583 resultados para planners


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Wind power based generation has been rapidly growing world-wide during the recent past. In order to transmit large amounts of wind power over long distances, system planners may often add series compensation to existing transmission lines owing to several benefits such as improved steady-state power transfer limit, improved transient stability, and efficient utilization of transmission infrastructure. Application of series capacitors has posed resonant interaction concerns such as through subsynchronous resonance (SSR) with conventional turbine-generators. Wind turbine-generators may also be susceptible to such resonant interactions. However, not much information is available in literature and even engineering standards are yet to address these issues. The motivation problem for this research is based on an actual system switching event that resulted in undamped oscillations in a 345-kV series-compensated, typical ring-bus power system configuration. Based on time-domain ATP (Alternative Transients Program) modeling, simulations and analysis of system event records, the occurrence of subsynchronous interactions within the existing 345-kV series-compensated power system has been investigated. Effects of various small-signal and large-signal power system disturbances with both identical and non-identical wind turbine parameters (such as with a statistical-spread) has been evaluated. Effect of parameter variations on subsynchronous oscillations has been quantified using 3D-DFT plots and the oscillations have been identified as due to electrical self-excitation effects, rather than torsional interaction. Further, the generator no-load reactance and the rotor-side converter inner-loop controller gains have been identified as bearing maximum sensitivity to either damping or exacerbating the self-excited oscillations. A higher-order spectral analysis method based on modified Prony estimation has been successfully applied to the field records identifying dominant 9.79 Hz subsynchronous oscillations. Recommendations have been made for exploring countermeasures.

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Michigan copper mining companies owned and rented more than 3,000 houses along the Keweenaw Peninsula at the time of the 1913-14 copper strike. The provision of company-constructed housing in mining districts has drawn a wide range of inquiry. Mining historians, community planners, architectural historians, and academics interested in the immigrant experience have identified miners' housing as intriguing examples of corporate paternalism, social planning, vernacular adaptation and ethnic segregation. Michigan's Copper Country retains many examples of such housing and recent research has shown that the Michigan copper mining companies championed the use of housing as a non-wage employment benefit. This paper will investigate the increasingly important role of occupancy and control of company housing during the strike. Illustrated with images collected during the strike by the fledgling U.S. Department of Labor, the presentation explores the history of company housing in the Copper Country, its part in a larger system of corporate welfare, and how the threat of evictions may have turned the tide of strike.

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Planning in realistic domains typically involves reasoning under uncertainty, operating under time and resource constraints, and finding the optimal subset of goals to work on. Creating optimal plans that consider all of these features is a computationally complex, challenging problem. This dissertation develops an AO* search based planner named CPOAO* (Concurrent, Probabilistic, Over-subscription AO*) which incorporates durative actions, time and resource constraints, concurrent execution, over-subscribed goals, and probabilistic actions. To handle concurrent actions, action combinations rather than individual actions are taken as plan steps. Plan optimization is explored by adding two novel aspects to plans. First, parallel steps that serve the same goal are used to increase the plan’s probability of success. Traditionally, only parallel steps that serve different goals are used to reduce plan execution time. Second, actions that are executing but are no longer useful can be terminated to save resources and time. Conventional planners assume that all actions that were started will be carried out to completion. To reduce the size of the search space, several domain independent heuristic functions and pruning techniques were developed. The key ideas are to exploit dominance relations for candidate action sets and to develop relaxed planning graphs to estimate the expected rewards of states. This thesis contributes (1) an AO* based planner to generate parallel plans, (2) domain independent heuristics to increase planner efficiency, and (3) the ability to execute redundant actions and to terminate useless actions to increase plan efficiency.

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Tax planners often choose debt over equity financing. As this has led to increased corporate debt financing, many countries have introduced thin capitalization rules to secure their tax revenues. In a general capital structure model we analyze if thin capitalization rules affect dividend and financing decisions, and whether they can partially explain why corporations receive both debt and equity capital. We model the Belgian, German and Italian rules as examples. We find that the so-called Miller equilibrium and definite financing effects depend significantly on the underlying tax system. Further, our results are useful for the treasury to decide what thin capitalization type to implement.

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Energy efficiency has become an important research topic in intralogistics. Especially in this field the focus is placed on automated storage and retrieval systems (AS/RS) utilizing stacker cranes as these systems are widespread and consume a significant portion of the total energy demand of intralogistical systems. Numerical simulation models were developed to calculate the energy demand rather precisely for discrete single and dual command cycles. Unfortunately these simulation models are not suitable to perform fast calculations to determine a mean energy demand value of a complete storage aisle. For this purpose analytical approaches would be more convenient but until now analytical approaches only deliver results for certain configurations. In particular, for commonly used stacker cranes equipped with an intermediate circuit connection within their drive configuration there is no analytical approach available to calculate the mean energy demand. This article should address this research gap and present a calculation approach which enables planners to quickly calculate the energy demand of these systems.

