914 resultados para prison alternatives


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A comparative study has been carried out of R-12, 22, 125, 134a, 152a, 218, 245, 500, 502, 507 and 717 as working fluids in a vapour-compression refrigeration system. Two performance parameters were defined, which are expressed in reduced quantities for a corresponding-states comparison of these refrigerants in the temperature range -20 to 50-degrees-C. One is based on the product of temperature drop to pressure penalty ratio and the available volumetric heat of vaporisation at the evaporator; the other considers the effect of isentropic compression in the ideal gas state. It was shown that R-125, 507 and 218 could be better alternatives to R-12 than R-134a. Among these, R-218 has a lower maximum cycle pressure.

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brusive Jet Machining (AJM) or Micro Blast Machining is a non-traditional machining process, wherein material removal is effected by the erosive action of a high velocity jet of a gas, carrying fine-grained abrasive particles, impacting the work surface. The AJM process differs from conventional sand blasting in that the abrasive is much finer and the process parameters and cutting action are carefully controlled. The process is particularly suitable to cut intricate shapes in hard and brittle materials which are sensitive to heat and have a tendency to chip easily. In other words, AJM can handle virtually any hard or brittle material. Already the process has found its ways Into dozens of applications; sometimes replacing conventional alternatives often doing jobs that could not be done in any other way. This paper reviews the current status of this non-conventional machining process and discusses the unique advantages and possible applications.

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The HOMO-LUMO gaps have been estimated in a graphite-like sp(2) carbon network with a progressive increase in the fraction of sp(3) carbons, taking into account several possible structural alternatives for each composition. The gap is shown to increase exponentially with the fraction of sp(3) carbons. Accordingly, the gap in a diamond-like sp(3) network decreases with the increase in the fraction of sp(2) carbons.

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The emergence of optoelectronics and photonics as viable alternatives to electronics in many key areas of engineering relevance is indeed significant. This paper presents a tutorial review of integrated optics � a technologically important development in photonics. Materials, processes, device technology and applications are highlighted.

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instead of using chemical-reducing agents to facilitate the reduction and dissolution of manganese and iron oxide in the ocean nodule, electrochemical reduction based on two approaches, namely, cathodic polarization and galvanic interaction, can also be considered as attractive alternatives. Galvanic leaching of ocean nodules in the presence of pyrite and pyrolusite for complete recovery of Cu, Ni and Co has been discussed. The key for successful and efficient dissolution of copper, nickel and cobalt from ocean nodules depends on prior reduction of the manganese and ferric oxides with which the above valuable nonferrous metals are interlocked. Polarization studies using a slurry electrode system indicated that maximum dissolution of iron and manganese due to electrochemical reduction occurred at negative DC potentials of -600 mV (SCE) and -1400 mV (SCE). The present work is also relevant to galvanic bioleaching of ocean nodules using autotrophic microorganisms, such as Thiobacillus ferrooxidans and T thiooxidans, which resulted in significant dissolution of copper, nickel and cobalt at the expense of microbiologically generated acids. Various electrochemical and biochemical mechanisms are outlined and the electroleaching and galvanic processes so developed are shown to yield almost complete dissolution of all metal values. (C) 2002 Elsevier Science B.V. All rights reserved.

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We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

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Automated synthesis of mechanical designs is an important step towards the development of an intelligent CAD system. Research into methods for supporting conceptual design using automated synthesis has attracted much attention in the past decades. The research work presented here is based on the processes of synthesizing multiple state mechanical devices carried out individually by ten engineering designers. The designers are asked to think aloud, while carrying out the synthesis. The ten design synthesis processes are video recorded, and the records are transcribed and coded for identifying activities occurring in the synthesis processes, as well as for identifying the inputs to and outputs from the activities. A mathematical representation for specifying multi-state design task is proposed. Further, a descriptive model capturing all the ten synthesis processes is developed and presented in this paper. This will be used to identify the outstanding issues to be resolved before a system for supporting design synthesis of multiple state mechanical devices that is capable of creating a comprehensive variety of solution alternatives could be developed.

