This study analyzes the syntactic structure of motion predicates in Mandarin, with a specific focus on how the language expresses paths of motion and telicity. It adopts a generative-constructionist model called the Exo-Skeletal Model. Data were gathered from three native speakers of Mandarin living in Taiwan, using video prompts depicting various types of motion events. Upon seeing a prompt, the speakers produced a sentence or sentences describing the event in the prompt. Based on the data, this study points out a number of syntactic patterns unique to Mandarin, and it proposes an explanatory account of these patterns.

Denna uppsats bygger på idén om att hacka det egna systemet före en utomstående hackare gör det för att upptäcka systemets läckor. Detta görs med ett automatiserat hackingverktyg som utför penetrationstester mot en utvecklad hemsida. Lagringstekniken som används är en eventdatabas med namnet Event Store som lagrar varje händelse som skedde mot hemsidan. Syftet med Event Store är att upptäcka de olika penetrationstesterna och lagra dess händelser för att sedan ge indikationer till administratören att hemsidan var under attack. Uppsatsen riktar sig främst på ifall Event Store är lämpligt att implementera tillsammans med en hemsida som blir attackerad med penetrationstester och vilka för- och nackdelar det finns med att använda Event Store. Resultatet visar att Event Store kan användas för att identifiera anomalier mot en hemsida vid hackingattacker. Med stor sannolikhet kan intrång mot hemsidan bevisas med hjälp utav det utvecklade systemet med Event Store. / This thesis is based on the idea of hacking your own system before an outside hacker does it to find the system vulnerabilities. This is done with an automated hacking tool that performs penetration tests against the created website. The database technology that is used is the event database Event Store that stores every event that take place against the website. The task of Event Store in this case is to discover the different penetration tests and to store the events and to give indications to the administrator that the website was under attack. The study is primarily aimed at finding out whether Event Store is advisable to implement with a website where different penetration testing shall be made, and what the advantages and disadvantages are to using Event Store. Results show that Event Store can be used to identify anomalies against a website during attacks. Intrusions against the website can with great probability be proven with the help of the developed system with Event Store.

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Accessing and exploiting organizational resources plays an integral role in not only a firm’s propensity to achieve a competitive advantage, but also its mere survival in a competitive environment (Ulrich & Barney, 1984). One of the most common means of resource acquisition for both large administrative firms and smaller entrepreneurial enterprises is interorganizational alliances (Ireland, Hitt, & Vaidyanath, 2002). Utilizing the resource-based view of the firm within a strategic alliance framework, this dissertation examines a particular type of interorganizational exchange relationship permeating the marketing discipline. The promotional alliance is defined within this research as a strategic alliance based on resource exchange between a promoting enterprise and a firm seeking to fulfill promotion-based objectives through an ongoing collaboration with the enterprise. Each of the two sides of the promotional alliance relationship served as a focus for one of the two studies presented within this work. In the first study, a longitudinal survival model was employed to investigate the dependency of a promotional enterprise on external resource acquisition via alliances with promotion-seeking firms. Also at issue were the heterogeneity of resources accessed and the dynamics of the institutional forces regulating such alliances. Alliances with sponsoring firms offering financial and performance-based resources, as opposed to operational resources, were found to have a significant influence on the survival of sponsored enterprises. However, these dependencies were subject to changes in institutional support and the potential for diminishing returns. The second study approached promotional alliances from the perspective of the firms seeking promotion. Relying on the theory of efficient capital markets (Fama, 1970), an event study analysis was undertaken to determine the impact of internationally prominent promotional alliance announcements on the equity value of the sponsoring firms, which theoretically reflects investors’ expectations of future cash flows. Contrary to prior research, the initiation of these alliances demonstrated a negative impact on shareholder value. Several alliance, firm, and promoting partner characteristics were hypothesized to influence alliance outcomes to varying degrees within the cross-sectional sample of promotion-seeking firms. Surprisingly, only the magnitude of the sponsoring firm’s alliance investment and the nationality congruence within the alliance were influential in predicting investors’ reaction to such alliances. Each study was embedded within the institutional context of Formula One (F1) motor racing and focused on the promotional alliances involving corporate partners (sponsoring firms) and their affiliated racing teams. In this context, the racing teams acted as the promoting enterprises charged with providing the marketing platform to meet their sponsoring firms’ objectives. With annual races on four or more continents; a global television audience rivaled only by the Olympics’ opening ceremony, FIFA World Cup finals, and the NFL’s Super Bowl; direct competition between promoting teams; and sponsoring firms hailing from fifteen different nations and over twenty diverse industry sectors; F1 provided an ideal setting for the evaluation of interorganizational alliances’ impact on the survival of promoting enterprises and a promotion-seeking firm’s value implications. To compliment and strengthen the applied contribution of both studies, the analyzed results were subjected to a discussion with industry experts representing both sides of the promotional alliance relationship (Lane & Jacobson, 1995). Not only did this closing analysis reinforce the relevance of the research offered here, but it also presented a practitioner-focused examination of the industry challenges inherent in the theoretical tenets underlying such research.

