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Partner participates Economic Commitment Economic Commitment destination Location Partner participates Agreement Partner participates Economic Commitment Economic Commitment reserves Economic Resource And finally with regard to Figure 2.16, the partial integration of the elements of the REA ontology with the components of the UMM business collaboration framework is illustrated by showing the class for Business Collaboration (with dotted lines) and some of its associations with REA classes (also illustrated with dotted lines). Outside of its use with the UMM, the REA ontology has a three-level architecture that is explained by Geerts and McCarthy [26]. In the UMM, this three-level architecture is effected by the integration of REA components within the business collaboration framework and by the connection of the BRV to the BDV above it and the BTV below it. REA concepts are more fully specified in working drafts of the UN/CEFACT eBusiness Transition Working Group [27], base documents for UMM User Guide to be released in 2003. 2.6.2 tML Framework A telecommunications industry application of XML, tML Framework, was approved as ITU-T Recommendation M.3030 in August 2002 under the ITU-T alternate approval

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IMPORT When processing many images at one time, the choices you make become increasingly important. Effective batch processing requires planning ahead, thinking carefully about the software settings, and considering the effects of your choices before going forward. After you ve run through the import process a few times, you ll easily remember the key settings to check before starting each Import. And new in Lightroom 3, you can save presets of your commonly used import settings.

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Classi cation: This is when a model is built to predict a categorical variable. For example, the model may predict whether a customer will or will not buy a particular product. Methods such as logistic regression, discriminant analysis, and naive Bayes classi ers are often used and these methods are outlined in 4 on Predictive Analytics. Regression: This is also referred to as estimation, forecasting, or prediction, and it refers to building models that generate an estimation or prediction for a continuous variable. A model that predicts the sales for a given quarter would be an example of a regression predictive task. Methods such as multiple linear regression are often used for this task and are discussed in 4.

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known as organizational social responsibility Online File W13 at the book s Web site lists some major areas of social responsibility related to business Government Regulations and Deregulation Several social responsibility issues are related to government regulations regarding health, safety, environmental control, and equal opportunity For example, companies that spray products with paint must use paper to absorb the overspray The paper must then be disposed of by a licensed company, usually at a high cost Such regulations cost money and make it more dif cult to compete with countries that lack such regulations They also may create the need for changes in organizational structure and processes Government regulations are usually viewed as expensive constraints on all who are affected Government deregulation, on the other hand, can be a blessing to one company but a curse to another that had been protected by the regulation.

In general, deregulation intensi es competition Terrorist Attacks and Protection Since September 11, 2001, organizations have been under increased pressure to protect themselves against terrorist attacks In addition, employees in the military reserves may be called up for active duty, creating personnel problems Information technology and especially intelligent systems may make a valuable contribution in the area of protection, by providing security systems and possibly identifying patterns of behavior that will help to prevent terrorist attacks and cyberattacks against organizations Ethical Issues Ethics relates to standards of right and wrong, and information ethics relates to standards of right and wrong in information processing practices Organizations must deal with ethical issues relating to their employees, customers, and suppliers Ethical issues are very important since they have the power to damage the image of an organization and to destroy the morale of the employees.

(B.19)

Ethics is a dif cult area because ethical issues are not cut-and-dried What is considered ethical by one person may seem unethical to another Likewise, what is considered ethical in one country may be seen as unethical in another The use of information technology raises many ethical issues These range from the monitoring of electronic mail to the potential invasion of privacy of millions of customers whose data are stored in private and public databases We consider ethical issues so signi cant that we have appended to this chapter a general framework of ethics in business and society (Appendix 1A) Speci c ethical issues are discussed in all chapters of the book (and are highlighted by an icon in the margin) Also, an Ethics Primer is available online The environments that surrounded organizations are increasingly becoming more complex and turbulent Advances in communications, transportation, and technology create many changes.

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