Thesis (Ph.D.)--Kent State University, 2005. / Title from PDF t.p. (viewed Feb. 23, 2005). Advisor: Acar, William. Available online via OhioLINK's ETD Center. Keywords: strategy making; causal mapping; multi-agent systems; knowledge management; dialectical inquiry Includes bibliographical references (p. 111-116).

This thesis is an effort to develop closed-loop control strategies on computer networks and study their stability in the presence of network delays and packet losses. An algorithm using predictors was designed to ensure the system stability in presence of network delays and packet losses. A single actuator magnetic ball levitation system was used as a test bed to validate the proposed algorithm. A brief study of real-time requirements of the networked control system is presented and a client-server architecture is developed using real-time operating environment to implement the proposed algorithm. Real-time performance of the communication on Ethernet based on user datagram protocol (UDP) was explored and UDP is presented as a suitable protocol for networked control systems. Predictors were designed based on parametric estimation models. Autoregressive (AR) and autoregressive moving average (ARMA) models of various orders were designed using MATLAB and an eighth order AR model was adopted based on the best-fit criterion. The system output was predicted several steps ahead using these predictors and control output was calculated using the predictions. This control output output was used in the events of excessive network delays to maintain system stability. Experiments employing simulations of consecutive packet losses and network delays were performed to validate the satisfactory performance of the predictor based algorithm. The current system compensates for up to 20 percent data losses in the network without loosing stability.

Multiparty computation is a computation between multiple players which want to compute a common function based on private input. It was first proposed over 20 years ago and has since matured into a well established science. The goal of this thesis has been to develop efficient protocols for different operations used in multiparty computation and to propose uses for multiparty computation in real world systems. This thesis therefore gives the reader an overview of multiparty computation from the simplest primitives to the current state of software frameworks for multiparty computation, and provides ideas for future applications. Included in this thesis is a proposed model of multiparty computation based on a model of communication complexity. This model provides a good foundation for the included papers and for measuring the efficiency of multiparty computation protocols. In addition to this model, a more practical approach is also included, which examines different secret sharing schemes and how they are used as building blocks for basic multiparty computation operations. This thesis identifies five basic multiparty computation operations: sharing, recombining, addition, multiplication and negation, and shows how these five operations can be used to create more complex operations. In particular two operations “less-than” and “bitwise decomposition” are examined in detail in the included papers. “less-than” performs the “<” operator on two secret shared values with a secret shared result and “bitwise decomposition” takes a secret shared value and transforms it into a vector of secret shared bitwise values. The overall goal of this thesis has been to create efficient methods for multiparty computation so that it might be used for practical applications in the future.

