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Figure 1-5: Excel 4 was another significant step forward, although still far from Excel 5. (Photo courtesy of Microsoft)
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KeepDynamic.com/QR Code 2d barcode The Framework Interfaces Area The framework interfaces area de nes the abstract factory interface and abstract product interface for each of the six subsystems in the starter kit. There are no interfaces de ned for the Ddbms Client subsystem, because it is not a service provider. The namespace for this area ( Srdbsoft.Ddbe.DnetSkit.Framework.Interface ) which is also the name of the assembly that contains the compiled code for these interfaces. The interfaces are listed in Table 19.1, without the namespace details. All of these interfaces are in the same namespace. If changes need to be made to the interfaces in this area, we have two options. We can choose to modify this assembly directly or we can choose to use a new assembly instead. If we choose to modify the assembly, we can either modify the existing interfaces or create new ones. Similarly, if we choose to modify the existing interfaces we can choose to modify the existing methods or we can create new ones. Obviously, whenever we change things directly, there is a potential for breaking other code. Therefore, we should take great care when modifying things in this area. Whenever possible, we should consider augmenting rather than modifying (adding but not modifying or
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Mechanisms for output selection and adaptation. Media data provided by the applications needs to be delivered to the best media output channel. Considering the user s situation, and therefore context information, the best selection of these channels (audio, video, etc.) should be ensured. Selection algorithms providing the expected behaviour need to be de ned, taking into account the available devices. The output selection mechanism needs to be able to handle the provided device descriptions. Uniform device interfaces. Heterogeneity of devices makes uniform interfacing with devices a dif cult task. By de ning uniform software components, the exchange of device and modality information and also the request for modality input and output is handled in a consistent way. The de nition of so-called device agents can accomplish this task. Discovery mechanisms. Mobility itself presumes the available devices in the user s environment change. It is thus necessary to continuously monitor the environment to discover devices that become available in the user s vicinity. Discovery mechanisms, based on technologies such as Bluetooth, Wireless LAN or UPnP, can provide these functionalities, but they need to be incorporated into a discovery framework in order to allow consistent access to the information, whatever the underlying protocols. Mechanisms to integrate context information. Context information is essential to achieve the targeted adaptation results. Therefore, mechanisms to take user preferences into account and interpret context information need to be elaborated. For the multimodal output decision, modality recommendations which provide the means of integrating context information in a uni ed way into the decision process are used. Modality recommendations de ne which device or which modality should be used or omitted in the current user situation based on context interpretation and context inference. Recommendations are provided by the personalisation function, described later in this chapter. In addition to these essential research requirements, the setting-up of a multimodal interface model in mobile environments and software architecture, in order to achieve a reference implementation for these requirements, is an important step in order to achieve true multimodality for mobile applications. The next sections introduce possible general solutions and some speci c details on them. 5.1.2 General Approach Model for Multimodal Interfaces in Mobile Environments The physical multimodal user interface model considered here consists of a user equipped with a portal device the main device the user carries at all times and, possibly, several other user interface (UI) devices (displays, speakers, cameras, etc.) providing various modalities for input and output, an approach described in [8]. In general, the user is interacting with the portal device and the available user interface devices, together forming the current multimodal user interface, as shown in the upper part of Figure 5.1. The user interface combines user input modalities and serves available user output modalities with application requested media output. In a simple scenario the applications are executed on the portal device. Limitations in the currently available devices that could act as such a portal device (e.g. PDA, smart phones) could make it necessary to consider distribution of parts of the applications and the interface management in the network to provide more computing capacity.
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Gone are the days when this was a simple text input field. In MT 3.0, the contents of this field are as follows: 1. If the blog requires an e-mail address from the commenter, the e-mail address will be the value stored. 2. If the blog does not require e-mail from TypeKey-authenticated commenters, this field will be the encrypted e-mail address of any TypeKey-authenticated commenter. 3. If the blog allows unregistered, anonymous commenters, the e-mail field may be left blank and hence NULL. In the first two cases, if the commenter is a TypeKey-authenticated commenter, the comment_ email field will be assigned the value of the author_email field after the TypeKey login. One important thing to note is that if you later change the blog s e-mail address requirements, the effect is not retroactive. You cannot make previous comments with no e-mails disappear just by turning on the requirement in the Weblog Config, nor will past comments from TypeKeyauthenticated commenters be encrypted.
