Variations on the Theme of Scarf's Counter-Example

We study the relation between the stability of a competitive equilibrium (CE)and the price adjustment mechanism used to attain that equilibrium point.Using two specific examples, a three-commodity exchange economy with a uniquecompetitive equilibrium (Scarf's global instability example) and atwo-commodity, two-trader type exchange economy with multiple competitiveequilibria, we show that the stability of a CE depends critically upon thedynamics of the price adjustment mechanism. A particular CE may be unstableunder one price adjustment mechanism but stable under another. The jointdynamics of the chosen price adjustment mechanism and the given economydetermines the overall stability of its competitive equilibrium. Our resultssuggest that context-rich studies of economic systems which focus on aspecific price adjustment mechanism may provide insights into the dynamics andstability of economic systems that are often not revealed through acontext-independent analysis.     

Detecting Ambiguities in Regression Problems using TSK Models

Regression refers to the problem of approximating measured data that are assumed to be produced by an underlying, possibly noisy function. However, in real applications the assumption that the data represent samples from one function is sometimes wrong. For instance, in process control different strategies might be used to achieve the same goal. Any regression model, trying to fit such data as good as possible, must fail, since it can only find an intermediate compromise between the different strategies by which the data were produced. To tackle this problem, an approach is proposed here to detect ambiguities in regression problems by selecting a subset of data from the total data set using TSK models, which work in parallel by sharing the data with each other in every step. The proposed approach is verified with artificial data, and finally utilised to real data of grinding, a manufacturing process used to generate smooth surfaces on work pieces.     

Fuzzy triangulation signature for detection of change in human emotion from face video image sequence

The present article proposes a geometry-based fuzzy relational technique for capturing gradual change in human emotion over time available from relevant face image sequences. As associated features, we make use of fuzzy membership arising out of five triangle signatures such as - (i) Fuzzy Isosceles Triangle Signature (FIS), (ii) Fuzzy Right Triangle Signature (FRS), (iii) Fuzzy Right Isosceles Triangle Signature (FIRS), (iv) Fuzzy Equilateral Triangle Signature (FES), and (v) Other Fuzzy Triangles Signature (OFS) to achieve the task of appropriate classification of facial transition from neutrality to one among the six expressions viz. anger (AN), disgust (DI), fear (FE), happiness (HA), sadness (SA) and surprise (SU). The effectiveness of the Multilayer Perceptron (MLP) classifier is tested and validated through 10 fold cross-validation method on three benchmark image sequence datasets namely Extended Cohn-Kanade (CK+), M&M Initiative (MMI), and Multimedia Understanding Group (MUG). Experimental outcomes are found to have achieved accuracy to the tune of 98.47%, 93.56%, and 99.25% on CK+, MMI, and MUG respectively vindicating the effectiveness by exhibiting the superiority of our proposed technique in comparison to other state-of-the-art methods in this regard.

     

Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.     

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.     

Network and device-level impacts: performance and reliability of active I/O storage systems

Distributed active storage architectures are designed to offload user-level processing to the peripheral from the host servers. In this paper, we report preliminary investigation on performance and fault recovery designs, as impacted by emerging storage interconnect protocols and state-of-the-art storage devices. Empirical results obtained using validated device-level and interconnect data demonstrate the significance of the said parameters on the overall system performance and reliability.     

Development of a Sensor Fusion Strategy for Robotic Application Based on Geometric Optimization

Fusion of multi-sensor information is an important technology, which is growing exponentially due to its tremendous application potential in many areas. Effective fusion of data from sensors is very critical in increasing an intelligent system's capability to accomplish complex tasks. Appropriate fusion technologies are needed to be developed specially when a system requires redundant sensors to be used. More the redundancy in sensors, more is the computational complexity for controlling the system and more is its intelligence level. This research presents a strategy developed for multiple sensor fusion, based on geometric optimization. Each sensor's uncertainty has been modeled using classical Lagrangian optimization techniques. However, the uniqueness and effectiveness of the present technique lies on the fact that starting from the optimized value as initial estimate the accuracy of the sensory information has further been improved up to any pre defined bounded range, by developing two architectures – FFA (fission–fusion architecture) and FDD (fusion in differential domain). Sufficient evidences and analyses have been provided in the paper to show its effectiveness in various applications.     

The stochastic queue center problem

This paper considers the Stochastic Queue Center problem, which seeks to locate a single facility with a center-type objective in an M/G/1 queue operating environment. The objective function that we consider is to minimize a positive weighted linear function of the square of the average response time and the variance of the response time to a call. The Stochastic Queue Center problem is discussed on both a discrete and a network location topology. When potential facility locations are restricted to a finite set of discrete points, an efficient algorithm is developed to solve for the optimal facility location parametrically in the arrival rate. By exploiting convexity properties of the objective function, we develop an efficient finite-step algorithm to find the Stochastic Queue Center on a network. The major conclusion of this work is that incorporating the variance term in the objective function has a major impact on the choice of the optimal location. We illustrate the results with an example drawn from a potential application of the model for locating an emergency transport center serving different municipalities in Camden County, NJ.