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The topic of this thesis is the study of energy storage systems operating with wind power plants. The motivation for applying energy storage in this context is that wind power generation is intermittent and generally difficult to predict, and that good wind energy resources are often found in areas with limited grid capacity. Moreover, energy storage in the form of hydrogen makes it possible to provide clean fuel for transportation. The aim of this work has been to evaluate how local energy storage systems should be designed and operated in order to increase the penetration and value of wind power in the power system. Optimization models and sequential and probabilistic simulation models have been developed for this purpose. Chapter 3 presents a sequential simulation model of a general windhydrogen energy system. Electrolytic hydrogen is used either as a fuel for transportation or for power generation in a stationary fuel cell. The model is useful for evaluating how hydrogen storage can increase the penetration of wind power in areas with limited or no transmission capacity to the main grid. The simulation model is combined with a cost model in order to study how component sizing and choice of operation strategy influence the performance and economics of the wind-hydrogen system. If the stored hydrogen is not used as a separate product, but merely as electrical energy storage, it should be evaluated against other and more energy efficient storage options such as pumped hydro and redox flow cells. A probabilistic model of a grid-connected wind power plant with a general energy storage unit is presented in chapter 4. The energy storage unit is applied for smoothing wind power fluctuations by providing a firm power output to the grid over a specific period. The method described in the chapter is based on the statistical properties of the wind speed and a general representation of the wind energy conversion system and the energy storage unit. This method allows us to compare different storage solutions. In chapter 5, energy storage is evaluated as an alternative for increasing the value of wind power in a market-based power system. A method for optimal short-term scheduling of wind power with energy storage has been developed. The basic model employs a dynamic programming algorithm for the scheduling problem. Moreover, different variants of the scheduling problem based on linear programming are presented. During on-line operation, the energy storage is operated to minimize the deviation between the generation schedule and the actual power output of the wind-storage system. It is shown how stochastic dynamic programming can be applied for the on-line operation problem by explicitly taking into account wind forecast uncertainty. The model presented in chapter 6 extends and improves the linear programming model described in chapter 5. An operation strategy based on model predictive control is developed for effective management of uncertainties. The method is applied in a simulation model of a wind-hydrogen system that supplies the local demand for electricity and hydrogen. Utilization of fuel cell heat and electrolytic oxygen as by-products is also considered. Computer simulations show that the developed operation method is beneficial for grid-connected as well as for isolated systems. For isolated systems, the method makes it possible to minimize the usage of backup power and to ensure a secure supply of hydrogen fuel. For grid-connected wind-hydrogen systems, the method could be applied for maximizing the profit from operating in an electricity market. Comprehensive simulation studies of different example systems have been carried out to obtain knowledge about the benefits and limitations of using energy storage in conjunction with wind power. In order to exploit the opportunities for energy storage in electricity markets, it is crucial that the electrical efficiency of the storage is as high as possible. Energy storage combined with wind power prediction tools makes it possible to take advantage of varying electricity prices as well as reduce imbalance costs. Simulation results show that the imbalance costs of wind power and the electricity price variations must be relatively high to justify the installation of a costly energy storage system. Energy storage is beneficial for wind power integration in power systems with high-cost regulating units, as well as in areas with weak grid connection. Hydrogen can become an economically viable energy carrier and storage medium for wind energy if hydrogen is introduced into the transportation sector. It is emphasized that seasonal wind speed variations lead to high storage costs if compressed hydrogen tanks are used for long-term storage. Simulation results indicate that reductions in hydrogen storage costs are more important than obtaining low-cost and high-efficient fuel cells and electrolyzers. Furthermore, it will be important to make use of the flexibility that the hydrogen alternative offers regarding sizing, operation and possibly the utilization of oxygen and heat as by-products. The main scientific contributions from this thesis are the development of - a simulation model for estimating the cost and energy efficiency of wind-hydrogen systems, - a probabilistic model for predicting the performance of a gridconnected wind power plant with energy storage, - optimization models for increasing the value of wind power in electricity markets by the use of hydrogen storage and other energy storage solutions and the system knowledge about wind energy and energy storage that has been obtained by the use of these models. / Paper 1 is reprinted with kind permission of ACTA Press. Paper 2 is reprinted with kind permission of Elsevier/ Science Direct. http://www.elsevier.com, http://www.sciencedirect.com Paper 3 is reprinted with kind permission of IEEE.

State estimation plays an essential role in the monitoring and control of power transmission systems. In modern, highly inter-connected power systems the state estimation should be performed in a distributed fashion and requires information exchange between the control centers of directly connected systems. Motivated by recent reportson trojans targeting industrial control systems, in this paper we investigate how a single compromised control center can affect the outcome of distributed state estimation. We describe five attack strategies, and evaluate their impact on the IEEE 118 benchmark power system. We show that that even if the state estimation converges despite the attack, the estimate can have up to 30% of error, and bad data detection cannot locate theattack. We also show that if powerful enough, the attack can impede the convergence of the state estimation, and thus it can blind the system operators. Our results show that it is important to provide confidentiality for the measurement data in order to prevent the most powerful attacks. Finally, we discuss a possible way to detect and to mitigate these attacks. / <p>QC 20130522</p>