Background and Objectives: I investigated the use of sensitivity analyses in assessing statistical results or analytical approaches in three different statistical issues: (1) accounting for within-subject correlations in analyzing discrete choice data, (2) handling both-armed zero-event studies in meta-analyses for rare event outcomes, and (3) incorporating external information using Bayesian approach to estimate rare-event rates. Methods: Project 1: I empirically compared ten statistical models in analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening. Logistic and probit models with random-effects, generalized estimating equations or robust standard errors were applied to binary, multinomial or bivariate outcomes. Project 2: I investigated the impacts of including or excluding both-armed zero-event studies on pooled odds ratios for classical meta-analyses using simulated data. Five commonly used pooling methods: Peto, Mantel-Haenszel fixed/random effects and inverse variance fixed/random effects, were compared in terms of bias and precision. Project 3: I explored the use of Bayesian approach to incorporate external information through priors to verify, enhance or modify the study evidence. Three study scenarios were derived from previous studies to estimate inhibitor rates for hemophilia A patients treated with rAHF-PFM: 1) a single cohort of previously treated patients, 2) individual patient data meta-analysis, and 3) an previously unexplored patient population with limited data. Results and Conclusion: Project 1: When within-subject correlations were substantial, the results from different statistical models were inconsistent. Project 2: Including both-armed zero-event studies in meta-analyses increased biases for pooled odd ratios when true treatment effects existed. Project 3: Through priors, Bayesian approaches effectively incorporated different types of information to strengthen or broaden research evidence. Through this thesis I demonstrated that when analyzing complicated health research data, it was important to use sensitivity analyses to assess the robustness of analysis results or proper choice of statistical models. / Dissertation / Doctor of Philosophy (PhD)

Объектом исследования является анализ накопленного российскими event-агентствами опыта составления программ и сценариев специальных мероприятий и раскрытие стратегии и технологии их планирования. Методологической основой исследования выступают теории event-менеджмента. Они позволяют раскрыть его специфику относительно процесса формирования механизмов нематериального стимулирования персонала и поддержания имиджа компаний посредством организации различных event'ов и, в частности, совершенствования их сценарной составляющей. / The objectives of the study are to analyze the experience gained by Russian event agencies in compiling programs and scenarios for special events and to reveal strategies and technologies for their planning. The methodological basis of the study is the theory of event management. They allow revealing its specifics regarding the process of formation of mechanisms of non-material incentives for personnel and maintaining the image of companies by organizing various events and, in particular, improving their scenario component. The research methods include document analysis, observation included, methods of comparison, analysis and synthesis.

