Time-Frequency Analysis of Nonlinear Systems: The Skeleton Linear Model and the Skeleton Curves

The joint time-frequency analysis method is adopted to study the nonlinear behavior varying with the instantaneous response for a class of S.D.O.F nonlinear system. A time-frequency masking operator, together with the conception of effective time-frequency region of the asymptotic signal are defined here. Based on these mathematical foundations, a so-called skeleton linear model (SLM) is constructed which has similar nonlinear characteristics with the nonlinear system. Two skeleton curves are deduced which can indicate the stiffness and damping in the nonlinear system. The relationship between the SLM and the nonlinear system, both parameters and solutions, is clarified. Based on this work a new identification technique of nonlinear systems using the nonstationary vibration data will be proposed through time-frequency filtering technique and wavelet transform in the following paper.

A Model For Residential Adoption of Photovoltaic Systems

The rapid rise in the residential photo voltaic (PV) adoptions in the past half decade has created a need in the electricity industry for a widely-accessible model that estimates PV adoption based on a combination of different business and policy decisions. This work analyzes historical adoption patterns and finds fiscal savings to be the single most important factor in PV adoption, with significantly greater predictive power compared to all other socioeconomic factors including income and education. We can create an application available on Google App Engine (GAE) based on our findings that allows all stakeholders including policymakers, power system researchers and regulators to study the complex and coupled relationship between PV adoption, utility economics and grid sustainability. The application allows users to experiment with different customer demographics, tier structures and subsidies, hence allowing them to tailor the application to the geographic region they are studying. This study then demonstrates the different type of analyses possible with the application by studying the relative impact of different policies regarding tier structures, fixed charges and PV prices on PV adoption.

Modelling and control of nonlinear systems using Gaussian processes with partial model information

Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

The Basic-Systems Model of Episodic Memory.

Behavior, neuropsychology, and neuroimaging suggest that episodic memories are constructed from interactions among the following basic systems: vision, audition, olfaction, other senses, spatial imagery, language, emotion, narrative, motor output, explicit memory, and search and retrieval. Each system has its own well-documented functions, neural substrates, processes, structures, and kinds of schemata. However, the systems have not been considered as interacting components of episodic memory, as is proposed here. Autobiographical memory and oral traditions are used to demonstrate the usefulness of the basic-systems model in accounting for existing data and predicting novel findings, and to argue that the model, or one similar to it, is the only way to understand episodic memory for complex stimuli routinely encountered outside the laboratory.

Enterprise architecture model: an approach proposition. A case study of information systems in the hospitality industry

This paper discusses the role of enterprise architecture representation, in the context of ERP (Enterprise Resource Planning) information systems, as an instrument for an organization to reflect on itself and develop its business strategies and respective alignment with Information Systems. The paper proposes a representation model of enterprise architecture, as a tool for recommending good practices, and it emerges from a case study undertaken in the context of and investigation on advantages and limitations of ERP systems in the hospitality industry. The proposed approach is also inspired on other academic or market propositions suitable for the objectives of the investigation. It consists on a set of items representing the steps that must be taken by top managers and IS managers.

A speculative systems model of the dynamic interaction among students, faculty and administration in the community college, with particular reference to intrinsic motivation and the teacher-administrator interface

