890 resultados para real option analysis


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The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized emission rates for various motor vehicle groups as a function of the conditions under which the vehicles are operating. The validation of aggregate measurements, such as speed and acceleration profile, is performed on an independent data set using three statistical criteria. The MEASURE algorithms have proved to provide significant improvements in both average emission estimates and explanatory power over some earlier models for pollutants across almost every operating cycle tested.

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Signalling layout design is one of the keys to railway operations with fixed-block signalling system and it also carries direct effect on overall train efficiency and safety. Based on an analysis to system objectives, this paper presents an optimization model with two objectives in order to devise an efficient signalling layout scheme. Taking into account the present railway line design practices in China, the paper describes steps of the computer-based signalling layout optimisation with real-coded genetic algorithms. A computer-aided system, based on train movement simulator, has also been employed to assist the optimisation process. A case study on a practical railway line has been conducted to make comparisons between the proposed GA-based approach and the current practices. The results illustrate the improved performance of the proposed approach in reducing signal block joints and shortening minimum train service headway.

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Wireless network technologies, such as IEEE 802.11 based wireless local area networks (WLANs), have been adopted in wireless networked control systems (WNCS) for real-time applications. Distributed real-time control requires satisfaction of (soft) real-time performance from the underlying networks for delivery of real-time traffic. However, IEEE 802.11 networks are not designed for WNCS applications. They neither inherently provide quality-of-service (QoS) support, nor explicitly consider the characteristics of the real-time traffic on networked control systems (NCS), i.e., periodic round-trip traffic. Therefore, the adoption of 802.11 networks in real-time WNCSs causes challenging problems for network design and performance analysis. Theoretical methodologies are yet to be developed for computing the best achievable WNCS network performance under the constraints of real-time control requirements. Focusing on IEEE 802.11 distributed coordination function (DCF) based WNCSs, this paper analyses several important NCS network performance indices, such as throughput capacity, round trip time and packet loss ratio under the periodic round trip traffic pattern, a unique feature of typical NCSs. Considering periodic round trip traffic, an analytical model based on Markov chain theory is developed for deriving these performance indices under a critical real-time traffic condition, at which the real-time performance constraints are marginally satisfied. Case studies are also carried out to validate the theoretical development.

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Most information retrieval (IR) models treat the presence of a term within a document as an indication that the document is somehow "about" that term, they do not take into account when a term might be explicitly negated. Medical data, by its nature, contains a high frequency of negated terms - e.g. "review of systems showed no chest pain or shortness of breath". This papers presents a study of the effects of negation on information retrieval. We present a number of experiments to determine whether negation has a significant negative affect on IR performance and whether language models that take negation into account might improve performance. We use a collection of real medical records as our test corpus. Our findings are that negation has some affect on system performance, but this will likely be confined to domains such as medical data where negation is prevalent.