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Many studies of coordination in teams operating in I /O domains have been undertaken in the field. One reason is that the individuals operating in these domains have been unwilling or unable to be detached from the field to engage in controlled laboratory studies (e.g., military personnel are often too busy). However, many I /O domains, such as command and control, involve large human and machine systems that comprise multiple, interacting, and dynamic elements. Consequently, researchers in I /O psychology have argued that ecological validity is too heavily compromised when aspects of these environments are studied in the laboratory (Hutchins, 1995). Thus, many studies of team coordination in I /O domains have involved methods associated with anthropological and sociological field studies, such as observations, augmented by note taking and video recording and interviewing. This is the case in the studies of teams involved in space shuttle mission control (e.g., Patterson & Woods, 2001), naval ship operations (e.g., Hutchins, 1995), and simulations of expeditions on the planet Mars (e.g., Clancey, 2001). Furthermore, researchers studying cognition in these types of domains have proposed the terms cognitive anthropology (e.g., Hutchins, 1995), and cognitive ethnography (e.g., Ball & Ormerod, 2000) to describe their approaches. The advantages of these approaches include providing a rich and detailed insight into the functioning of teams as they operate in the real world, yet they are not without their critics. Researchers more familiar with experimental approaches to scientific inquiry often criticize such methods as inherently subjective and remain skeptical of their scientific value. Furthermore, even when more controlled studies of team functioning have been undertaken in I /O domains, progress in developing objective measures of team processes or performance has not been substantial. Measures are often in the form of subjective ratings of a given variable (e.g., communication quality) undertaken by socially recognized subject-matter experts (see Ward et al., in press). However, given the nature of the teams and the environments in which they operate in these domains (i.e., comprising multiple, interacting, and dynamic elements), there has been limited progress in developing objective measures. The challenge facing sport psychologists is to develop methods and measures of coordination given the potential for the tradeoff between internal and ecological validity introduced by sport team environments. A brief description of a selection of these measures follows to provide insight into the variety of measures of team coordination and communication that have been used in I /O psychology. Note that the only goal of this section is to introduce these methods, and so, to achieve
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BEYOND THE FIRST LABORATORY: EVOLUTION OF THE DISCIPLINE Psychology in Germany One of Wundt s contemporaries who believed that higher mental processes could be the object of experimental investigation was Hermann Ebbinghaus (1850 1909). Inspired by the psychophysics of G. T. Fechner and philosopher J. F. Herbart s attempt to apply mathematics to mental representations, Ebbinghaus used precise quantitative methods to investigate memory (Murray, 1976). He served as both the experimenter and the subject of his investigations. In order to have relatively homogeneous material to learn and to reduce the impact of any previous semantic associations, such as occurred in his early experiments in learning and remembering poetry, Ebbinghaus developed the nonsense syllable, largely pronounceable consonant-vowel-consonant combinations. He created syllable lists of various lengths that he learned and then later relearned after different lengths of time. The percentage of time saved in relearning the lists became known as the savings method of memory (Murray, 1976, p. 206; Hoffman, Bringmann, Bamberg, & Klein, 1987). Ebbinghaus found that the amount of time spent in relearning lists was greater for longer lists and for longer retention intervals. The graph of his results became the standard curve of forgetting, still reproduced in textbooks as a classic result. The curve showed that recall of learned lists was perhaps 85% after one hour, approximately 50% after one day, and as little as 15% after about six days. These ndings stimulated a long tradition of memory research (e.g., Postman, 1968). After publication of his monograph ber das Ged chtnis (On Memory), Ebbinghaus established laboratories at several universities and attracted some American students, but his time was increasingly devoted to a editing a journal and writing (Fuchs, 1997). Leadership of memory research fell to Georg Elias M ller (1850 1931) at G ttingen University. M ller, a dedicated experimentalist, invented the memory drum, a mechanical device for presenting one verbal stimulus at a time, used in conjunction with experiments on serial list learning and list retention. The memory drum, modi ed subsequently by M ller for research in paired associate learning (Haupt, 1998), became a standard piece of laboratory equipment for studies of verbal learning and memory until replaced by the computer. M ller s research reports on his studies of memory extended from 1893 to 1917 and included
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