Principals in the nation's schools have been tasked with managing crisis incidents that may occur with students and others on their campuses on a daily basis. The purposes of this study were to determine the differences, if any, that existed in Central Florida public school principals' perceptions regarding school security, their perceived confidence to address critical crisis incidents on their campuses, their perceptions of the likelihood critical incidents would occur, their perceptions of interaction with law enforcement, the critical incidents they fear the most, and their perceptions of factors impacting the incidents they fear the most. Principal subgroup mean responses to the Principal Safety and Security Perceptions Survey in the three areas of Bandura's (1997) triadic reciprocal causation were examined in the context of principals' gender, longevity, student enrollment, grade configuration, free and reduced lunch rate, presence of a law enforcement officer, and presence of a security plan. Findings revealed significant differences between categorical groups of principals in multiple areas. It was determined that significant differences in principals' perceptions warrant further study. Recommendations for practice include security policy development and practical application of noted trends.

Personal computer desktops, and other standardized computer architectures are optimized to provide the best performance for frequently occurring conditions. Real-time systems designed using worst-case analysis for such architectures under-utilize the hardware. This shortcoming provides the motivation for scheduling algorithms that can improve overall utilization by accounting for inherent uncertainty in task execution duration. A real-time task dispatcher must perform its function with constant scheduling overhead. Given the NP-hard nature of the problem of scheduling non-preemptible tasks, dispatch decisions for such systems cannot be made in real-time. This argues for a hybrid architecture that includes an offline policy generator, and an online dispatcher. This dissertation proposes, and demonstrates a hybrid operating system architecture that enables cost-optimal task dispatch on Commercial-Off-The-Shelf (COTS) systems. This is achieved by explicitly accounting for the stochastic nature of each task?s execution time, and dynamically learning the system behavior. Decision Theoretic Scheduling (DTS) provides the framework for scheduling under uncertainty. The real-time scheduling problem is cast as a Markov Decision Process (MDP). An offline policy generator discovers an epsilon-optimal policy using value iteration with model learning. For the selected representation of state, action, model, and rewards, the policydiscovered using value iteration is proved to have a probability of failure that is less than any arbitrarily small user-specified value. The PromisQoS operating system architecture demonstrates a practical implementation of the proposed approach. PromisQoS is a Linux based platform that supports concurrent execution of time-based (preemptible and non-preemptible) real-time tasks, and best-effort processes on an interactive workstation. Several examples demonstrate that model learning, and scheduling under uncertainty enables PromisQoS to achieve better CPU utilization than other scheduling methods. Real-time task sets that solve practical problems, such as a Laplace solver, matrix multiplication, and transpose, demonstrate the robustness and correctness of PromisQoS design and implementation. This pioneering application demonstrates the feasibility of MDP based scheduling for real-time tasks in practical systems. It also opens avenues for further research into the use of such DTS techniques in real-time system design.

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In this thesis, we investigate attack vectors against Markov decision processes anddynamical systems. This work is motivated by the recent interest in the researchcommunity towards making Machine Learning models safer to malicious attacks. Wefocus on different attack vectors: (I) attacks that alter the input/output signal of aMarkov decision process; (II) eavesdropping attacks whose aim is to detect a change ina dynamical system; (III) poisoning attacks against data-driven control methods.(I) For attacks on Markov decision processes we focus on 2 types of attacks: (1) attacksthat alter the observations of the victim, and (2) attacks that alter the control signalof the victim. Regarding (1), we investigate the problem of devising optimal attacksthat minimize the collected reward of the victim. We show that when the policy andthe system are known to the attacker, designing optimal attacks amounts to solving aMarkov decision process. We also show that, for the victim, the system uncertaintiesinduced by the attack can be modeled using a Partially Observable Markov decisionprocess (POMDP) framework. We demonstrate that using Reinforcement Learningmethods tailored to POMDP lead to more resilient policies. Regarding (2), we insteadinvestigate the problem of designing optimal stealthy poisoning attacks on the controlchannel of Markov decision processes. Previous work constrained the amplitude ofthe adversarial perturbation, with the hope that this constraint will make the attackimperceptible. However, such constraints do not grant any level of undetectabilityand do not take into account the dynamic nature of the underlying Markov process.To design an optimal stealthy attack, we investigate a new attack formulation, basedon information-theoretical quantities, that considers the objective of minimizing thedetectability of the attack as well as the performance of the controlled process.(II) In the second part of this thesis we analyse the problem where an eavesdropper triesto detect a change in a Markov decision process. These processes may be affected bychanges that need to remain private. We study the problem using theoretical tools fromoptimal detection theory to motivate a definition of online privacy based on the averageamount of information per observation of the underlying stochastic system. We provideways to derive privacy upper-bounds and compute policies that attain a higher privacylevel, concluding with examples and numerical simulations.(III) Lastly, we investigate poisoning attacks against data-driven control methods.Specifically, we analyse how a malicious adversary can slightly poison the data soas to minimize the performance of a controller trained using this data. We show thatidentifying the most impactful attack boils down to solving a bi-level non-convexoptimization problem, and provide theoretical insights on the attack. We present ageneric algorithm finding a local optimum of this problem and illustrate our analysisfor various techniques. Numerical experiments reveal that minimal but well-craftedchanges in the data-set are sufficient to deteriorate the performance of data-drivencontrol methods significantly, and even make the closed-loop system unstable. / <p>QC 20220510</p><p></p><p>Topic: Alessio Russo - LicentiateTime: May 31, 2022 04:00 PM Madrid</p><p> Zoom Meeting link https://kth-se.zoom.us/j/69452765598</p>