In this study, we consider a relay network, with two transceivers and r relay nodes. We assume that each of relays and the two transceivers have a single antenna. For establishing the connection between these two transceivers, we propose a two-way relaying scheme which takes three phases (time slots) to accomplish the exchange of two information symbols between the two transceivers. In the first and second phases, the transceivers, transmit their signals, toward the relays, one after other. The signals that are received by relays are noisy versions of the original signals. Each relay, multiplies its received signal by a complex beamforming coefficient to adjust the phase and amplitude of the signal. Then in the third phase, each relay transmits the summation of so-obtained signals to both transceivers. Our goal is to find the optimal values of transceivers’ transmit powers and the optimal values of the beamforming coefficients by minimizing the total transmit power subject to quality of service constraints. In our approach, we minimize the total transmit power under two constraints. These two constraints are used to guarantee that the transceivers’ receive Signal-to-Noise Ratios (SNRs) are above given thresholds. To solve the underlying optimization problem, we develop two techniques. The first technique is a combination of a two-dimensional search and Second-Order Convex Cone Programming (SOCP). More specifically, the set of feasible values of transceivers’ transmit powers is quantized into a sufficient fine grid. Then, at each vertice of this grid, an SOCP problem is solved to obtain the beamforming coefficients such that for the given pair of transceivers’ transmit powers, the total transmit power is minimized. The pair of the transceivers’ transmit powers, which result in the smallest possible value of the total transmit power, leads us to the solution of the problem. This approach requires a two-dimensional search and solving an SOCP problem at each point of the corresponding two-dimensional grid. Thus, it can be prohibitively expensive in terms of computational complexity. As a second method, we resort to a gradient based steepest descent technique. Our simulation results show that this second technique performs very close to the optimal two-dimensional search based algorithm. Finally we compare our technique with multi-relay distributed beamforming schemes, previously developed in literature and show that our three-phase two-way relaying scheme requires less total power as compared to the two-phase two-way relaying method. On the other hand, the two-phase two-way relaying achieves higher data rates when compared with three-phase two-way relaying for the same total transmit power. Also, we observe that the three-phase scheme has more degrees of freedom while multi-relay distributed beamforming schemes, previously developed in literature appears to be more bandwidth efficient. / UOIT

Distributed Leadership is often considered an optimal form of leadership to improve student achievement. The challenge though is that previous research on distributed leadership has often described what distributed leadership is as opposed to what distributed leadership's impact on student achievement might be. Since leadership has an indirect effect on student achievement, exploring organizational factors that may have a more direct impact on student achievement is important. Academic optimism describes teachers' perceptions of the staff's collective efficacy, the trust experienced between teachers, and between teachers and administrators, and the extent to which academic press (high expectations) is evident in the school. Academic optimism is an organizational factor that improves student achievement according to previous research. This thesis examined patterns of distributed leadership and their correlation to academic optimism. Further I examined the impact that academic optimism has on student achievement. By surveying 2122 teachers in 113 schools in a large school board in south-central Ontario, I determined that planfully aligned distributed leadership had a significant correlation to academic optimism but academic optimism did not have a significant correlation to student achievement. Rather, academic press, one of the variables within academic optimism, did have a significant correlation to student achievement in language and math. This study concluded that planfully aligned distributed leadership mediated by academic press had a significant impact on student achievement.

In this work, a systematic methodology to construct distributed layouts has been developed. Previous researches in this field suggest distributed layouts as an alternative to process layouts. But there has been no systematic methodology so far to develop distributed layouts. Earlier works concentrate on evaluating different production schedules for randomly distributed resources throughout the plant floor. As opposed to former approaches, in this work, distributed layouts are developed based on actual production and routing data. Taking into account the exact capacity requirements of machines, a methodical approach to distribute resources rather than random assignment is considered. The need for developing process layouts is analyzed and justified using product similarity and cell utilization. Process layouts are developed only when the given production data meets process layout requirements. The efficiency of proposed approach relative to traditional process layout strategy has been evaluated in terms of material handling cost for both single and multi period settings. In a multi period setting, the impact of demand disturbances on both process and distributed layouts is studied using case studies. From the case study results, it is concluded that distributed layouts constructed using proposed approach performs exceedingly well over traditional process layout approach. Distributed layouts proved to be efficient and robust for both single and multi-period cases. Even huge fluctuations in demand level of products had only little impact on distributed layouts whereas process layouts suffered tremendous loss in terms of material handling cost. It turned out that for all cases, the improvement in efficiency of distributed layouts was more than 30% over process layouts. / Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering.

The thesis addresses three main problems in the area of user modeling and adaptation in the context of online communities:<p> 1) Dealing with unique and changing user modeling needs of online communities. <p> 2) Involving users in design of the user modeling process.<p> 3) Interoperability of user models across different communities.<p> A new policy based-approach for user modeling is proposed, that allows explicit declarative representation of the user modeling and adaptation process in terms of policies, which can be viewed and edited by users. This policy-based user model framework is implemented in the MCComtella community framework, developed as part of this thesis work, which allows hosting multiple communities, creating new communities by users, and which supports users in setting explicit user modeling policies defining participation rewards, roles and movement of users across communities.