In the field of vehicle durability, many individuals are focusing on methods for better replicating the durability a user will experience throughout the typical design lifespan of a vehicle (e.g., 100,000 miles). To estimate user durability a means of understand the types of damaging events and driving styles of uses must be understood. The difficulty with accurately estimating customer usage is, firstly, there is a large pool of possible roads for a user to drive along, for example, there are over 4 million miles of public roads in the United States, alone [1]. In addition, while measurements of these surfaces could be collected it would be impractical for two reasons, the first is the financial and extreme time burden this would take. Second, when collecting measurements of a road surface only the current state of a road surface can be measured, thus as a road deteriorates or is repaved the measurements collected would no longer be an accurate representation of the road. It should be mentioned that even, if all of the road surfaces were measured performing simulation and analysis of all of these road surfaces would be computationally intensive. Instead, it would be beneficial if select events that account for a significant portion of the damage a vehicle experiences can be identified. These damaging events could then be used in more complex vehicle simulation models and as input and validation of proving ground and laboratory durability testing. The objective of this research is to provide a means for improved estimation of vehicle durability, specifically a means for identifying, characterizing, and grouping unique separable damaging events from a road profile measurement. In order to achieve this objective a measure that can be used to identify separate damaging events from a road profile is developed. This measure is defined as Localized Pseudo Damage (LPD), which identifies the amount of damage each individual road excitation makes to the total accumulated damage for a single load path in a vehicle system. LPD is defined as a damage density to minimize the effect of measurement spacing on the resulting metric. The developed LPD measure is causal in that the value of LPD at a location is not affected by any future locations. In addition, for a singular event (e.g., impulse or step) in the absences of other excitations, the LPD value at the singular event location is equivalent to the total pseudo damage divided by the step size at the location. Once a measure of pseudo damage density is known at multiple locations along a road profile for multiple load paths of interest, then separable damaging events can be identified. To identify separable damaging events the activity of the vehicle system must be considered because separate damaging events can only occur when a region of inactivity is present across all load paths. Subsequently, an optimization problem is formed to determine the optimal active regions to maintain. The cost function associated with the optimization problem is defined to minimize the cost (number of locations maintained in damaging events) and maximize the benefit (the amount of pseudo damage maintained). Lastly, a statistical test is developed to assess if separate damaging events can be considered to be from the same general class of events based on their damage characteristics. The developed assessment methods establish the similarity between two more separable damaging events based on application specific user defined inputs. In the development, two example similarity metrics are defined. The first similarity metric is in terms of distance and the second is in terms of likelihood (probability). The developed statistical analysis uses the current state-of-the-art in clustering algorithms to allow for multiple damaging events to be identified and grouped together. / Doctor of Philosophy / In the automotive field determining the level of damage a typical production vehicle experiences over its lifetime has always been a desirable criterion to identify. This criterion is commonly referred to as customer usage. By understanding the typical customer usage of a vehicle over the lifetime of a vehicle, automotive engineers are able to improve the design of vehicle components. The issue with defining customer usage is that there are millions of miles of roads that a customer can travel on and millions of customers that all have unique driving characteristics. While it is possible to collect measurements of these road surfaces to use in further vehicle simulations, it is not feasible both from a financial and time perspective. In addition, the simulation and analysis of all road surfaces would be computationally intensive. However, if select damaging events (regions of the road surface that excessively contribute to accumulated damage) are identified, then they can be used in more complex vehicle durability analyses with lower computational efforts. In conventional damage analysis a total amount of accumulated damage is established for a known road surface. The issue with defining damage this way is that unique events which likely contributed a large amount of the accumulated damage cannot be identified. The first objective of this research is to define damage as a function of the vehicle's location along a road surface. Then, unique and separable damaging events can be identified and separated from sections of the road that do not significantly contribute to the accumulated damage. After defining this measure, an optimization problem is developed to identify damaging events based on maximizing the benefit (amount of damage accounted for in damaging events) and minimizing the cost (amount of road surface retained). Unique and separable damaging events are identified by solving this optimization problem. While the optimization problem identifies unique, separable damaging events, it is likely that some damaging events contain similar characteristics to each other. When performing additional durability analysis, it would be beneficial to form connections between similar damaging events to allow for analysis to be performed based on groups of events. To identify damaging events with similar characteristics, a statistical analysis is developed as the last contribution of this work. By combining this analysis with current state-of-the-art clustering algorithms and user provided definitions based on applications, similar damaging events are able to be grouped together.

Whilst studies on rhythm-keeping and error-related negativity have been conducted, previous studies have given participants auditory or visual cues to indicate the rhythm they are meant to be maintaining. In this electroencephalography study, a novel experiment called the Human Metronome Task was introduced, using healthy university students as participants. The Human Metronome Task tested the participants by having them tap in synchrony with a beat, and then having the beat be removed, with the participants still being supposed to maintain the same beat with their taps, now without any auditory or visual aids. The purpose was to see if deviations in unassisted rhythm keeping are sufficient to elicit error-related negativity. When comparing different deviations of the tap-timing of each participant to their average tap-timing, no significant differences in electroencephalography amplitude were found. It was concluded that the Human Metronome Task is unable to elicit error-related negativity in participants. It seems plausible that this is due to the ambiguity of whether responses are erroneous or accurate. Thus, it seems as if it is necessary for more indications of whether a response is erroneous or not for the elicitation of error-related negativity than was present in the Human Metronome Task.

No description available.

No description available.