Organizations are adaptive systems that continually attempt to push the limits of their own effectiveness to approach perfection. This approach is true of the "mom and pop" store that is threatened by the growth of shopping malls. It is true of the gigantic corporation that is threatened by public regulation and private competition. It is particularly true of organizations that are confronted with complex tasks, the vagaries of uncertainty, and the high and visible costs of irreversible error. The cause of organization ineffectiveness or, indeed, failure is often perceived to be human frailty (Perrow 1984).
SINCE WE ARE FIRMLY CONVINCED that ideas like people have histories and can only be fully understood in the context of those histories, we will begin by discussing the underlying ideas that motivated us to initiate the Steamer effort. Without richer and more detailed understandings of the nature of these models, instructional applications will be severely limited. Graphical Interfaces for Interactave Inspectable Simulatzons - We believe that graphical interfaces to simulations of physical systems deserve extensive exploration. They make possible new types of instructional interactions by allowing one to control, manipulate, and monitor simulations of dynamic systems at many different hierarchical levels The key idea in Steamer is the conception of an znteractive inspectable simulation. We have consistently sought to make the system inspectable.
Having convenient access to expert knowledge is important. In the past, we have seen users reinvent solutions because they did not have access to previous experience on the same fault. This lack of available information has led to wasted resources and, in some cases, has generated responses to the fleet that were not accurate enough. The development began in fiscal year 1992, and the area between the solid and dotted lines approximates the cost for development. The peak in fiscal year 1994 represents the end of the operational evaluation and the beginning of production operation.
This article reports on the activities, papers, speakers, and workshops of the Seventh International Conference on Case-Based Reasoning, held 13-16 August in Belfast, Northern Ireland. CCBR 2007, the Seventh International Conference on Case-Based Reasoning, was held in the joyful city of Belfast, Northern Ireland, UK. Our host in Belfast was David Patterson from the University of Ulster. The 2007 program attempted to open the field's frontiers by inviting speakers from neighboring areas and insiders who could expand the vision of the attending case-based reasoning (CBR) researchers and practitioners. An introspective talk, given by David W. Aha (Naval Research Lab, USA) kicked off the event, making attendees question how case-based reasoning is perceived by the outside world and the balance between theoretical foundations and applied research. His talk, "Addressing Perceptions of Case-Based Reasoning," set the tone for discussions throughout the conference.
Human error is an increasingly important and addressable concern in modernday high-technology accidents. Avoidable human errors led to many famous accidents, including Bhopal, the space shuttle Challenger, Chernobyl, the Exxon Valdez, and Three Mile Island. Many hundreds of thousands of nonfamous accidents occur each year that are equally or more avoidable. Dramatic examples make the local headlines, such as car crashes, train and plane wrecks, and military-related operations mishaps. Less dramatic consequences happen even more frequently because of millions of mundane errors that appear daily in the products we use (for example, poorly designed cars), the processes we are affected by (for example, banking or healthcare institutions), and the automation that surrounds us (for example, unfriendly computers that expect us to adapt to their interfaces).
Eastman Kodak (Rochester, N.Y.), a manufacturer of imaging-related products, has developed an online neural network-based machine vision system for surface mount solder paste inspection. Caere (Los Gatos, Calif.), a provider of neural network-based optical character recognition (OCR) technology, has signed an agreement to supply IBM Ireland with OCR Readers for AN POST, Ireland's national postal service. Using a handheld wand, postal employees will be able to scan text and read bar codes from anywhere on a document. BrainTech (Scottsdale, Ariz.), a developer of neural network and fuzzy logic-based pattern recognition technologies, has signed a development agreement with Raven (Alexandria, Va.), a developer of acoustic systems for the U.S. Navy. BrainTech will integrate its pattern-matching recognition engine into Raven's new medical diagnostic systems.
It was motivated by two difficulties in scaling up existing generators. Current generators only accept input that are relatively poor in information, such as feature structures or lists of propositions; they are unable to deal with input rich in information, as one might expect from, for example, an expert system with a complete model of its domain or a natural language understander with good inference ability. Current generators also have a very restricted knowledge of language-- indeed, they succeed largely because they have few syntactic or lexical options available (McDonald 1987)-- and they are unable to cope with more knowledge because they deal with interactions among the various possible choices only as special cases. An utterance is simply the result of successive word choices. The treatment of syntax in connectionist and spreading activation systems is a well-known problem.
The Chinese armies are now able to use robots to fire ballistic missiles after successfully developing an automated launching system, Chinese military media claimed. The advanced system would help China fire warheads three times faster and halve the number of soldiers involved. The news emerged as tensions between Beijing and Washington have escalated over the claims that China had allowed oil into North Korea, which violated a United Nations embargo. Beijing has denied the allegations. Beijing's next-generation intercontinental ballistic missile, Dongfeng-41 (pictured) could allegedly strike anywhere in the world.
The United States Navy is reportedly expanding their ocean combat network, known as the Consolidated Afloat Networks and Enterprise Services (CANES), to seamlessly connect their ships, submarines, and on-shore locations using artificial intelligence (AI). The hope is that CANES will reduce the number of sailors required to maintain operations, thus potentially saving the Navy billions of dollars over years of use. By 2020, the Navy hopes to deploy CANES on 190 vessels and Maritime Operations Centers. "We are very interested in artificial intelligence being able to help us better than it is today," Rear Adm. Danelle Barrett, Navy Cyber Security Division Director, told Warrior. "We want to trust a machine and also look at AI in terms of how we use it against adversaries."
Boeing recently offered a first glimpse of its newest military aircraft, a large, stingray-shaped drone it hopes will win an intense Navy competition to build an uncrewed aircraft capable of landing on an aircraft carrier. Drones have been a vital part of the Pentagon's arsenal for years, but the competition for a Navy carrier-based version that can refuel jet fighters in the midair would mark a significant advancement in the technology -- and become another sign how the military is increasingly integrating robots into the way it fights. In addition to Boeing, two of the Pentagon's top suppliers, General Atomics and Lockheed Martin, are also vying for a contract to build as many as 76 of the vehicles that would become operational in the mid 2020s. Bids are due Jan. 3, setting the stage for a high-stakes competition in 2018. Though the Navy has not yet released the value of the contract, an earlier incarnation of the effort--in which the drones would both serve as refueling aircraft and have attack capabilities -- would have been worth $3 billion through 2022.