Electric power systems are experiencing dramatic changes with respect to structure, operation and regulation and are facing increasing pressure due to environmental and societal constraints. Bulk electric system reliability is an important consideration in power system planning, design and operation particularly in the new competitive environment. A wide range of methods have been developed to perform bulk electric system reliability evaluation. Theoretically, sequential Monte Carlo simulation can include all aspects and contingencies in a power system and can be used to produce an informative set of reliability indices. It has become a practical and viable tool for large system reliability assessment technique due to the development of computing power and is used in the studies described in this thesis. The well-being approach used in this research provides the opportunity to integrate an accepted deterministic criterion into a probabilistic framework. This research work includes the investigation of important factors that impact bulk electric system adequacy evaluation and security constrained adequacy assessment using the well-being analysis framework.<p> Load forecast uncertainty is an important consideration in an electrical power system. This research includes load forecast uncertainty considerations in bulk electric system reliability assessment and the effects on system, load point and well-being indices and reliability index probability distributions are examined. There has been increasing worldwide interest in the utilization of wind power as a renewable energy source over the last two decades due to enhanced public awareness of the environment. Increasing penetration of wind power has significant impacts on power system reliability, and security analyses become more uncertain due to the unpredictable nature of wind power. The effects of wind power additions in generating and bulk electric system reliability assessment considering site wind speed correlations and the interactive effects of wind power and load forecast uncertainty on system reliability are examined. The concept of the security cost associated with operating in the marginal state in the well-being framework is incorporated in the economic analyses associated with system expansion planning including wind power and load forecast uncertainty. Overall reliability cost/worth analyses including security cost concepts are applied to select an optimal wind power injection strategy in a bulk electric system. The effects of the various demand side management measures on system reliability are illustrated using the system, load point, and well-being indices, and the reliability index probability distributions. The reliability effects of demand side management procedures in a bulk electric system including wind power and load forecast uncertainty considerations are also investigated. The system reliability effects due to specific demand side management programs are quantified and examined in terms of their reliability benefits.

Lack of patient adherence with medication results in health care costs and adverse clinical outcomes. Although fear of side effects can contribute to non-adherence, being informed about them can actually improve matters. Nonetheless, questions persist as to the most efficient way to convey that type of information to patients for a given medication. Information on side effects is largely limited to a simple list in medication leaflets, often without frequency data (that is, lacking detail as to how often they might occur). The decision-making literature suggests that the interpretation of information varies depending on the presentation format or the frame used. This study examined the impact of providing numerical information for side effect frequency, levels of illness severity, and side effect framing on the likelihood of taking an OTC medicine.<p> Participants received a headache scenario with three drug options (X, Y and Z) to consider for use. These painkillers had three levels of potency (defined as 50, 75, and 100% effective) and were accompanied with three levels of side effects (two, four, and six items). When considering their drug choice for the headaches, participants received drug information written without side effect frequency data, then again with side effect frequency data. Subjects rated their likelihood of taking Drug X, Y and Z on a scale of 1 (very unlikely) to 100 (very likely). Participants were also asked to show their likelihood of taking a different set of two medications for headaches (coined Drug N and P) based on positively-slanted or negatively-slanted wording in relation to chances of experiencing a side effect (heartburn).<p> Thirty subjects from Saskatoon over 50 years of age participated. The average age was 66.6 years and 63.3 percent of participants were female. Less than half of participants (n=11) had previous experience with side effects. Most participants were using at least one medicine (whether OTC or prescribed) and described themselves as knowledgeable or somewhat knowledgeable.<p> Participants were more likely to take the hypothetical drugs in the situations described when they received frequency data for side effects (p<0.05). Also, there was a significant higher mean likelihood of use when the drug was framed positively (p<0.01).<p> When considering decisions involving drug effectiveness and their side effects, the provision of frequency data increased patient likelihood of use. Framing the context in positive format also increased patient likelihood to use a medicine. This information could be important for pharmacists counseling on medication side effects, especially for those patients with medication adherence problems.

