This study was designed to explore the relations between some aspects of the global digital and human development over the last decade, using an analytical framework which includes factors considered to have an impact on national development suggested by theory and practice. The operational definition of the global digital divide linked access, adaptation and creation of information and knowledge via the use of digital information and communication technologies to national development processes, within a demographic, economic, political and social context. The methodology carried out to analyze the relations between the global digital divide and national development included the construction of a quantitative model for 174 developed and developing countries which explained more than 91% of the variability in development in 1997 in terms of the national info tech infrastructure, and another quantitative model which explained more than 43% of the changes in development over the last decade in terms of the national core computing and network capacity. Findings from the study suggest the existence of an S-shaped curve depicting differences between inadequate, weak, medium and strong national info tech infrastructures. In conclusion, the existence of a significant, strong and positive relation between national core computing and network capacity and progress in national development in developing countries over the last decade suggests that this single factor will play an increasingly important role in the near future / acase@tulane.edu

In this research, a theoretical foundation for modeling, analysis, and testing of a system for voltage collapse is developed. The boundary theorem of the load flow feasibility region (FR) is presented. Based on the proposed boundary theorem, a method of voltage stability analysis referred to as the Eigen-Structure Analysis (ESA) method, is developed that does not require complicated nonlinear programming calculations for evaluation of the closest unfeasible or boundary injection corresponding to a given power network operating point with voltage controlled and load buses. Furthermore the steady-state stability margin and the sensitivity of the stability margin to bus voltages and bus injections are defined. An algorithm for determining the stability margin and its sensitivity to bus voltages and bus injections is proposed which is capable of handling large scale power systems by utilizing the sparse matrix techniques for saving computation time and memory space. The unification of the concept of feasibility region and the concept of multiple load flow solution is also presented in this dissertation The Eigen-Structure Analysis method is applied to a number of test system models. The simulation results confirm the theory and show that the proposed stability margin decreases monotonically to zero when the system approaches voltage collapse. The voltage-weak points and key contributing factors affecting the system voltage instability can be identified according to the values of the sensitivity of the stability margin to bus voltages and bus injections / acase@tulane.edu

In this dissertation, we present an Extended Object Model (XOM) for the design and development of Knowledge Based Management Systems (KBMS). We define a set of operations on the object model and explain the semantics of the model in terms of first order logic. To study the inferencing capabilities of the graph underlying our model, we introduce the notion of XOM graph and capture the behaviors of the object classes present in a XOM through an Action Integrated Extended Object Model (AIXOM). Furthermore, we incorporate imprecision in XOM in the basic object types as well in their abstractions. We apply the XOM in conceptualizing the design of Knowledge Based Management Systems and propose a KBMS Developing Environment (KBMSDE) on the basis of that design. Subsequently, we show that the set of XOM operations is complete in KBMSDE and then outline the ways of implementing imprecision in it. At a deeper level of abstraction, we conceptualize the Knowledgebase, the KBMS Shell and the Knowledge-Editor, all constituents of a KBMS. We analyze the XOM graph, derived from its associated Rulebase, for its connectivity in relation to its inference intensive completeness and describe the activities of the Shell and the Editor through their AIXOM. To explain and illustrate the underlying theories, we provide several examples. Finally, we compare the capabilities and limitations of our approach with other models with an insight to future research in this area. / Source: Dissertation Abstracts International, Volume: 52-08, Section: B, page: 4304. / Major Professor: Abraham Kandel. / Thesis (Ph.D.)--The Florida State University, 1991.

Relationship Systems Outside the Therapy Room| A Grounded Theory on Seasoned MFT Doctoral Graduates Utilizing Their Systemic Training in Human Service Team-based Organizations

Visible Light Communications (VLC) is a fast-growing technology to provide data communication using low-cost and omni-present LEDs and photodiodes. In this thesis, we make the case for the use of vehicular VLC (V2LC) as follows. We describe an architecture for V2LC networks and introduce five network services that V2LC needs to provide for vehicular applications. We use a custom VLC prototype developed at Intel on which we investigate the unique networking properties of V2LC. Specifically, our experiments show that a V2LC receiver's narrow filed-of-view angle makes V2LC resilient to visible light noise from sunlight and legacy LED sources and interference from active VLC transmitters; further, V2LC can operate in full-duplex mode with the exception of being subject to multipath effects at very short distances, e.g., 1.5 m in our experiment. By performing a large scale simulation study and leveraging our experimental data, we evaluate V2LC's ability to provide network services for vehicular applications. Our results reveal two key findings: (i) in dense vehicle traffic conditions (e.g., urban highway during peak hours), V2LC takes advantage of multiple available paths to reach vehicles and overcomes the effects of packet collisions; (ii) in the presence of a visible light blockage in traffic, V2LC can still have a significant number of successful transmissions because of the dynamic gaps in the blockage caused by vehicular movements.

Systematic design and analysis of fuzzy dynamic systems has been a problem which attracted much attention from researchers in recent years. In this dissertation, we propose a methodology for analysis and design of fuzzy dynamic systems. First, we introduce a new way to treat fuzzy sets: fuzzy sets as points in fuzzy state space. We investigate the relationship between membership functions and their corresponding fuzzy set points in fuzzy state space. We then examine the formulation and stability issues of fuzzy dynamic systems based on the geometric structure of fuzzy state space, resulting in the generalization and extension of classical stability definitions to fuzzy dynamic systems. We also introduce cellular structure to fuzzy state space, allowing a discrete cell-to-cell mapping method to be developed to approximate a fuzzy dynamic system model. This method leads to an efficient global behavior analysis algorithm based on a simple cell-to-cell mapping search. Finally, we outline the cellmapping-based search algorithm for fuzzy optimal control design and demonstrate its validity and advantages by applying it to time-optimal trajectory generation for coordinated manipulator systems with uncertain parameters.

