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Table 1. A Taxonomy of Decision Making Styles Ensuing research will be identifying decision phases, problem types, and decision making styles of subjects while monitoring and evaluating the use made of hypertext-based qualitative analysis aids embedded in the subjects apos; existing computer environment. Our premise that qualitative analysis can be enhanced by new types of computer-based support will be validated if the subjects find improved help and/or results in the categories of the taxonomy identified as heuristic.
"... In PAGE 7: ... As well, analytic processing continues to be better understood than the heuristic, or qualitative, approach; the analytic approach is easier to model. Table1 categorizes the possible range of decision phases, problem types, and decision making styles. It can be seen from this table that there are situations in which a heuristic approach might be as justifiable as an analytic approach, not to mention the fact that many problem solvers are intuitive by nature anyway.... In PAGE 24: ... In order to be successful, first of all one must be able to identify those activities which may be considered to be aiding the decision making process in a heuristic manner. The taxonomy of decision making styles shown in Table1 will be used to categorize problem states according to problem type, decision phase, and problem-solving style of the user. Support for qualitative decision making and qualitative analysis will be available through a variety of hypertext features which will be embedded in the user apos;s computer environment.... ..."
Table 1. A Taxonomy of Decision Making Styles Ensuing research will be identifying decision phases, problem types, and decision making styles of subjects while monitoring and evaluating the use made of hypertext-based qualitative analysis aids embedded in the subjects apos; existing computer environment. Our premise that qualitative analysis can be enhanced by new types of computer-based support will be validated if the subjects find improved help and/or results in the categories of the taxonomy identified as heuristic.
"... In PAGE 7: ... As well, analytic processing continues to be better understood than the heuristic, or qualitative, approach; the analytic approach is easier to model. Table1 categorizes the possible range of decision phases, problem types, and decision making styles. It can be seen from this table that there are situations in which a heuristic approach might be as justifiable as an analytic approach, not to mention the fact that many problem solvers are intuitive by nature anyway.... In PAGE 24: ... In order to be successful, first of all one must be able to identify those activities which may be considered to be aiding the decision making process in a heuristic manner. The taxonomy of decision making styles shown in Table1 will be used to categorize problem states according to problem type, decision phase, and problem-solving style of the user. Support for qualitative decision making and qualitative analysis will be available through a variety of hypertext features which will be embedded in the user apos;s computer environment.... ..."
Table 1. Aspects of research in Virtual Humans
2001
"... In PAGE 2: ...1 Virtual Humans But, the modelling of Virtual Huma ns is an immense challenge as it requires to solve many problems in various areas. Table1 shows the various aspects of research in Virtual Human Technology. Each aspects will be detailed and the problems to solve will be identified.... ..."
Cited by 14
Table 1. Aspects of research in Virtual Humans
2000
"... In PAGE 1: ...1 Virtual Humans But, the modelling of Virtual Humans is an immense challenge as it requires to solve many problems in var ious areas. Table1 shows the various aspects of research in Virtual Human Technology. Each aspects will be detailed and the problems to solve will be identified.... ..."
Cited by 1
Table 2 illustrates a classification scheme for the literature on the application of fuzzy set theory in production management research. Seven major categories are defined and the frequency of citations in each category is identified. Quality management resulted in the largest number of citations (15), followed by project scheduling (14), and facility location and layout (14). This survey is restricted to research on the application of fuzzy sets to production management decision problems. Research on fuzzy optimization and expert systems are not generally included in this survey. Readers who are interested in fuzzy optimization and operations research should consult Negoita (1981), Zimmerman (1983) and Kaufmann (1986). A comprehensive review of fuzzy expert systems in industrial engineering, operations research, and management science may be found in Turksen (1992).
1998
"... In PAGE 4: ...Table2 : Classification Scheme for Fuzzy Set Research in Production Management Research Topic Number of Citations 1. Job Shop Scheduling 9 2.... ..."
Cited by 3
Table 1. Adoption factors identified by the research
"... In PAGE 11: ... The better the device and its software could suport them, the greater would be their intention to use such a device. Table1 lists the ... ..."
TABLE 4 MEANS OF PROBLEMS IN RESEARCH BY SECTOR d
2005
Cited by 1
Table 1.1 lists some advantageous features of AI, CS theory and OR. This table does not pretend to be a complete list of all beneficial features, it only highlights some of already identified ones within the considered areas. For example, AI researchers have long realized that prior knowledge can significantly improve empirical performance in practical applications. A solution to the problem, found with the help of the prior knowledge guidance, serves as a benchmark for methods from other areas. Moreover, it can also carry an additional bounding value, for example, any feasible solution establishes an upper bound on the value of the goal function in a minimization problem.
Table 1. Classification of research traditions along two orthogonal dimensions: analytic vs. synthetic and representational vs. non-representational
"... In PAGE 7: ... Describing a model as being synthetic or analytic is using a dimension that it is completely orthogonal to the one used when describing a model as being representational or not. This is illustrated in Table1 , which categorizes some examples of research programs in terms of these two different dimensions. Synthetic psychology should involve research that is both synthetic and representational.... In PAGE 7: ... Synthetic psychology should involve research that is both synthetic and representational. In Table1 , one example of research that fits these two characteristics is connectionist modeling. With respect to synthesis, connectionist research typically proceeds as follows: First, a researcher identifies a problem of interest, and then translates this problem into some form that can be presented to a connectionist network.... ..."
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