，將跨領域的人才結合起來，利用群策群力及不同領域的思考藝術互相激盪，激發出創意。將這些觀點整合起來，提出一個共同創造服務的架構，讓人們在獲得服務的同時，也參與創造服務，得到服務的最佳化。本研究透過服務科學的服務組成、服務流程、以及服務價值三方面來探討，並採用結合協同式共同演化基因演算法、互動式基因演算法所組合成的協同互動式共同演化基因演算法，以共同演化的方式，達到使用者的設計需求。系統共分四大模組：設計問題定義模組、設計建議模組、協同互動式共同演化模組、評估模組，將設計思考、共同創作並演化的概念，並透過互動式基因演算法修正適應函數評估的偏差，讓顧客設計過程中，得到最佳化的服務。本系統之預期貢獻分為：(1)利用服務科學創新設計服務e化傳遞。(2)為服務科學提供應用典範與原件發展方向。 / The notion of service science addresses the use of information technology to reform services in terms of designing thinking and value co-production, bringing the catalyst of the innovation to the service world. This paper proposes a novel e-service platform about interior design featuring (semi-)automated mutualism of co-produced values. This platform encompasses a few autonomous cognitive learning components to guarantee effective accomplishment of reaching a user's design demand. These components include models of interior design concepts, cooperative co-evolutionary genetic algorithm (CGA) and interactive genetic algorithm (IGA). The intended contributions of this platform are two-folds: (1) Showcase an intelligent service design as characterized by the sixth quadrant of Figure1. (2) Provide some intelligent service design components (e.g., CICGA) for unfolding future systematic service innovation in service science.

La thèse aborde différentes questions de chimie prébiotique dans le contexte de l’origine de la vie par une approche de chimie systémique. La première partie est dédiée à l’étude de processus d’activation chimique important non seulement pour la formation de polymères, mais aussi pour alimenter le système en énergie de manière à le maintenir dans un état éloigné de l’équilibre, un prérequis pour l’auto-organisation. Il a été suggéré que les intermédiaires 5(4H)-oxazolones formés par l’activation de l’extrémité C-terminale des peptides pourrait être impliquée dans l’auto-organisation du vivant. Dans ce but, nous avons évalué la réactivité de réactifs pertinents dans un contexte prébiotique et décrits dans la littérature comme capables d’activer des acides α-aminés. Aucun d’entre eux n’a manifesté une activité satisfaisante pour l’activation C-terminale des peptides, montrant qu’une voie possible pour alimenter un protométabolisme des peptides en énergie n’est pas identifiée à ce jour à l’exception notable des N-carboxyanhydrides (NCA) qui peuvent être formé par des voies prébiotiquement plausibles. Nous avons par ailleurs démontré que les carbodiimides sont aussi efficaces pour l’activation des N-carbamoylamino acides que pour celle du carboxyle terminal des peptides en milieu aqueux dilué. La seconde partie du document expose de nouveaux résultats en faveur d’un processus de coévolution peptides-nucléotides. D’abord, une étude de la réactivité d’agents d’aminoacylation de l’extrémité 3’ de l’ARN est présentée. Ensuite, nous évaluons des co-polymères acides α-aminés-nucléotides liés par des enchaînements phosphoramidate et esters comme partenaires éventuels de l’évolution chimique. La pertinence cinétique de ces structures est démontrée ainsi que des voies chimiques permettant leur formation. / The thesis addresses several issues in prebiotic chemistry in the context of the origins of life through a systems chemistry approach. The first part is devoted to the study of chemical activation processes that are not only important in the formation of polymers, but also to feed the system with energy in order that a far from equilibrium state is maintained, a prerequisite for self-organization. It has been suggested that 5(4H)-oxazolones intermediates formed by C-terminus peptide activation could be involved in self-organization of life. To this aim, we have checked the reactivity of relevant prebiotic reagents previously proposed to activate α-amino acids. None of them led to a satisfactory C-terminus activation of peptides, showing that no general process for feeding a protometabolism of peptides with energy is identified yet, with the notable exception of N-carboxyanhydrides (NCAs) that can be formed through prebiotically relevant pathways. Additionally, we demonstrated that carbodiimides reagents are as efficient in the activation of N-carbamoyl amino acids as in that of the C-terminus of peptides in diluted aqueous media. The second part of the dissertation discloses new results in support of a process of coevolution of peptides and nucleotides. Firstly, a study of non-enzymatic aminoacylation reagents of the 3’-terminus of RNA is presented. Secondly, we assessed co-polymers of α-amino acids and nucleotides bound by phosphoramidate and ester linkages as potential players in chemical evolution. The kinetic relevance of these structures was demonstrated as well as potential chemical processes that allow their formation.