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In designing research a major decision that the researcher must make concerns the selection of a sampling method. Sampling is a very important tool in marketing research. It involves selecting a small number of people from the larger survey population whose characteristics, attitudes and behaviour are representative of the larger group. Before selecting the sample, however, the researcher must rst de ne the research population from which to draw the sample. Exploratory research can help to de ne the population to include all the players and variables that are relevant to the survey. For some surveys, particularly if the survey population is small or concentrated in one geographical area, it may be possible to take a census, which is a useful method in some business surveys. More commonly a representative sample is interviewed as this reduces both the time and the cost of the research.
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3.8.2.4. Data processing Topology. The network topology might play an important role in the design of speci c data processing. The perfect knowledge of the network topology, for instance, can be used to determine the position of better collector nodes. Moreover, if the topology is pre-planned, nodes with more computational capabilities can be placed in strategic positions. On the contrary, in the case of random topologies, the choice of more suitable aggregation points have to be made in a distributed manner and can be less ef cient. In regards to the organization of the network structure, the data processing techniques can lie on different communication topologies. Most known algorithms (DD, LEACH, PEGASIS, TAG and TiNA) run over tree-based or hierarchical structures. In contrst, other schemes such as Synopsis Diffusion, and Tributaries and Deltas organize the network in a concentric ring structure. Scalability. Scalability is an important goal in the design of ef cient data processing techniques, especially in large and dynamic networks. Existing data processing techniques based on the construction of an aggregation tree are less scalable than the multipath schemes due to the high cost of maintaining the organization of the network. This characteristic is accentuated in large or dynamic networks where adding or removing nodes from the tree structure heavily impacts on the performance of the algorithms. On the other hand, multipath solutions offer good scalability, due to the local and distributed functionalities. Fault tolerance. Data processing, in general, is performed in order to reduce the intrinsic data redundancy that might characterize CO scenarios (e.g. WSNEM). On the other hand, data redundancy may ensure a higher reliability in the cases of sensor failure, connectivity holes and so on. Hence, a trade-off between fault tolerance and redundancy reduction has to be cut. In the case of low packet loss probability, treebased algorithms achieve better performance because they are able to minimize the number of transmissions required to deliver a given amount of data, so the redundancy is kept to a minimum. On the other hand, the multipath schemes preserve some data redundancy so it performs better in the case of high packet loss probability. There are also some hybrid approaches such as Tributaries and Deltas which are able to adjust their behavior according to the link conditions. Localization. In some cases, data aggregation techniques require information about the location of nodes. Nevertheless, almost all data processing techniques do not require any type of localization methods. Data traf c characteristics. The design of data processing techniques is strongly correlated to the speci c considered application. In some cases, for instance in WSNEM, it may be useful to perform data aggregation as near as possible to the data sources due to the high redundancy among data collected in the same spatial region. In other cases, data processing can be performed along the path, for instance to merge information ows directed to a common destination.
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An MBS portfolio may very well be duration-matched to an index and matched on a cash flow and curve basis, but mismatched on convexity. That is, the portfolio may carry more or less convexity relative to the benchmark, and in this way the portfolio may be better positioned for a market move.
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UBIQUITOUS COMPUTING Ubiquitous computing has been termed the third wave in computing. In this representation, the rst wave was the era of the mainframe computer large, complex computers run by centralized corporate organizations with each computer providing support to large numbers of people. Then, in the second wave, known as the personal computing era, individuals and personal computing machines shared the same desktop. This was the era of decentralized computing. The nal phase, or third wave, comes as ubiquitous computing is introduced, creating a work environment in which each person is connected to lots of devices.4 The key technology to enable this transformation to the third wave is networking, and networking impacts computing at each level from the personal computing level to the global level. The concept of ubiquitous computing (UC) was rst identi ed by Mark Weiser in 1988 while he was working at the Computer Science Laboratory (CSL) at Xerox s Palo Alto Research Center (PARC). Weiser described UC as a radical approach to achieving the full potential of what computing and networking ought to be. People s lives are often affected by powerful things that are effectively invisible. This may soon include the impacts from dispersed collections of wireless computing devices that operate in the background and could amount to hundreds of devices per person. Such a decentralized system of processors and related equipment requires the coordination of new operating systems, user interfaces, networks, wireless displays, and other devices. Ubiquitous computing is different from simply providing small computing devices such as PDAs to large numbers of people, because the invisible interconnection of the devices is a key element. The existence of computer and microprocessor systems that are embedded and invisible creates the possibility that we will use them without even being conscious of them, just as we don t think of electricity when we ick on the light switch. Weiser said, My colleagues and I at PARC think that the idea of a personal computer itself is misplaced, and that the vision of laptop machines,
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The dependences of the self and coupling inductances for a system of two identical interconnections on the spacing between the interconnections in the range 1 30 nm are shown in Fig. 2.9.6. In this gure, the mutual inductances are plotted for currents in the two interconnections owing in the same as well as opposite directions. This gure suggests that the self-inductances of the two interconnections are essentially independent of the spacing between them whereas the mutual inductances decrease with an increase in the interconnection spacing with a change of sign of the mutual inductance for the cases of similar and opposite currents.
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Using the file system to implement a persistent state service is the most lightweight approach. It does not involve any licensing costs for databases. The PDL compiler does not have to generate a database schema but only utilizes serialization or structured storage techniques. The use of files, however, does not scale to large-scale, multi-user applications due to the lack of concurrency control and fault-tolerance. The use of relational databases overcomes this problem as theysupport concurrencycontrol and transaction processing. To employ relational databases, a PDL compiler generates a set of tables for the persistent representation of storage homes and storage objects. Storage object and storage home incarnations have embedded SQL or database connectivityin order to query and update the database. The large installation base of relational databases may make them the persistence mechanism of choice because no additional licensing costs are incurred. This section should have demonstrated that object databases are the most elegant way to implement a persistent state service. They do not suffer from the scalability problems of file systems and overcome the impedance mismatch that occurs when using relational database technology. It is, therefore, not surprising that most object database vendors have a strong interest in providing mechanisms for persistence of distributed objects. Most of the main vendors were party to the specification of the C O RBA persistent state service. Object databases, however, do not have the market penetration that relational databases have and for managing large amounts of similarly-structured data, RDBMSs may still be the best choice.
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FIGURE 4.4.3 Crosstalk voltage waveforms in range 0 200 ps for several interconnection lengths for single-level interconnections in Fig. 4.4.2a.
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