The purpose of this descriptive case study was to identify the strategies used by post-secondary military institutions to adopt, implement and train faculty for the use of new instructional technologies in the learning environment. Termed the Innovation Migration Process, it includes: 1) the adoption decision (selection of the innovation), 2) strategies for implementation and, 3) how faculty are trained on its use. The study was a two phased, explanatory, mixed-methods design beginning with a quantitative survey, followed by twelve qualitative interviews conducted at two exemplary institutions. The study identified two strategies are used to adopt new technology: 1) authoritative decisions from the "top-down" and 2) a bottom-up strategy where new technology is first used by innovators who work with a central organization to adopt the change. Five strategies were identified to implement the innovation: 1) centralized training; 2) leadership commitment; 3) tapping expertise; 4) well defined support for pedagogy and technical issues; and 5) a robust infrastructure. Four strategies were found for training faculty: 1) tapping expertise (indicating training and implementation are interwoven); 2) formal training; and 4) dedicated training time. The fourth strategy, incentives and rewards, was used successfully by one of the two exemplary institutions, but few of the other institutions offered either of these for training. Suggested guidelines for post-secondary, military institutions include: create a culture of innovativeness; demonstrated commitment by the leadership; follow Ely's Eight Conditions for Implementation; develop a centralized training organization; develop a robust technical support organization; invest in the infrastructure; seek out and support innovators; use a formal faculty development program. / Ph. D.

Situated within the belief that faculty development is a key institutional mechanism through which colleges and universities will be able to meet emerging social, cultural, and technological challenges in the coming years, this study sought to better understand the underlying psychological processes that facilitate the adoption of innovations by teaching faculty and GTAs in higher education. Specifically, three types of self-efficacy (college teaching, teaching with technology, and general) were considered in light of demographic variables and Rogers' model of the innovation-decision process. Most significant among the findings were that women have significantly higher college teaching self-efficacy and general self-efficacy than men; however, men have higher teaching with technology self-efficacy. Those in their forties, fifties and sixties have higher college teaching self-efficacy than those in their twenties. Full-time instructors have higher college teaching self-efficacy than doctoral GTAs and assistant professors. Those who rate themselves as having higher computer skills also have higher teaching with technology self-efficacy. When considering teaching with technology self-efficacy and instructional technology-based innovation-decision stage, it was found that this type of self-efficacy differs significantly between most stages and consistently increases from the knowledge stage through the confirmation stage. / Ph. D.

Understanding cage aquaculture adoption decisions and factors affecting adoption is necessary to ensure that fish production from cage aquaculture in Ghana is both significant and sustainable. The goal of this study was to provide a framework for understanding cage aquaculture adoption decisions and to identify factors affecting adoption, to inform decision makers as they formulate policies aimed at promoting cage aquaculture adoption in Ghana. I surveyed 122 respondents comprising current cage fish farmers, farmers who have abandoned cage aquaculture, and potential adopters of cage aquaculture such as, fish traders, fishermen and land-based fish farmers. Respondents answered questions related to knowledge, interest, constraints in cage aquaculture, and demographics. I used non-metric multidimensional scaling and discriminant function analysis to identify unique groups within the respondents, classify respondents according to their position in the innovation-decision continuum, and identify factors affecting cage aquaculture adoption. Based on their differences in knowledge and interests, I placed respondents into one of three stages of the cage aquaculture innovation-decision process model I developed: (1) Unawareness, (2) Knowledge, Persuasion, and Decision (KPD), and (3) Implementation (Confirmation and Abandonment). Respondents in the KPD and Implementation stages had knowledge, were more interested in cage aquaculture, and were aware of constraints in cage aquaculture, whereas respondents in the Unawareness stage lacked knowledge and interest in cage aquaculture, and did not clearly understand the constraints. Respondents who were males, belonged to the tribes Ewe and Akan, and who had fishing experience tended to be more interested in cage aquaculture. The lack of capital, high input costs, inability to adequately market fish, theft, lack of information sources, conflict over water use, and cage destruction by storms, were identified as the main constraints to cage aquaculture adoption in Ghana. The results of the study suggest that programs aimed at encouraging new entrants into cage aquaculture should focus on demographic characteristics such as gender, and tribe. However, demographic characteristics may affect adoption decisions and it may be important to consider them as such. Some recommendation to address the major constraints in cage aquaculture include: the Fisheries Directorate should (1) develop an efficient extension program that farmers can access regularly, especially, for farmers with no other information sources, (2) provide feed subsidy to enable farmers produce fish at competitive prices, (3) facilitate the formation of fish farmers' cooperative groups that would purchase large quantities of feed, (4) encourage local production of high quality fish feed, and (5) develop credit facilities that can be accessed by individuals interested in cage aquaculture to assist potential farmers who would, otherwise, not be able to adopt cage aquaculture . In addition, fish farmers should (6) be proactive in marketing their fish by identifying potential niche markets prior to production, and (7) join cooperative groups to ease the burden of accessing loans to increase production. / Master of Science

