3D Hair sketching for real-time dynamic & key frame animations

Physically based simulation of human hair is a well studied and well known problem. But the “pure” physically based representation of hair (and other animation elements) is not the only concern of the animators, who want to “control” the creation and animation phases of the content. This paper describes a sketch-based tool, with which a user can both create hair models with different styling parameters and produce animations of these created hair models using physically and key frame-based techniques. The model creation and animation production tasks are all performed with direct manipulation techniques in real-time.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

Design improvements on rotary valve particle feeders used for obtaining suspended airflows

The back repulsion of low density particles, sticking of particles in feeder valve and interlocking and cohesive archs of particles in feeder hopper have been widely observed problems of a conventional rotary valve feeder used for feeding of granular particles into an airflow line. In this study, these problems of the rotary valve feeders were isolated by means of novel modifications to its conventional design. Results of the modifications showed that the modified feeder can be sensitively used to feed granular particles with mass feeding rates ranging between 5±0.15 and 85±0.85 g/s without encountering problems experienced with conventional rotary valves.     

Use of Warranties on Highway Projects: A Real Option Perspective

Since the introduction of warranty provisions in federal highway jobs, more and more state departments of transportation (DOTs) have considered the use of such provisions to protect their initial investment. This paper describes the pros and cons of warranty contracting in highway construction based on a survey of warranty practices in the United States. In particular, the need for state DOTs to buy a warranty for a well-built project is questioned. As an alternative, this paper introduces the warranty option, which gives the DOT the right to buy a warranty only if it becomes necessary at the end of construction. This option is exercised if the performance on site warrants it. This paper describes the mechanics of the warranty option and its advantages over the conventional warranty. A bid evaluation model is also developed for the warranty option approach.     

Methacrylic acid–acrylamide-g-poly(ethyleneterephthalate) fibres for urea hydrolysis

This paper presents the results of urease immobilization onto methacrylic acid–acrylamide grafted poly(ethyleneterephthalate) fibres. The graft yield strongly affected the maximum activity of the immobilized enzyme up to a value of 70·2%. Higher grafting caused a decline in urease activity and led to the degradation of the fibres. The minor changes observed in K_m and V_max demonstrated that the conformational changes existed during immobilization were not extensive. However, 70·2% methacrylic acid–acrylamide-g-fibres containing urease were more stable towards acidic and alkaline pH, high temperature and storage conditions compared with free enzyme. Apart from the increase in stability to heat inactivation, the initial enzymatic activity of the urease–fibre system remained almost unchanged even after 40 repeated assays corresponding to 10 h of operation in 4 months, indicating the excellent durability of the system.     

Synthesis of artificial neural networks by transconductors only

Hardware implementation of artificial neural networks has been attracting great attention recently. In this work, the analog VLSI implementation of artificial neural networks by using only transconductors is presented. The signal flow graph approach is used in synthesis. The neural flow graph is defined. Synthesis of various neural network configurations by means of neural flow graph is described. The approach presented in this work is technology independent. This approach can be applied to new neural network topologies to be proposed or used with transconductors designed in future technologies.     

CFAR processing with switching exponential smoothers for nonhomogeneous environments

Conventional constant false alarm rate (CFAR) methods use a fixed number of cells to estimate the background variance. For homogeneous environments, it is desirable to increase the number of cells, at the cost of increased computation and memory requirements, in order to improve the estimation performance. For nonhomogeneous environments, it is desirable to use less number of cells in order to reduce the number of false alarms around the clutter edges. In this work, we present a solution with two exponential smoothers (first order IIR filters) having different time-constants to leverage the conflicting requirements of homogeneous and nonhomogeneous environments. The system is designed to use the filter having the large time-constant in homogeneous environments and to promptly switch to the filter having the small time constant once a clutter edge is encountered. The main advantages of proposed Switching IIR CFAR method are computational simplicity, small memory requirement (in comparison to windowing based methods) and its good performance in homogeneous environments (due to the large time-constant smoother) and rapid adaptation to clutter edges (due to the small time-constant smoother).