We introduce a family of logics extending the lightweight Description Logic EL, that allows us to define concepts in an approximate way. The main idea is to use a graded membership function m, which for each individual and concept yields a number in the interval [0,1] expressing the degree to which the individual belongs to the concept. Threshold concepts C~t for ~ in {<,<=,>,>=} then collect all the individuals that belong to C with degree ~t. We further study this framework in two particular directions. First, we define a specific graded membership function deg and investigate the complexity of reasoning in the resulting Description Logic tEL(deg) w.r.t. both the empty terminology and acyclic TBoxes. Second, we show how to turn concept similarity measures into membership degree functions. It turns out that under certain conditions such functions are well-defined, and therefore induce a wide range of threshold logics. Last, we present preliminary results on the computational complexity landscape of reasoning in such a big family of threshold logics.

Thesis (MA (Philosophy))--University of Stellenbosch, 2005. / It seems to be a priori impossible to formulate any general theory or model that encompasses all of the properties of complexity. So, one must make do with partial solutions. A possible approach we propose is to take inspiration from quantum theory, since there seems to be a strong analogy between complex systems and quantum systems. Although we do not propose any literal application of quantum mechanical formalism to complexity, we suggest that the language of quantum mechanics is already so well developed - and for a much wider spectrum of problems than most theories - that it can serve as a model for complexity theory. There are many problems common to both complex systems and quantum systems and we suggest that it might be useful to test the applicability of aspects of the “language” of quantum mechanics to a general complex system. What we suggest here is an interdisciplinary talk led between the natural sciences and philosophy, which we believe is the only way in which to deal with complexity “as such”.