El escenario actual de las redes móviles se caracteriza por la creciente demanda de los usuarios por los servicios de datos, circunstancia que se ha visto potenciada por la popularidad de los teléfonos inteligentes y el auge de aplicaciones que necesitan de una conexión permanente a internet, como aquellas que hacen uso de recursos "en la nube" o los servicios de streaming para vídeo. El consumo de datos crece exponencialmente, tanto para los países desarrollados como en los países en desarrollo, y esto ha llevado a los operadores a plantearse soluciones que permitan proveer dichas condiciones de acceso. Las redes heterogéneas se caracterizan por utilizar diferentes tecnologías de una manera coherente y organizada para proveer a los usuarios con la calidad de servicio requerida en sus comunicaciones, de tal manera que la comunicación sea para estos "transparente". Dicha heterogeneidad se puede dar a nivel de acceso, con la coexistencia de tecnologías como 802.11, WiMAX y redes móviles en sus diferentes generaciones, o incluso a nivel de capas dentro de las redes móviles con la coexistencia de macro, micro, pico y femto celdas. Haciendo un uso organizado de estos múltiples recursos, es posible optimizar las prestaciones de la red y proveer a los usuarios con una mejor calidad de servicio. Pero la posibilidad de mejorar las prestaciones de la red no se da sólo por el uso simultáneo de estas tecnologías de acceso. Para mejorar la eficiencia en el uso del espectro electromagnético, un recurso limitado y subutilizado según diferentes estudios, se propuso la tecnología de cognitive radio. Por medio de esta tecnología es posible que un usuario sea capaz de medir el instante en el que una parte del espectro electromagnético no esta siendo utilizado para enviar información, siempre evitando interferir en las comunicaciones de aquellos usuarios que usan dicho espectro regularmente. En el presente trabajo se proveen diferentes soluciones dentro del contexto de las redes heterogéneas que buscan optimizar el uso de los recursos disponibles en la red para proveer a los usuarios con la calidad de servicio esperada, ya sea por medio del control de acceso o la gestión de recursos. Por un lado se estudia el efecto que la reserva de canales para realizar handoff espectral tiene sobre las prestaciones para los usuarios secundarios en un sistema de cognitive radio. Por otro lado se estudian políticas de acceso para una red en la que dos tecnologías de acceso están disponibles: TDMA y WCDMA, y los usuarios tienen acceso a los servicios de voz y datos. Por otro lado / Performance requirements on mobile networks are tighter than ever as a result of the adoption of mobile devices such as smartphones or tablets, and the QoS levels that mobile applications demand for their correct operation. The data traffic volume carried in mobile networks for 2012 is the same as the total internet traffic in 2000, and this exponential growth tendency will continue in years to come. In order to fulfill users¿ expectations, it is imperative for mobile networks to make the best use of the available resources. Heterogeneous networks (Hetnets) have the ability to integrate several technologies in a coherent and efficient manner in order to enhance users¿ experience. The first challenge of heterogeneous networks is to integrate several radio access technologies, which exist as a result of simultaneous technology developments and a paced replacement of legacy technology. A joint management of several RAT¿s enhances network¿s efficiency, and this influences user¿s experience. Another challenge of heterogeneous networks is the improvement of current macrocells through an efficient use of the electromagnetic spectrum. Some approaches aim to optimize the antennas or use higher-order modulation techniques, but a more disruptive approach is the use of dynamic spectrum techniques through a technology known as cognitive radio. Finally, heterogeneous networks should be able to integrate several layers. In addition to the well studied micro and pico cells, a new generation of cheaper and easily configurable small cell networks have been proposed. However, its success is attached to its ability to adapt to the current context of mobile networks. / Pacheco Páramo, DF. (2013). Performance analysis of access control and resource management methods in heterogeneous networks [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34782

The radio-frequency spectrum is a precious resource, with many applications and users, especially with the recent spectrum auction in the United States. Future platforms and devices, such as radars and radios, need to be adaptive to their spectral environment in order to continue serving the needs of their users. This thesis considers an environment with one tracking radar, a single target, and a communications system. The radar-communications coexistence problem is modeled as a Markov decision process (MDP), and reinforcement learning is applied to drive the radar to optimal behavior. / Master of Science / The radio-frequency electromagnetic spectrum is a precious resource, in which users and operators are assigned frequency slots in which they can operate. The federal spectrum auction in the United States freed up some of the spectrum for shared use. The implications of this are the spectrum will become more dense; there will be more devices and users in the same amount of spectrum. The devices and platforms of this spectrum need to be more adaptive and agile in order to (1) not be interfered by other systems, (2) cause interference to other systems, and (3) continue to meet the needs of users (e.g. cell phone users) and operators (e.g. military radar). The work presented in this thesis applies Markov decision process and reinforcement learning to solve the problem.