Estimating starting point of conduction of CMOS gates

To model effectively the output waveform and propagation delay of a CMOS gate, knowledge of the time point at which it starts to conduct is essential. An efficient method for calculating analytically this time point taking into account the structure of the gate and the input waveform, is introduced. Such a method can easily be integrated into a timing analysis system     

Video shot detection and condensed representation. a review

There is an urgent need to develop techniques that organize video data into more compact forms or extract semantically meaningful information. Such operations can serve as a first step for a number of different data access tasks such as browsing, retrieval, genre classification, and event detection. In this paper, we focus not on the high-level video analysis task themselves but on the common basic techniques that have been developed to facilitate them. These basic tasks are shot boundary detection and condensed video representation     

Neural networks and response surface polynomials for design of vehicle joints

Typically, design of a complex system starts by setting targets for its performance characteristics. Then, design engineers cascade these targets to the components and design the components to meet these targets. It is important to have efficient tools that check if a set of performance targets for a component corresponds to a feasible design and determine the dimensions and mass of this design. This paper describes a method to develop tools that relate response parameters that describe the performance of a component to the physical design variables that specify its geometry. Neural networks and response surface polynomials are used to rapidly predict the performance characteristics of the components given the component dimensions. The method is demonstrated on design of an automotive joint. The paper compares neural networks and response surface polynomials and shows that they are almost equally accurate for the problem considered.     

Selective Idling: Experiments in Transport Layer Energy Conservation

In this paper we consider the potential of using an aggressive form of energy conservation for mobile computing environments. The estimators for the round-trip time and round-trip time variance used by TCP are used to direct the transceiver of a mobile node to idle over extended periods of time when packet activity is not anticipated. In addition, we consider data link layer extensions that provide additional control information allowing the mobile to be further selective as to when to idle and when to activate the network interface device. Simulations are conducted to examine the performance of the proposed scheme under various levels of congestion in the fixed part of the network, from completely unloaded to fully congested. The simulations reveal that the technique is promising but its effectiveness depends crucially on the control of the maximum window size used by TCP and on accurate knowledge of the congestion conditions in the network.     

Subclass discriminant Nonnegative Matrix Factorization for facial image analysis

Nonnegative Matrix Factorization (NMF) is among the most popular subspace methods, widely used in a variety of image processing problems. Recently, a discriminant NMF method that incorporates Linear Discriminant Analysis inspired criteria has been proposed, which achieves an efficient decomposition of the provided data to its discriminant parts, thus enhancing classification performance. However, this approach possesses certain limitations, since it assumes that the underlying data distribution is unimodal, which is often unrealistic. To remedy this limitation, we regard that data inside each class have a multimodal distribution, thus forming clusters and use criteria inspired by Clustering based Discriminant Analysis. The proposed method incorporates appropriate discriminant constraints in the NMF decomposition cost function in order to address the problem of finding discriminant projections that enhance class separability in the reduced dimensional projection space, while taking into account subclass information. The developed algorithm has been applied for both facial expression and face recognition on three popular databases. Experimental results verified that it successfully identified discriminant facial parts, thus enhancing recognition performance.     

Multi-view human movement recognition based on fuzzy distances and linear discriminant analysis

In this paper, a novel multi-view human movement recognition method is presented. A novel representation of multi-view human movement videos is proposed that is based on learning basic multi-view human movement primitives, called multi-view dynemes. The movement video is represented in a new feature space (called dyneme space) using these multi-view dynemes, thus producing a time invariant multi-view movement representation. Fuzzy distances from the multi-view dynemes are used to represent the human body postures in the dyneme space. Three variants of Linear Discriminant Analysis (LDA) are evaluated to achieve a discriminant movement representation in a low dimensionality space. The view identification problem is solved either by using a circular block shift procedure followed by the evaluation of the minimum Euclidean distance from any dyneme, or by exploiting the circular shift invariance property of the Discrete Fourier Transform (DFT). The discriminant movement representation combined with camera viewpoint identification and a nearest centroid classification step leads to a high human movement classification accuracy.     

Soil-washing design methodology for a lead-contaminated sandy-soil

Soils located near high traffic roadways, particularly where renovations have taken place, typically exhibit elevated levels of trace metals in the upper soil horizon. Regulators are currently seeking an efficient method of site characterization and treatment system design which will lend itself to timely and environmentally efficacious clean-up. The soil investigated in this study was a silty sand collected near a bridge abutment for a major interstate highway. The soil had a total lead content of 1392 mg/kg. In addition, the soil contained a considerable fraction of organic carbon (approximately 6.3%). A sequential chemical extraction indicated that a fraction of contaminants were in labile soil phases and thus amenable to chemical extraction (soil-washing). A soil washing design methodology is presented based on surface chemistry and equilibrium stage operation. In this work, a double layer surface complexation model was used to describe equilibrium sorption behavior and a preliminary design of an ex-situ counter-current equilibrium stage extraction process is presented. Model calibration was conducted using sorption data obtained from a 1:40 solid to liquid ratio (s/l), adsorption edge. Model validation was accomplished with batch titration data and a 1:20 s/l, adsorption edge. The model accurately predicted leachable lead concentrations over a wide pH range. The required number of ideal equilibrium stages was highly sensitive to pH.