University of Macau / Institute of Chinese Medical Sciences

This thesis is written for the Bachelor of Arts degree in Game Design and Graphics at Gotland University in Sweden. A method used in graphic design for games with low-pixel density was initially studied in the course Advanced Game Project and has in this work been further developed. In general, since regular size-reduction of pictures often results in visually incomplete bitmaps, the goal of this thesis is to provide a better overview on the process of reduction where the important features of the original picture are maintained throughout the reduction phase.

This thesis addresses two main issues: first, forecasting short-term electricity market prices; and second, the application of short-term electricity market price forecasts to operation planning of demand-side Bulk Electricity Market Customers (BEMCs). The Ontario electricity market is selected as the primary case market and its structure is studied in detail. A set of explanatory variable candidates is then selected accordingly, which may explain price behavior in this market. In the process of selecting the explanatory variable candidates, some important issues, such as direct or indirect effects of the variables on price behavior, availability of the variables before real-time, choice of appropriate forecasting horizon and market time-line, are taken into account. Price and demand in three neighboring electricity markets, namely, the New York, New England, and PJM electricity markets, are also considered among the explanatory variable candidates. Electricity market clearing prices in Ontario are calculated every five minutes. However, the hourly average of these 5-minute prices, referred to as the Hourly Ontario Energy Price (HOEP), applies to most Ontario market participants for financial settlements. Therefore, this thesis concentrates on forecasting the HOEP by employing various linear and non-linear modeling approaches. The multivariate Transfer Function (TF), the multivariate Dynamic Regression (DR), and the univariate Auto Regressive Integrated Moving Average (ARIMA) are the linear time series models examined. The non-linear approaches comprise the Multivariate Adaptive Regression Splines (MARS), and the Multi-Layer Perceptron (MLP) neural networks. Multivariate HOEP models are developed considering two forecasting horizons, i.e. 3 hours and 24 hours, taking into account the case market time-line and the ability of market participants to react to the generated forecasts. Univariate ARIMA models are also developed for day-ahead market prices in the three neighboring electricity markets. The developed models are used to generate price forecasts for low-demand, summer peak-demand, and winter peak-demand periods. The HOEP forecasts generated in this work are significantly more accurate than any other available forecast. However, the accuracy of the generated HOEP forecasts is relatively lower than those of the price forecasts for Ontario's neighboring electricity markets. The low accuracy of the HOEP forecasts is explained by conducting a price volatility analysis across the studied electricity markets. This volatility analysis reveals that the Ontario electricity market has the most volatile prices compared to the neighboring electricity markets. The high price volatility of the Ontario electricity market is argued to be the direct result of the real-time nature of this market. It is further observed that the inclusion of the just-in-time publicly available data in multivariate HOEP models does not improve the HOEP forecast accuracy significantly. This lack of significant improvement is attributed to the information content of the market data which are available just-in-time. The generated HOEP forecasts are used to plan the short-term operation of two typical demand-side case-study BEMCs. The first case-study BEMC is a process industry load with access to on-site generation facilities, and the second one is a municipal water plant with controllable electric demand. Optimization models are developed for the next-day operation of these BEMCs in order to minimize their total energy costs. The optimization problems are solved when considering market price forecasts as the expected future prices for electricity. The economic impact of price forecast inaccuracy on both the case study is analyzed by introducing the novel Forecast Inaccuracy Economic Impact (FIEI) index. The findings of this analysis show that electricity market price forecasts can effectively be used for short-term scheduling of demand-side BEMCs. However, sensitivity to price forecast inaccuracy significantly varies across market participants. In other words, a set of price forecasts may be considered ``accurate enough'' for a customer, while leading to significant economic losses for another.

Smart cards are small, portable, tamper-resistant computers used in security-sensitive applications ranging from identification and access control to payment systems. Side-channel attacks, which use clues from timing, power consumption, or even electromagnetic (EM) signals, can compromise the security of these devices and have been an active research area since 1996. Newer ``contactless'' cards communicate using radio frequency (RF), without physical contact. These contactless smart cards are sometimes grouped with radio frequency identification (RFID) devices in popular usage of the term. This thesis investigates devices that use the ISO 14443 (proximity card) protocol, a large class of contactless/RFID devices. Although contactless smart cards are increasingly common, very few reproducible practical attacks have been published. Presently, there are no known documented side-channel attacks against contactless Java Cards (open standard multi-application cards) using generic unmodified hardware. This thesis develops a research-friendly platform for investigating side-channel attacks on ISO 14443 contactless smart cards. New techniques for measurement and analysis, as well as the first fully documented EM side-channel monitoring procedure, are presented for a contactless Java Card. These techniques use unmodified, commercial off-the-shelf hardware and are both practical and broadly applicable to a wide range of ISO 14443 devices, including many payment cards and electronic passports.

