965 resultados para feature based cost


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In this paper, we present the study and implementation of a low-cost system to detect the occurrences of tsunamis at significantly smaller laboratory scale. The implementation is easily scalable for real-time deployment. Information reported in this paper includes the experimentally recorded response from the pressure sensor giving an indication as well as an alarm at remote place for the detection of water turbulence similar to the case of tsunami. It has been found that the system developed works very well in the laboratory scale.

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This work describes the parallelization of High Resolution flow solver on unstructured meshes, HIFUN-3D, an unstructured data based finite volume solver for 3-D Euler equations. For mesh partitioning, we use METIS, a software based on multilevel graph partitioning. The unstructured graph used for partitioning is associated with weights both on its vertices and edges. The data residing on every processor is split into four layers. Such a novel procedure of handling data helps in maintaining the effectiveness of the serial code. The communication of data across the processors is achieved by explicit message passing using the standard blocking mode feature of Message Passing Interface (MPI). The parallel code is tested on PACE++128 available in CFD Center

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Multimedia mining primarily involves, information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the Internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution(STI). Content Based Image Retrieval(CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The paper proposes a CBIR System named STIRF (Shape, Texture, Intensity-distribution with Relevance Feedback) that uses a neural network for nonlinear combination of the heterogenous STI features. Further the system is self-adaptable to different applications and users based upon relevance feedback. Prior to retrieval of relevant images, each feature is first clustered independent of the other in its own space and this helps in matching of similar images. Testing the system on a database of images with varied contents and intensive backgrounds showed good results with most relevant images being retrieved for a image query. The system showed better and more robust performance compared to existing CBIR systems

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The phenomena of nonlinear I-V behavior and electrical switching find extensive applications in power control, information storage, oscillators, etc. The study of I-V characteristics and switching parameters is necessary for the proper application of switching materials and devices. In the present work, a simple low-cost electrical switching analyzer has been developed for the measurement of the electrical characteristics of switching materials and devices. The system developed consists of a microcontroller-based excitation source and a high-speed data acquisition system. The design details of the excitation source, its interface with the high-speed data acquisition system and personal computer, and the details of the application software developed for automated measurements are described. Typical I-V characteristics and switching curves obtained with the system developed are also presented to illustrate the capability of the instrument developed.

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Describes a new type of magnetoresistor based on magnetic composite material. This device exhibits a magnetoresistance which is comparable to that of conventional magnetoresistors but can be realised with a very low cost technology. The theoretical analysis of the magnetoresistance characteristics of this device is also described.

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Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

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The management and coordination of business-process collaboration experiences changes because of globalization, specialization, and innovation. Service-oriented computing (SOC) is a means towards businessprocess automation and recently, many industry standards emerged to become part of the service-oriented architecture (SOA) stack. In a globalized world, organizations face new challenges for setting up and carrying out collaborations in semi-automating ecosystems for business services. For being efficient and effective, many companies express their services electronically in what we term business-process as a service (BPaaS). Companies then source BPaaS on the fly from third parties if they are not able to create all service-value inhouse because of reasons such as lack of reasoures, lack of know-how, cost- and time-reduction needs. Thus, a need emerges for BPaaS-HUBs that not only store service offers and requests together with information about their issuing organizations and assigned owners, but that also allow an evaluation of trust and reputation in an anonymized electronic service marketplace. In this paper, we analyze the requirements, design architecture and system behavior of such a BPaaS-HUB to enable a fast setup and enactment of business-process collaboration. Moving into a cloud-computing setting, the results of this paper allow system designers to quickly evaluate which services they need for instantiationg the BPaaS-HUB architecture. Furthermore, the results also show what the protocol of a backbone service bus is that allows a communication between services that implement the BPaaS-HUB. Finally, the paper analyzes where an instantiation must assign additional computing resources vor the avoidance of performance bottlenecks.

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Synthesis of cost-optimal shell-and-tube heat exchangers is a difficult task since it involves a large number of parameters. An attempt is made in this article to simplify the process of choosing the parameter values that will minimize the cost of any heat exchanger satisfying a given heat duty and a particular set of constraints. The simplification is based on decoupling of the geometric and the thermal aspects of the problem. The concept of curves for cost-optimal design is introduced and is shown to simplify the synthesis process for shell-and-tube heat exchangers.

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Heat exchanger design is a complex task involving the selection of a large number of interdependent design parameters. There are no established general techniques for optimizing the design, though a few earlier attempts provide computer software based on gradient methods, case study methods, etc. The authors felt that it would be useful to determine the nature of the optimal and near-optimal feasible designs to devise an optimization technique. Therefore, in this article they have obtained a large number of feasible designs of shell and tube heat exchangers, intended to perform a given heat duty, by an exhaustive search method. They have studied how their capital and operating costs varied. The study reveals several interesting aspects of the dependence of capital and total costs on various design parameters. The authors considered a typical shell and tube heat exchanger used in an oil refinery. Its heat duty, inlet temperature and other details are given.

