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The transformation in interface boundaries relative to our own bodies raises many new questions about how we might interact with new technologies. as the boundary moves closer to us, so the focus of the interaction and how it will affect their own personal experience needs to be better understood by the individual. as these devices become part of us, it raises issues about what defines an individual, and whether embedded devices are part of that definition. the issues are more complicated than this, however. personal, intimate devices can be networked and therefore can interact with other people and other devices within the wider environment. so we need to consider the spectrum of use, ranging from private and personal interaction at one end to public and aggregated interaction at the other. we can now receive unwanted bluetoothed files on our mobile phones. it is not long before personal devices might be detected by billboards, shopfronts, pavements and walls as we walk along them, delivering customised information or messages to us. at any one moment this means we may be simultaneously interacting with multiple boundaries, some under our control and some not. this will cause shifts in what we perceive as personal space, and what is shared. how do human values affect the interface boundaries? for example, the desire for vitality and independence as we grow older might motivate us to place medical devices close to or even within our bodies. but how does this affect other human values, such as the need to define our own identity? if computers are embedded within us, are they then part of that identity? and what about sharing that data with others? if others have access to our most intimate data, do we then feel a loss of the independence we might seek? likewise, if the boundary between us and embedded devices is invisible, how important is it that we questions of broader impact will the embedding of bio-sensing devices be acceptable only for cases of extreme frailty or illness or for other purposes too? should the bodily functions of people be allowed to be monitored without their awareness or permission? how should we access and control information from intimate, embodied devices? questions for interaction and design how will we know what computational resources are available within us and how these will interact with resources around us? what interaction techniques are appropriate if embedded devices have no explicit or recognisable interface? will more intimate devices mean old concepts of `the interface' become obsolete and irrelevant in the future? manage and control that boundary? these are all issues that we will increasingly have to deal with in future.
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Governance process can be coordinated, particularly as the innovative nature of internet technology and use keep extending and changing critical issues of all three internet governance types, and the dynamics of the interplay between them. governance layers for the technical infrastructure different types of issues identified in table 1 could be grouped into different subsets when viewed from particular viewpoints. for instance, a useful reference point in forum discussions was a `thickthinthick' layered model of internet standards and protocols described by crocker see table 2 ; . the thin layer in the middle consists of a relatively few but vital type i internet-centric governance issues at the core of the internet's architecture and stability, which are covered by icann's main responsibilities. the top layer includes the protocols underpinning the vast range of internet applications that have numerous deep and diverse implications for wider types ii and iii user and international policy issues. the lower layer relates to the telecommunications media carrying the internet's data. this is decoupled by the internet's design from the internet's infrastructure, and therefore can be depicted in table 1 as dealing with non-internet centric issues. table 2: layers of internet standards and protocols.
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The purpose of this tutorial is to introduce attendees to empirical tools including experiment and metrics design, exploratory data analysis, statistical hypothesis testing, and modeling. through case studies and other examples, this tutorial introduces a variety of evaluation methods, including methods for visualizing, summarizing and detecting clues in data; for designing controlled experiments; and for testing hypotheses, both with classical tests and with new, computer-intensive bootstrap and randomization methods. the case studies are organized around ten themes, each a "mantra" that i find helpful when conducting evaluations e.g., "follow the variance, " and "evaluation begins with claims." ; . the tutorial does not require any prior knowledge of the subject, and specifically will not require background in statistics. the tutorial will therefore is suitable for the general ai audience, both academic and industrial. paul r. cohen is deputy director of the intelligent systems division at usc's information sciences institute and research professor of computer science at usc. his ph.d. is from stanford university in computer science and psychology, in 1983; and his m.s. and b.a. degrees in psychology are from university of california, los angeles and the university of california, san diego, respectively. he is author of empirical methods for artificial intelligence mit press, 1995 ; . cohen advises several government agencies on the design of evaluations for programs, and has published widely in methodology and in several areas of ai.
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At december 31, 2001, the company had federal and alternative minimum tax "amt" ; net operating loss carryforwards of , 524 and , 521, which will begin to expire after the year ended december 31, 2018. the company also had general business and amt tax credit carryforwards of , 073 and 1, respectively. at december 31, 2001, a valuation allowance was recorded to reduce the deferred tax asset because recognition of the tax benefit could not be assured. 14. earnings per share the following table reflects the company's basic and diluted earnings per share for the years ended december 31, 2001, 2000 and 1999: 2001 - net income loss ; weighted average number of shares outstanding: basic assumed conversion of stock options diluted earnings per share: basic diluted $ 9, 700 ; 2000 - $ 22, 105 ; 1999 - $ 932.