Thesis (MA (Philosophy))--University of Stellenbosch, 2010. / ENGLISH ABSTRACT: This thesis is a philosophical exposition of violence informed by two theoretical positions which confront complexity as a phenomenon. These positions are complexity theory and deconstruction. Both develop systemsbased understandings of complex phenomena in which relations of difference are constitutive of the meaning of those phenomena. There has been no focused investigation of the implications of complexity for the conceptualisation of violence thus far. In response to this theoretical gap, this thesis begins by distinguishing complexity theory as a general, trans-disciplinary field of study from critical complexity theory. The latter is used to develop a critique and criticism of epistemological foundationalism, emphasising the limits to knowledge and the normative and ethical dimension of knowledge and understanding. The epistemological break implied by this critique reiterates the epistemological shift permeating the work of, among others, Friedrich Nietzsche and Jacques Derrida. In this context, critical complexity theory begins to articulate the idea of violence on two levels: first, as an empirical, ethical problem in the system; and, secondly, as asymmetry and antagonism. Violence in this second sense is implicated in the dynamic relations of difference through which structure and meaning are generated in complex organisation. The sensitivity to difference and violence shared by critical complexity theory and deconstruction allows for the parallel reading of these philosophical perspectives; and for the supplementation and opening of critical complexity theory by deconstruction within the architecture of this thesis. This supplementation seeks to preserve the singularity of each perspective, while exploring the potential of their points of affinity and tension in the production of a coherent philosophical analysis of violence. Deconstruction offers a more developed understanding of violence and a wealth of related motifs: différance, framing, law, singularity, aesthetics and others. These motifs necessitate the inclusion of other philosophical voices, notably, that of Nietzsche, Arendt, Kant, Levinas, and Benjamin. In conversation with these authors, this thesis links violence to meaning, to its possibility, to its production and to the process by which meaning comes to change. Given these links, violence is conceptualised in relation to the notion of difference on three distinct levels. The first is the difference between elements in a complex system of meaning; the second is the notion of difference between systems or texts around which boundaries or frames can be drawn; and the third is the notion of difference between meaning and the absence of meaning. This discussion examines the relationship between this violence implicated in the constitution of meaning and the more colloquial understanding of violence as atrocity, as rape, murder and other socially, politically and ethically problematic expressions thereof. It is to empirical violence, following Derrida and Levinas, that we are called to respond and to intervene in the suffering of the other. The ethical and political necessity of response anchors this discussion of violence. And, it is towards the possibility of an adequate response – the possibility of an ethics sensitive to its own violence and a politics that is directed at the eradication of empirical violence – which this discussion navigates. / AFRIKAANSE OPSOMMING: Hierdie tesis is ’n filosofiese uiteensetting van geweld wat deur twee denkwyses ingelig word wat kompleksiteit as fenomeen konfronteer. Hierdie denkwyses is kompleksiteitsteorie en dekonstruksie. Altwee ontwikkel sisteemgebaseerde verduidelikings van komplekse fenomene waar verhoudings van verskille die betekenis van hierdie fenomene beslaan. Daar is tot dusver nog geen gefokusde ondersoek na die implikasies van kompleksiteit vir die konsepsualisering van geweld nie. As antwoord op hierdie teoretiese leemte, begin hierdie tesis deur kompleksiteitsteorie as ’n algemene, trans-dissiplinêre studierigting van kritiese kompleksiteitsteorie te onderskei. Laasgenoemde word gebruik om kritiese denke van epistemologiese grondslae te ontwikkel, en beklemtoon die perke op kennis en die normatiewe en etiese aspek van kennis en verstaan. Die epistemologiese verwydering wat deur hierdie kritiek geïmpliseer word, herhaal die epistemologiese verskuiwing wat die werk van onder andere Friedrich Nietzsche en Jacques Derrida, deurdring. In hierdie konteks begin kritiese kompleksiteitsteorie om die konsep van geweld op twee vlakke te verwoord: eerstens as ’n empiriese, etiese probleem in die stelsel en tweedens as asimmetrie en antagonisme. Geweld in die tweede opsig word in die dinamiese verhoudings van verskil geïmpliseer, waar struktuur en betekenis in komplekse organisasie gegenereer word. Die sensitiwiteit vir verskil en geweld wat deur kritiese kompleksiteitsteorie en dekonstruksie gedeel word neem parallelle lesings van hierdie filosofiese perspektiewe in ag; sowel as die aanvulling en oopmaak van kritiese kompleksiteitsteorie deur dekonstruksie binne die struktuur van hierdie tesis. Hierdie aanvulling wil die enkelvoudigheid van elke perspektief bewaar, terwyl dit die potensiaal van hul punte van verwantskap en spanning in die produksie van ’n koherente filosofiese analise van geweld verken. Dekonstruksie bied ’n meer ontwikkelde verstaan van geweld en ’n rykdom van verwante motiewe: différance, beraming, wet, enkelvoudigheid, estetika en ander. Hierdie motiewe noodsaak die insluiting van ander filosofiese stemme, soos Nietzsche, Arendt, Kant, Levinas en Benjamin. Hierdie tesis tree in gesprek met hierdie skrywers en skakel geweld aan betekenis, aan die moontlikheid, aan die produksie en aan die proses waardeur betekenis na verandering lei. Gegewe hierdie skakels, word geweld in verhouding tot die begrip van verskil op drie spesifieke vlakke gekonsepsualiseer. Die eerste is die verskil tussen elemente in ’n komplekse stelstel van betekenis; die tweede is die begrip van verskil tussen stelsels of tekste waar grense of rame om getrek kan word; en die derde is die begrip van verskil tussen betekenis en die afwesigheid van betekenis. Hierdie bespreking stel ondersoek in na die verhouding tussen hierdie geweld wat in die samestelling van betekenis geïmpliseer word en die meer alledaagse verstaan van geweld as wreedardigheid, as verkragting, moord en ander maatskaplike, politiese en etiese problematiese uitdrukkings daarvan. Ons word geroep om op empiriese geweld, in navolging van Derrida en Levinas, te reageer en in te gryp om die lyding van ander te keer. Die etiese en politiese noodsaaklikheid van reaksie dien as grondslag vir hierdie bespreking van geweld. Uiteindelik beweeg hierdie bespreking nader aan die moontlikheid van ’n voldoende reaksie – die moontlikheid van ’n etiek wat sensitief vir sy eie geweld is en ’n politiek wat op die uitwis van empiriese geweld gerig is.

