997 resultados para Input bias


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Nigerian electricity market is characterized by inadequate electricity generation framework, compounded by lack of timely routine maintenances. This results in significant deterioration in plant electricity output. This study analyzes the productivity changes in the Nigerian power sector. Productivity increased on average in the power sector by the adoption of new technologies from best-practice power plants. The assumption of Hicks neutral technological change is found not to be suitable for the Nigerian power sector. This study finds that the plants are not using their capacity meaningfully, instead, there is a tendency to use labor.

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Technology scaling has caused Negative Bias Temperature Instability (NBTI) to emerge as a major circuit reliability concern. Simultaneously leakage power is becoming a greater fraction of the total power dissipated by logic circuits. As both NBTI and leakage power are highly dependent on vectors applied at the circuit’s inputs, they can be minimized by applying carefully chosen input vectors during periods when the circuit is in standby or idle mode. Unfortunately input vectors that minimize leakage power are not the ones that minimize NBTI degradation, so there is a need for a methodology to generate input vectors that minimize both of these variables.This paper proposes such a systematic methodology for the generation of input vectors which minimize leakage power under the constraint that NBTI degradation does not exceed a specified limit. These input vectors can be applied at the primary inputs of a circuit when it is in standby/idle mode and are such that the gates dissipate only a small amount of leakage power and also allow a large majority of the transistors on critical paths to be in the “recovery” phase of NBTI degradation. The advantage of this methodology is that allowing circuit designers to constrain NBTI degradation to below a specified limit enables tighter guardbanding, increasing performance. Our methodology guarantees that the generated input vector dissipates the least leakage power among all the input vectors that satisfy the degradation constraint. We formulate the problem as a zero-one integer linear program and show that this formulation produces input vectors whose leakage power is within 1% of a minimum leakage vector selected by a search algorithm and simultaneously reduces NBTI by about 5.75% of maximum circuit delay as compared to the worst case NBTI degradation. Our paper also proposes two new algorithms for the identification of circuit paths that are affected the most by NBTI degradation. The number of such paths identified by our algorithms are an order of magnitude fewer than previously proposed heuristics.

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In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

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In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

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This article reviews a teaching process that aimed to prepare final year social work students for critical practice with diverse and marginalized populations. Alongside lecture input, in small group discussions and in the two sequenced written assignments students were encouraged to personalize questions of bias and stigma by recalling both their experiences of being “other-ed” as well as their participation in practices that “other-ed”, such as racist and homophobic imaging and acting. Feedback to the unit’s first iteration in 2004 was generally positive yet a significant minority of students were clearly dissatisfied. Whilst retaining the same formal content in 2005, greater attention was devoted to generating a supportive group process and a positive environment for “negative” self-disclosure. This milieu acted to contain and normalize the students’ struggle with internalized stereotypes, a stage associated with their greater preparedness to identify and challenge their own personal, cultural and ideological locations. Within the context of the unit remaining explicit about its value stance, by adopting an approach to the teaching / learning process that neither collided nor colluded, as teachers we believe the 2005 revision better achieved the units aims. First, the unit received broader positive appraisal from students and, second, it appeared that the unit more firmly promoted the prospects for students carrying forward a capacity for critical self review post graduation.

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The superior colliculus (SC) is responsible for sensorimotor transformations required to direct gaze toward or a way from unexpected, biologically salient events. Significant changes in the external world are signaled to SC through primary multisensory afferents, spatially organized according to a retinotopic topography. For animals, where anunexpected event could indicate the presence of either predator or prey, early decisions to approach or avoid are particularly important. Rodents' ecology dictates predators are most often detected initially as movements in upper visual field (mapped in medial SC), while appetitive stimuli are normally found in lower visual field (mapped in lateral SC). Our purpose was to exploit this functional segregation to reveal neural sites that can bias or modulate initial approach or avoidance responses. Small injections of Fluoro-Gold were made into medial or lateral sub-regions of intermediate and deep layers of SC (SCm/SCl). A remarkable segregation of input to these two functionally defined areas was found. (i) There were structures that projected only to SCm (e.g., specific cortical areas, lateral geniculate and suprageniculate thalamic nuclei, ventromedial and premammillary hypothalamic nuclei, and several brain-stem areas) or SCl (e.g., primary somatosensory cortex representing upper body parts and vibrissae and parvicellular reticular nucleus in the brainstem). (ii) Other structures projected to both SCm and SCl but from topographically segregated populations of neurons (e.g., zona incerta and substantia nigra pars reticulata). (iii) There were a few brainstem areas in which retrogradely labeled neurons were spatially overlapping (e.g., pedunculopontine nucleus and locus coeruleus). These results indicate significantly more structures across the rat neuraxis are in a position to modulate defense responses evoked from SCm, and that neural mechanisms modulating SC-mediated defense or appetitive behavior are almost entirely segregated.

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Daily we cope with upcoming potentially disadvantageous events. Therefore, it makes sense to be prepared for the worst case. Such a 'pessimistic' bias is reflected in brain activation during emotion processing. Healthy individuals underwent functional neuroimaging while viewing emotional stimuli that were earlier cued ambiguously or unambiguously concerning their emotional valence. Presentation of ambiguously announced pleasant pictures compared with unambiguously announced pleasant pictures resulted in increased activity in the ventrolateral prefrontal, premotor and temporal cortex, and in the caudate nucleus. This was not the case for the respective negative conditions. This indicates that pleasant stimuli after ambiguous cueing provided 'unexpected' emotional input, resulting in the adaptation of brain activity. It strengthens the hypothesis of a 'pessimistic' bias of brain activation toward ambiguous emotional events.

