Purpose The purpose of this study was to determine how Utah educators and school board members view the future of education in the state. This was done by comparing the ratings for importance and the predictions on the time of occurrence of 53 educational events. An event was an incident or happening which might effect the education of the state . The hypotheses were based on the assumption that the various educational groups would hold differing views concerning the future of Utah education. Procedure The study provided data on the perceptions of 236 individual s representing five groups of educational participants (State Department personnel, superintendents, other administrators, teachers, and school board members) concerning the future of education in the State of Utah within a 20-year period of time. The sample was randomly selected, with the exception of the superintendent group which included all of the superintendents of the state. An instrument consisting of 53 educational events was developed which enabled the respondents to express their perceptions of the importance of the events and predict when each of the events would occur in 60 percent of the schools of the state. Leik's Measure of Ordinal Consensus was used to arrive at a consensus score which indicated the dispersion or lack of dispersion of responses within a group to a particular event. An analysis of variance was used to test for differences among the groups. where a significant F-ratio was found, using the .05 level of significance, Duncan's New Multiple Range Test was also utilized. This test was designed to locate differences between paired groups.

<p>The forecast control for the heating system tries to maintain the buildings’ indoor</p><p>temperature at a desired level, by using technical building characteristics, data on its</p><p>mode of operation, data on the building location and meteorological parameters. By</p><p>forecasting the conditions of the building and calculating the free energies (solar radiation</p><p>and internal heat generation) it is possible to know the amount of additional heat that</p><p>should be supplied to the building every moment, avoiding heat surpluses or deficits.</p><p>By applying the theory developed by Roger Taesler to buildings 92911 and</p><p>92917 placed in Sandvik AB, it is seen that if the desired temperature was 21ºC it would</p><p>be possible to save a 16.3% of energy, 15518 SEK/year, and that the payback time for the</p><p>installation of such a system is 3 years.</p><p>Other efficiency measures as changing the ventilation schedule or installing a</p><p>heat exchanger are also discussed in the present report.</p>

<p>This Master’s Degree is a futurology that aims to analyse how the Chinese stock market might develop for a period of ten years, i.e. between the years 2005-2015. Since the future never with certainty can be predicted, scenarios will be presented displaying other possible outcomes. Naturally these scenarios are built upon given assumptions which otherwise could be as many as one’s imagination allows. The thought is to present the results as an index so the reader easily can see the possible development and scenarios.</p><p>The methodology used to collect necessary data is through the classical Delphi method, by which one interviews the selected “experts” that have the knowledge needed of the Chinese stock market. Moreover, the authors have collected further information through literature, the Internet, articles, reports and other written sources needed to continue further investigation. Further, the forecast was measured by two steps. The first step was to calculate the value at the start point. The second step was to create tow types of scenarios, added as a frame of the forecast outcomes. To transform the analysis and the scenarios in to a numerical index, a technical measurement of Quasi Monte Carlo Simulation was applied.</p><p>The theories applied when creating the index is foremost the Arbitrage Pricing Theory, which makes it possibly to measure several factors at the same time, including macro economical effects on the stock market.</p><p>According to the result, four factors were identified as the driving forces when finding a balanced economy, which affect the stock exchange: the investment structure; equal standard of living; the state of the financial sector and increased transparency. The result also indicates that the Chinese stock market will not stay in parity with the earlier development. A healthier and more efficient market will occur, due to structural reforms and the expected improvements within the financial sector including the stock exchange.</p><p>It is with great anticipation that the authors await a bright and successful future for the Chinese stock market. A new direction has been settled, although there are many difficult challenges.</p>

This study investigates whether market learning explains the absence of the accrual anomaly in recent years by examining three conditions associated with the presence of the anomaly in prior research: (i) a differential relation between future earnings and cash flows versus accruals, (ii) incorrect weighting of cash flows and accruals by investors when predicting earnings, and (iii) association of earnings forecast errors with returns. All of these conditions are widely documented in the anomaly period. In the no-anomaly period, I continue to find a differential relation of cash flows and accruals with future earnings. However, investors appear to correctly weight accruals and cash flows in their earnings predictions implicit in beginning-of-year security prices, consistent with learning. This study also investigates whether improvements in analyst forecasts contribute to investor learning and the absence of the anomaly. The association between analyst optimism and accruals is weaker in the no-anomaly period, but is still statistically significant. Furthermore, the anomaly ended simultaneously for firms followed by analysts and for non-followed firms, suggesting that improvements in analyst forecasts alone cannot account for improved market efficiency with respect to accruals. The results suggest that the anomaly was similar for firms held by institutional investors and for firms with no institutional holdings before the discovery of the anomaly while the anomaly ended sooner for held firms than for non-held firms after the discovery of the anomaly, consistent with the conjecture that arbitrage by institutional investors reduce the anomaly. Overall, the findings are consistent with market learning and suggest that improvement in investors' interpretation of accruals after the discovery of the anomaly explains the end of the anomaly. This improvement in investor learning is not due to changes in analysts' forecasting behavior, however.

