Fuzzy parametric programming model for multi-objective integrated solid waste management under uncertainty

Solid waste management is increasingly becoming a challenging task for the municipal authorities due to increasing waste quantities, changing waste composition, decreasing land availability for waste disposal sites and increasing awareness about the environmental risk associated with the waste management facilities. The present study focuses on the optimum selection of the treatment and disposal facilities, their capacity planning and waste allocation under uncertainty associated with the long-term planning for solid waste management. The fuzzy parametric programming model is based on a multi-objective, multi-period system for integrated planning for solid waste management. The model dynamically locates the facilities and allocates the waste considering fuzzy waste quantity and capacity of waste management facility. The model addresses uncertainty in waste quantity as well as uncertainties in the operating capacities of waste management facilities simultaneously. It was observed that uncertainty in waste quantity is likely to affect the planning for waste treatment/disposal facilities more as compared with the uncertainty in the capacities of the waste management facilities. The relationship between increase in waste quantity and increase in the total cost/risk involved in waste management is found to be nonlinear. Therefore, it is possible that a marginal change in waste quantity could increase the total cost/risk substantially. The information obtained from the analysis of modeling results can be effectively used for understanding the effect of changing the priorities and objectives of planning decisions on facility selections and waste diversions.     

Rocking stiffness of mounting arrangements in electrical cabinets and control panels

Several studies have shown that the consideration of a rigid body-rocking mode in a cabinet is necessary to evaluate accurate incabinet spectra. Observations from finite element analyses are used to study cabinet rocking behavior and to show that accurate representation of the boundary conditions at the cabinet base is essential in the evaluation of correct rocking mode. Simple formulations for evaluating the rocking stiffness are developed by conducting detailed analytical studies for three different types of cabinet mounting arrangements. Availability of these formulations enables incorporation of a cabinet rocking mode in the Ritz vector approach [Nucl. Eng. Des. 190 (1990) 225] for evaluating the cabinet dynamic properties in significant mode and for generating the incabinet response spectra.     

Efficient approximation of correlated sums on data streams

In many applications such as IP network management, data arrives in streams and queries over those streams need to be processed online using limited storage. Correlated-sum (CS) aggregates are a natural class of queries formed by composing basic aggregates on (x, y) pairs and are of the form SUM{g(y) : x /spl les/ f(AGG(x))}, where AGG(x) can be any basic aggregate and f(), g() are user-specified functions. CS-aggregates cannot be computed exactly in one pass through a data stream using limited storage; hence, we study the problem of computing approximate CS-aggregates. We guarantee a priori error bounds when AGG(x) can be computed in limited space (e.g., MIN, MAX, AVG), using two variants of Greenwald and Khanna's summary structure for the approximate computation of quantiles. Using real data sets, we experimentally demonstrate that an adaptation of the quantile summary structure uses much less space, and is significantly faster, than a more direct use of the quantile summary structure, for the same a posteriori error bounds. Finally, we prove that, when AGG(x) is a quantile (which cannot be computed over a data stream in limited space), the error of a CS-aggregate can be arbitrarily large.     

On Advances in Statistical Modeling of Natural Images

Statistical analysis of images reveals two interesting properties: (i) invariance of image statistics to scaling of images, and (ii) non-Gaussian behavior of image statistics, i.e. high kurtosis, heavy tails, and sharp central cusps. In this paper we review some recent results in statistical modeling of natural images that attempt to explain these patterns. Two categories of results are considered: (i) studies of probability models of images or image decompositions (such as Fourier or wavelet decompositions), and (ii) discoveries of underlying image manifolds while restricting to natural images. Applications of these models in areas such as texture analysis, image classification, compression, and denoising are also considered.     

Hilbert-Schmidt lower bounds for estimators on matrix lie groupsfor ATR

Deformable template representations of observed imagery model the variability of target pose via the actions of the matrix Lie groups on rigid templates. In this paper, we study the construction of minimum mean squared error estimators on the special orthogonal group, SO(n), for pose estimation. Due to the nonflat geometry of SO(n), the standard Bayesian formulation of optimal estimators and their characteristics requires modifications. By utilizing Hilbert-Schmidt metric defined on GL(n), a larger group containing SO(n), a mean squared criterion is defined on SO(n). The Hilbert-Schmidt estimate (HSE) is defined to be a minimum mean squared error estimator, restricted to SO(n). The expected error associated with the HSE is shown to be a lower bound, called the Hilbert-Schmidt bound (HSB), on the error incurred by any other estimator. Analysis and algorithms are presented for evaluating the HSE and the HSB in cases of both ground-based and airborne targets     

Design and analysis of a video-on-demand server

The availability of high-speed networks, fast computers and improved storage technology is stimulating interest in the development of video on-demand services that provide facilities similar to a video cassette player (VCP). In this paper, we present a design of a video-on-demand (VOD) server, capable of supporting a large number of video requests with complete functionality of a remote control (as used in VCPs), for each request. In the proposed design, we have used an interleaved storage method with constrained allocation of video and audio blocks on the disk to provide continuous retrieval. Our storage scheme interleaves a movie with itself (while satisfying the constraints on video and audio block allocation. This approach minimizes the starting delay and the buffer requirement at the user end, while ensuring a jitter-free display for every request. In order to minimize the starting delay and to support more non-concurrent requests, we have proposed the use of multiple disks for the same movie. Since a disk needs to hold only one movie, an array of inexpensive disks can be used, which reduces the overall cost of the proposed system. A scheme supported by our disk storage method to provide all the functions of a remote control such as “fast-forwarding”, “rewinding” (with play “on” or “off”), “pause” and “play” has also been discussed. This scheme handles a user request independent of others and satisfies it without degrading the quality of service to other users. The server design presented in this paper achieves the multiple goals of high disk utilization, global buffer optimization, cost-effectiveness and high-quality service to the users.     

On fuzzy sobriety

This paper mainly shows that sober fuzzy topological spaces form the epireflective hull of the fuzzy Sierpinski space in the category of T₀-fuzzy topological spaces.     

Irregular, unknown light sources in dynamic global illumination

The goal in global illumination solutions for dynamic environments is to update a scene based on past scenes. For this difficult problem, current state of the art solutions are either not applicable, or unduly complex, when there are large changes in the illumination of unbounded number of objects. Such changes may be caused by the appearance of unexpected (at modeling time), irregular light sources.

We define a subset of dynamic environments in which new light sources may be user introduced, and implement solutions that complement existing schemes.     

A quick method for estimation of long-lived alpha activity in work atmospheres

In an operating plant quick reporting of the status of long-lived alpha activity concentrations in the work atmosphere is required. This will help in taking any corrective control measures if required. Radon and thoron progeny concentrations prevalent in the general atmosphere predominantly interfere in measurement of long-lived alpha activity in air. The alpha counts due to radon and thoron progeny vary widely in many atmospheric conditions. Therefore, conventionally, 5 days delay is allowed for all interfering activity to decay completely and true alpha air activity is then estimated. An approach for quick assessment of long-lived alpha activity by eliminating interference due to radon and thoron progeny in air, is made here. Based on the study of the pattern of alpha count rate due to radon and thoron progeny in air, a method for estimation of long-lived alpha activity within 8 hours delay time is suggested in this paper.