Delay optimal control algorithm for a multiaccess fading channel with peak power constraint

We consider an optimal power and rate scheduling problem for a multiaccess fading wireless channel with the objective of minimising a weighted sum of mean packet transmission delay subject to a peak power constraint. The base station acts as a controller which, depending upon the buffer lengths and the channel state of each user, allocates transmission rate and power to individual users. We assume perfect channel state information at the transmitter and the receiver. We also assume a Markov model for the fading and packet arrival processes. The policy obtained represents a form of Indexability.

Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm

Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

Influence lines for bending under a ring load of a free shell, a shell embedded in a soft medium and a shell containing a soft core

Theoretical expressions for stresses and displacements have been derived for bending under a ring load of a free shell, a shell embedded in a soft medium, and a shell containing a soft core. Numerical work has been done for typical cases with an Elliot 803 Digital Computer and influence lines are drawn therefrom.

Stress concentration and load diffusion in rectangular panels with constant stress flanges

The stress concentration that occurs when load is diffused from a constant stress member into thin sheet is an important problem in the design of light weight structures. By using solutions in biharmonic polar-trigonometric series, the stress concentration can be effectively isolated so that highly accurate information necessary for design can be obtained. A method of analysis yielding high accuracy with limited effort is presented for rectangular panels with transverse edges free or supported by inextensional end ribs. Numerical data are given for panels with length twice the width.

What should I think; How should I feel? : The balancing of personal experiences and social norms in the outgroup attitude formation of youth

The present study focused on the associations between the personal experiences of intergroup contact, perceived social norms and the outgroup attitudes of Finnish majority and Russian-speaking minority youth living in Finland. The theoretical background of the study was derived from Allport s (1954) theory of intergroup contact (i.e., the contact hypothesis), social psychological research on normative influences on outgroup attitudes (e.g., Rutland, 2004; Stangor and Leary, 2006) and developmental psychological research on the formation of explicit (deliberate) and implicit (automatically activated) outgroup attitudes in adolescence (e.g., Barrett, 2007; Killen, McGlothlin and Henning, 2008). The main objective of the study was to shed light on the role of perceived social norms in the formation of outgroup attitudes among adolescents. First, the study showed that perceived normative pressure to hold positive attitudes towards immigrants regulated the relationship between the explicit and implicit expression of outgroup attitudes among majority youth. Second, perceived social norms concerning outgroup attitudes (i.e., the perceived outgroup attitudes of parents and peers) affected the relationship between intergroup contact and explicit outgroup attitudes depending on gender and group status. Positive social norms seem to be especially important for majority boys, who need both pleasant contact experiences and normative support to develop outgroup attitudes that are as positive as girls attitudes. The role of social norms is accentuated also among minority youth, who, contrary to majority youth with their more powerful and independent status position, need to reflect upon their attitudes and experiences of negative intergroup encounters in relation to the experiences and attitudes of their ingroup members. Third, the results are indicative of the independent effects of social norms and intergroup anxiety on outgroup attitudes: the effect of perceived social norms on the outgroup attitudes of youth seems to be at least as strong as the effect of intergroup anxiety. Finally, it was shown that youth evaluate intergroup contact from the viewpoint of their ingroup and society as a whole, not just based on their own experiences. In conclusion, the outgroup attitudes of youth are formed in a close relationship with their social environment. On the basis of this study, the importance of perceived social norms for research on intergroup contact effects among youth cannot be overlooked. Positive normative influences have the potential to break the strong link between rare and/or negative personal contact experiences and negative outgroup attitudes, and norms also influence the relationship between implicit and explicit attitude expression.

A Geometric Algorithm for Learning Oblique Decision Trees

In this paper we present a novel algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess goodness of hyperplanes at each node. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy, based on some recent variants of SVM, to assess the hyperplanes in such a way that the geometric structure in the data is taken into account. We show through empirical studies that our method is effective.

A fast time-domain algorithm for the assessment of tissue blood flow in laser-Doppler flowmetry

In this study, we derive a fast, novel time-domain algorithm to compute the nth-order moment of the power spectral density of the photoelectric current as measured in laser-Doppler flowmetry (LDF). It is well established that in the LDF literature these moments are closely related to fundamental physiological parameters, i.e. concentration of moving erythrocytes and blood flow. In particular, we take advantage of the link between moments in the Fourier domain and fractional derivatives in the temporal domain. Using Parseval's theorem, we establish an exact analytical equivalence between the time-domain expression and the conventional frequency-domain counterpart. Moreover, we demonstrate the appropriateness of estimating the zeroth-, first- and second-order moments using Monte Carlo simulations. Finally, we briefly discuss the feasibility of implementing the proposed algorithm in hardware.

A fast algorithm for macromolecular packing calculation

An algorithm to improve the computation time of packing calculations for macromolecules is presented. This is achieved by reducing the three-dimensional search to a small set of two-dimensional searches.

An approximate algorithm for the minimal vertex nested polygon problem

Given two simple polygons, the Minimal Vertex Nested Polygon Problem is one of finding a polygon nested between the given polygons having the minimum number of vertices. In this paper, we suggest efficient approximate algorithms for interesting special cases of the above using the shortest-path finding graph algorithms.

A reinforcement learning based algorithm for finite horizon Markov decision processes

We develop a simulation based algorithm for finite horizon Markov decision processes with finite state and finite action space. Illustrative numerical experiments with the proposed algorithm are shown for problems in flow control of communication networks and capacity switching in semiconductor fabrication.