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These guidelines provide an overview of proven good practice in water harvesting from all over the world. They form a practical reference guide while providing support and specific technical expertise for the integration of water harvesting technologies into the planning and design of projects. Thus existing information and experience is strengthened. On a broader scale, the guidelines’ objective is to facilitate, share and upscale good practice in water harvesting given the state of current knowledge. Targeted end users include local and regional planners / advisors, rural development consultants, rainwater harvesting networks and communitiesof- practice, project managers, extension agents and other implementing staff. Through informing these professionals, the aim is to stimulate discussion and new thinking about improved water management in general, and water harvesting in particular, within rainfed agriculture, particularly in the drylands. The ultimate goal is to contribute to lifting 80 million rural people out of poverty by 2015: water security is a prerequisite to achieve food security for these people.

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Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering “free or low cost visits”, meeting “all of the patient’s health care needs”, and seeing “the patient quickly” were all ranked higher than geographic reasons. Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts.

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Individuals who are diagnosed with a chronic mental illness and an alcohol use disorder comprise a high risk population that challenges the mental health care system. Effective treatment for the dually diagnosed, who are characterized by heterogeneity in their psychiatric diagnoses, their substance use patterns, and their current degree of dysfunction, presents a challenge. Several integrated treatment models have been developed that attempt to concurrently treat patients' psychiatric and substance abuse problems. At this point in the development of these "dual diagnosis" programs, treatment planning is hindered by a lack of knowledge about the relation of psychiatric severity to the process of recovery from alcohol abuse and dependence.^ The present study sought to advance the field's understanding of the relation between psychiatric severity and the process of behavior change through an examination of the relation between dimensions of psychiatric severity and Prochaska and DiClemente's Transtheoretical Model (TTM) constructs. The TTM, which focuses on identifying the processes of change that appear to underlie the modification of addictive behaviors, provides a way of conceptualizing and measuring specific elements relevant to the desired behavior change. Knowledge of the relation between these constructs and psychiatric severity will enable treatment planners to develop dual diagnosis programs which target clients' needs with a much higher level of specificity.^ One hundred-thirty two alcohol dependent patients in a dual diagnosis treatment program were assessed on psychiatric severity (defined as number of symptoms and level of distress resulting from symptoms) and the Transtheoretical Model constructs. The constructs include stages and processes of change for alcohol use, alcohol decisional balance, and alcohol abstinence self-efficacy. Results indicate that the TTM variable of "temptation to drink" is most strongly related to psychiatric severity: the more psychiatric distress a person is experiencing, the more he or she is tempted to drink. The "cons" of drinking were also related to psychiatric severity, indicating that participants who were experiencing more psychiatric distress also endorsed as important a higher number of the negative aspects of drinking.^ Additional aims of this investigation were to determine whether participants' scores on the Transtheoretical Model variables were associated with their: (a) severity of drinking, defined as frequency, quantity and consequences of use, (b) previous psychiatric and substance abuse treatment episodes, and (c) functional impairment. Associations were found among these variables and each of the key constructs of the Transtheoretical Model. Each association is explored in detail and implications for treatment programming are discussed. ^

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The purpose of this dissertation was to examine the relationship between key psychosocial and behavioral components of the Transtheoretical Model and the Theory of Reasoned Action for sexual risk reduction in a population of crack cocaine smokers and sex workers, not in drug treatment. ^ The first study examined the results of an analysis of the association between two principal constructs in the Transtheoretical Model, the processes of change and the stages of change for condom use, in a high risk population. In the analysis of variance for all respondents, the overall F-test revealed that people in different stages have different levels of experiential process use, F(3,317) = 17.79, p = 0.0001 and different levels of behavioral process use, F(3,317) = 28.59, p = .0001. For the experiential processes, there was a significant difference between the precontemplation/contemplation stage, and both the action, and maintenance, stages.^ The second study explored the relationship between the Theory of Reasoned Action “beliefs” and the stages-of-change in the same population. In the analysis of variance for all participants, the results indicate that people in different stages did value the positive beliefs differently, F(3,502) = 15.38, p = .0001 but did not value the negative beliefs differently, F(3,502) = 2.08, p = .10. ^ The third study explored differences in stage-of-change by gender, partner type drug use, and HIV status. Three discriminant functions emerged, with a combined χ2(12) = 139.57, p = <.0001. The loading matrix of correlations between predictors and discriminant functions demonstrate that the strongest predictor for distinguishing between the precontemplation/contemplation stage and the preparation, action, and maintenance stages (first function) is partner type (.962). The loadings on the second discriminant function suggest that once partner type has been accounted for, ever having HIV/AIDS (.935) was the best predictor for distinguishing between the first three stages and the maintenance stage. ^ These studies demonstrate that behavioral change theories can contribute important insight to researchers and program planners attempting to alter HIV risk behavior in high-risk populations. ^