Forecasts, predictions and opinions about the future should not be treated in the same way as hard information is treated under the Securities Act. Because this type of soft information cannot be verified in advance, the imposition of liability in respect of these statements about the future may hinder their production and have a result that is adverse to the interests of investors – who would prefer to hear management speak candidly about its thoughts on the company’s future performance. This essay examines the way in which the Ontario Securities Act treats statements about the future, as well as the most important decision in this area up to the present: Kerr v. Danier Leather. It will also discuss whether there should be a duty to update predictions when the circumstances that formed the basis of these forecasts have changed significantly.

Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

Forecasts, predictions and opinions about the future should not be treated in the same way as hard information is treated under the Securities Act. Because this type of soft information cannot be verified in advance, the imposition of liability in respect of these statements about the future may hinder their production and have a result that is adverse to the interests of investors – who would prefer to hear management speak candidly about its thoughts on the company’s future performance. This essay examines the way in which the Ontario Securities Act treats statements about the future, as well as the most important decision in this area up to the present: Kerr v. Danier Leather. It will also discuss whether there should be a duty to update predictions when the circumstances that formed the basis of these forecasts have changed significantly.

Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

La posada en marxa del Mercat Ibèric de l'Electricitat va introduir al sector elèctric espanyol un seguit de nous mecanismes de participació que han forçat els agents a renovar les seves polítiques de gestió. D'aquesta nova situació sorgeix l'oportunitat d'estudiar noves estratègies d'oferta a curt termini per a companyies de generació price-taker que participin diàriament al Mercat Ibèric de l'Electricitat. Aquestes estratègies se centraran al mercat diari, ja que és aquí on es negocia un 80% de l'electricitat que es consumeix diàriament a Espanya i on s'integren gran part de la resta de mecanismes de participació. La liberalització dels mercats elèctrics obre a noves tècniques d'optimització els problemes clàssics de gestió de l'energia. En particular, atesa la incertesa que l'existència del mercat ocasiona als preus, les tècniques de programació estocàstiques es converteixen en la forma més natural per abordar aquests problemes. Als mercats elèctrics el preu es fixa horàriament com a resultat d'un procés de casació , és a dir que quan l'agent ha d'efectuar la seva oferta desconeix el preu al qual li vindrà remunerada l'energia. Aquesta incertesa fa imprescindible l'ús de tècniques estadístiques per obtenir informació del mercat i introduir-la als models d'optimització. En aquest aspecte, una de les contribucions d'aquesta tesi és l'estudi dels preus del mercat de l'electricitat a Espanya i el seu modelat mitjançant models factorials. D'altra banda, s'hi es descriuen els nous mecanismes presents al Mercat Ibèric de l'Electricitat que afecten directament la producció física de les unitats. En particular, s'inclou el modelat detallat dels contractes de futurs físics i bilaterals i de la seva inclusió a l'oferta del mercat diari per part de les companyies de generació. Als models presentats, es tenen en compte explícitament les regles del mercat, així com les clàssiques restriccions d'operació de les unitats, tant tèrmiques com de cicle combinat. A més, es deriva i es demostra l'expressió de la funció d'oferta. Per tant, els models construïts són una eina per decidir l'assignació de les unitats, la generació dels contractes de futurs físics i bilaterals a través seu i l'oferta òptima d'una companyia de generació. Un cop s'han cobert aquests objectius, es presenta una millora dels models mitjançant la inclusió de la seqüència de mercats de molt curt termini per tal de modelar la influència que tenen en l'oferta al mercat diari. Aquests mercats es casen just abans i durant el dia en què l'energia ha de ser consumida, i això permetrà veure com la possibilitat d'augmentar els beneficis participant-hi afecta directament les estratègies d'oferta òptima del mercat diari. Els models presentats en aquest treball han estat provats amb dades reals provinents del Mercat Ibèric de l'Electricitat i d'una companyia de generació que hi opera. Els resultats obtinguts són adequats i es discuteixen al llarg del document / La puesta en marcha del Mercado Ibérico de la Electricidad introdujo en el sector eléctrico español una serie de nuevos mecanismos de participación que han forzado a los agentes a renovar sus políticas de gestión. De esta nueva situación surge la oportunidad de estudiar nuevas estrategias de oferta para las compañías de generación. Esta tesis se enmarca en las estrategias de oferta a corto plazo para compañías de generación price-taker que participen diariamente en el Mercado Ibérico de la Electricidad. Estas estrategias se centraran en el mercado diario ya que es donde se negocia un 80% de la electricidad consumida diariamente en España y es donde se integran gran parte del resto de los mecanismos de