To boldly go:an occam-π mission to engineer emergence

Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances. This paper describes a process-oriented architecture for fine-grained concurrent systems that enables experiments with such indirect engineering. Examples are presented showing the differing complex behaviours that can arise from minor (non-linear) adjustments to low-level parameters, the difficulties in suppressing the emergence of unwanted (bad) behaviour, the unexpected relationships between apparently unrelated physical phenomena (shown up by their separate emergence from the same primordial process swamp) and the ability to explore and engineer completely new physics (such as force fields) by their emergence from low-level process interactions whose mechanisms can only be imagined, but not built, at the current time

Looking Past, Looking Forward: America\u27s National Parks, Archaeology and Climate Change

America’s National Parks are rich with cultural history, flora, fauna and some of nature’s most impressive landscapes. As climate change continues to accelerate, these parks and their cultural and natural resources are being threatened. In this project, I will present a colorful, informational booklet that concentrates on 4 specific parks: Yellowstone National Park, National Park of American Samoa, Glacier Bay National Park and Mesa Verde National Park. I will focus on the archaeology and cultural significance of these parks, while also examining the ways that climate change is putting these, and other associated assets of the parks, at risk. I will tie the past and present together, while also exploring the future, and discussing possible climate-induced implications and the risks they pose to the cultural heritage of these parks. The goal of this project is to be an educational resource for national park staff, and other concerned citizens. While there are currently resources on many of the aspects I will discuss in this booklet, they are not comprehensive and most do not connect the archaeologically and culturally significant features of the parks with the threats of climate change. This project draws upon information from various articles, books and personal experiences and seeks to connect these two interesting, relevant topics in a new, thought-provoking way

Mobility in wireless sensor networks : advantages, limitations and effects

The primary aim of this thesis is to study the benefits and limitations of using a mobile base station for data gathering in wireless sensor networks. The case of a single mobile base station and mobile relays are considered. A cluster-based algorithm to determine the trajectory of a mobile base station for data gathering within a specified delay time is presented. The proposed algorithm aims for an equal number of sensors in each cluster in order to achieve load balance among the cluster heads. It is shown that there is a tradeoff between data-gathering delay and balancing energy consumption among sensor nodes. An analytical solution to the problem is provided in terms of the speed of the mobile base station. Simulation is performed to evaluate the performance of the proposed algorithm against the static case and to evaluate the distribution of energy consumption among the cluster heads. It is demonstrated that the use of clustering with a mobile base station can improve the network lifetime and that the proposed algorithm balances energy consumption among cluster heads. The effect of the base station velocity on the number of packet losses is studied and highlights the limitation of using a mobile base station for a large-scale network. We consider a scenario where a number of mobile relays roam through the sensing field and have limited energy resources that cannot reach each other directly. A routing scheme based on the multipath protocol is proposed, and explores how the number of paths and spread of neighbour nodes used by the mobile relays to communicate affects the network overhead. We introduce the idea of allowing the source mobile relay to cache multiple routes to the destination through its neighbour nodes in order to provide redundant paths to destination. An analytical model of network overhead is developed and verified by simulation. It is shown that the desirable number of routes is dependent on the velocity of the mobile relays. In most cases the network overhead is minimized when the source mobile relay caches six paths via appropriately distributed neighbours at the destination. A new technique for estimating routing-path hop count is also proposed. An analytical model is provided to estimate the hop count between source-destination pairs in a wireless network with an arbitrary node degree when the network nodes are uniformly distributed in the sensing field. The proposed model is a significant improvement over existing models, which do not correctly address the low-node density situation

