We present a novel algorithm to reconstruct curves with self-intersections and multiple parts from unorganized strip-shaped points, which may have different local shape scales and sampling densities. We first extract an initial curve, a graph composed of polylines, to model the different structures of the points. Then a least-squares optimization is used to improve the geometric approximation. The initial curve is extracted in three steps: anisotropic farthest point sampling with an adaptable sphere, graph construction followed by non-linear region identification, and edge refinement. Our algorithm produces faithful results for points sampled from non-simple curves without pre-segmenting them. Experiments on many simulated and real data demonstrate the efficiency of our method, and more faithful curves are reconstructed compared to other existing methods.

We propose a method for procedural modeling and animation of cartoon water effects such as water caustics, foamy wake, and longshore currents. In our method we emulate the visual abstraction of these cartoon effects by the use of Voronoi diagrams and the motion abstraction by designing relevant controlling mechanisms corresponding to each effect. Our system enables the creation of cartoon effects with minimal intervention from the animator. Through high-level initial specification, the effects are animated procedurally in the style of hand-drawn cartoons.

Hyperspectral imagery generally contains a very large amount of data due to hundreds of spectral bands. Band selection is often applied firstly to reduce computational cost and facilitate subsequent tasks such as land-cover classification and higher level image analysis. In this paper, we propose a new band selection algorithm using sparse nonnegative matrix factorization (sparse NMF). Though acting as a clustering method for band selection, sparse NMF need not consider the distance metric between different spectral bands, which is often the key step for most common clustering-based band selection methods. By imposing sparsity on the coefficient matrix, the bands’ clustering assignments can be easily indicated through the largest entry in each column of the matrix. Experimental results showed that sparse NMF provides considerable insight into the clustering-based band selection problem and the selected bands are good for land-cover classification.

Wireless sensor networks (WSNs) are vulnerable to security attacks due to their deployment and resource constraints. Considering that most large-scale WSNs follow a two-tiered architecture, we propose an efficient and denial-of-service (DoS)-resistant user authentication scheme for two-tiered WSNs. The proposed approach reduces the computational load, since it performs only simple operations, such as exclusive-OR and a one-way hash function. This feature is more suitable for the resource-limited sensor nodes and mobile devices. And it is unnecessary for master nodes to forward login request messages to the base station, or maintain a long user list. In addition, pseudonym identity is introduced to preserve user anonymity. Through clever design, our proposed scheme can prevent smart card breaches. Finally, security and performance analysis demonstrates the effectiveness and robustness of the proposed scheme.

The network-on-chip (NoC) architecture is a main factor affecting the system performance of complicated multiprocessor systems-on-chips (MPSoCs). To evaluate the effects of the NoC architectures on communication efficiency, several kinds of techniques have been developed, including various simulators and analytical models. The simulators are accurate but time consuming, especially in large space explorations of diverse network configurations; in contrast, the analytical models are fast and flexible, providing alternative methods for performance evaluation. In this paper, we propose a general analytical model to estimate the communication performance for arbitrary NoCs with wormhole routing and virtual channel flow control. To resolve the inherent dependency of successive links occupied by one packet in wormhole routing, we propose the routing path decomposition approach to generating a series of ordered link categories. Then we use the traditional queuing system to derive the fine-grained transmission latency for each network component. According to our experiments, the proposed analytical model provides a good approximation of the average packet latency to the simulation results, and estimates the network throughput precisely under various NoC configurations and workloads. Also, the analytical model runs about 10⁵ times faster than the cycle-accurate NoC simulator. Practical applications of the model including bottleneck detection and virtual channel allocation are also presented.

This paper addresses the problem of creating a geometric map with a mobile robot in a dynamic indoor environment. To form an accurate model of the environment, we present a novel map representation called the ‘grid vector’, which combines each vector that represents a directed line segment with a slender occupancy grid map. A modified expectation maximization (EM) based approach is proposed to evaluate the dynamic objects and simultaneously estimate the robot path and the map of the environment. The probability of each grid vector is evaluated in the expectation step and then used to distinguish the vector into static and dynamic ones. The robot path and map are estimated in the maximization step with a graph-based simultaneous localization and mapping (SLAM) method. The representation we introduce provides advantages on making the SLAM method strictly statistic, reducing memory cost, identifying the dynamic objects, and improving the accuracy of the data associations. The SLAM algorithm we present is efficient in computation and convergence. Experiments on three different kinds of data sets show that our representation and algorithm can generate an accurate static map in a dynamic indoor environment.

Based on our recent study on probability distributions for evolution in extremal optimization (EO), we propose a modified framework called EOSAT to approximate ground states of the hard maximum satisfiability (MAXSAT) problem, a generalized version of the satisfiability (SAT) problem. The basic idea behind EOSAT is to generalize the evolutionary probability distribution in the Bose-Einstein-EO (BE-EO) algorithm, competing with other popular algorithms such as simulated annealing and WALKSAT. Experimental results on the hard MAXSAT instances from SATLIB show that the modified algorithms are superior to the original BE-EO algorithm.

Low-frequency noises (LFN) and noise-like oscillations (NLO) in GaAs metal semiconductor field effect transistor (MESFET) channel current were investigated under sidegating bias conditions. It was found that the fluctuations of the channel current were directly dependent upon the sidegating bias. As the sidegating bias decreased, the amplitudes of the oscillations would increase correspondingly. Furthermore, the LFN and NLO would attenuate sharply when the sidegating bias increased to more than a certain voltage. Two mechanisms are presented to demonstrate that the effective substrate resistivity or the channel-substrate junction modulated by sidegating bias and deep level traps would take responsibilities for the LFN and NLO.

An addition is a fundamental arithmetic operation which is used extensively in many very large-scale integration (VLSI) systems such as application-specific digital signal processing (DSP) and microprocessors. An adder determines the overall performance of the circuits in most of those systems. In this paper we propose a novel 1-bit full adder cell which uses only eight transistors. In this design, three multiplexers and one inverter are applied to minimize the transistor count and reduce power consumption. The power dissipation, propagation delay, and power-delay produced using the new design are analyzed and compared with those of other designs using HSPICE simulations. The results show that the proposed adder has both lower power consumption and a lower power-delay product (PDP) value. The low power and low transistor count make the novel 8T full adder cell a candidate for power-efficient applications.

The S parameter expression of high-frequency models of the high electron mobility transistors (HEMTs) with basic feedback structure, especially the transmission gain S₂₁, is presented and analyzed. In addition, an improved feedback structure and its theory are proposed and demonstrated, in order to obtain a better gain-flatness through the mutual interaction between the series inductor and the parallel capacitor in the feedback loop. The optimization solution for the feedback amplifier can eliminate the negative impacts on transmission gain S₂₁ caused by things such as resonance peaks. Furthermore, our theory covers the shortage of conventional feedback amplifiers, to some extent. A wideband low-noise amplifier (LNA) with the improved feedback technology is designed based on HEMT. The transmission gain is about 20 dB with the gain variation of 1.2 dB from 100 MHz to 6 GHz. The noise figure is lower than 2.8 dB in the whole band and the amplifier is unconditionally stable.

In the online version of the original article, Fig. 11 was incorrect. The correct version is given.