We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing

- the light field. This function completely characterizes the flow of light through unobstructed space in a static scene with fixed illumination. We describe a

ltaic (PV) electricity production from an intermittent Since 1978, compressed air energy storage (CAES) compressed air can then be released on demand to the CAES plant’s turbo-generator set to generate premium value electricity. The first CAES plant was built in broadened in the ittency of wind g with Cavallo,2 nomic feasibility as turbine (GT) oduction.3–8 The ate underground o the wind farms and shape the

field studies. A set of principles for the conduct and evaluation of interpretive field research in information systems is proposed, along with their philosophical rationale. The usefulness of the principles is illustrated by evaluating three published interpretive field studies drawn from

. The latter relates to how data is observed and is problem domain dependent. The former depends on how various prior constraints are expressed. Markov Random Field Models (MRF) theory is a tool to encode contextual constraints into the prior probability. This paper presents a unified approach for MRF modeling

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing

number of general assumptions used in this research field are identified and the character of these assumptions indicates that the research field is still in an early stage of development. To evaluate the state of the art, the major application areas are identified and performances are analyzed in light

We survey 392 CFOs about the cost of capital, capital budgeting, and capital structure. Large firms rely heavily on present value techniques and the capital asset pricing model, while small firms are relatively likely to use the payback criterion. We find that a surprising number of firms use their firm risk rather than project risk in evaluating new investments. Firms are concerned about maintaining financial flexibility and a good credit rating when issuing debt, and earnings per share dilution and recent stock price appreciation when issuing equity. We find some support for the pecking-order and trade-off capital structure hypotheses but little evidence that executives are concerned about asset substitution, asymmetric information, transactions costs, free cash flows, or personal taxes. Key words: capital structure, cost of capital, cost of equity, capital budgeting, discount rates, project valuation, survey. 1 We thank Franklin Allen for his detailed comments on the survey instrument and the overall project. We

Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We

The problems of designing large software systems were studied through interviewing personnel from 17 large projects. A layered behavioral model is used to analyze how three lgf these problems-the thin spread of application domain knowledge, fluctuating and conflicting requirements, and communication bottlenecks and breakdowns-affected software productivity and quality through their impact on cognitive, social, and organizational processes.