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This study investigated preservice teachers’ perceptions for teaching and sustaining gifted and talented students while developing, modifying and implementing activities to cater for the diverse learner. Participants were surveyed at the end of a gifted and talented education program on their perceptions to differentiate the curriculum for meeting the needs of the student (n=22). SPSS data analysis with the five-part Likert scale indicated these preservice teachers agreed or strongly agreed they had developed skills in curriculum planning (91%) with well-designed activities (96%), and lesson preparation skills (96%). They also claimed they were enthusiastic for teaching (91%) and understanding of school practices and policies (96%). However, 46% agreed they had knowledge of syllabus documents with 50% claiming an ability to provide written feedback on student’s learning. Furthermore, nearly two-thirds suggested they had educational language from the syllabus and effective student management strategies. Preservice teachers require more direction on how to cater for diversity and begin creating sustainable societies by building knowledge from direct GAT experiences. Designing diagnostic surveys associated with university coursework can be used to determine further development for specific preservice teacher development in GAT education. Preservice teachers need to create opportunities for students to realise their potential by involving cognitive challenges through a differentiated curriculum. Differentiation requires modification of four primary areas of curriculum development (Maker, 1975) content (what we teach), process (how we teach), product (what we expect the students to do or show) and learning environment (where we teach/our class culture). Ashman and Elkins (2009) and Glasson (2008) emphasise the need for preservice teachers, teachers and other professionals to be able to identify what gifted and talented (GAT) students know and how they learn in relation to effective teaching. Glasson (2008) recommends that educators keep up to date with practices in pedagogy, support, monitoring and profiling of GAT students to create an environment conducive to achieving. Oral feedback is one method to communicate to learners about their progress but has advantages and disadvantages for some students. Oral feedback provides immediate information to the student on progress and performance (Ashman & Elkins, 2009). However, preservice teachers must have clear understandings of key concepts to assist the GAT student. Implementing teaching strategies to engage innovate and extend students is valuable to the preservice teacher in focusing on GAT student learning in the classroom (Killen, 2007). Practical teaching strategies (Harris & Hemming, 2008; Tomlinson et al., 1994) facilitate diverse ways for assisting GAT students to achieve learning outcomes. Such strategies include activities to enhance creativity, co-operative learning and problem-solving activities (Chessman, 2005; NSW Department of Education and Training, 2004; Taylor & Milton, 2006) for GAT students to develop a sense of identity, belonging and self esteem towards becoming an autonomous learner. Preservice teachers need to understand that GAT students learn in a different way and therefore should be assessed differently. Assessment can be through diverse options to demonstrate the student’s competence, demonstrate their understanding of the material in a way that highlights their natural abilities (Glasson, 2008; Mack, 2008). Preservice teachers often are unprepared to assess students understanding but this may be overcome with teacher education training promoting effective communication and collaboration in the classroom, including the provision of a variety of assessment strategies to improve teaching and learning (Callahan et al., 2003; Tomlinson et al., 1994). It is also critical that preservice teachers have enthusiasm for teaching to demonstrate inclusion, involvement and the excitement to communicate to GAT students in the learning process (Baum, 2002). Evaluating and reflecting on teaching practices must be part of a preservice teacher’s repertoire for GAT education. Evaluating teaching practices can assist to further enhance student learning (Mayer, 2008). Evaluation gauges the success or otherwise of specific activities and teaching in general (Mayer, 2008), and ensures that preservice teachers and teachers are well prepared and maintain their commitment to their students and the community. Long and Harris (1999) advocate that reflective practices assist teachers in creating improvements in educational practices. Reflective practices help preservice teachers and teachers to improve their ability to pursue improved learning outcomes and professional growth (Long & Harris, 1999). Context This study is set at a small regional campus of a large university in Queensland. As a way to address departmental policies and the need to prepare preservice teachers for engaging a diverse range of learners (see Queensland College of Teachers, Professional Standards for Teachers, 2006), preservice teachers at this campus completed four elective units within their Bachelor of Education (primary) degree. The electives include: 1. Middle years students and schools 2. Teaching strategies for engaging learners 3. Teaching students with learning difficulties, and 4. Middle-years curriculum, pedagogy and assessment. In the university-based component of this unit, preservice teachers engaged in learning about middle years students and schools, and gained knowledge of government policies pertaining to GAT students. Further explored within in this unit was the importance of: collaboration between teachers, parents/carers and school personnel in supporting middle years GAT students; incorporating challenging learning experiences that promoted higher order thinking and problem solving skills; real world learning experiences for students and; the alignment and design of curriculum, pedagogy and assessment that is relevant to the students development, interests and needs. The participants were third-year Bachelor of Education (primary) preservice teachers who were completing an elective unit as part of the middle years of schooling learning with a focus on GAT students. They were assigned one student from a local school. In the six subsequent ninety minute weekly lessons, the preservice teachers were responsible for designing learning activities that would engage and extend the GAT students. Furthermore, preservice teachers made decisions about suitable pedagogical approaches and designed the assessment task to align with the curriculum and the developmental needs of their middle years GAT student. This research aims to describe preservice teachers’ perceptions of their education for teaching gifted and talented students.

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The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

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The period from 2007 to 2009 covered the residential property boom from early 2000, to the property recession following the Global Financial Crisis. Since late 2008, a number of residential property markets have suffered significant falls in house prices, buth this has not been consistent across all market sectors. This paper will analyze the housing market in Brisbane Australia to determine the impact, similarities and differences that the4 GFC had on range of residential sectors across a divesified property market. Data analysis will provide an overview of residential property prices, sales and listing volumes over the study period and will provide a comparison of median house price performance across the geographic and socio-economic areas of Brisbane.

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Catheter associated urinary tract infections (CAUTI) are a worldwide problem that may lead to increased patient morbidity, cost and mortality.1e3 The literature is divided on whether there are real effects from CAUTI on length of stay or mortality. Platt4 found the costs and mortality risks to be largeyetGraves et al found the opposite.5 A reviewof the published estimates of the extra length of stay showed results between zero and 30 days.6 The differences in estimates may have been caused by the different epidemiological methods applied. Accurately estimating the effects of CAUTI is difficult because it is a time-dependent exposure. This means that standard statistical techniques, such asmatched case-control studies, tend to overestimate the increased hospital stay and mortality risk due to infection. The aim of the study was to estimate excess length of stay andmortality in an intensive care unit (ICU) due to a CAUTI, using a statistical model that accounts for the timing of infection. Data collected from ICU units in lower and middle income countries were used for this analysis.7,8 There has been little research for these settings, hence the need for this paper.

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This paper presents a method of voice activity detection (VAD) suitable for high noise scenarios, based on the fusion of two complementary systems. The first system uses a proposed non-Gaussianity score (NGS) feature based on normal probability testing. The second system employs a histogram distance score (HDS) feature that detects changes in the signal through conducting a template-based similarity measure between adjacent frames. The decision outputs by the two systems are then merged using an open-by-reconstruction fusion stage. Accuracy of the proposed method was compared to several baseline VAD methods on a database created using real recordings of a variety of high-noise environments.

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This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%.