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-03-30T11:51:21Z No. of bitstreams: 1 Carlos Eduardo de Jesus Guimarães Oliveira.pdf: 1236896 bytes, checksum: ef9d04e6f25aee7908b56a622411bc74 (MD5) / Made available in DSpace on 2015-03-30T11:51:21Z (GMT). No. of bitstreams: 1 Carlos Eduardo de Jesus Guimarães Oliveira.pdf: 1236896 bytes, checksum: ef9d04e6f25aee7908b56a622411bc74 (MD5) Previous issue date: 2014-01-31 / Nenhuma / Este trabalho apresenta um algoritmo de otimização baseado na metaheurística dos Sistemas Imunológicos Artificiais, princípios de Teoria dos Jogos, Co-evolução e Paralelização. Busca-se a combinação adequada dos conceitos de Teoria dos Jogos, Co-evolução e Paralelização aplicados ao algoritmo AISO (Artificial Immune System Optimization) para resolução do Problema de Alocação de Berços (PAB). Dessa maneira, o algoritmo é formalizado a partir das técnicas citadas, formando o PCAISO-GT: Parallel Coevolutionary Artificial Immune System Optimization with Game Theory. Inicialmente, foram realizados experimentos visando à sintonia dos parâmetros empregados nas diferentes versões da ferramenta desenvolvida. Com base nas melhores configurações identificadas, foram realizados experimentos de avaliação através da solução de um conjunto de instâncias do PAB. Os resultados obtidos permitiram a indicação da versão co-evolutiva associada à teoria dos jogos como a melhor para solução do problema em estudo. / This paper presents an optimization algorithm based on metaheuristic of Artificial Immune Systems, principles of Game Theory, Co-evolution and parallelization. The objective is find the appropriate combination of the concepts of Game Theory, Co-evolution and Parallelization applied to AISO algorithm (Artificial Immune System Optimization) for solving the Berth Allocation Problem (BAP). Thus, the algorithm is formalized from the above mentioned techniques, forming the PCAISO-GT: Parallel Coevolutionary Artificial Immune System Optimization with Game Theory. Initially, experiments aiming to tune the parameters were performed using different versions of the tool developed. Based on the identified best settings, evaluation experiments were carried out by solving a set of instances of the PAB. The results obtained allowed the appointment of co-evolutionary version associated with game theory as the best solution to the problem under study.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-06-11T19:24:34Z No. of bitstreams: 1 Débora de Oliveira Lemos Rocha de Souza.pdf: 11262812 bytes, checksum: 1afc26309c47e8dc71f1c5e88aae7409 (MD5) / Made available in DSpace on 2015-06-11T19:24:34Z (GMT). No. of bitstreams: 1 Débora de Oliveira Lemos Rocha de Souza.pdf: 11262812 bytes, checksum: 1afc26309c47e8dc71f1c5e88aae7409 (MD5) Previous issue date: 2015-03-27 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / FAPERGS - Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul / Algumas ações do processo projetual se restringem aos pensamentos dos designers, gerando uma dificuldade para compreender o processo e torná-lo explícito. As pesquisas nessa área tentam transpor essas limitações, buscando perceber o modo como os designers resolvem os problemas para aprimorar a sua atuação. Esses problemas são caracterizados como mal-estruturados e podem ser vistos de diferentes perspectivas, gerando respostas distintas. O conceito de coevolução percebe a resolução de problemas de forma evolutiva: à medida que compreende-se um pouco mais o problema, as respostas tornam-se mais aprimoradas. Esta dissertação tem como objetivo geral compreender a coevolução do problema de design. Para isso, realizou-se uma pesquisa exploratória em um workshop em design, coletando as informações por meio de grupos focais e do registro, em vídeo, do processo realizado pelos participantes. A técnica utilizada para analisar as informações coletadas nos grupos focais e nos vídeos foi a análise de conteúdo, com algumas adaptações necessárias à pesquisa realizada. Na análise, percebeu-se que a coevolução é influenciada: 1) pela formulação inicial do problema que funciona como uma força motora, impulsionando o processo de resolução do problema; 2) pela forma como as equipes se articulam, levando-se em conta o modo como os integrantes desempenham diferentes papeis e estabelecem um ritmo de resolução do problema de acordo com experiências anteriores que trazem para o projeto; 3) pelos questionamentos em relação ao problema ou à solução, caracterizando-se como uma das estratégias utilizadas pelos designers para avançar no espaço-problema ou no espaço-solução. Concluiu-se, assim, que não só o