L’efficacité contestée du recours aux agents de santé communautaires pour la prise en charge du paludisme : évaluation du programme burkinabé dans les districts de Kaya et de Zorgho

Contexte. Le paludisme provoque annuellement le décès d’environ 25 000 enfants de moins de cinq ans au Burkina Faso. Afin d’améliorer un accès rapide à des traitements efficaces, les autorités burkinabées ont introduit en 2010 la prise en charge du paludisme par les agents de santé communautaires (ASC). Alors que son efficacité a été démontrée dans des études contrôlées, très peu d’études ont évalué cette stratégie implantée dans des conditions naturelles et à l’échelle nationale. Objectif. L’objectif central de cette thèse est d’évaluer, dans des conditions réelles d’implantation, les effets du programme burkinabé de prise en charge communautaire du paludisme sur le recours aux soins des enfants fébriles. Les objectifs spécifiques sont : (1) de sonder les perceptions des ASC à l’égard du programme et explorer les facteurs contextuels susceptibles d’affecter leur performance ; (2) d’estimer le recours aux ASC par les enfants fébriles et identifier ses déterminants ; (3) de mesurer, auprès des enfants fébriles, le changement des pratiques de recours aux soins induit par l’introduction d’une intervention concomitante – la gratuité des soins dans les centres de santé. Méthodes. L’étude a été conduite dans deux districts sanitaires similaires, Kaya et Zorgho. Le devis d’évaluation combine des volets qualitatifs et quantitatifs. Des entrevues ont été menées avec tous les ASC de la zone à l’étude (N=27). Des enquêtes ont été répétées annuellement entre 2011 et 2013 auprès de 3002 ménages sélectionnés aléatoirement. Les pratiques de recours aux soins de tous les enfants de moins de cinq ans ayant connu un récent épisode de maladie ont été étudiées (N2011=707 ; N2012=787 ; N2013=831). Résultats. Les résultats montrent que le recours aux ASC est très modeste en comparaison de précédentes études réalisées dans des milieux contrôlés. Des obstacles liés à l’implantation du programme de prise en charge communautaire du paludisme ont été identifiés ainsi qu’un défaut de faisabilité dans les milieux urbains. Enfin, l’efficacité du programme communautaire a été négativement affectée par l’introduction de la gratuité dans les centres de santé. Conclusion. La prise en charge communautaire du paludisme rencontre au Burkina Faso des obstacles importants de faisabilité et d’implantation qui compromettent son efficacité potentielle pour réduire la mortalité infantile. Le manque de coordination entre le programme et des interventions locales concomitantes peut générer des effets néfastes et inattendus.

Identification of spectral lines of elements using artificial neural networks

Artificial neural networks (ANNs) are relatively new computational tools that have found extensive utilization in solving many complex real-world problems. This paper describes how an ANN can be used to identify the spectral lines of elements. The spectral lines of Cadmium (Cd), Calcium (Ca), Iron (Fe), Lithium (Li), Mercury (Hg), Potassium (K) and Strontium (Sr) in the visible range are chosen for the investigation. One of the unique features of this technique is that it uses the whole spectrum in the visible range instead of individual spectral lines. The spectrum of a sample taken with a spectrometer contains both original peaks and spurious peaks. It is a tedious task to identify these peaks to determine the elements present in the sample. ANNs capability of retrieving original data from noisy spectrum is also explored in this paper. The importance of the need of sufficient data for training ANNs to get accurate results is also emphasized. Two networks are examined: one trained in all spectral lines and other with the persistent lines only. The network trained in all spectral lines is found to be superior in analyzing the spectrum even in a noisy environment.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

‘Studies on some topics in product graphs’

For routing problems in interconnection networks it is important to find the shortest containers between any two vertices, since the w-wide diameter gives the maximum communication delay when there are up to w−1 faulty nodes in a network modeled by a graph. The concept of ‘wide diameter’ was introduced by Hsu [41] to unify the concepts of diameter and The concept of ‘domination’ has attracted interest due to its wide applications in many real world situations [38]. A connected dominating set serves as a virtual backbone of a network and it is a set of vertices that helps in routing. In this thesis, we make an earnest attempt to study some of these notions in graph products. This include, the diameter variability, the diameter vulnerability, the component factors and the domination criticality.connectivity

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Research Directions in Cyber Physical Systems

Cyber Physical systems (CPS) connect the physical world with cyber world. The events happening in the real world is enormous and most of it go unnoticed and information is lost. CPS enables to embed tiny smart devices to capture the data and send it to Internet for further processing. The entire set-up call for lots of challenges and open new research problems. This talk is a journey through the landscape of research problems in this emerging area.