Although there have been tremendous improvements in crash safety there has been an increasing trend in side impact fatalities, rising from 30% to 37% of total fatalities from 1975 to 2004 (NHTSA, 2004). Between 1979 and 2004, 63% of AIS≥4 injuries in side impact resulted from thoracic trauma (NHTSA, 2004). Lateral impact fatalities, although decreasing in absolute numbers, now comprise a larger percentage of total fatalities. Safety features are typically more effective in frontal collisions compared to side impact due to the reduced distance between the occupant and intruding vehicle in side impact collisions. Therefore, an increased understanding of the mechanisms governing side impact injury is necessary in order to improve occupant safety in side impact auto crash. This study builds on an advanced numerical human body model with focus on a detailed thoracic model, which has been validated using available post mortem human subject (PMHS) test data for pendulum and side sled impact tests (Forbes, 2005). Crash conditions were investigated through use of a modified side sled model used to reproduce the key conditions present in full scale crash tests. The model accounts for several important factors that contribute to occupant response based on the literature. These factors are; the relative velocities between the seat and door, the occupant to door distance, the door shape and compliance. The side sled model was validated by reproducing the crash conditions present in FMVSS 214 and IIHS side impact tests and comparing the thoracic compression, velocity, and Viscous Criterion (VC) response determined by the model to the response of the ES-2 dummy used in the crash tests. Injury was predicted by evaluating VCmax, selected for its ability to predict rate-sensitive soft tissue injury during thoracic compression (Lau & Viano, 1986). The Ford Taurus FMVSS 214 and Nissan Maxima IIHS tests were selected from side impact crash test data found in the NHTSA database because they included factors not present in standard side impact test procedures. These factors were; the presence of door accelerometers used to provide input velocities to the side impact model and the use of a ES-2 (rather than the SID) to facilitate comparison of VC response to the human body model. Also, the two crash test procedures (FMVSS 214 & IIHS) were selected to ensure accurate side impact model response to different impact scenarios. The side impact model was shown to closely reproduce the timing and injury response of the full-scale FMVSS 214 side impact test of a Ford Taurus, as well as the IIHS side impact test of a Nissan Maxima. The side impact model was then used to investigate the effects of door to occupant spacing, door velocity profile, armrest height, seat foam, restraint system, and arm position. It was found that the VCmax was controlled by both the first and second peaks typically found in door velocity profiles, but the effect of each varies depending on the situation. This study found that VCmax was reduced by 73-88% when door intrusion was eliminated compared to the VC response incurred by an intruding door. Also, the presence of a deformable door based on physical geometry and material characteristics rather than a simplified rigid door reduced VCmax by 16% in this study. The study on seat foam determined that significant effects on VC response can be made by modest adjustments in foam properties. Low stiffness seat foam was found to increase VCmax by 41% when compared to the VC response when using high stiffness foam. Arm position has been proven to be a relevant factor in side impact crash. Positioning the arms parallel to the thorax, in the “down” position, caused a 42% increase in VCmax when compared to the VC response determined with the arms positioned at 45 degrees. Finally, although restraint systems have limited influence on side impact crash safety compared to front and rear impacts, this study found that the presence of a pre-tensioning restraint system reduced VCmax by 13% when compared to the VC response of an un-belted occupant. It should be noted that the current study was limited to velocity profiles obtained from a specific FMVSS 214 test and therefore results and observations are restricted to the confines of the input conditions used. However, the side impact model developed is a useful tool for evaluating factors influencing side impact and can be used to determine occupant response in any side impact crash scenario when the appropriate input conditions are provided.