participación. La liberalización de los mercados eléctricos permite aplicar nuevas técnicas de optimización a los problemas clásicos de gestión de la energía. En concreto, dada la incertidumbre en el precio existente en el mercado, las técnicas de programación estocástica se convierten en la forma más natural para abordar estos problemas. En los mercados eléctricos el precio se fija horariamente como resultado de un proceso de casación, es decir, cuando el agente debe efectuar sus ofertas desconoce el precio al que la energía le será pagada. Esta incertidumbre hace imprescindible el uso de técnicas estadísticas para obtener información del mercado e introducirla en los modelos de optimización. En este aspecto, una de las contribuciones de esta tesis es el estudio del precio de la electricidad en España y su modelado mediante modelos factoriales. Se describen los nuevos mecanismos presentes en el Mercado Ibérico de la Electricidad que afectan directamente a la producción física de las unidades. En particular, se incluye una modelización detallada de los contratos de futuros físicos y bilaterales y su inclusión en la oferta enviada al mercado diario por las compañías de generación. En los modelos presentados se tiene en cuenta explícitamente las reglas del mercado así como las clásicas restricciones de operación de las unidades, tanto térmicas como de ciclo combinado. La expresión de la función de oferta óptima se deriva y se demuestra. Por lo tanto, los modelos construidos son una herramienta para decidir la asignación de unidades, la generación de los contratos de futuros físicos y bilaterales a través de ellas y la oferta óptima de una compañía de generación. Una vez alcanzados estos objetivos, se presenta una mejora del modelo con la inclusión de la secuencia de mercados de muy corto plazo. El objetivo es modelar la influencia que esta tiene en la oferta al mercado diario. Estos mercados se casan justo antes y durante el día en el que la energía va a ser consumida y se verá cómo la posibilidad de aumentar los beneficios participando en ellos afecta a las estrategias de oferta óptima del mercado diario. Los modelos presentados en este trabajo se han probado con datos reales procedentes del Mercado Ibérico de la Electricidad y de una compañía de generación que opera en él. Los resultados obtenidos son adecuados y se discuten a lo largo del documento. / The start-up of the Iberian Electricity Market introduced a set of new mechanisms in the Spanish electricity sector that forced the agents participating in the market to change their management policies. This situation created a great opportunity for studying the bidding strategies of the generation companies in this new framework. This thesis focuses on the short-term bidding strategies of a price-taker generation company that bids daily in the Iberian Electricity Market. We will center our bidding strategies on the day-ahead market because 80% of the electricity that is consumed daily in Spain is negotiated there and also because it is the market where the new mechanisms are integrated. The liberalization of the electricity markets opens the classical problems of energy management to new optimization approaches. Specifically, because of the uncertainty that the market produces in the prices, the stochastic programming techniques have become the most natural way to deal with these problems. Notice that, in deregulated electricity markets the price is hourly fixed through a market clearing procedure, so when the agent must bid its energy it is unaware of the price at which it will be paid. This uncertainty makes it essential to use some statistic techniques in order to obtain the information coming from the markets and to introduce it in the optimization models in a suitable way. In this aspect, one of the main contributions of this thesis has been the study the Spanish electricity price time series and its modeling by means of factor models. In this thesis, the new mechanism introduced by the Iberian Market that affects the physical operation of the units is described. In particular, it considers in great detail the inclusion of the physical futures contracts and the bilateral contracts into the day-ahead market bid of the generation companies. The rules of the market operator have been explicitly taken into account within the mathematical models, along with all the classical operational constraints that affect the thermal and combined cycle units. The expression of the optimal bidding functions are derived and proved. Therefore, the models built in this thesis provide the generation company with the economic dispatch of the committed futures and bilateral contracts, the unit commitment of the units and the optimal bidding strategies for the generation company. Once these main objectives were fulfilled, we improved the previous models with an approach to the modeling of the influence that the sequence of very short markets have on optimal day-ahead bidding. These markets are cleared just before and during the day in which the electricity will be consumed and the opportunity to obtain benefits from them changes the optimal day-ahead bidding strategies of the generation company, as it will be shown in this thesis. The entire models presented in this work have been tested using real data from a generation company and Spanish electricity prices. Suitable results have been obtained and discussed.

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