Betweenness Centrality in Some Classes of Graphs

There are several centrality measures that have been introduced and studied for real world networks. They account for the different vertex characteristics that permit them to be ranked in order of importance in the network. Betweenness centrality is a measure of the influence of a vertex over the flow of information between every pair of vertices under the assumption that information primarily flows over the shortest path between them. In this paper we present betweenness centrality of some important classes of graphs.

Einige Ergebnisse von vergleichenden Untersuchungen in England und Deutschland zum Lehren und Lernen von Mathematik in Realitätsbezügen

In der Arbeit werden einige Resultate von vergleichenden empirischen Untersuchungen zu unterschiedlichen Konzeptionen eines realitätsbezogenen Mathematikunterrichts, wie sie in England und Deutschland häufig vertreten werden, dargestellt. Bei diesen Untersuchungen werden in verschiedenen Fallstudien, die u.a. auch strukturelle Unterschiede zwischen den Bildungssystemen in England und Deutschland und den zugrundeliegenden Erziehungsphilosophien berücksichtigen, Auswirkungen dieser Konzeptionen auf die Einstellung der Lernenden zum Mathematikunterricht, ihr Bild von Mathematik, ihr Verständnis mathematischer Begriffe und Methoden sowie ihre Fähigkeiten zur Anwendung mathematischer Methoden zum Lösen realer Problemaufgaben untersucht. Die hier dargestellten Erhebungen sind Teil eines längerdauernden Kollaborationsprojekts zwischen den Universitäten Exeter und Kassel.

Context as a Service

In the vision of Mark Weiser on ubiquitous computing, computers are disappearing from the focus of the users and are seamlessly interacting with other computers and users in order to provide information and services. This shift of computers away from direct computer interaction requires another way of applications to interact without bothering the user. Context is the information which can be used to characterize the situation of persons, locations, or other objects relevant for the applications. Context-aware applications are capable of monitoring and exploiting knowledge about external operating conditions. These applications can adapt their behaviour based on the retrieved information and thus to replace (at least a certain amount) the missing user interactions. Context awareness can be assumed to be an important ingredient for applications in ubiquitous computing environments. However, context management in ubiquitous computing environments must reflect the specific characteristics of these environments, for example distribution, mobility, resource-constrained devices, and heterogeneity of context sources. Modern mobile devices are equipped with fast processors, sufficient memory, and with several sensors, like Global Positioning System (GPS) sensor, light sensor, or accelerometer. Since many applications in ubiquitous computing environments can exploit context information for enhancing their service to the user, these devices are highly useful for context-aware applications in ubiquitous computing environments. Additionally, context reasoners and external context providers can be incorporated. It is possible that several context sensors, reasoners and context providers offer the same type of information. However, the information providers can differ in quality levels (e.g. accuracy), representations (e.g. position represented in coordinates and as an address) of the offered information, and costs (like battery consumption) for providing the information. In order to simplify the development of context-aware applications, the developers should be able to transparently access context information without bothering with underlying context accessing techniques and distribution aspects. They should rather be able to express which kind of information they require, which quality criteria this information should fulfil, and how much the provision of this information should cost (not only monetary cost but also energy or performance usage). For this purpose, application developers as well as developers of context providers need a common language and vocabulary to specify which information they require respectively they provide. These descriptions respectively criteria have to be matched. For a matching of these descriptions, it is likely that a transformation of the provided information is needed to fulfil the criteria of the context-aware application. As it is possible that more than one provider fulfils the criteria, a selection process is required. In this process the system has to trade off the provided quality of context and required costs of the context provider against the quality of context requested by the context consumer. This selection allows to turn on context sources only if required. Explicitly selecting context services and thereby dynamically activating and deactivating the local context provider has the advantage that also the resource consumption is reduced as especially unused context sensors are deactivated. One promising solution is a middleware providing appropriate support in consideration of the principles of service-oriented computing like loose coupling, abstraction, reusability, or discoverability of context providers. This allows us to abstract context sensors, context reasoners and also external context providers as context services. In this thesis we present our solution consisting of a context model and ontology, a context offer and query language, a comprehensive matching and mediation process and a selection service. Especially the matching and mediation process and the selection service differ from the existing works. The matching and mediation process allows an autonomous establishment of mediation processes in order to transfer information from an offered representation into a requested representation. In difference to other approaches, the selection service selects not only a service for a service request, it rather selects a set of services in order to fulfil all requests which also facilitates the sharing of services. The approach is extensively reviewed regarding the different requirements and a set of demonstrators shows its usability in real-world scenarios.

