Real‐time causal message ordering in multimedia systems

Messages that are sent to and received by multiple sites need to have a consistent order imposed by all sites. Causal ordering allows the cause and effect relations of messages to be maintained. This paper presents an algorithm that ensures that multimedia data with real‐time deadlines are delivered to the application layer in causal order. The algorithm is designed to ensure that any message that arrives at a destination site before its deadline will be delivered to the application before the message expires. In addition, by focusing on a form of causal ordering violations caused by “the triangle inequality”, this algorithm has a low overhead with respect to the amount of information that must be appended to each message. This revised version was published online in June 2006 with corrections to the Cover Date.     

Analysis of the probability of transaction abort and throughput oftwo timestamp ordering algorithms for database systems

The author analyzes and compares the performance of two timestamp ordering concurrency control algorithms, namely, the basic and multiversion, for database systems. The multiversion algorithm improves the performance of the basic timestamp ordering algorithm by keeping multiple versions of data objects. The author discusses the performance enhancement in the multiversion algorithm over the basic algorithm. The author also discusses the storage overhead due to multiple versions of data objects in the multiversion algorithm. The exact performance model of these algorithms is so complex that it is impossible to find a closed-form solution. The author reduces the complexity of the analysis by analyzing a single transaction in isolation and reflects the presence of other transactions on the isolated transaction by the probability of conflict/abort. The analysis provides useful insight into the performance of these algorithms     

Optimal placement of piezoelectric patches over a smart structure

Control of structural vibrations has significant applications in manufacturing, infrastructure engineering, aerospace engineering and various consumer products. In last two decades, considerable attention has been focused to suppress structural vibrations using active vibration control technique. Various researchers have proposed various optimization criteria for optimal placement of piezoelectric patches over a smart structure to suppress vibrations using various optimization techniques. This paper presents a review of various optimization criteria and techniques that have been used by various researchers in the field of smart structures. Mathematical expressions of objective functions of twelve optimization criteria have been presented and their justifications have been reasoned. Step by step procedures of commonly used optimization techniques have also been presented.     

Effect of iron content on permeability and power loss characteristics of Li0.35Cd0.3Fe2.35O4 and Li0.35Zn0.3Fe2.35O4

Substituted lithium ferrites having the chemical formula, Li_0.35Cd_0.3Fe_2.35O₄ and Li_0.35Zn_0.3Fe_2.35O₄, with different iron (metal) contents (2, 4, 6, 8 and 10) in wt% have been prepared by solid-state technique. Complex permeability and power loss of all samples have been measured by network analyser in the frequency range of 50–5000 kHz. Magnetic properties like saturation magnetization, coercivity, retentivity have been measured by vibrating sample magnetometer (VSM). The permeability of cadmium doped lithium ferrites exhibited higher values than zinc doped lithium ferrites. The power loss of cadmium doped lithium ferrites is lesser as compared to zinc doped lithium ferrites in the frequency range of 50–5000 kHz and at flux density of 10 mT. The behaviour of power loss with flux density has been found near about same for both series. Magnetic and power loss behaviour of the samples suggest that a small amount of Fe content can improve the properties of ferrite samples for microwave devices.     

Optimum power from a solar thermal power plant using solar concentrators

In this paper, the optimum temperature of operation of a solar concentrator and thus the maximum power obtained from a solar thermal power plant has been calculated. Results are plotted graphically and discussed.     

An experimentally validated thermo-mechanical model for the prediction of thermal contact conductance

A predictive model for estimating thermal contact conductance between two nominally flat metallic rough surfaces has been developed and experimentally validated. The predictive model consists of two complementary parts, the first of which is a surface deformation analysis to calculate the actual area of contact for each contact spot, while the second accounts for the effects of constriction resistance and gas gap conductance between the contacting surfaces. A surface characterization technique is developed which generates an equivalent 3-D surface profile from multiple 2-D profiles and determines the unique wavelengths of importance for the surface deformation and constriction resistance models. For given surface profiles and material properties of two contacting surfaces, and a specified contact pressure, the surface characterization technique filters out non-essential wavelengths on the surface, after which the surface deformation analysis calculates the deformation and contact area of each contacting asperity by considering three different modes of deformation, namely, elastic, elastic–plastic, and plastic. The constriction resistance model is then used to calculate the constriction resistance for each contacting asperity based on the area of contact and radius of curvature of the asperity. The constriction resistance values for all the contacting asperities are then used to calculate the total thermal contact conductance. An experimental facility has also been constructed to measure thermal contact conductance of interfaces to verify the results of the predictive model. Good agreement has been found between the model predictions and experimental measurements, validating the modeling approach.     

Normalized Kemeny and Snell distance: a novel metric for quantitative evaluation of rank-order similarity of images

There are needs for evaluating rank order-based similarity between images. Region importance maps from image understanding algorithms or human observer studies are ordered rankings of the pixel locations. We address three problems with Kemeny and Snell's distance (d/sub KS/), an existing measure from ordinal ranking theory, when applied to images: its high-computational cost, its bias in favor of images with sparse histograms, and its image-size dependent range of values. We present a novel computationally efficient algorithm for computing d/sub KS/ between two images and we derive a normalized form d/sub KS/ with no bias whose range is independent of image size. For evaluating similarity between images that can be considered as ordered rankings of pixels, d/sub KS/ is subjectively superior to cross correlation.