Modern mobile robots navigate uncertain environments using complex compositions of camera, laser, and sonar sensor data. Manual calibration of these sensors is a tedious process that involves determining sensor behavior, geometry and location through model specification and system identification. Instead, we seek to automate the construction of sensor model geometry by mining uninterpreted sensor streams for regularities. Manifold learning methods are powerful techniques for deriving sensor structure from streams of sensor data. In recent years, the proliferation of manifold learning algorithms has led to a variety of choices for autonomously generating models of sensor geometry. We present a series of comparisons between different manifold learning methods for discovering sensor geometry for the specific case of a mobile robot with a variety of sensors. We also explore the effect of control laws and sensor boundary size on the efficacy of manifold learning approaches. We find that "motor babbling" control laws generate better geometric sensor maps than mid-line or wall following control laws and identify a novel method for distinguishing boundary sensor elements. We also present a new learning method, sensorimotor embedding, that takes advantage of the controllable nature of robots to build sensor maps.

In this paper a new completely unsupervised mesh segmentation algorithm is proposed, which is based on the PCA interpretation of the Laplacian eigenvectors of the mesh and on parametric clustering using Gaussian mixtures. We analyse the geometric properties of these vectors and we devise a practical method that combines single-vector analysis with multiple-vector analysis. We attempt to characterize the projection of the graph onto each one of its eigenvectors based on PCA properties of the eigenvectors. We devise an unsupervised probabilistic method, based on one-dimensional Gaussian mixture modeling with model selection, to reveal the structure of each eigenvector. Based on this structure, we select a subset of eigenvectors among the set of the smallest non-null eigenvectors and we embed the mesh into the isometric space spanned by this selection of eigenvectors. The final clustering is performed via unsupervised classification based on learning a multi-dimensional Gaussian mixture model of the embedded graph.

We present an interactive learning method that enables a user to iteratively refine a regression model. The user examines the output of the model, visualized as the vertical axis of a 2D scatterplot, and provides corrections by repositioning individual data points to the correct output level. Each repositioned data point acts as a control point for altering the learned model, using the geometry underlying the data. We capture the underlying structure of the data as a manifold, on which we compute a set of basis functions as the foundation for learning. Our results show that manifold-based interactive learning achieves dramatic improvement over alternative approaches.

The propagation of blood flow along the fetoplacental arterial system has been hypothesized to have a compensatory response to placental anomalies that may result in fetal stress. When the placenta generates increased resistance, the umbilical artery blood flow would decrease and in the worst scenario become absent, which will lead to fetal asphyxia and hypoxia. To compensate for the decreased oxygen supply from maternal placenta, the fetal middle cerebral arteries would become dilated leading to an increased diastolic flow, hence more oxygen. This compensatory phase , however, only lasts for a certain period of time, after which the hypoxia may lead to fetal demise or long term irreversible organ damages. In high-risk pregnancies, Doppler ultrasound technology is commonly used to monitor the fetoplacental arterial blood flow to assess fetal well being. If the anomalies occur prior to the end of the 40-week of gestation, surgical or aggressive medical intervention might be necessary to save the fetal life. Timing this intervention, however, is complex due to the fine balancing act to minimize potential risks from prematurity and organ damage vs. rescuing a fetal life through cesarean section or aggressive medical treatment or natural delivery at the earliest possible gestational age. A reasonable goal is to allow the pregnancy to continue to the point just before fetal damage occurs. To achieve that goal, various testing criteria, e.g. venous Doppler and fetal heart rate, have been used to identify de-compensation. In this work, we conducted computer simulation of the fetoplacental arterial blood flow of a Systemic Lupus Erythematosus (SLE) pregnancy based on Doppler blood flow readings taken during the 10-day period prior to the delivery. The simulation suggests that timing the delivery based on either Doppler waveform readings or fetal heart rates give similar pregnancy outcome.