The Role of Epistemic Monitoring in Language Comprehension

In der psycholinguistischen Forschung ist die Annahme weitverbreitet, dass die Bewertung von Informationen hinsichtlich ihres Wahrheitsgehaltes oder ihrer Plausibilität (epistemische Validierung; Richter, Schroeder & Wöhrmann, 2009) ein strategischer, optionaler und dem Verstehen nachgeschalteter Prozess ist (z.B. Gilbert, 1991; Gilbert, Krull & Malone, 1990; Gilbert, Tafarodi & Malone, 1993; Herbert & Kübler, 2011). Eine zunehmende Anzahl an Studien stellt dieses Zwei-Stufen-Modell von Verstehen und Validieren jedoch direkt oder indirekt in Frage. Insbesondere Befunde zu Stroop-artigen Stimulus-Antwort-Kompatibilitätseffekten, die auftreten, wenn positive und negative Antworten orthogonal zum aufgaben-irrelevanten Wahrheitsgehalt von Sätzen abgegeben werden müssen (z.B. eine positive Antwort nach dem Lesen eines falschen Satzes oder eine negative Antwort nach dem Lesen eines wahren Satzes; epistemischer Stroop-Effekt, Richter et al., 2009), sprechen dafür, dass Leser/innen schon beim Verstehen eine nicht-strategische Überprüfung der Validität von Informationen vornehmen. Ausgehend von diesen Befunden war das Ziel dieser Dissertation eine weiterführende Überprüfung der Annahme, dass Verstehen einen nicht-strategischen, routinisierten, wissensbasierten Validierungsprozesses (epistemisches Monitoring; Richter et al., 2009) beinhaltet. Zu diesem Zweck wurden drei empirische Studien mit unterschiedlichen Schwerpunkten durchgeführt. Studie 1 diente der Untersuchung der Fragestellung, ob sich Belege für epistemisches Monitoring auch bei Informationen finden lassen, die nicht eindeutig wahr oder falsch, sondern lediglich mehr oder weniger plausibel sind. Mithilfe des epistemischen Stroop-Paradigmas von Richter et al. (2009) konnte ein Kompatibilitätseffekt von aufgaben-irrelevanter Plausibilität auf die Latenzen positiver und negativer Antworten in zwei unterschiedlichen experimentellen Aufgaben nachgewiesen werden, welcher dafür spricht, dass epistemisches Monitoring auch graduelle Unterschiede in der Übereinstimmung von Informationen mit dem Weltwissen berücksichtigt. Darüber hinaus belegen die Ergebnisse, dass der epistemische Stroop-Effekt tatsächlich auf Plausibilität und nicht etwa auf der unterschiedlichen Vorhersagbarkeit von plausiblen und unplausiblen Informationen beruht. Das Ziel von Studie 2 war die Prüfung der Hypothese, dass epistemisches Monitoring keinen evaluativen Mindset erfordert. Im Gegensatz zu den Befunden anderer Autoren (Wiswede, Koranyi, Müller, Langner, & Rothermund, 2013) zeigte sich in dieser Studie ein Kompatibilitätseffekt des aufgaben-irrelevanten Wahrheitsgehaltes auf die Antwortlatenzen in einer vollständig nicht-evaluativen Aufgabe. Die Ergebnisse legen nahe, dass epistemisches Monitoring nicht von einem evaluativen Mindset, möglicherweise aber von der Tiefe der Verarbeitung abhängig ist. Studie 3 beleuchtete das Verhältnis von Verstehen und Validieren anhand einer Untersuchung der Online-Effekte von Plausibilität und Vorhersagbarkeit auf Augenbewegungen beim Lesen kurzer Texte. Zusätzlich wurde die potentielle Modulierung dieser Effeke durch epistemische Marker, die die Sicherheit von Informationen anzeigen (z.B. sicherlich oder vielleicht), untersucht. Entsprechend der Annahme eines schnellen und nicht-strategischen epistemischen Monitoring-Prozesses zeigten sich interaktive Effekte von Plausibilität und dem Vorhandensein epistemischer Marker auf Indikatoren früher Verstehensprozesse. Dies spricht dafür, dass die kommunizierte Sicherheit von Informationen durch den Monitoring-Prozess berücksichtigt wird. Insgesamt sprechen die Befunde gegen eine Konzeptualisierung von Verstehen und Validieren als nicht-überlappenden Stufen der Informationsverarbeitung. Vielmehr scheint eine Bewertung des Wahrheitsgehalts oder der Plausibilität basierend auf dem Weltwissen – zumindest in gewissem Ausmaß – eine obligatorische und nicht-strategische Komponente des Sprachverstehens zu sein. Die Bedeutung der Befunde für aktuelle Modelle des Sprachverstehens und Empfehlungen für die weiterführende Forschung zum Vehältnis von Verstehen und Validieren werden aufgezeigt.

