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based computer; and the GRiD Convertible, a pen-based tablet computer in which the screen swivels, transforming it into a standard laptop device. Throughout his career, Hawkins maintained a keen interest in the science of human brain function. His interest in PDAs was, in part, driven by his fascination with the organization of information and its storage and recovery, key elements of both a digital information organizer and the human brain. When he returned to GRiD Systems, he indicated that his goal was to become famous enough and wealthy enough to really promote and sponsor signi cant research in neurobiology and theoretical neurobiology. 9 As he expressed in an interview with MIT s Technology Review,10 Hawkins saw intelligence in terms of the ability of a being to predict the conditions of the surrounding environment based on sensory inputs and logic. He saw that the ability to recognize patterns is a key element of intelligence, and he worked to understand these processes and apply the resulting insights to pattern recognition applications in computer technology. He observed that the more complex patterns you can predict over a longer time, the more you understand your environment and the more intelligent you are. 11 The GRiDPad had a simple operating system, a relatively ef cient processor, removable storage, and a pen interface. But it was too big and too heavy and had an insuf cient battery life. After pursuing some initial concepts in handwriting recognition for the tablet PC, Hawkins decided to switch gears and create a new hand-held device for organizing information. His concept, known as Zoomer (a play on the word consumer), a cross between a tablet PC and a PDA, would not be supported by the management at GRiD Systems because of its desire to focus on existing products. So, in 1992, Hawkins left GRiD Systems and founded Palm Computing to work on the Zoomer. He saw great potential in the area of smaller computers. The Zoomer hardware would be developed by Casio and the operating system would be provided by GeoWorks. Palm Computing would put the whole thing together and would integrate the application software, Graf ti. At the start, Palm Computing was primarily a software company. Hawkins said, We started Palm Computing with the thought that this would be like the PC world. And the conventional wisdom was that you wanted to be in software. That s where all the big money was being made: Microsoft, Lotus, and Ashton Tate. So we structured it so that Palm would be doing the application software, we partnered with people to do the OS I selected GeoWorks we partnered with Tandy to bring it to market, and they brought in Casio to manufacture it, and then we added AOL and Intuit. 12
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Table 22.1.1 GSM promotion seminars under the auspices of the GSM MoU Group Date 12 14 October 1988 Location Hagen (Germany) Purpose Co-ordination A. Silberhorn, P. Dupuis, L. Kittel (University of Hagen) F. Hillebrand
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2.6. Scenario description structure As stated, COs and WSNs are applicable to a wide range of environments and in various conditions. Also, each sensor network may have assorted roles depending
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minority, albeit an important one. Probably the largest amount of on-line disruption and loss of business is caused by people who do not at least start out with the motive of personal gain. Some of it is simple curiosity aligned in some cases to social inadequacy the traditional hacker or anorak . There is an above normal level of obsessiveness in some of these people, which means that they can and will devote a large amount of time and personal savings to mounting attacks on on-line systems. The privacy, anonymity and ease-of-access to the Internet, together with the widely held belief that it is a victimless crime , provide an ideal environment for this obsession. It has been said that some hackers feel they are doing customers and companies a favour, by exposing such weaknesses and it is up to companies to ensure that they can protect themselves against attack. Whatever the strength of their argument, the damage they can do to the businesses they attack, can be very serious. Even if they do not deliberately or accidentally destroy or disclose critical data, they can seriously damage a company s reputation. Increasingly, we also see the rise of single-issue protests, directed against government , big-business , etc. Sometimes the resulting activist behaviour can go well beyond any legitimate democratic rights to protest, but large numbers of people may still passively or actively support it. Some of these will have the capability to assist in these victimless crimes . Others will look on indulgently at friends or children thus involved. The attackers in these cases are not motivated from sheer curiosity and they may feel entirely justi ed in doing as much damage as they can. Returning to directly criminal activity, we note that the competitive business environment has always had its share of unscrupulous participants. It is impossible to put a reliable gure on the gains and losses accrued, as businesses will seek to minimise publicity on the activity, whilst security consultants will do the opposite, but it undoubtedly occurs to a greater degree than we hear about. On-line systems provide mass, global access to corporate IT systems, on a scale signi cantly greater than ever before. There is also a semi-clandestine network of hacking resources available on-line and through closed eMail groups. Through this network, one can gain access to a fund of information on weaknesses in speci c systems, much of which is unknown to or forgotten by legitimate systems administrations. Since take-up of any practice, criminal as well as legal, is directly related to opportunity, we need to give increasing attention to the protection of sensitive data, either our own, or that of other parties we deal with. These different reasons for attack manifest themselves in different sets of visible symptoms which have implications on the technologies used for the attack and for its defence (Table 2.1). Recreational hackers do not really care which part of the system they get into; the challenge is the most important thing. They are often not even
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FIGURE 9.16 Bayes predictive density (dashed line) with kernel density estimate (solid line) for the time to total failure, 0 6, for the M/G/1 queue.
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