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Most of the developing countries including India depend heavily on bioenergy and it accounts for about 15% of the global energy usage. Its role in meeting a region’s requirement has increased the interest of assessing the status of biomass availability in a region. The present work deals with the bioenergy status in the Linganamakki reservoir catchment of the Sharavathi river basin, Western Ghats,India, by assessing the energy supply and sector wise energy consumption. The study reveals that majority of the households (92.17%) depend on fuelwood for their domestic energy needs with the per capita fuelwood consumption of 1.2 tonnes/year, which is higher than the national average (0.7 tonnes/year). This higher dependence on fuelwood has contributed to the degradation of forests,resulting in scarcity of bioresources necessitating exploration of viable energy alternatives to meet the growing energy demand.

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The economic prosperity and quality of life in a region are closely linked to the level of its per capita energy consumption. In India more than 70% of the total population inhabits rural areas and 85-90% of energy requirement is being met by bioresources. With dwindling resources, attention of planners is diverted to viable energy alternatives to meet the rural energy demand. Biogas as fuel is one such alternative, which can be obtained by anaerobic digestion of animal residues and domestic and farm wastes, abundantly available in the countryside. Study presents the techniques to assess biogas potential spatially using GIS in Kolar district, Karnataka State, India. This would help decision makers in selecting villages for implementing biogas programmes based on resource availability. Analyses reveal that the domestic energy requirement of more than 60% population can be met by biogas option. This is based on the estimation of the per capita requirement of gas for domestic purposes and availability of livestock residues.

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It is being realized that the traditional closed-door and market driven approaches for drug discovery may not be the best suited model for the diseases of the developing world such as tuberculosis and malaria, because most patients suffering from these diseases have poor paying capacity. To ensure that new drugs are created for patients suffering from these diseases, it is necessary to formulate an alternate paradigm of drug discovery process. The current model constrained by limitations for collaboration and for sharing of resources with confidentiality hampers the opportunities for bringing expertise from diverse fields. These limitations hinder the possibilities of lowering the cost of drug discovery. The Open Source Drug Discovery project initiated by Council of Scientific and Industrial Research, India has adopted an open source model to power wide participation across geographical borders. Open Source Drug Discovery emphasizes integrative science through collaboration, open-sharing, taking up multi-faceted approaches and accruing benefits from advances on different fronts of new drug discovery. Because the open source model is based on community participation, it has the potential to self-sustain continuous development by generating a storehouse of alternatives towards continued pursuit for new drug discovery. Since the inventions are community generated, the new chemical entities developed by Open Source Drug Discovery will be taken up for clinical trial in a non-exclusive manner by participation of multiple companies with majority funding from Open Source Drug Discovery. This will ensure availability of drugs through a lower cost community driven drug discovery process for diseases afflicting people with poor paying capacity. Hopefully what LINUX the World Wide Web have done for the information technology, Open Source Drug Discovery will do for drug discovery. (C) 2011 Elsevier Ltd. All rights reserved.

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The term Structural Health Monitoring has gained wide acceptance in the recent pastas a means to monitor a structure and provide an early warning of an unsafe conditionusing real-time data. Utilization of structurally integrated, distributed sensors tomonitor the health of a structure through accurate interpretation of sensor signals andreal-time data processing can greatly reduce the inspection burden. The rapidimprovement of the Fiber Bragg Grating sensor technology for strain, vibration andacoustic emission measurements in recent times make them a feasible alternatives tothe traditional strain gauges transducers and conventional Piezoelectric sensors usedfor Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM).Optical fiber-based sensors offers advantages over conventional strain gauges, PVDFfilm and PZT devices in terms of size, ease of embedment, immunity fromelectromagnetic interference(EMI) and potential for multiplexing a number ofsensors. The objective of this paper is to demonstrate the feasibility of Fiber BraggGrating sensor and compare its utility with the conventional strain gauges and PVDFfilm sensors. For this purpose experiments are being carried out in the laboratory on acomposite wing of a mini air vehicle (MAV). In this paper, the results obtained fromthese preliminary experiments are discussed.

