how to read pdf file in asp.net using c#

how to read pdf file in asp.net c#

how to read pdf file in asp.net using c#

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The limit to the Grid is straightforward. It can be used properly only by those who honestly seek to enable people s enhancing potentials. The Ethical Grid can be used legitimately only by those who are consistently opposed to dwar ng, and devoted to the ght against it. It is meant for people committed to the same Ethics B as I am. The Grid can be used as it is supposed to be only by people who have made a commitment to work for health, and are seeking to do so with integrity. If it is used insincerely, if the grid is employed cynically merely in order to further personal goals, for instance then this is not a moral use, even though the outcomes might sometimes be the same as those that result from sincere use.

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behavioural cues to deceit, as in the latter case contradictory ndings are common place (Vrij, 2000) Some of the laboratory researchers reported accuracy rates, that is the correct classi cations of truth tellers and liars on the basis of CBCA assessments Unfortunately, in none of the eld studies were accuracy rates reported, so the accuracy scores below are based solely on laboratory studies3 Vrij (2000) calculated the average accuracy rate in CBCA studies This was around 70%, with slightly higher scores for detecting accounts of genuinely experienced events (76%) than for detecting accounts not relating to genuinely experienced events (68%) Although these accuracy rates are higher than the accuracy rates in non-verbal lie detection, they are simply too low to justify CBCA assessments to be used as the main piece of evidence in criminal courts.

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How can different types of value be distinguished from one another And how can this be done so that more light is thrown upon the nature of morality The analysis of values given here is by no means exhaustive. However, it is useful to note: (a) that different types of valuing have different ethical implications; and (b) that all valuing is done by subjects who exist within a wider culture.10

Especially the substantial number of incorrect classi cations of accounts not relating to genuinely experienced events is worrying The incorrect decision falsely to believe stories made by alleged victims would have serious consequences Such an error could result in somebody who is actually innocent being falsely accused of a crime and may lead to an unjusti ed conviction if a court (either jury or judges) bases its decision on the opinion of a CBCA expert False convictions of innocent suspects are seen as serious mistakes in Western legal systems which are founded on the principle that it is better to acquit 10 guilty people than to convict one person who is innocent Some people are highly critical of CBCA assessments and would like such evaluations not to be used as evidence in criminal courts (Rassin, in press; Ruby and Brigham, 1997).

A software system using CBR and fuzzy logic, named CREW [25], was developed to simulate a time-series model of astronaut crews. Without the expense and risk of actual ights, it can predict how a given crew might respond to mission stress under different scenarios. In the frame of CBR, some adaptation rules, coming from the statements of researchers, act as a supplement to the case base. The conditions of these rules are often described by linguistic terms such as low, medium, and high with modi ers such as very or not. The nonquantitative nature of these rules lends itself to formulation and computation using fuzzy logic. They are translated reasonably into numeric computations by the de ned membership functions, preserving suf cient precision considering the limited effect that any given rule or condition has on the overall simulation. In 2002, Passone et al. [26] provided an application of CBR technology to support the design of estuarine models (i.e., models for evaluating water quality). The system aims to help nonexpert users to select a model that matches their goal and the nature of the problem to be solved. It consists of three components: a case-based reasoning scheme, a genetic algorithm, and a library of numerical estuarine models. Once an appropriate model procedure is selected using the case-based reasoning scheme, a genetic algorithm with problem-speci c knowledge is activated to adjust the model parameters. An example based on the Upper Milford Haven estuary in the United Kingdom is used to demonstrate the ef ciency of the system s structure for supporting estuarine model design.

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