Polygon offsetting using a Voronoi diagram and two stacks

The generation of the trimmed offset of a simple polygon is a conceptually simple but important and computationally non-trivial geometric problem for many applications. This article presents a linear time algorithm to compute a trimmed offset of a simple polygon consisting of arcs as well as line segments in a plane. Assuming that a Voronoi diagram of the polygon is available, the algorithm uses two stacks: T-stack and C-stack. The T-stack contains intersections between an offset and Voronoi edges, and the C-stack contains an offset chain which is a part of the trimmed offset. The contents of both stacks are pushed into and popped from the stacks in a synchronized fashion depending on the events that occur during the offsetting process.     

Invariant ellipsoid method for minimization of unmatched disturbances effects in sliding mode control

A new sliding mode control design algorithm for a linear and a class of nonlinear quasi-Lipschitz disturbed system is presented. It is based on the appropriate selection of the sliding surface via invariant ellipsoid method. The designed control guarantees minimization of unmatched disturbances effects to system motions in a sliding mode. The obtained theoretical results are approved by numerical simulations.     

State of the art of frameworks and middleware for facilitating mobile and ubiquitous learning development

The emergence of mobile and ubiquitous technologies as important tools to complement formal learning has been accompanied by a growing interest in their educational benefits and applications. Mobile devices can be used to promote learning anywhere and anytime, to foster social learning and knowledge sharing, or to visualize augmented reality applications for learning purposes. However, the development of these applications is difficult for many researchers because it requires understanding many different protocols; dealing with distributed schemas, processes, platforms, and services; learning new programming languages; and interacting with different hardware sensors and drivers. For that reason, the use of frameworks and middleware that encapsulate part of this complexity appears to be fundamental to the further development of mobile learning projects. This study analyzes the state of the art of frameworks and middleware devoted to simplifying the development of mobile and ubiquitous learning applications. The results can be useful to many researchers involved in the development of projects using these technologies by providing an overview of the features implemented in each of these frameworks.     

Position USBL/DVL sensor-based navigation filter in the presence of unknown ocean currents

This paper presents a novel approach to the design of globally asymptotically stable (GAS) position and velocity filters for Autonomous Underwater Vehicles (AUVs) based directly on the sensor readings of an Ultra-short Baseline (USBL) acoustic array system and a Doppler Velocity Log (DVL). The proposed methodology is based on an equivalent linear time-varying (LTV) system that fully captures the dynamics of the nonlinear system, allowing for the use of powerful linear system analysis and filtering design tools that yield GAS filter error dynamics. Numerical results using Monte Carlo simulations and comparison to the Bayesian Cramér Rao Bound (BCRB) reveal that the performance of the proposed filter is tight to this theoretical estimation error lower bound. In comparison with other approaches, the present solution achieves the same level of performance of the Extended Kalman Filter (EKF), which does not offer GAS guarantees, and outperforms other classical filtering approaches designed in inertial coordinates instead of the body-fixed coordinate frame.     

Text line and word segmentation of handwritten documents

In this paper, we present a segmentation methodology of handwritten documents in their distinct entities, namely, text lines and words. Text line segmentation is achieved by applying Hough transform on a subset of the document image connected components. A post-processing step includes the correction of possible false alarms, the detection of text lines that Hough transform failed to create and finally the efficient separation of vertically connected characters using a novel method based on skeletonization. Word segmentation is addressed as a two class problem. The distances between adjacent overlapped components in a text line are calculated using the combination of two distance metrics and each of them is categorized either as an inter- or an intra-word distance in a Gaussian mixture modeling framework. The performance of the proposed methodology is based on a consistent and concrete evaluation methodology that uses suitable performance measures in order to compare the text line segmentation and word segmentation results against the corresponding ground truth annotation. The efficiency of the proposed methodology is demonstrated by experimentation conducted on two different datasets: (a) on the test set of the ICDAR2007 handwriting segmentation competition and (b) on a set of historical handwritten documents.     

Linear-code multicast on parallel architectures

Parallel architectures involve communication with the aim of fast receiving of complete information at each node. Several architectures have been proposed to overcome the problem of high communicational and computational time complexity for transferring and receiving information. To reduce the complexity of such communication, we have implemented Linear Network Coding (LNC) in the parallel environment. For verification of our approach, we have considered some parallel architecture for implementing network coding approach and examined our results on these networks in a generic environment. We have formulated a standard approach for parallel networks, showing that by applying this approach effect of faulty nodes, information size and communication complexity exponentially decreases with code length.     

An industrial and academic perspective on plantwide control

The purpose of this paper is to stress the importance of selecting the right plantwide control structure and the need for a formalized approach that can encompass the many issues that arise in plantwide control design. Since the concept of process control design based on a holistic view of the process came about, the variety of procedures and approaches to the design problem has illustrated the difficulty of a unified approach. Using examples, the need and advantages of using a systematic approach based on considering the plant economics are highlighted. The examples deal with disturbance rejection, throughput maximization and economic optimization of plants consisting of parallel units.     

Decentralized coordination of autonomous swarms using parallel Gibbs sampling

In this paper we present analysis of a discrete-time, decentralized, stochastic coordination algorithm for a group of mobile nodes, called an autonomous swarm, on a finite spatial lattice. All nodes take their moves by sampling in parallel their locally perceived Gibbs distributions corresponding to a pairwise, nearest-neighbor potential. The algorithm has no explicit requirements on the connectedness of the underlying information graph, which varies with the swarm configuration. It is established that, with an appropriate annealing schedule, the algorithm results in swarm configurations converging to the (global) minimizers of a modified potential energy function. The extent of discrepancy between the modified and original potential energy functions is determined by the maximum node travel between time steps, and when such distance is small, the ultimate swarm configurations are close to the global minimizers of the original potential energy. Simulation results are further presented to illustrate the capability of the sampling algorithm in approximate global optimization for swarms.     

A constructive speed observer design for general Euler–Lagrange systems

Astolfi, Ortega, and Venkatraman (2010) recently proved the existence of a globally exponentially convergent speed observer for general Euler–Lagrange systems. Key to their result, is a function defined by certain integrals which cannot be solved a priori, and may not have explicit analytic solutions. In this paper, this obstacle to a constructive design is removed and equations that solve the speed observer problem are given in closed form. The design is further simplified by removing up to one third of the observer states used in Astolfi et al. (2010). With the significant reduction in complexity, the new observer is easily applied to estimate the angular velocities in a Furuta pendulum example.     

Computation of approximate optimal policies in a partially observed inventory model with rain checks

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite-dimensional states that are conditional distributions of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It then uses an appropriate functional basis to represent the state. Considering the speed and stability of computations, we choose truncated Chebyshev polynomials as the basis. We use Fast Fourier Transforms along with an appropriate discretization of inventory levels to speed up the computations. These main ideas are blended to obtain an iterative algorithm to solve a partially observed inventory model with rain checks. In this model, the inventory manager (IM) does not know the inventory level when it is positive. Otherwise, the IM fully observes it. This model provides a context to illustrate our methodology, which applies to other such models. Although this model has been studied mathematically in the literature, the use of our algorithm provides a numerical approximation of the optimal order quantities. These are compared to the orders released under a base mean-stock policy, where the IM replaces the unobserved inventory level with its mean and applies the well-known base stock policy. We show numerically that the optimal order quantity is very close to the base mean-stock order quantity, when the variance of the inventory distribution is small. When the mean of the inventory distribution is large, the optimal order quantity is more than the base mean-stock quantity, and it is the other way around when the mean is small or negative. These insights are explained via uncertainty and information effects and their interplay. We expect this interplay to show up in other partially observed inventory models.