Thoracic injury is the most dominant segment of automotive side impact traumas. A numerical model that can predict such injuries in crash simulation is essential to the process of designing a safer motor vehicle. The focus of this study was to develop a numerical model to predict lung response and injury in side impact car crash scenarios. A biofidelic human body model was further developed. The geometry, material properties and boundary condition of the organs and soft tissues within the thorax were improved with the intent to ensure stress transmission continuity and model accuracy. The thoracic region of the human body model was revalidated against three pendulum and two sled impact scenarios at different velocities. Other body regions such as the shoulder, abdomen, and pelvis were revalidated. The latest model demonstrated improvements in every response category relative to the previous version of the human body model. The development of the lung model involved advancements in the material properties, and boundary conditions. An analytical approach was presented to correct the lung properties to the in-situ condition. Several injury metric predictor candidates of pulmonary contusion were investigated and compared based on the validated pendulum and sled impact scenarios. The results of this study confirmed the importance of stress wave focusing, reflection, and concentration within the lungs. The bulk modulus of the lung had considerable influence on injury metric outcomes. Despite the viscous criterion yielded similar response for different loading conditions, this study demonstrated that the level of contusion volume varied with the size of the impact surface area. In conclusion, the human body model could be used for the analysis of thoracic response in automotive impact scenarios. The overall model is capable of predicting thoracic response and lung contusion. Future development on the heart and aorta can expand the model capacity to investigate all vital organ injury mechanisms.

Sripada and Konrath (forthcoming) use Structural Equation Modeling techniques to provide empirical evidence for the claim that implicit and automatic inferences about people’s dispositions, and not normative judgments, are the driving cause behind the pattern of folk judgments of intentional action in Knobe’s (2003a) chairman case. However, I will argue that their evidence is not as strong as they claim due to the potential of methodological and statistical problems with the way they tested their model. After correcting for these problems, I show that even after accounting for the role of dispositional inferences, normative judgments are still playing a significant role in folk judgments of intentional action.

Syftet med studien var att beskriva vilka biverkningar individer som behandlas med antipsykotika upplever och dess konsekvenser för livskvaliteten samt hur vårdpersonalen kan ge stöd till drabbade individer i vardagen för att minska obehaget av biverkningar. Metoden som användes var en avgränsad systematisk litteraturstudie. Vetenskapliga artiklar söktes via två databaser. Totalt inkluderades tio artiklar som genomgick kvalitets- och resultatanalys. Resultatet visade att vanligt förekommande biverkningar av antipsykotika som patienterna upplevde och rapporterade var psykiska, extrapyramidala följt av endokrina och metaboliska effekter samt övriga biverkningar som autonoma, antikolinerga och allergirelaterade. Resultaten visade att en sjuksköterskeledd vårdtjänst kunde upptäcka fysiska problem som ohälsosam livsstil och fetma och därmed åstadkomma positiv livsförändig och viktnedgång. Studierna ger även förslag på copingstrategier som stöd vid biverkningar trötthet och viktuppgång. Slutsatsen: Studien har visat att patienter med psykossjukdomar upplevde olika biverkningar av antipsykotika som de måste ta för att förebygga återfall i psykos. Det finns omvårdnadsåtgärder och stöd till patienter som gör det lättare att klara vardagslivet trots biverkningar. Dock behövs mer forskning om omvårdnadsåtgärder och stöd. / The aim of this study was to describe the side effects experienced by individuals treated with antipsychotics, their consequence in life quality and how care staff can give support to these individuals to reduce discomfort of the side effects in their daily life. The method was a determinate literature review. The scientific articles where found in the database PubMed. A total of ten articles where included and were analyzed based on their quality and contents. The results showed that the most common of antipsychotic side effects that the patient experienced and reported  were psychic, extrapyramidal followed by endocrine and the metabolic issue and other side effects with autonomic, anticholinergic and allergy related. The result showed that a nurse-led service with provided care delivery could discover physical health problems such as unhealthy lifestyle and obesity, and consequently achieve positive changes of life and weight loss. The studies even gave suggestions of strategies to cope with sedation, tiredness and weight gain. Conclusion of this literature review was that the patients with psychotic illnesses perceived different side effects from the antipsychotic medication that they had to take to prevent fallback in psychos. There is even nursing care and support to patients which make daily life easier in spite of side effects. However more research is needed about nursing methods and support.