A framework for local terrain deformation based on diffusion theory

Terrains have a key role in making outdoor virtual scenes believable and immersive as they form the support for every other natural element in the scene. Although important, terrains are often given limited interactivity in real-time applications. However, in nature, terrains are dynamic and interact with the rest of the environment changing shape on different levels, from tracks left by a person running on a gravel soil (micro-scale), to avalanches on the side of a mountain (macro-scale). The challenge in representing dynamic terrains correctly is that the soil that forms them is vastly heterogeneous and behaves differently depending on its composition. This heterogeneity introduces difficulties at different levels in dynamic terrains simulations, from modelling the large amount of different elements that compose the oil to simulating their dynamic behaviour. This work presents a novel framework to simulate multi-material dynamic terrains by taking into account the soil composition and its heterogeneity. In the proposed framework soil information is obtained from a material description map applied to the terrain mesh. This information is used to compute deformations in the area of interaction using a novel mathematical model based on diffusion theory. The deformations are applied to the terrain mesh in different ways depending on the distance of the area of interaction from the camera and the soil material. Deformations away from the camera are simulated by dynamically displacing normals. While deformations in a neighbourhood of the camera are represented by displacing the terrain mesh, which is locally tessellated to better fit the displacement. For gravel based soils the terrain details are added near the camera by reconstructing the meshes of the small rocks from the texture image, thus simulating both micro and macro-structure of the terrain. The outcome of the framework is a realistic interactive dynamic terrain animation in real-time

Fortschritte im unüberwachten Lernen und Anwendungsbereiche: Subspace Clustering mit Hintergrundwissen, semantisches Passworterraten und erlernte Indexstrukturen

Over the past few years, advances in data science, machine learning and, in particular, unsupervised learning have enabled significant progress in many scientific fields and even in everyday life. Unsupervised learning methods are usually successful whenever they can be tailored to specific applications using appropriate requirements based on domain expertise. This dissertation shows how purely theoretical research can lead to circumstances that favor overly optimistic results, and the advantages of application-oriented research based on specific background knowledge. These observations apply to traditional unsupervised learning problems such as clustering, anomaly detection and dimensionality reduction. Therefore, this thesis presents extensions of these classical problems, such as subspace clustering and principal component analysis, as well as several specific applications with relevant interfaces to machine learning. Examples include password guessing using semantic word embeddings and learning spatial index structures using statistical models. In essence, this thesis shows that application-oriented research has many advantages for current and future research.In den letzten Jahren haben Fortschritte in der Data Science, im maschinellen Lernen und insbesondere im unüberwachten Lernen zu erheblichen Fortentwicklungen in vielen Bereichen der Wissenschaft und des täglichen Lebens geführt. Methoden des unüberwachten Lernens sind in der Regel dann erfolgreich, wenn sie durch geeignete, auf Expertenwissen basierende Anforderungen an spezifische Anwendungen angepasst werden können. Diese Dissertation zeigt, wie rein theoretische Forschung zu Umständen führen kann, die allzu optimistische Ergebnisse begünstigen, und welche Vorteile anwendungsorientierte Forschung hat, die auf spezifischem Hintergrundwissen basiert. Diese Beobachtungen gelten für traditionelle unüberwachte Lernprobleme wie Clustering, Anomalieerkennung und Dimensionalitätsreduktion. Daher werden in diesem Beitrag Erweiterungen dieser klassischen Probleme, wie Subspace Clustering und Hauptkomponentenanalyse, sowie einige spezifische Anwendungen mit relevanten Schnittstellen zum maschinellen Lernen vorgestellt. Beispiele sind das Erraten von Passwörtern mit Hilfe semantischer Worteinbettungen und das Lernen von räumlichen Indexstrukturen mit Hilfe statistischer Modelle. Im Wesentlichen zeigt diese Arbeit, dass anwendungsorientierte Forschung viele Vorteile für die aktuelle und zukünftige Forschung hat

Two houses and the pain of separation in Tamang narratives from highland Nepal

At stake in my presentation are two central reflections. First is the question of whether or not power and resistance, hegemony and autonomy, interact in the same way between women and men, and more specifically between contemporary Tamang men and women from central highland Nepal, as has been described between colonial authorities and local peoples in wider South Asia. To the extent that gendered and other forms of domination are not isomorphic, of course, an important subsidiary question arises: if present understandings of colonialism and postcoloniality are inadequate to disassemble gender, then, is this more because gender is different, or more because subaltern studies are inadequate?Issue title; "South Asian Oral Traditions.