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The urban transition almost always involves wrenching social adjustment as small agricultural communities are forced to adjust rapidly to industrial ways of life. Large-scale in-migration of young people, usually from poor regions, creates enormous demand and expectations for community and social services. One immediate problem planners face in approaching this challenge is how to define, differentiate, and map what is rural, urban, and transitional (i.e., peri-urban). This project established an urban classification for Vietnam by using national census and remote sensing data to identify and map the smallest administrative units for which data are collected as rural, peri-urban, urban, or urban core. We used both natural and human factors in the quantitative model: income from agriculture, land under agriculture and forests, houses with modern sanitation, and the Normalized Difference Vegetation Index. Model results suggest that in 2006, 71% of Vietnam's 10,891 communes were rural, 18% peri-urban, 3% urban, and 4% urban core. Of the communes our model classified as peri-urban, 61% were classified by the Vietnamese government as rural. More than 7% of Vietnam's land area can be classified as peri-urban and approximately 13% of its population (more than 11 million people) lives in peri-urban areas. We identified and mapped three types of peri-urban places: communes in the periphery of large towns and cities; communes along highways; and communes associated with provincial administration or home to industrial, energy, or natural resources projects (e.g., mining). We validated this classification based on ground observations, analyses of multi-temporal night-time lights data, and an examination of road networks. The model provides a method for rapidly assessing the rural–urban nature of places to assist planners in identifying rural areas undergoing rapid change with accompanying needs for investments in building, sanitation, road infrastructure, and government institutions.

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Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.

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Most case studies of successful high-technology industry regions highlight the role of research universities in fostering regional economic development. The Portland, Oregon, region managed to root a thriving high-tech industry in the absence of this critical factor. In this article, I present a case study of the evolution of Portland's high-tech industry and propose that high-tech firms can act as surrogate universities that attract and develop labor, create knowledge, and function as incubators for startups. I conclude that planners working to develop high-tech industries in regions without major research universities should attract R&D-intensive firms, maintain information on key busineses and entrepreneurial ventures, support an innovation milieu, and set realistic goals.

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This paper describes an ArcView extension that allows police planners to design patrol districts and to evaluate them by displaying various performance measures. It uses a spatially distributed queuing system (the Larson Hypercube) to calculate expected travel times, workloads, preventive patrol frequencies, and other variables; and it allows planners to see the unavoidable tradeoffs among their objectives. Using this tool, planners can experiment with various patrol patterns to find those that best meet their Department.s goals. For example, those patrol patterns which are best in terms of average response time don.t do as well as others in terms of workload balance, or those that are best in terms of achieving a uniform response time across different parts of the city don't do as well as others in terms of minimizing inter-district dispatches. There is, of course, no perfect solution for this problem: the facts of the situation force us to balance competing goals. Described here is a way of explicitly weighting the alternative objectives.

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In the last several decades traditional community health indicators have become ambiguous and lost some of their relevance. During this same period national and international health agencies adopted new expanded definitions of Health that include underlying social determinants. These two influences are responsible for a proliferation of new health indicators and many are constructed from a combination of older mortality measures and available information on morbidity. Problems inherent in attempting to combine these sources of information have produced a situation where some indicators are difficult to calculate at the national level and may not function at all for small communities. What is needed is a relevant measure of the burden of ill health appropriate for smaller populations that is accessible to local health planners. ^ Death records are still the best available population health information. In Europe the burden of health problems is often portrayed using 'premature' death. Health agencies in the United States have moved to adopt Years of Potential Life Lost. Both these regions are also developing systems of 'avoidable' or 'preventable' death as health indicators. This research proposes a method combining these methodologies to produce a relevant indicator portraying the burden of ill health in communities. ^

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Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. ^ During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. ^ Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering "free or low cost visits", meeting "all of the patient's health care needs", and seeing "the patient quickly" were all ranked higher than geographic reasons. ^ Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts. ^