The challenge the community college faces in helping meet the needs of the living open system of society is examined in this study. It is postulated that internalization student outcomes are required by society to reduce entropy and remain self-renewing. Such behavior is characterized as having an intrinsically motivated energy source and displays the seeking and conquering of challenge, the development of reflective knowledge and skill, full use of all capabilities, internal control, growth orientation, high self-esteem, relativistic thinking and competence. The development of a conceptual systems model that suggests how transactions among students, faculty and administration might occur to best meet the needs of internalization outcomes in students, and intrinsic motivation in faculty is a major purpose of this study. It is a speculative model that is based on a synthesis of a wide variety of variables. Empirical evidence, theoretical considerations, and speculative ideas are gathered together from researchers and theoretici.ans who are working on separate answers to questions of intrinsic motivation, internal control and environments that encourage their development. The model considers the effect administrators·have on faculty anq the corresponding effect faculty may have on students. The major concentration is on the administrator--teacher interface.For administrators the model may serve as a guide in planning effective transactions, and establishing system goals. The teacher is offered a means to coordinate actions toward a specific overall objective, and the administrator, teacher and researcher are invited to use the model to experiment, innovate, verify the assumptions on which the model is based, and raise additional hypotheses. Goals and history of the community colleges in Ontario are examined against current problems, previous progress and open system thinking. The nature of the person as a five part system is explored with emphasis on intrinsic motivation. The nature, operation, conceptualization, and value of this internal energy source is reviewed in detail. The current state of society, education and management theory are considered and the value of intrinsically motivating teaching tasks together with "system four" leadership style are featured. Evidence is reviewed that suggests intrinsically motivated faculty are needed, and "system four" leadership style is the kind of interaction-influence system needed to nurture intrinsic motivation in faculty.

Numerical aspects in the data model of conceptual information systems

While most data analysis and decision support tools use numerical aspects of the data, Conceptual Information Systems focus on their conceptual structure. This paper discusses how both approaches can be combined.

ACTORS: A Model of Concurrent Computation in Distributed Systems

A foundational model of concurrency is developed in this thesis. We examine issues in the design of parallel systems and show why the actor model is suitable for exploiting large-scale parallelism. Concurrency in actors is constrained only by the availability of hardware resources and by the logical dependence inherent in the computation. Unlike dataflow and functional programming, however, actors are dynamically reconfigurable and can model shared resources with changing local state. Concurrency is spawned in actors using asynchronous message-passing, pipelining, and the dynamic creation of actors. This thesis deals with some central issues in distributed computing. Specifically, problems of divergence and deadlock are addressed. For example, actors permit dynamic deadlock detection and removal. The problem of divergence is contained because independent transactions can execute concurrently and potentially infinite processes are nevertheless available for interaction.

Model-Based Troubleshooting of Digital Systems

This thesis describes a methodology, a representation, and an implemented program for troubleshooting digital circuit boards at roughly the level of expertise one might expect in a human novice. Existing methods for model-based troubleshooting have not scaled up to deal with complex circuits, in part because traditional circuit models do not explicitly represent aspects of the device that troubleshooters would consider important. For complex devices the model of the target device should be constructed with the goal of troubleshooting explicitly in mind. Given that methodology, the principal contributions of the thesis are ways of representing complex circuits to help make troubleshooting feasible. Temporally coarse behavior descriptions are a particularly powerful simplification. Instantiating this idea for the circuit domain produces a vocabulary for describing digital signals. The vocabulary has a level of temporal detail sufficient to make useful predictions abut the response of the circuit while it remains coarse enough to make those predictions computationally tractable. Other contributions are principles for using these representations. Although not embodied in a program, these principles are sufficiently concrete that models can be constructed manually from existing circuit descriptions such as schematics, part specifications, and state diagrams. One such principle is that if there are components with particularly likely failure modes or failure modes in which their behavior is drastically simplified, this knowledge should be incorporated into the model. Further contributions include the solution of technical problems resulting from the use of explicit temporal representations and design descriptions with tangled hierarchies.

Evaluation of the model representation of the evolution of convective systems using satellite observations of outgoing longwave radiation

We introduce a technique for assessing the diurnal development of convective storm systems based on outgoing longwave radiation fields. Using the size distribution of the storms measured from a series of images, we generate an array in the lengthscale-time domain based on the standard score statistic. It demonstrates succinctly the size evolution of storms as well as the dissipation kinematics. It also provides evidence related to the temperature evolution of the cloud tops. We apply this approach to a test case comparing observations made by the Geostationary Earth Radiation Budget instrument to output from the Met Office Unified Model run at two resolutions. The 12km resolution model produces peak convective activity on all lengthscales significantly earlier in the day than shown by the observations and no evidence for storms growing in size. The 4km resolution model shows realistic timing and growth evolution although the dissipation mechanism still differs from the observed data.