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Radar technologies have been developed to improve the efficiency when detecting targets. Radar is a system composed by several devices connected and working together. Depending on the type of radar, the improvements are focused on different functionalities of the radar. One of the most important devices composing a radar is the antenna, that sends the radio-frequency signal to the space in order to detect targets. This project is focused on a specific type of radar called phased array radar. This type of radar is characterized by its antenna, which consist on a linear array of radiating elements, in this particular case, eight dipoles working at the frequency band S. The main advantage introduced by the phased array antenna is that using the fundamentals of arrays, the directivity of the antenna can change by shifting the phase of the signal at the input of each radiating element. This can be done using phase shifters. Phase shifter consists on a device which produces a phase shift in the radio-frequency input signal depending on a control DC voltage. Using a phased array antenna allows changing the directivity of the antenna without a mechanical rotating system. The objective of this project is to design the feed network and the bias network of the phased antenna. The feed network consists on a parallel-fed network composed by power dividers that sends the radio-frequency signal from the source to each radiating element of the antenna. The bias network consists on a system that generates the control DC voltages supplied to the phase shifters in order to change the directivity. The architecture of the bias network is composed by a software, implemented in Matlab and run in a laptop which is connected to a micro-controller by a serial communication port. The software calculates the control DC voltages needed to obtain a determined directivity or scan angle. These values are sent by the serial communication port to the micro-controller as data. Then the micro-controller generates the desired control DC voltages and supplies them to the phase shifters. In this project two solutions for bias network are designed. Each one is tested and final conclusions are obtained to determine the advantages and disadvantages. Finally a graphic user interface is developed in order to make the system easy to use. RESUMEN. Las tecnologías empleadas por lo dispositivos radar se han ido desarrollando para mejorar su eficiencia y usabilidad. Un radar es un sistema formado por varios subsistemas conectados entre sí. Por lo que dependiendo del tipo de radar las mejoras se centran en los subsistemas correspondientes. Uno de los elementos más importantes de un radar es la antena. Esta se emplea para enviar la señal de radiofrecuencia al espacio y así poder detectar los posibles obstáculos del entorno. Este proyecto se centra en un tipo específico de radar llamado phased array radar. Este tipo de radar se caracteriza por la antena que es un array de antenas, en concreto para este proyecto se trata de un array lineal de ocho dipolos en la banda de frequencia S. El uso de una antena de tipo phased array supone una ventaja importante. Empleando los fundamentos de radiación aplicado a array de antenas se obtiene que la directividad de la antena puede ser modificada. Esto se consigue aplicando distintos desfasajes a la señal de radiofrecuencia que alimenta a cada elemento del array. Para aplicar los desfasajes se emplea un desplazador de fase, este dispositivo aplica una diferencia de fase a su salida con respecto a la señal de entrada dependiendo de una tensión continua de control. Por tanto el empleo de una antena de tipo phased array supone una gran ventaja puesto que no se necesita un sistema de rotación para cambiar la directividad de la antena. El objetivo principal del proyecto consiste en el diseño de la red de alimentación y la red de polarización de la antena de tipo phased array. La red de alimentación consiste en un circuito pasivo que permite alimentar a cada elemento del array con la misma cantidad de señal. Dicha red estará formada por divisores de potencia pasivos y su configuración será en paralelo. Por otro lado la red de polarización consiste en el diseño de un sistema automático que permite cambiar la directividad de la antena. Este sistema consiste en un programa en Matlab que es ejecutado en un ordenador conectado a un micro-controlador mediante una comunicación serie. El funcionamiento se basa en calcular las tensiones continuas de control, que necesitan los desplazadores de fase, mediante un programa en Matlab y enviarlos como datos al micro-controlador. Dicho micro-controlador genera las tensiones de control deseadas y las proporciona a cada desplazador de fase, obteniendo así la directividad deseada. Debido al amplio abanico de posibilidades, se obtienen dos soluciones que son sometidas a pruebas. Se obtienen las ventajas y desventajas de cada una. Finalmente se implementa una interfaz gráfica de usuario con el objetivo de hacer dicho sistema manejable y entendible para cualquier usuario.

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In most treatments of the regression problem it is assumed that the distribution of target data can be described by a deterministic function of the inputs, together with additive Gaussian noise having constant variance. The use of maximum likelihood to train such models then corresponds to the minimization of a sum-of-squares error function. In many applications a more realistic model would allow the noise variance itself to depend on the input variables. However, the use of maximum likelihood to train such models would give highly biased results. In this paper we show how a Bayesian treatment can allow for an input-dependent variance while overcoming the bias of maximum likelihood.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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This paper reports on the experiences of an extracurricular program in English language learning (ELL) that was implemented in an institute of technology in the hinterland of the People's Republic of China (PRC). Following the guidelines set out in an impact study of the reform of curriculum change in Hong Kong (Adamson & Morris, 2000), this study takes account of the context of the particular socio-cultural and political environment in which the research program takes place. Three distinct phases emerged in the career of the extracurricular program - the establishment of the program; successful implementation; and the decline. The study identifies three key factors that shaped these phases: teacher motivation; student motivation and its various influences; and available resources (including collegial and administrative support). The findings suggest that of the key factors impacting on the ELL extracurriculum, student motivation was the most influential.

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Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

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The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.