espaço-problema e o espaço-solução se modificam no percurso do projeto de forma a provocar uma evolução mútua, mas os diversos fatores que envolvem o processo projetual também influenciam na coevolução do problema de design. / Some actions in the design process are restricted to the designers’ thoughts, what may cause some difficulties in understanding the process itself and making it explicit. Studies in this area attempt to overcome these limitations by looking into the way designers solve problems to improve their performance. These problems are usually characterized as ill-structured and can be seen from different perspectives, leading to distinct answers. The concept of co-evolution regards problem resolution in an evolutive manner: as the problem is better understood, the answers become more refined. The overall objective of this work is to understand the co-evolution of the design problem. In order to do this, an exploratory research was conducted within a design workshop, where data was collected by means of both focal groups and videos recording the participants’ process. The technique used to analyse all this data was Content Analysis, with some necessary adaptations to the context of the present research. In the analysis, it was possible to observe that co-evolution is influenced by: 1) the initial formulation of the problem that works as a driving force, boosting the problem resolution process; 2) the way the groups manage themselves, taking into consideration the manner in which different members play distinct roles and establish a problem resolution pace based on previous experiences they bring to the project; and 3) inquiries related to the problem or the solution, which can be regarded as one of the strategies used by designers to move forward into the problem space or the solution space. In conclusion, all these observations lead to the understanding that not only the problem space and the solution space modify themselves in the course of the project, triggering mutual evolution, but the diverse aspects involved in the design context also have some influence on the co-evolution of the design problem.

The automatic synthesis of embodied creatures through artificial evolution has become a key area of research in robotics, artificial life and the cognitive sciences. However, the research has mainly focused on genetic encodings and fitness functions. Considerably less has been said about the role of controllers and how they affect the evolution of morphologies and behaviors in artificial creatures. Furthermore, the evolutionary algorithms used to evolve the controllers and morphologies are pre-dominantly based on a single objective or a weighted combination of multiple objectives, and a large majority of the behaviors evolved are for wheeled or abstract artifacts. In this thesis, we present a systematic study of evolving artificial neural network (ANN) controllers for the legged locomotion of embodied organisms. A virtual but physically accurate world is used to simulate the evolution of locomotion behavior in a quadruped creature. An algorithm using a self-adaptive Pareto multi-objective evolutionary optimization approach is developed. The experiments are designed to address five research aims investigating: (1) the search space characteristics associated with four classes of ANNs with different connectivity types, (2) the effect of selection pressure from a self-adaptive Pareto approach on the nature of the locomotion behavior and capacity (VC-dimension) of the ANN controller generated, (3) the effciency of the proposed approach against more conventional methods of evolutionary optimization in terms of computational cost and quality of solutions, (4) a multi-objective approach towards the comparison of evolved creature complexities, (5) the impact of relaxing certain morphological constraints on evolving locomotion controllers. The results showed that: (1) the search space is highly heterogeneous with both rugged and smooth landscape regions, (2) pure reactive controllers not requiring any hidden layer transformations were able to produce sufficiently good legged locomotion, (3) the proposed approach yielded competitive locomotion controllers while requiring significantly less computational cost, (4) multi-objectivity provided a practical and mathematically-founded methodology for comparing the complexities of evolved creatures, (5) co-evolution of morphology and mind produced significantly different creature designs that were able to generate similarly good locomotion behaviors. These findings attest that a Pareto multi-objective paradigm can spawn highly beneficial robotics and virtual reality applications.

