Certain nonlinear partially observable stochastic optimal controlproblems with explicit control laws equivalent to LEQG/LQG problems

This paper is concerned with partially observed stochastic optimal control problems when nonlinearities enter the dynamics of the unobservable state and the observations as gradients of potential functions. Explicit representations for the information state are derived in terms of a finite number of sufficient statistics. Consequently, the partially observed problem is recast as one of complete information with a new state generated by a modified version of the Kalman filter. When the terminal cost is quadratic in the unobservable state and includes the integral of the nonlinearities, the optimal control laws are explicitly computed, similar to linear-exponential-quadratic-Gaussian (LEQG) and linear-quadratic-Gaussian (LQG) tracking problems. The results are applicable to filtering and control of Hamiltonian systems     

Modeling wireless fading channels via stochastic differential equations: identification and estimation based on noisy measurements

This paper is concerned with modeling and identification of wireless channels using noisy measurements. The models employed are governed by stochastic differential equations (SDEs) in state space form, while the identification method is based on the expectation-maximization (EM) algorithm and Kalman filtering. The algorithm is tested against real channel measurements. The results presented include state space models for the channels, estimates of inphase and quadrature components, and estimates of the corresponding Doppler power spectral densities (DPSDs), from sample noisy measurements. Based on the available measurements, it is concluded that state space models of order two are sufficient for wireless flat fading channel characterization.     

Constitutive modelling and numerical simulation of multivariant phase transformation in superelastic shape‐memory alloys

This work concerns the micromechanical constitutive modelling, algorithmic implementation and numerical simulation of polycrystalline superelastic alloys under multiaxial loading. The model is formulated in finite deformations and incorporates the effect of texture. The numerical implementation is based on the constrained minimization of the Helmholtz free energy with dissipation. Simulations are conducted for thin tubes of Nitinol under tension–torsion, as well as for a simplified model of a biomedical stent. Copyright © 2004 John Wiley & Sons, Ltd.     

A computational method for the LU decomposition of rectangularmatrices and its implications to the realization of 2-D digital filters

The realization of 2-D digital filters based on the lower-upper triangular decomposition of the coefficient matrix is investigated. A numerical method based on the QA decomposition, which has some important characteristics, is proposed for reaching the LU structure. The coefficients in the final LU structure have values favorable to fixed-point arithmetic implementation. Furthermore, the QR structure can be used for the realization and possesses good numerical characteristics in terms of the approximate decomposition scheme. The symmetry in the impulse response coefficient matrix of an octagonally symmetric 2-D FIR filter is utilized to reduce the computational effort spent in the decomposition and the total number of multipliers in the final realization structure     

A Holistic Evolutionary and 3D Pharmacophore Modelling Study Provides Insights into the Metabolism,Function, and Substrate Selectivity of the Human Monocarboxylate Transporter 4 (hMCT4)

Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.     

Exploring the use of information visualization for digital libraries

This paper presents the findings from a study conducted to explore the current and future use of information visualization (IV) for digital libraries (DL). A series of query techniques and participatory design workshops were employed with the goal of actively involving users in identifying the key characteristics and applications of IV for DLs. The methodology employed, key findings and overall conclusions are presented and discussed.     

Power efficiency through tuple ranking in?wireless sensor network monitoring

In this paper, we present an innovative framework for efficiently monitoring Wireless Sensor Networks (WSNs). Our framework, coined KSpot, utilizes a novel top-k query processing algorithm we developed, in conjunction with the concept of in-network views, in order to minimize the cost of query execution. For ease of exposition, consider a set of sensors acquiring data from their environment at a given time instance. The generated information can conceptually be thought as a horizontally fragmented base relation R. Furthermore, the results to a user-defined query Q, registered at some sink point, can conceptually be thought as a view V. Maintaining consistency between V and R is very expensive in terms of communication and energy. Thus, KSpot focuses on a subset V??(?V) that unveils only the k highest-ranked answers at the sink, for some user defined parameter k. To illustrate the efficiency of our framework, we have implemented a real system in nesC, which combines the traditional advantages of declarative acquisition frameworks, like TinyDB, with the ideas presented in this work. Extensive real-world testing and experimentation with traces from UC-Berkeley, the University of Washington and Intel Research Berkeley, show that KSpot provides an up to 66% of energy savings compared to TinyDB, minimizes both the size and number of packets transmitted over the network (up to 77%), and prolongs the longevity of a WSN deployment to new scales.     

A Glance into Social and Evolutionary Aspects of an Artifact Ecology for Collaborative Learning through the Lens of Distributed Cognition

There is steadily growing interest in the design and evaluation of digitally enhanced spaces in the real-world where users use, combine, and appropriate different physical and digital tools based on the task at hand. Under the notion of “ubiquitous computing,” researchers have explored tools and theories to analyze, understand, and model users in complex socio-technical systems. Yet, even though theoretical approaches play a significant role in the work of practitioners, there is a general difficulty in applying them, pushing researchers to explore methodological frameworks with clearer guidelines. Using the distributed cognition for teamwork (DiCoT) framework, we study collaboration and communication patterns, physical movement, and social structures of two groups of learners working on a design problem as they evolve over a 3-month period. Through an in-depth investigation, we present detailed accounts of the social and evolutionary models of DiCoT for each group. Our analysis enriches the DiCoT framework by identifying five new principles: social emersion and social circles of privacy for the social model, and continuity, mutual adaptation, and semantics of body for the evolutionary model. This article contributes to HCI research by refining and extending the existing DiCoT framework and elaborating on two dimensions that have previously been under-developed in the literature.