Strategies towards evaluation beyond scientific impact

Various research fields, like organic agricultural research, are dedicated to solving real-world problems and contributing to sustainable development. Therefore, systems research and the application of interdisciplinary and transdisciplinary approaches are increasingly endorsed. However, research performance depends not only on self-conception, but also on framework conditions of the scientific system, which are not always of benefit to such research fields. Recently, science and its framework conditions have been under increasing scrutiny as regards their ability to serve societal benefit. This provides opportunities for (organic) agricultural research to engage in the development of a research system that will serve its needs. This article focuses on possible strategies for facilitating a balanced research evaluation that recognises scientific quality as well as societal relevance and applicability. These strategies are (a) to strengthen the general support for evaluation beyond scientific impact, and (b) to provide accessible data for such evaluations. Synergies of interest are found between open access movements and research communities focusing on global challenges and sustainability. As both are committed to increasing the societal benefit of science, they may support evaluation criteria such as knowledge production and dissemination tailored to societal needs, and the use of open access. Additional synergies exist between all those who scrutinise current research evaluation systems for their ability to serve scientific quality, which is also a precondition for societal benefit. Here, digital communication technologies provide opportunities to increase effectiveness, transparency, fairness and plurality in the dissemination of scientific results, quality assurance and reputation. Furthermore, funders may support transdisciplinary approaches and open access and improve data availability for evaluation beyond scientific impact. If they begin to use current research information systems that include societal impact data while reducing the requirements for narrative reports, documentation burdens on researchers may be relieved, with the funders themselves acting as data providers for researchers, institutions and tailored dissemination beyond academia.

Alignment by Maximization of Mutual Information

A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach registering magnetic resonance (MR) images with computed tomography (CT) images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image called EMMA. As applied here the technique is intensity-based, rather than feature-based. It works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. Finally, we will describe a number of additional real-world applications that can be solved efficiently and reliably using EMMA. EMMA can be used in machine learning to find maximally informative projections of high-dimensional data. EMMA can also be used to detect and correct corruption in magnetic resonance images (MRI).

Teaching an Old Robot New Tricks: Learning Novel Tasks via Interaction with People and Things

As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.