New Zealand’s isolation and periods of marine transgression have limited its biota to an extent which can be considered depauperate, even by island standards. Endemic vertebrates are rare and prominent invertebrate families, such as the renowned forest defoliators of the Lymantriidae, are absent. The proven vulnerability of the flora to introduced vertebrates reaffirms a belief in the invasiveness of islands and fuels the contingency plans aimed at averting similar devastation from further alien invertebrate defoliators. Nothofagus is a dominant element of the climax forests of New Zealand and the larger landmasses bordering the South Pacific Ocean. Assessments of the resistance to defoliation of continental and New Zealand species of Nothofagus, and a range of other forest genera endemic to New Zealand, was undertaken using bioassays of naïve polyphagous defoliators. The bioassays were undertaken in Europe, utilising gypsy moth, Lymantria dispar (Lepidoptera: Lymantriidae) and the fall webworm, Hyphantria cunea (Lepidoptera: Arctiidae) as defoliators, fed foliage plants growing in European arboreta. In New Zealand, bioassays utilised Australian painted apple moth, Teia anartoides (Lepidoptera: Lymantriidae) and tree species from local arboreta, gardens and natural populations. Larval growth rate was the primary parameter recorded to assess plant resistance. The relevance of growth rate was investigated by comparison with other recorded parameters and resistance to a surrogate pathogen, in the form of commercially available bio-insecticide. Larval growth rate was positively correlated with survivorship, potential fecundity, mating success and resistance to disease. The growth rate of larvae fed Nothofagus was positively correlated to the species-specific leaf nitrogen content. The results of the bioassays showed that despite the accepted paradigms, New Zealand’s flora was largely resistant to exotic defoliators. As an explanation of this apparent anomaly, the Island Resource Allocation (IRA) hypothesis was developed and posits that ‘the palatability iv of a plant to invertebrate herbivores is proportional to the geographic range of the plant’. The basis for the IRA hypothesis proposes a redefinition of the fundamental ecological principle of the species: area relationship. Islands, or similarly geographically constrained ecosystems, which support lower biodiversity, have impoverished trophic levels and consequently have weaker top-down regulation of herbivores by natural enemies. The IRA hypothesis argues that island ecosystem stability is achieved through the bottom-up process of plant defence. The IRA hypothesis was tested intra-specifically using bioassays using painted apple moth in which larvae were offered foliage of specimens from naturally discontinuous populations of Nothofagus truncata. The results supported the hypothesis in that the smallest populations of N. truncata exhibited the greatest resistance to the defoliator. The IRA hypothesis and a demonstrated mechanism for a differential resistance in Nothofagus species could resolve a number of enduring debates in ecology. Habitat area appears to explain the relative strengths of top-down and bottom-up regulation of herbivores. It also predicts the strengths of reciprocal evolution within the geographic mosaic of co-evolution and highlights the influence of biodiversity in invasive ecology. It may also help to resolve the contentious and extremely relevant debate of the role of biodiversity in ecosystem function.

The overall aim of this thesis is to look at some philosophical issues surrounding autonomous systems in society and war. These issues can be divided into three main categories. The first, discussed in papers I and II, concerns ethical issues surrounding the use of autonomous systems – where the focus in this thesis is on military robots. The second issue, discussed in paper III, concerns how to make sure that advanced robots behave ethically adequate. The third issue, discussed in papers IV and V, has to do with agency and responsibility. Another issue, somewhat aside from the philosophical, has to do with coping with future technologies, and developing methods for dealing with potentially disruptive technologies. This is discussed in papers VI and VII. Paper I systemizes some ethical issues surrounding the use of UAVs in war, with the laws of war as a backdrop. It is suggested that the laws of war are too wide and might be interpreted differently depending on which normative moral theory is used. Paper II is about future, more advanced autonomous robots, and whether the use of such robots can undermine the justification for killing in war. The suggestion is that this justification is substantially undermined if robots are used to replace humans to a high extent. Papers I and II both suggest revisions or additions to the laws or war. Paper III provides a discussion on one normative moral theory – ethics of care – connected to care robots. The aim is twofold: first, to provide a plausible and ethically relevant interpretation of the key term care in ethics of care, and second, to discuss whether ethics of care may be a suitable theory to implement in care robots. Paper IV discusses robots connected to agency and responsibility, with a focus on consciousness. The paper has a functionalistic approach, and it is suggested that robots should be considered agents if they can behave as if they are, in a moral Turing test. Paper V is also about robots and agency, but with a focus on free will. The main question is whether robots can have free will in the same sense as we consider humans to have free will when holding them responsible for their actions in a court of law. It is argued that autonomy with respect to norms is crucial for the agency of robots. Paper VI investigates the assessment of socially disruptive technological change. The coevolution of society and potentially disruptive technolgies makes decision-guidance on such technologies difficult. Four basic principles are proposed for such decision guidance, involving interdisciplinary and participatory elements. Paper VII applies the results from paper VI – and a workshop – to autonomous systems, a potentially disruptive technology. A method for dealing with potentially disruptive technolgies is developed in the paper. / <p>QC 20130911</p>