Macro-economic analysis of forestry options on carbon sequestration in India

The forestry sector provides a number of climate change mitigation options. Apart from this ecological benefit, it has significant social and economic relevance. Implementation of forestry options requires large investments and sustained long-term planning. Thus there is a need for a detailed analysis of forestry options to understand their implications on stock and flow of carbon, required investments, value of forest wealth, contribution to GNP and livelihood, demand management, employment and foreign trade. There is a need to evaluate the additional spending on forestry by analysing the environmental (particularly carbon abatement), social and economic benefits. The biomass needs for India are expected to increase by two to three times by 2020. Depending upon the forest types, ownership patterns and land use patterns, feasible forestry options are identified. It is found among many supply options to be feasible to meet the 'demand based needs' with a mix of management options, species choices and organisational set up. A comparative static framework is used to analyze the macro-economic impacts. Forestry accounts for 1.84% of GNP in India. It is characterized by significant forward industrial linkages and least backward linkage. Forestry generates about 36 million person years of employment annually. India imports Rs. 15 billion worth of forest based materials annually. Implementation of the demand based forestry options can lead to a number of ecological, economic and institutional changes. The notable ones are: enhancement of C stock from 9578 to 17 094 Mt and a net annual C-sequestration from 73 to 149 Mt after accounting for all emissions; a trebling of the output of forestry sector from Rs. 49 billion to Rs. 146 billion annually; an increase in GDP contribution of forestry from Rs. 32 billion to Rs. 105 billion over a period of 35 years; an increase in annual employment level by 23 million person years, emergence of forestry as a net contributor of foreign exchange through trading of forestry products; and an increase in economic value of forest capital stock by Rs. 7260 billion with a cost benefit analysis showing forestry as a profitable option. Implementation of forestry options calls for an understanding of current forest policies and barriers which are analyzed and a number of policy options are suggested. (C) 1997 Elsevier Science B.V.

Counselling and predictive testing for familial adenomatous polyposis in a rural South Indian community

Background—Mutations of the APC gene cause familial adenomatous polyposis (FAP), a hereditary colorectal cancer predisposition syndrome.Aims—To conduct a cost comparison analysis of predictive genetic testing versus conventional clinical screening for individuals at risk of inheriting FAP, using the perspective of a third party payer. Methods—All direct health care costs for both screening strategies were measured according to time and motion, and the expected costs evaluated using a decision analysis model.Results—The baseline analysis predicted that screening a prototype FAP family would cost $4975/£3109 by molecular testingand $8031/£5019 by clinical screening strategy, when family members were monitored with the same frequency of clinical surveillance (every two to three years). Sensitivity analyses revealed that the genetic testing approach is cost saving for key variables including the kindred size, the age of screening onset, and the cost of mutation identification in a proband. However, if the APC mutation carriers were monitored at an increased (annual) frequency, the cost of the genetic screening strategy increased to $7483/ £4677 and was especially sensitive to variability in age of onset of screening, family size, and cost of genetic testing of at risk relatives. Conclusions—In FAP kindreds, a predictive genetic testing strategy costs less than conventional clinical screening, provided that the frequency of surveillance is identical using either strategy. An additional significant benefit is the elimination of unnecessary colonic examinations for those family members found to be noncarriers.

Rural electrification: Optimising the choice between decentralised renewable energy sources and grid extension

The study presents an analysis aimed at choosing between off-grid solar photovoltaic, biomass gasifier based power generation and conventional grid extension for remote village electrification. The model provides a relation between renewable energy systems and the economical distance limit (EDL) from the existing grid point, based on life cycle cost (LCC) analysis, where the LCC of energy for renewable energy systems and grid extension will match. The LCC of energy feed to the village is arrived at by considering grid availability and operating hours of the renewable energy systems. The EDL for the biomass gasifier system of 25 kW capacities is 10.5 km with 6 h of daily operation and grid availability. However, the EDL for a similar 25 kW capacity photovoltaic system is 35 km for the same number of hours of operation and grid availability. The analysis shows that for villages having low load demand situated far away from the existing grid line, biomass gasification based systems are more cost competitive than photovoltaic systems or even compared to grid extension. (C) 2012 Elsevier Inc. All rights reserved.

NUcache: an efficient multicore cache organization based on next-use distance

The effectiveness of the last-level shared cache is crucial to the performance of a multi-core system. In this paper, we observe and make use of the DelinquentPC - Next-Use characteristic to improve shared cache performance. We propose a new PC-centric cache organization, NUcache, for the shared last level cache of multi-cores. NUcache logically partitions the associative ways of a cache set into MainWays and DeliWays. While all lines have access to the MainWays, only lines brought in by a subset of delinquent PCs, selected by a PC selection mechanism, are allowed to enter the DeliWays. The PC selection mechanism is an intelligent cost-benefit analysis based algorithm that utilizes Next-Use information to select the set of PCs that can maximize the hits experienced in DeliWays. Performance evaluation reveals that NUcache improves the performance over a baseline design by 9.6%, 30% and 33% respectively for dual, quad and eight core workloads comprised of SPEC benchmarks. We also show that NUcache is more effective than other well-known cache-partitioning algorithms.

Framework for enabling highly available distributed applications for utility computing

The move towards IT outsourcing is the first step towards an environment where compute infrastructure is treated as a service. In utility computing this IT service has to honor Service Level Agreements (SLA) in order to meet the desired Quality of Service (QoS) guarantees. Such an environment requires reliable services in order to maximize the utilization of the resources and to decrease the Total Cost of Ownership (TCO). Such reliability cannot come at the cost of resource duplication, since it increases the TCO of the data center and hence the cost per compute unit. We, in this paper, look into aspects of projecting impact of hardware failures on the SLAs and techniques required to take proactive recovery steps in case of a predicted failure. By maintaining health vectors of all hardware and system resources, we predict the failure probability of resources based on observed hardware errors/failure events, at runtime. This inturn influences an availability aware middleware to take proactive action (even before the application is affected in case the system and the application have low recoverability). The proposed framework has been prototyped on a system running HP-UX. Our offline analysis of the prediction system on hardware error logs indicate no more than 10% false positives. This work to the best of our knowledge is the first of its kind to perform an end-to-end analysis of the impact of a hardware fault on application SLAs, in a live system.

A Low-Cost System for Measurement and Spectral Analysis of Motor Acoustic Noise

Workplace noise has become one of the major issues in industry not only because of workers’ health but also due to safety. Electric motors, particularly, inverter fed induction motors emit objectionably high levels of noise. This has led to the emergence of a research area, concerned with measurement and mitigation of the acoustic noise. This paper presents a lowcost option for measurement and spectral analysis of acoustic noise emitted by electric motors. The system consists of an electret microphone, amplifier and filter. It makes use of the windows sound card and associated software for data acquisition and analysis. The measurement system is calibrated using a professional sound level meter. Acoustic noise measurements are made on an induction motor drive using the proposed system as per relevant international standards. These measurements are seen to match closely with those of a professional meter.

ON THE UTILITY OF CANONICAL CORRELATION ANALYSIS FOR DOMAIN ADAPTATION IN MULTI-VIEW HEADPOSE ESTIMATION

The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.