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This book examines the principles and practice of real estate mortgages in an easily accessible text referenced to all the Australian States. It specifically deals with the major theoretical and practical aspects of the land mortgage including vitiating factors in formation, mortgagees powers and duties and mortgagors’ rights both statutory and other, assignment, insurance and discharge. As a successor to Mortgages Law in Australia, this book adopts an exclusive focus on real estate mortgages in Australia and provides a thorough account of the law through analysis of the plethora of court decisions and statutory provisions in this area. Duncan and Dixon analyse the substance of the mortgage transaction from creation through to rights of enforcement. This analysis includes detailed consideration of the rights and obligations of both mortgagors and mortgagees covering topics such as priorities and tacking, insurance, variation and assignment, rights of discharge, entry into possession, foreclosure and power of sale. In addition, the book contains a separate chapter on factors that may affect the validity and enforcement of a mortgage together with separate consideration of a mortgagee’s right to enforce a guarantee provided on behalf of a mortgagor and the rights and liabilities associated with a receivership regime initiated by a mortgagee. Written for the national market, the book is one of the few substantial works on this subject for practitioners throughout Australia. It is a very accessible text which enables readers to decide whether or not they have a problem and provides primary guidance to its solution. The book has been deliberately, heavily referenced to incorporate statutory references from across Australia and contains extensive case analysis in order to satisfy both these objectives.

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A Networked Control System (NCS) is a feedback-driven control system wherein the control loops are closed through a real-time network. Control and feedback signals in an NCS are exchanged among the system’s components in the form of information packets via the network. Nowadays, wireless technologies such as IEEE802.11 are being introduced to modern NCSs as they offer better scalability, larger bandwidth and lower costs. However, this type of network is not designed for NCSs because it introduces a large amount of dropped data, and unpredictable and long transmission latencies due to the characteristics of wireless channels, which are not acceptable for real-time control systems. Real-time control is a class of time-critical application which requires lossless data transmission, small and deterministic delays and jitter. For a real-time control system, network-introduced problems may degrade the system’s performance significantly or even cause system instability. It is therefore important to develop solutions to satisfy real-time requirements in terms of delays, jitter and data losses, and guarantee high levels of performance for time-critical communications in Wireless Networked Control Systems (WNCSs). To improve or even guarantee real-time performance in wireless control systems, this thesis presents several network layout strategies and a new transport layer protocol. Firstly, real-time performances in regard to data transmission delays and reliability of IEEE 802.11b-based UDP/IP NCSs are evaluated through simulations. After analysis of the simulation results, some network layout strategies are presented to achieve relatively small and deterministic network-introduced latencies and reduce data loss rates. These are effective in providing better network performance without performance degradation of other services. After the investigation into the layout strategies, the thesis presents a new transport protocol which is more effcient than UDP and TCP for guaranteeing reliable and time-critical communications in WNCSs. From the networking perspective, introducing appropriate communication schemes, modifying existing network protocols and devising new protocols, have been the most effective and popular ways to improve or even guarantee real-time performance to a certain extent. Most previously proposed schemes and protocols were designed for real-time multimedia communication and they are not suitable for real-time control systems. Therefore, devising a new network protocol that is able to satisfy real-time requirements in WNCSs is the main objective of this research project. The Conditional Retransmission Enabled Transport Protocol (CRETP) is a new network protocol presented in this thesis. Retransmitting unacknowledged data packets is effective in compensating for data losses. However, every data packet in realtime control systems has a deadline and data is assumed invalid or even harmful when its deadline expires. CRETP performs data retransmission only in the case that data is still valid, which guarantees data timeliness and saves memory and network resources. A trade-off between delivery reliability, transmission latency and network resources can be achieved by the conditional retransmission mechanism. Evaluation of protocol performance was conducted through extensive simulations. Comparative studies between CRETP, UDP and TCP were also performed. These results showed that CRETP significantly: 1). improved reliability of communication, 2). guaranteed validity of received data, 3). reduced transmission latency to an acceptable value, and 4). made delays relatively deterministic and predictable. Furthermore, CRETP achieved the best overall performance in comparative studies which makes it the most suitable transport protocol among the three for real-time communications in a WNCS.

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Analytical expressions are derived for the mean and variance, of estimates of the bispectrum of a real-time series assuming a cosinusoidal model. The effects of spectral leakage, inherent in discrete Fourier transform operation when the modes present in the signal have a nonintegral number of wavelengths in the record, are included in the analysis. A single phase-coupled triad of modes can cause the bispectrum to have a nonzero mean value over the entire region of computation owing to leakage. The variance of bispectral estimates in the presence of leakage has contributions from individual modes and from triads of phase-coupled modes. Time-domain windowing reduces the leakage. The theoretical expressions for the mean and variance of bispectral estimates are derived in terms of a function dependent on an arbitrary symmetric time-domain window applied to the record. the number of data, and the statistics of the phase coupling among triads of modes. The theoretical results are verified by numerical simulations for simple test cases and applied to laboratory data to examine phase coupling in a hypothesis testing framework