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This paper proposes a method of sharing power/energy between multiple sources and multiple loads using an integrated magnetic circuit as a junction between sources and sinks. It also presents a particular use of the magnetic circuit as an ac power supply, delivering sinusoidal voltage to load irrespective of the presence of the grid, taking only active power from the grid. The proposed magnetic circuit is a three-energy-port unit, viz.: 1) power/energy from grid; 2) power energy from battery-inverter unit; and 3) power/energy delivery to the load in its particular application as quality ac power supply (QPS). The product provides sinusoidal regulated output voltage, input power-factor correction, electrical isolation between the sources and loads, low battery voltage, and control simplicity. Unlike conventional series-shunt-compensated uninterruptible power supply topologies with low battery voltage, the isolation is provided using a single magnetic circuit that results in a smaller size and lower cost. The circuit operating principles and analysis, as well as simulation and experimental results, are presented for this QPS.

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A simple, cost-effective and environment-friendly pathway for preparing highly porous matrix of giant dielectric material CaCu3Ti4O12 (CCTO) through combustion of a completely aqueous precursor solution is presented. The pathway yields phase-pure and impurity-less CCTO ceramic at an ultra-low temperature (700 degrees C) and is better than traditional solid-state reaction schemes which fail to produce pure phase at as high temperature as 1000 degrees C (Li, Schwartz, Phys. Rev. B 75, 012104). The porous ceramic matrix on grinding produced CCTO powder having particle size in submicron order with an average size 300 nm. On sintering at 1050 degrees C for 5 h the powder shows high dielectric constants (>10(4) at all frequencies from 100 Hz to 100 kHz) and low loss (with 0.05 as the lowest value) which is suitable for device applications. The reaction pathway is expected to be extended to prepare other multifunctional complex perovskite materials. (C) 2010 Elsevier B.V. All rights reserved.

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A new range of programmable logic devices are revolutionizing the way complex digital hardware is designed and built all over the world. Being able to test these devices in order to validate and dynamically improve on the design is crucial. This paper describes a low-cost FPGA tester that can test SRAM based FPGAs in the laboratory.

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In the past few years there have been attempts to develop subspace methods for DoA (direction of arrival) estimation using a fourth?order cumulant which is known to de?emphasize Gaussian background noise. To gauge the relative performance of the cumulant MUSIC (MUltiple SIgnal Classification) (c?MUSIC) and the standard MUSIC, based on the covariance function, an extensive numerical study has been carried out, where a narrow?band signal source has been considered and Gaussian noise sources, which produce a spatially correlated background noise, have been distributed. These simulations indicate that, even though the cumulant approach is capable of de?emphasizing the Gaussian noise, both bias and variance of the DoA estimates are higher than those for MUSIC. To achieve comparable results the cumulant approach requires much larger data, three to ten times that for MUSIC, depending upon the number of sources and how close they are. This is attributed to the fact that in the estimation of the cumulant, an average of a product of four random variables is needed to make an evaluation. Therefore, compared to those in the evaluation of the covariance function, there are more cross terms which do not go to zero unless the data length is very large. It is felt that these cross terms contribute to the large bias and variance observed in c?MUSIC. However, the ability to de?emphasize Gaussian noise, white or colored, is of great significance since the standard MUSIC fails when there is colored background noise. Through simulation it is shown that c?MUSIC does yield good results, but only at the cost of more data.

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There exists a maximum in the products of the saturation properties such as T(p(c) - p) and p(T-c - T) in the vapour-liquid coexistence region for all liquids. The magnitudes of those maxima on the reduced coordinate system provide an insight to the molecular complexity of the liquid. It is shown that the gradients of the vapour pressure curve at temperatures where those maxima occur are directly given by simple relations involving the reduced pressures and temperatures at that point. A linear relation between the maximum values of those products of the form [p(r)(1 - T-r)](max) = 0.2095 - 0.2415 [T-r(1 - p(r))](max) has been found based on a study of 55 liquids ranging from non-polar monatomic cryogenic liquids to polar high boiling point liquids.

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Particulate reinforcements for polymers are selected with dual objective of improving composite properties and save on the total cost of the system. In the present study fly ash, an industrial waste with good properties is used as filler in epoxy and the compressive properties of such composites are studied. Particle surfaces are treated chemically using a silane-coupling agent to improve the compatibility with the matrix. The compressive properties of these are compared with those made of untreated fly ash particulates. Furthermore properties of fly ash composites with two different average particle sizes are first compared between themselves and then with those made using the as-received bimodal nature of particle size distribution. Microscopic observations of compression tested samples revealed a better adherence of the particles with the matrix in case of treated particles and regards the size effect the composites with lower average particle size showed improved strength at higher filler contents. Experimental values of strengths and modulii are compared with some of the theoretical models for composite properties. (C) 2002 Kluwer Academic Publishers.