Stream ciphers are private key cryptosystems used for security in communication and data transmission systems. Because they are used to encrypt streams of data, it is necessary for stream ciphers to use primitives that are easy to implement and fast to operate. LFSRs and the recently invented FCSRs are two such primitives, which give rise to certain security measures for the cryptographic strength of sequences, which we refer to as complexity measures henceforth following the convention. The linear (resp. N-adic) complexity of a sequence is the length of the shortest LFSR (resp. FCSR) that can generate the sequence. Due to the availability of shift register synthesis algorithms, sequences used for cryptographic purposes should have high values for these complexity measures. It is also essential that the complexity of these sequences does not decrease when a few symbols are changed. The k-error complexity of a sequence is the smallest value of the complexity of a sequence obtained by altering k or fewer symbols in the given sequence. For a sequence to be considered cryptographically ‘strong’ it should have both high complexity and high error complexity values. An important problem regarding sequence complexity measures is to determine good bounds on a specific complexity measure for a given sequence. In this thesis we derive new nontrivial lower bounds on the k-operation complexity of periodic sequences in both the linear and N-adic cases. Here the operations considered are combinations of insertions, deletions, and substitutions. We show that our bounds are tight and also derive several auxiliary results based on them. A second problem on sequence complexity measures useful in the design and analysis of stream ciphers is to determine the number of sequences with a given fixed (error) complexity value. In this thesis we address this problem for the k-error linear complexity of 2n-periodic binary sequences. More specifically: 1. We characterize 2n-periodic binary sequences with fixed 2- or 3-error linear complexity and obtain the counting function for the number of such sequences with fixed k-error linear complexity for k = 2 or 3. 2. We obtain partial results on the number of 2n-periodic binary sequences with fixed k-error linear complexity when k is the minimum number of changes required to lower the linear complexity.

Drawing upon the writing literature and the task-based language teaching literature, the study examined two cognitive complexity dimensions of L2 writing tasks: rhetorical task varying in reasoning demand and topic familiarity varying in the amount of direct knowledge of topics. Four rhetorical tasks were studied: narrative, expository, expo-argumentative, and argumentative tasks. Three topic familiarity tasks were investigated: personal-familiar, impersonal-familiar, and impersonal-less familiar tasks. Specifically, the study looked into the effects of these two cognitive complexity dimensions on L2 writing quality scores, their effects on complexity, accuracy, and fluency (CAF) of L2 production, and the predictive power of the CAF features on L2 writing scores for each task. Three hundred and seventy five Chinese university EFL students participated in the study, and each student wrote on one of the six writing tasks used to study the cognitive complexity dimensions. The essays were rated by trained raters using a holistic scale. Thirteen CAF measures were used, and the measures were all automated through computer tools. One-way ANOVA tests revealed that neither rhetorical task nor topic familiarity had an effect on the L2 writing scores. One-way MANOVA tests showed that neither rhetorical task nor topic familiarity had an effect on accuracy and fluency of the L2 writing, but that the argumentative essays were significantly more complex in global syntactic complexity features than the essays on the other rhetorical tasks, and the essays on the less familiar topic were significantly less complex in lexical features than the essays on the more familiar topics. All-possible subsets regression analyses revealed that the CAF features explained approximately half of the variance in the writing scores across the tasks and that writing fluency was the most important CAF predictor for five tasks. Lexical sophistication was however the most important CAF predictor for the argumentative task. The regression analyses further showed that the best regression models for the narrative task were distinct from the ones for the expository and argumentative types of tasks, and the best models for the personal-familiar task were distinct from the ones for the impersonal tasks.

The search for a satisfactory model for complexity, meant as an intermediate condition between total order and total disorder, is still subject of debate in the scientific community. In this dissertation the emergence of non-Poisson renewal processes in several complex systems is investigated. After reviewing the basics of renewal theory, another popular approach to complexity, called modulation, is introduced. I show how these two different approaches, given a suitable choice of the parameter involved, can generate the same macroscopic outcome, namely an inverse power law distribution density of events occurrence. To solve this ambiguity, a numerical instrument, based on the theoretical analysis of the aging properties of renewal systems, is introduced. The application of this method, called renewal aging experiment, allows us to distinguish if a time series has been generated by a renewal or a modulation process. This method of analysis is then applied to several physical systems, from blinking quantum dots, to the human brain activity, to seismic fluctuations. Theoretical conclusions about the underlying nature of the considered complex systems are drawn.

Fractional calculus enables the possibility of using real number powers or complex number powers of the differentiation operator. The fundamental connection between fractional calculus and subordination processes is explored and affords a physical interpretation for a fractional trajectory, that being an average over an ensemble of stochastic trajectories. With an ensemble average perspective, the explanation of the behavior of fractional chaotic systems changes dramatically. Before now what has been interpreted as intrinsic friction is actually a form of non-Markovian dissipation that automatically arises from adopting the fractional calculus, is shown to be a manifestation of decorrelations between trajectories. Nonlinear Langevin equation describes the mean field of a finite size complex network at criticality. Critical phenomena and temporal complexity are two very important issues of modern nonlinear dynamics and the link between them found by the author can significantly improve the understanding behavior of dynamical systems at criticality. The subject of temporal complexity addresses the challenging and especially helpful in addressing fundamental physical science issues beyond the limits of reductionism.