Kritische, kulturelle und multimodale Zugangsweisen zur Verwendung von Songs als literarische Texte im Fremdsprachenlernen

This paper provides an overview of recent scholarship on the value of using literature and song lyrics to help students of English as a Foreign Language improve their pronunciation, vocabulary, grammar and accuracy, linguistic competence and confidence, motivation, cultural knowledge, empathy and objectivity, and literary awareness. Literature and multimodal materials can help to promote better understanding of the cultural background of the target language, resulting in improved comprehension of context, dialect, and idioms through the use of language as it is spoken by native speakers. Students are more likely to learn if they are given materials that they enjoy, and if they can see immediate benefits from studying, so teachers are encouraged to promote cross-curricular applications of the skills taught in language classes. The paper then provides a case study to illustrate these principles with an analysis of the popular song “Let It Go” from the recent Disney film Frozen.U radu se donosi pregled novije znanstvene i stručne literature o uporabi književnosti u riječima pjesama kako bi se pomoglo učenicima engleskoga kao stranoga jezika da unaprijede svoj izgovor, rječnik, gramatičku točnost, jezičnu kompetenciju i samopouzdanje, motivaciju, poznavanje kulture, empatiju i objektivnost, kao i književnu svjesnost. Književni i višemodalni materijali mogu pomoći promicanju boljega razumijevanja kulturne podloge ciljnoga jezika, što također vodi boljemu razumijevanju konteksta, dijalekata i idioma u jezičnoj uporabi izvornih govornika. Uspješnost učenja jezika potencijalno je veća ako se učenicima ponude materijali u kojima nalaze zadovoljstvo i ako pritom iskuse neposrednu korist od učenja. Stoga se učiteljima preporuča poticanje primjene vještina usvojenih na nastavi jezika u drugim predmetima. Rad uključuje i analizu pojedinačnoga slučaja popularne pjesme „Let It Go“ iz nedavnoga Disneyeva filma Frozen, kojom se ilustriraju navedena načela.Der Beitrag bietet einen Überblick über die Ergebnisse der wissenschaftlichen Forschung zur Verwendung von literarischen Texten bzw. Songs als Hilfe beim Erwerb der korrekten Aussprache, des Vokabulars, der Grammatik, der Sprachkompetenz und des Selbstvertrauens, der Motivation, der kulturellen Kompetenzen, der Empathie und der Objektivität sowie der Förderung von literarischen Kompetenzen im Rahmen des englischen FSU. Literarische und multimodale Unterrichtsmaterialien können zum besseren Verständnis des kulturellen Hintergrunds der Zielsprache beitragen, wodurch auch ein besseres Verständnis des Kontextes, der Mundart und der seitens der Muttersprachler verwendeten Idiome gefördert wird. Dabei ist der Erfolg beim Erlernen einer Fremdsprache potenziell größer, bietet man den Schülern Unterrichtsmaterialien an, an denen sie Gefallen finden und anhand deren der Lernnutzen unmittelbar erfahrbar ist. Deshalb wird den Lehrenden empfohlen, die in anderen Fremdsprachen erworbenen Fähigkeiten und Fertigkeiten der Lernenden aufzugreifen. Im Beitrag wird als Beispiel für die Anwendung der angeführten Grundsätze die Analyse der neuerdings durch den Disney-Film Frozen populär gewordene Song „Let It Go“ vorgelegt