A form of categorical perception occurs constantly outside the laboratory, as when different The history of research on speech perception is speakers produce the "same" word or when a speaker says replete with examples of nonlinearities, or threshold the "same" word quickly or slowly. This means that phenomena, relating acoustics to perception. These speech perception cannot be a simple concatenation of nonlinearities are essential in that they allow stable sound elements to yield syllables, syllables to yield communication despite variation in the acoustic signal words, or words to yield sentences. The interdependency across speakers, emphasis, background noise, etc. across scales reveals a complex system with nonlinearly Furthermore, the range of acoustic signals perceived as interacting elements that somehow allow veridical equivalent is much larger for speech sounds than for communication.

A peloton is a group of cyclists whose individual and collective energy expenditures are reduced when cyclists ride behind others in zones of reduced air pressure; this effect is known in cycling as ‘drafting’. As an aggregate of biological agents (human), a peloton is a complex dynamical system from which patterns of collective behaviour emerge, including phases and transitions between phases, through which pelotons oscillate. Coupling of cyclists’ energy expenditures when drafting is the basic peloton property from which self-organized collective behaviours emerge. Shown here are equations that model coupling behaviours. Environmental constraints are further parameters that affect peloton dynamics. Phases are defined by thresholds of aggregate energy expenditure; shown here are two different, but consistent, conceptual descriptions of these phase transitions. The first is an energetic model that describes phases in terms of individual, bi-coupled and globally-coupled energy output thresholds that define four observable changes in peloton behaviour. A second, economic model incorporates competition and cooperation dynamics: cooperation increases as power outputs and course constraints increase and population diminishes, and where competition and cooperation for resources results in peloton divisions into sub-pelotons whose average fitness levels are more closely homogeneous.

The availability of online documents coupled with emergent text mining methods has opened new research horizons. To achieve their potential, mining technologies need to be theoretically focused. We present data theory as a crucial component of text mining, and provide a substantive proto- theory from the synthesis of complex multigames, prototype concepts, and emotio-cognitive orientation fields. We discuss how the data theory presented informs the application of text mining to mining discourse(s) and how, in turn, this allows for modeling across contextual thresholds. Finally, the relationship between discourse mining, data theory, and thresholds is illustrated with an historical example, the events surrounding the 1992 civil war in Tajikistan.

A state is not alive, yet it performs many of the central enjoys few bonds of kinship: and residence depends upon functions of life like replication and adaptation to new conditions occupational specialization rather than blood relations. A to balance social protection and opportunity. As a modern state can declare war on behalf of the entire collectivity, lifelike system the rise of the modern state raises four sets reserving the right to declare mandatory participation of fundamental questions about its evolutionary design. A and to contract the area of private vengeance. They proclaim first set concerns how it became a sustainable, autonomously a monopoly of force and of law, while requiring citizens to replicating system, capable of evolution. All non-state agglomerations forgo violence; vengeance is not the responsibility of the offended such as empires or chiefdoms eventually stagnate party. Almost any crime against one member is a because they are closed systems that break down over crime against the state. Subgroups seeking vengeance are time (Weber). A state is an open system that must able to viewed as threatening to the order of the state.

Recent research identifies stochastic dominance as critical for understanding the relationship between network structure and diffusion. This paper introduces the concept of stochastic dominance, explains the theory linking stochastic dominance and diffusion, and applies this theory to a number of diffusion studies in the literature. The paper illustrates how the theory connects observations from different disciplines, and details when and how those observations can be generalized to broader classes of networks.

Early studies of public budgeting emphasized uncertainty Two of us (BJ and FB) have published a set of papers, in the decision-making environment. Budgeting in the books focusing on annual budget changes (Jones and absence of information about the impacts of decisions led Baumgartner 2005b). Leptokurtic distribution of percentual to an adjustment process rooted in simple decision rules budget changes were observed in a broad range of settings: and bargaining among interests. This led to marginal or small increases and small decreases of budgets and budget incremental adjustments from the budgetary status quo, components are the most frequent, but time to time large with all major actors wary of big changes to the budgetary increases and cutoffs are observed as well.