The geometric element transformation method for mixed mesh smoothing

The geometric element transformation method (GETMe) is a geometry-based smoothing method for mixed and non-mixed meshes. It is based on a simple geometric transformation applicable to elements bounded by polygons with an arbitrary number of nodes. The transformation, if applied iteratively, leads to a regularization of the polygons. Global mesh smoothing is accomplished by averaging the new node positions obtained by local element transformations. Thereby, the choice of transformation parameters as well as averaging weights can be based on the element quality which leads to high quality results. In this paper, a concept of an enhanced transformation approach is presented and a proof for the regularizing effect of the transformation based on eigenpolygons is given. Numerical examples confirm that the GETMe approach leads to superior mesh quality if compared to other geometry-based methods. In terms of quality it can even compete with optimization-based techniques, despite being conceptually significantly simpler.     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.     

Infrared target-flare discrimination using a ZISC hardware neural network

The last generation of infrared imaging aircraft seekers and trackers uses pattern recognition algorithms to find and keep a lock on an aircraft in the presence of decoy flares. These algorithms identify targets, based on the features of the various objects in the missile’s field of view. Because modern both aircrafts and missiles fly faster than sound, speed of operation of the target identifier is critical. In this article, we propose a target recognition system that respects this time constraint. It is based on an artificial neural network implemented in hardware, as a set of parallel processors on a commercially available silicon chip called a ZISC, for zero instruction set computer. This chip would be integrated in the infrared missile seeker and tracker. We describe the characteristics of the images that the image processing module of this seeker and tracker extracts from the infrared video frames and show how to construct from these translation and rotation invariant features that can be used as input to the neural network. We determine the individual discriminating power of these features by constructing their histograms, which allows us to eliminate some as not being useful for our purpose. Finally, by testing our system on real data, we show that it has a 90% success rate in aircraft-flare identification, and a processing time that during this time, the aircrafts and missiles will have traveled only a few millimeters. Most of the images on which the neural network makes its mistakes are seen to be hard to recognize even by a human expert.     

Gender differences in digital music distribution methods

This study examines gender differences among Greek Internet users in using digital music distribution methods. First, a Web-based questionnaire was developed and placed on most popular Greek forums. Then, 300 Greek Internet users stated their opinions regarding digital music and the following downloading methods: 1) Http downloading, 2) P2P downloading, 3) Torrent downloading, and 4) Combined iTunes method. The results revealed that P2P programs are the first choice for downloading mp3. The responders were satisfied with the P2P’s easiness of use, the variety of songs and the no need to pay. However, they worried about P2P’s safety. Gender differences were identified in several areas. Music industry managers could consider these findings in their strategies to reach the consumers. Advertising companies could use the results to target differently male or female consumers.     

A queue based mutual exclusion algorithm

A new elegant and simple algorithm for mutual exclusion of N processes is proposed. It only requires shared variables in a memory model where shared variables need not be accessed atomically. We prove mutual exclusion by reformulating the algorithm as a transition system (automaton), and applying simulation of automata. The proof has been verified with the higher-order interactive theorem prover PVS. Under an additional atomicity assumption, the algorithm is starvation free, and we conjecture that no competing process is passed by any other process more than once. This conjecture was verified by model checking for systems with at most five processes.     

Utility function of TCP

Understanding the TCP congestion control mechanism from a global optimization point of view is not only important in its own right, but also crucial to the design of other transport layer traffic control protocols with provable properties. In this paper, we derive a global utility function and the corresponding optimal control law, known as TCP control law, which maximizes the global utility. The TCP control law captures the essential behaviors of TCP, including slow start, congestion avoidance, and the binary nature of congestion feedback in TCP. We find that the utility function of TCP is linear in the slow start phase and is proportional to the additive increase rate and approaches the well-known logarithm function as the data rate becomes large in the congestion avoidance phase. We also find that understanding the slow start phase with a fixed threshold is critical to the design of new transport layer control protocols to enable quality of service features. Finally, as an application, we design a Minimum Rate Guaranteed (MRG) traffic control law that shares the same utility function as the TCP control law. Our simulation study of the MRG control law indicates that it is indeed TCP friendly and can provide minimum rate guarantee as long as the percentage of network resource consumed by the MRG flows is moderately small.     

A passive tree-based backbone construction scheme for MANETs

Backbone-based broadcast schemes are effective in alleviating the broadcast storm problem in mobile ad hoc networks (MANETs). However, periodically hello packets used to maintain a backbone usually lead to extra control overhead. In this paper, passive tree-based backbone construction scheme (PTBCS) is proposed as a backbone construction scheme for MANETs. Different from other schemes, each node in PTBCS determines its role by intercepting packet transmissions in the air during a special waiting period. Hence, its most remarkable advantage is that there are no periodical packet transmissions specially for backbone construction. The property that the nodes selected by PTBCS make up a connected dominating set (CDS) of the network is proven with several ideal assumptions. Simulation results show that PTBCS is effective when compared with some other typical backbone construction schemes.     

An improved lossless data hiding scheme based on image VQ-index residual value coding

Copyright protection and information security have become serious problems due to the ever growing amount of digital data over the Internet. Reversible data hiding is a special type of data hiding technique that guarantees not only the secret data but also the cover media can be reconstructed without any distortion. Traditional schemes are based on spatial, discrete cosine transformation (DCT) and discrete wavelet transformation (DWT) domains. Recently, some vector quantization (VQ) based reversible data hiding schemes have been proposed. This paper proposes an improved reversible data hiding scheme based on VQ-index residual value coding. Experimental results show that our scheme outperforms two recently proposed schemes, namely side-match vector quantization (SMVQ)-based data hiding and modified fast correlation vector quantization (MFCVQ)-based data hiding.     

Efficient Leave-<Emphasis Type="Italic">m</Emphasis>-out Cross-Validation of Support Vector Regression by Generalizing Decremental Algorithm

We propose a computationally efficient method for cross-validation of the Support Vector Regression (SVR) by generalizing the decremental algorithm of SVR. Incremental and decremental algorithm of Support Vector Machines (SVM) ^{2, 8, 9)} efficiently update the trained SVM model when a single data point is added to or removed from the training set. The computational cost of leave-one-out cross-validation can be reduced using the decremental algorithm. However, when we perform leave-m-out cross-validation (m > 1), we have to repeatedly apply the decremental algorithm for each data point. In this paper, we extend the decremental algorithm of SVR^{8, 9)} in such a way that several data points can be removed more efficiently. Experimental results indicate that the proposed approach can reduce the computational cost. In particular, we observed that the number of breakpoints, which is the main computational cost of the involved path-following, were reduced from \({\mathcal O}(m)\) to \({\mathcal O}(\sqrt{m})\).     

An algebraic characterization of the optimum of regularized kernel methods

The representer theorem for kernel methods states that the solution of the associated variational problem can be expressed as the linear combination of a finite number of kernel functions. However, for non-smooth loss functions, the analytic characterization of the coefficients poses nontrivial problems. Standard approaches resort to constrained optimization reformulations which, in general, lack a closed-form solution. Herein, by a proper change of variable, it is shown that, for any convex loss function, the coefficients satisfy a system of algebraic equations in a fixed-point form, which may be directly obtained from the primal formulation. The algebraic characterization is specialized to regression and classification methods and the fixed-point equations are explicitly characterized for many loss functions of practical interest. The consequences of the main result are then investigated along two directions. First, the existence of an unconstrained smooth reformulation of the original non-smooth problem is proven. Second, in the context of SURE (Stein’s Unbiased Risk Estimation), a general formula for the degrees of freedom of kernel regression methods is derived.