In response to reductionist neoliberal approaches to organizational change that have been prevalent in American education since the 1980s, some educators have begun to employ a whole-systems approach to improving student learning. These approaches, based in complexity sciences, recognize the nonlinear, unpredictable nature of learning and the interconnected relationships among myriad factors that influence the teaching/learning that occurs in schools. In the summer preceding the 2011-2012 school year, a cohort of educators from California Unified School District participated in a 10-day training regarding human systems dynamics (HSD) and complexity thinking. Their goal was to build adaptive capacity throughout the district in the pursuit of improving student learning. Through analysis of the interviews from seven target participants from this training, this study investigates what target participants report regarding their use of HSD methods and models in their work in schools across the 2011-2012 school year. Findings indicate that target participants displayed distinct arcs of use of HSD methods/models. In addition, findings suggest that target participants’ need for support in learning and implementing HSD methods/models, the influence of systemic and individual history, and the role of agency affected their “arcs of use.” This study illuminates the ways in which HSD methods/models support both organizational change efforts and the ways in which teaching/learning occur in the classroom, including the applicability of HSD methods/models in building collaborative cultures and in helping students develop the kinds of thinking required in the use of 21st-century literacies.

Submitted by Marlene Aparecida de Souza Cardozo (mcardozo@pucsp.br) on 2016-08-27T18:02:06Z No. of bitstreams: 1 Bruna Mazzer Nogueira.pdf: 418701 bytes, checksum: 11957f3efac0c000d36d74cc72c622c4 (MD5) / Made available in DSpace on 2016-08-27T18:02:06Z (GMT). No. of bitstreams: 1 Bruna Mazzer Nogueira.pdf: 418701 bytes, checksum: 11957f3efac0c000d36d74cc72c622c4 (MD5) Previous issue date: 2016-05-20 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This is a theoretical research that aims to identify approaches between the following theories: Semiotics of Charles Sanders Peirce, historical-cultural of Lev S. Vygotsky, the complex theory of Edgar Morin and the connectivism of Siemens and Downes, prioritizing the issues surrounding education in the contemporary context. The method adopted included careful readings of the existant literature regarding the mentioned theories, the use of reading records and a case study that together allowed the careful and systematic analysis of the materials, as well as the organization of some of the key concepts of each theory, relevant to further discussions. The importance of the social nature of man was highlighted and related to its development. Language is understood as fundamental in the human development process and has been addressed here in a specific way, with emphasis on learning new words, considered linguistic signs, in a foreign language. It was analyzed and presented examples of both literature and real life, this experienced by the researcher, which allowed the establishment of approaches and reflections on the theories adopted. Finally, it became evident the need to promote an education able to reconcile different strategies, ideas and experiences of successful learning, recognizing the complexity of the phenomena and driving more discussions and studies for the existence of progress in the classroom and online education / Trata-se de uma pesquisa teórica que tem por objetivo identificar aproximações entre as teorias Semiótica de Charles Sanders Peirce, histórico-cultural de Lev S. Vigostski, o pensamento complexo de Edgar Morin e o conectivismo de Siemens e Downes, priorizando as questões que envolvem a educação no contexto contemporâneo. O método adotado contou com um cuidadoso levantamento bibliográfico das teorias mencionadas, a utilização de fichas de leitura e um estudo de campo que, juntos, permitiram a análise cuidadosa e sistemática dos materiais, além da organização de alguns dos principais conceitos de cada teoria, pertinentes às discussões posteriores. A importância do caráter social do homem foi destacada e relacionada ao seu desenvolvimento. A linguagem é compreendida como fundamental no processo de desenvolvimento humano e foi aqui abordada de maneira específica, com destaque para aprendizagem de palavras em idioma estrangeiro, consideradas signos linguísticos. São apresentados e analisados exemplos tanto da bibliografia quanto real, este vivenciado pela pesquisadora, que permitiram o estabelecimento de aproximações e reflexões sobre as teorias interacionistas adotadas. Por fim, tornou-se evidente a necessidade de se favorecer uma educação capaz de conciliar diferentes estratégias, ideias e experiências de aprendizagens de sucesso, reconhecendo a complexidade dos fenômenos e impulsionando mais discussões e estudos para a existência de progressos na Educação presencial e online