The importance of effective and efficient distribution is evident from its associated costs. Transportation and shipping alone comprise roughly 15 percent of a product's sales in the U.S. Physical distribution is very energy and labor intensive, which have both become relatively more expensive in the last 10-15 years. Not surprisingly, there is a growing demand for automated planning systems that produce economical routes. Other than the cost savings, introduction of these systems enables companies to maintain a higher level of service for their customers, it makes them less dependent on human planners, it supplies better management information facilities and it makes distribution planning work faster and simpler.

A number of alternatives were considered to keep pecan processing economically competitive and sustainable. The industry needed a low risk evaluation technique for testing new high capital plant configurations. A simulation model was developed using the AweSimTM simulation system to form the model structure and framework. The Visual SLAMTM and Visual BASIC programming languages were used to build a network model that provided a mathematical-logical representation of the system. The model mathematically expresses all sub-processes including moisture conditioning, pasteurizing, cracking, shelling, sizing, manual and electronic sorting, resizing, resorting, and packaging. The pecan process simulation model consists of 24 RESOURCES, 353 ACTIVITIES, 48 AWAIT/QUEUE and FREE nodes, 83 BATCH and UNBATCH nodes, 79 ASSIGN nodes, 20 COLCT nodes, 39 GOON nodes, 10 other miscellaneous nodes and a graphic user interface (GUI). The model provides information on equipment utilization, delays, queues and bottlenecks for each process in the system. It also predicts total pecan cracked and total pecan packed, including details of production for each size class i.e. halves; large; medium; small; midget; fine; granule; and oil stock. The model was validated quantitatively by comparing output with actual production figures and qualitatively by plant management. Five options of process alternatives were simulated using the pecan simulation model. The first alternative (including 3 options) was a management proposed configuration for dual electronic sorting of pecan halves to reduce the shell pieces and ensure a lighter color product. Two options were found not viable as they required major capital investments and plant reconfiguration. The third option for dual sorting was found to be a viable process alternative with minor labor additions.

An efficient methodology for parameter identification is developed for general multi-degree of freedom linear or nonlinear systems in continuous time. The new methodology is based on a gradient flow algorithm and demonstrated to be useful in identifying unknown parameters for the systems defined by both linear and nonlinear differential equations. The new methodology identifies the unknown parameters by solving a system of differential equations rather than the conventional post-data fitting analysis. It is named the trajectory gradient integral flow (TGIF) algorithm. For the cases of stable, one-dimensional linear systems, the asymptotic stability of the TGIF algorithm is guaranteed in the neighborhood of the operating point. For higher order linear or nonlinear systems, certain criteria for stability are developed using the eigenvalue analysis and the Routh-Hurwitz stability criteria. A well-known system identification result is that any method works the best with non-steady, non-periodic data set that is driven by randomized inputs, however this is not an essential requirement with the TGIF algorithm. In fact, it is possible to perform efficient parameter identification with the TGIF algorithm using an unit step input or a simple sine input. Improvements over previous approaches include: (1) the new methodology is easy to apply for nonlinear systems, (2) it works well with a simple unit step or sinusoidal inputs as well as bounded (control) inputs, (3) it demonstrates a reasonable large "domain of attraction", (4) it can be applied for either "on-line" or "off-line" parameter identification processes.

This research, denoted MILOS (Multi-objective Integrated Large-scale Optimized ramp metering System) is a hierarchical structure for solution of the large-scale freeway management problem to address the key features of this problem (dynamic state changes, stochasticity, multi-dimensionality, unpredictability, partial-observability, and existence of multiple objectives). MILOS decomposes the freeway control problem into subproblems along temporal/spatial boundaries and is composed of three primary components: SPC-based anomaly detection and optimization scheduling, area-wide coordination layer, and predictive-cooperative real-time (PC-RT) optimization layer. The area-wide coordination component of the hierarchical control system considers the impact of queue growth on the adjacent interchanges in a quadratic programming optimization model with a multi-criterion objective function. The formulation of the area-wide optimization problem is augmented with overflow variables to guarantee a feasible solution. The nominal solution of the areawide coordination problem is then modified in real-time by the locally traffic-reactive, PC-RT algorithm based on a linear-program using a linearized dynamic difference equation implementation of the macroscopic FREFLO model. The PC-RT formulation pro-actively plans to utilize opportunities to disperse queues or hold back additional vehicles when freeway and ramp demand conditions are appropriate. The cost coefficients of this optimization problem is linked to the solution of the area-wide coordination problem by using information on the dual of the solution to the area-wide coordination problem. The optimization runs of the area-wide coordination problem and the PC-RT optimization problems at each ramp are scheduled by a demand/flow monitoring system based on statistical process control. A simulation experiment is executed to evaluate the MILOS hierarchical system against "no control", ADOT's current ramp metering policy, and an area-wide LP optimization problem resolved in 5-minute intervals on a small freeway network in the metropolitan Phoenix, AZ area. Three test cases are presented for a short "burst" of heavy-volume flows to all ramps, a 3-hour commuting peak, and a 3-hour commuting peak with a 30-minute incident occurring in the middle of the network. The performance results indicate that MILOS is able to reduce freeway travel time, increase freeway average speed, and improve recovery performance of the system when flow conditions become congested.