Evaluation of clustering results and novel cluster algorithms

Cluster analysis is frequently performed in many application fields to find groups in data. For example, in medicine, researchers have used gene expression data to cluster patients suffering from a particular disease (e.g., breast cancer), in order to detect new disease subtypes. Many cluster algorithms and methods for cluster validation, i.e., methods for evaluating the quality of cluster analysis results, have been proposed in the literature. However, open questions about the evaluation of both clustering results and novel cluster algorithms remain. It has rarely been discussed whether a) interesting clustering results or b) promising performance evaluations of newly presented cluster algorithms might be over-optimistic, in the sense that these good results cannot be replicated on new data or in other settings. Such questions are relevant in light of the so-called "replication crisis"; in various research disciplines such as medicine, biology, psychology, and economics, many results have turned out to be non-replicable, casting doubt on the trustworthiness and reliability of scientific findings. This crisis has led to increasing popularity of "metascience". Metascientific studies analyze problems that have contributed to the replication crisis (e.g., questionable research practices), and propose and evaluate possible solutions. So far, metascientific studies have mainly focused on issues related to significance testing. In contrast, this dissertation addresses the reliability of a) clustering results in applied research and b) results concerning newly presented cluster algorithms in the methodological literature. Different aspects of this topic are discussed in three Contributions. The first Contribution presents a framework for validating clustering results on validation data. Using validation data is vital to examine the replicability and generalizability of results. While applied researchers sometimes use validation data to check their clustering results, our article is the first to review the different approaches in the literature and to structure them in a systematic manner. We demonstrate that many classical cluster validation techniques, such as internal and external validation, can be combined with validation data. Our framework provides guidance to applied researchers who wish to evaluate their own clustering results or the results of other teams on new data. The second Contribution applies the framework from Contribution 1 to quantify over-optimistic bias in the context of a specific application field, namely unsupervised microbiome research. We analyze over-optimism effects which result from the multiplicity of analysis strategies for cluster analysis and network learning. The plethora of possible analysis strategies poses a challenge for researchers who are often uncertain about which method to use. Researchers might be tempted to try different methods on their dataset and look for the method yielding the "best" result. If only the "best" result is selectively reported, this may cause "overfitting" of the method to the dataset and the result might not be replicable on validation data. We quantify such over-optimism effects for four illustrative types of unsupervised research tasks (clustering of bacterial genera, hub detection in microbial association networks, differential network analysis, and clustering of samples). Contributions 1 and 2 consider the evaluation of clustering results and thus adopt a metascientific perspective on applied research. In contrast, the third Contribution is a metascientific study about methodological research on the development of new cluster algorithms. This Contribution analyzes the over-optimistic evaluation and reporting of novel cluster algorithms. As an illustrative example, we consider the recently proposed cluster algorithm "Rock"; initially deemed promising, it later turned out to be not generally better than its competitors. We demonstrate how Rock can nevertheless appear to outperform competitors via optimization of the evaluation design, namely the used data types, data characteristics, the algorithm’s parameters, and the choice of competing algorithms. The study is a cautionary tale that illustrates how easy it can be for researchers to claim apparent "superiority" of a new cluster algorithm. This, in turn, stresses the importance of strategies for avoiding the problems of over-optimism, such as neutral benchmark studies

The Monkeys and the Magical Cave (Rāmāyaṇa IV 49-52): Paradises, birds, and trees of gold and jewels

According to classical Indian aesthetic theory, adbhuta, the ‘marvellous’, is one of the nine canonical rasas, ‘moods’, that can be aroused in the audience by a theatrical or literary work, and Sanskrit epics largely resonate with adbhuta features. An episode of the Rāmāyaṇa (Rāmāyaṇa [Critical Edition], IV 49-52) recounts how, during their search for Sītā, a handful of monkeys led by Hanumān find themselves entering and remaining for some time almost imprisoned in a cave created by Maya, the great architect of the Asuras. The description of this cave is steeped in the imagery that connotes, in the Sanskrit epics and Buddhist literature of the early centuries CE, paradises and remote, fabulous places. Recurring elements of these places include vegetation made of gold and jewels and the presence of birds, and brilliance is a constant attribute.Secondo la teoria estetica classica indiana, adbhuta, il ‘meraviglioso’, è uno dei nove canonici rasa, ‘stati d'animo’, che possono essere suscitati nel pubblico da un lavoro teatrale o letterario, e l’epica sanscrita ne è colma. Un episodio del Rāmāyaṇa (Rāmāyaṇa [Critical Edition], IV 49-52) narra di come un manipolo di scimmie, capeggiate da Hanumān, durante la loro ricerca di Sītā si trovino a entrare e a restare per un periodo quasi imprigionate in una grotta creata da Maya, il grande architetto degli Asura. La descrizione di questa grotta è intrisa dell’immaginario che connota, nell’epica sanscrita e nella letteratura buddhista dei primi secoli e.c., i paradisi e i luoghi remoti e favolosi. Gli elementi ricorrenti di questi luoghi includono una vegetazione fatta di oro e gemme e la presenza di uccelli, e la luminosità è un attributo costante