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Arteries are heterogeneous, composite structures that undergo large cyclic deformations during blood transport. Presence, build-up and consequent rupture of blockages in blood vessels, called atherosclerotic plaques, lead to disruption in the blood flow that can eventually be fatal. Abnormal lipid profile and hypertension are the main risk factors for plaque progression. Treatments span from pharmacological methods, to minimally invasive balloon angioplasty and stent procedures, and finally to surgical alternatives. There is a need to understand arterial disease progression and devise methods to detect, control, treat and manage arterial disease through early intervention. Local delivery through drug eluting stents also provide an attractive option for maintaining vessel integrity and restoring blood flow while releasing controlled amount of drug to reduce and alleviate symptoms. Development of drug eluting stents is hence interesting albeit challenging because it requires an integration of knowledge of mechanical properties with material transport of drug through the arterial wall to produce a desired biochemical effect. Although experimental models are useful in studying such complex multivariate phenomena, numerical models of mass transport in the vessel have proved immensely useful to understand and delineate complex interactions between chemical species, physical parameters and biological variables. The goals of this review are to summarize literature based on studies of mass transport involving low density lipoproteins in the arterial wall. We also discuss numerical models of drug elution from stents in layered and porous arterial walls that provide a unique platform that can be exploited for the design of novel drug eluting stents.

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Structural Support Vector Machines (SSVMs) have become a popular tool in machine learning for predicting structured objects like parse trees, Part-of-Speech (POS) label sequences and image segments. Various efficient algorithmic techniques have been proposed for training SSVMs for large datasets. The typical SSVM formulation contains a regularizer term and a composite loss term. The loss term is usually composed of the Linear Maximum Error (LME) associated with the training examples. Other alternatives for the loss term are yet to be explored for SSVMs. We formulate a new SSVM with Linear Summed Error (LSE) loss term and propose efficient algorithms to train the new SSVM formulation using primal cutting-plane method and sequential dual coordinate descent method. Numerical experiments on benchmark datasets demonstrate that the sequential dual coordinate descent method is faster than the cutting-plane method and reaches the steady-state generalization performance faster. It is thus a useful alternative for training SSVMs when linear summed error is used.

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Organic plastic crystalline soft matter ion conductors are interesting alternatives to liquid electrolytes in electrochemical storage devices such as Lithium-ion batteries. The solvent dynamics plays a major role in determining the ion transport in plastic crystalline ion conductors. We present here an analysis of the frequency-dependent ionic conductivity of succinonitrile-based plastic crystalline ion conductors at varying salt composition (0.005 to 1 M) and temperature (-20 to 60 degrees C) using time-temperature superposition principle (TTSP). The main motivation of the work has been to establish comprehensive insight into the ion transport mechanism from a single method viz, impedance spectroscopy rather than employing cluster of different characterization methods probing various length and time scales. The TTSP remarkably aids in explicit identification of the extent of the roles of solvent dynamics and ion-ion interactions on the effective conductivity of the orientationally disordered plastic crystalline ion conductors.

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The role of a computer emerged from modeling and analyzing concepts (ideas) to generate concepts. Research into methods for supporting conceptual design using automated synthesis had attracted much attention in the past decades. To find out how designers synthesize solution concepts for multi-state mechanical devices, ten experimental studies were conducted. Observations from these empirical studies would be used as the basis to develop knowledge involved in the multi-state design synthesis process. In this paper, we propose a computational representation for expressing the multi-state design task and for enumerating multi-state behaviors of kinematic pairs and mechanisms. This computational representation would be used to formulate computational methods for the synthesis process to develop a system for supporting design synthesis of multiple state mechanical devices by generating a comprehensive variety of solution alternatives.