An Optimized Content-Aware Authentication Scheme for Streaming JPEG-2000 Images Over Lossy Networks

This paper proposes an optimized content-aware authentication scheme for JPEG-2000 streams over lossy networks, where a received packet is consumed only when it is both decodable and authenticated. In a JPEG-2000 codestream, some packets are more important than others in terms of coding dependency and image quality. This naturally motivates allocating more redundant authentication information for the more important packets in order to maximize their probability of authentication and thereby minimize the distortion at the receiver. Towards this goal, with the awareness of its corresponding image content, we formulate an optimization framework to compute an authentication graph to maximize the expected media quality at the receiver, given specific authentication overhead and knowledge of network loss rate. System analysis and experimental results demonstrate that the proposed scheme achieves our design goal in that the rate-distortion (R-D) curve of the authenticated image is very close to the R-D curve when no authentication is required     

Multichannel Security Protocols

Multichannel security protocols transmit messages over multiple communication channels, taking into account each channel's security properties. Our first intentional use of these protocols goes back to a 1999 article that proposed physical contact for imprinting as opposed to the wireless channel used in subsequent operations. Only later did we understand three key points. First, explicit use of multiple channels in the same protocol can offer significant advantages for both security and usability. Second, explicitly stating the properties of the channel on which each protocol message is transmitted is useful for understanding one's own protocol in greater depth and therefore for addressing subtle vulnerabilities early on. Third, multichannel protocols existed long before we recognized them as such - think of the courier handcuffed to the briefcase carrying the code book that will later protect postal or telegraphic traffic. The paper presents a security protocol that exploit additional transmissions over lower-capacity channels, typically found in ubicomp environments, that offer a different combination of security properties.     

Analysis and synthesis of on-chip spiral inductors

This paper presents a physically based compact model for estimating high-frequency performance of spiral inductors. The model accurately accounts for skin and proximity effects in the metal conductors as well as eddy current losses in the substrate. The model shows excellent agreement with measured data mostly within 10% across a variety of inductor geometries and substrate dopings up to 20 GHz. A web-based spiral inductor synthesis and analysis tool COILS, which makes use of the compact models, is presented. An optimization algorithm using binary searches speeds up the synthesis of inductor designs.     

新型复合弹簧的研究

提出一种金属圆锥弹簧与橡胶圆锥弹簧复合而成的弹簧．分析表明：它可以应用于弹性耦合激励振动筛和座式直线振动筛。     

Performance model of interactive video-on-demand systems

An interactive video-on-demand (VoD) system allows users to access video services, such as movies, electronic encyclopedia, interactive games, and educational videos from video servers on a broadband network. This paper develops a performance evaluation tool for the system design. In particular, a user activity model is developed to describe the usage of system resources, i.e., network bandwidth and video server usage, by a user as it interacts with the service. In addition, we allow batching of user requests, and the effect of such batching is captured in a batching model. Our proposed queueing model integrates both the user activity and the batching model. This model can be used to determine the requirements of network bandwidth and video server and, hence, the trade-off in communication and storage costs for different system resource configurations     

Adaptive weighted outer-product learning associative memory

Associative-memory neural networks with adaptive weighted outer-product learning are proposed in this paper. For the correct recall of a fundamental memory (FM), a corresponding learning weight is attached and a parameter called signal-to-noise-ratio-gain (SNRG) is devised. The sufficient conditions for the learning weights and the SNRG's are derived. It is found both empirically and theoretically that the SNRG's have their own threshold values for correct recalls of the corresponding FM's. Based on the gradient-descent approach, several algorithms are constructed to adaptively find the optimal learning weights with reference to global- or local-error measure.     

A genetic algorithm for multiple molecular sequence alignment

MOTIVATION: Multiple molecular sequence alignment is among the most important and most challenging tasks in computational biology. The currently used alignment techniques are characterized by great computational complexity, which prevents their wider use. This research is aimed at developing a new technique for efficient multiple sequence alignment. APPROACH: The new method is based on genetic algorithms. Genetic algorithms are stochastic approaches for efficient and robust searching. By converting biomolecular sequence alignment into a problem of searching for optimal or near-optimal points in an 'alignment space', a genetic algorithm can be used to find good alignments very efficiently. RESULTS: Experiments on real data sets have shown that the average computing time of this technique may be two or three orders lower than that of a technique based on pairwise dynamic programming, while the alignment qualities are very similar. AVAILABILITY: A C program on UNIX has been written to implement the technique. It is available on request from the authors.