As recentes inovações em técnicas de Aprendizado de Máquina levaram a uma ampla utilização de modelos inteligentes para resolver problemas complexos que são especialmente difíceis de computar com algoritmos e estruturas de dados convencionais. Em particular, pesquisas recentes em Processamento de Imagens e Vídeo mostram que é possível desenvolver modelos de Aprendizado de Máquina que realizam reconhecimento de objetos e até mesmo de ações com altos graus de confiança. Além disso, os últimos avanços em algoritmos de treinamento para Redes Neurais Profundas (Deep Learning Neural Networks) estabeleceram um importante marco no estudo de Aprendizado de Máquina, levando a descobertas promissoras em Visão Computacional e outras aplicações. Estudos recentes apontam que também é possível desenvolver modelos inteligentes capazes de reduzir drasticamente o espaço de otimização do modo de decisão em codificadores de vídeo com perdas irrelevantes em eficiência de compressão. Todos esses fatos indicam que Aprendizado de Máquina para redução de complexidade em aplicações de vídeo é uma área promissora para pesquisa. O objetivo desta tese é investigar técnicas baseadas em aprendizado para reduzir a complexidade das decisões da codificação HEVC, com foco em aplicações de codificação e transcodificação rápidas. Um perfilamento da complexidade em codificadores é inicialmente apresentado, a fim de identificar as tarefas que requerem prioridade para atingir o objetivo dessa tese. A partir disso, diversas variáveis e métricas são extraídas durante os processos de codificação e decodificação para avaliar a correlação entre essas variáveis e as decisões de codificação associadas a essas tarefas. Em seguida, técnicas de Aprendizado de Máquina são empregadas para construir classificadores que utilizam a informação coletada para prever o resultado dessas decisões, eliminando o custo computacional necessário para computá-las. As soluções de codificação e transcodificação foram desenvolvidas separadamente, pois o tipo de informação é diferente em cada caso, mas a mesma metologia foi aplicada em ambos os casos. Além disso, mecanismos de complexidade escalável foram desenvolvidos para permitir o melhor desempenho taxa-compressão para um dado valor de redução de complexidade. Resultados experimentais apontam que as soluções desenvolvidas para codificação rápida atingiram reduções de complexidade entre 37% e 78% na média, com perdas de qualidade entre 0.04% e 4.8% (medidos em Bjontegaard Delta Bitrate – BD-BR). Já as soluções para trancodificação rápida apresentaram uma redução de 43% até 67% na complexidade, com BD-BR entre 0.34% e 1.7% na média. Comparações com o estado da arte confirmam a eficácia dos métodos desenvolvidos, visto que são capazes de superar os resultados atingidos por soluções similares. / The recent innovations in Machine Learning techniques have led to a large utilization of intelligent models to solve complex problems that are especially hard to compute with traditional data structures and algorithms. In particular, the current research on Image and Video Processing shows that it is possible to design Machine Learning models that perform object recognition and even action recognition with high confidence levels. In addition, the latest progress on training algorithms for Deep Learning Neural Networks was also an important milestone in Machine Learning, leading to prominent discoveries in Computer Vision and other applications. Recent studies have also shown that it is possible to design intelligent models capable of drastically reducing the optimization space of mode decision in video encoders with minor losses in coding efficiency. All these facts indicate that Machine Learning for complexity reduction in visual applications is a very promising field of study. The goal of this thesis is to investigate learning-based techniques to reduce the complexity of the HEVC encoding decisions, focusing on fast video encoding and transcoding applications. A complexity profiling of HEVC is first presented to identify the tasks that must be prioritized to accomplish our objective. Several variables and metrics are then extracted during the encoding and decoding processes to assess their correlation with the encoding decisions associated with these tasks. Next, Machine Learning techniques are employed to construct classifiers that make use of this information to accurately predict the outcome of these decisions, eliminating the timeconsuming operations required to compute them. The fast encoding and transcoding solutions were developed separately, as the source of information is different on each case, but the same methodology was followed in both cases. In addition, mechanisms for complexity scalability were developed to provide the best rate-distortion performance given a target complexity reduction. Experimental results demonstrated that the designed fast encoding solutions achieve time savings of 37% up to 78% on average, with Bjontegaard Delta Bitrate (BD-BR) increments between 0.04% and 4.8%. In the transcoding results, a complexity reduction ranging from 43% to 67% was observed, with average BD-BR increments from 0.34% up to 1.7%. Comparisons with state of the art confirm the efficacy of the designed methods, as they outperform the results achieved by related solutions.