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referred to simply as continuing education) encompasses any program of study offered to mature people who have completed their formal education and wish to pursue further learning In this chapter, however, the definition is limited to work-related or leisure-oriented programs that are designed to bene t individual adults by promoting their career and profession or by enhancing their quality of life It includes inservice education, a term commonly used in education to refer to individual professional development of K 12 and higher education personnel Further, it covers professional development as a distinct category for people seeking further specialized training in law, the health professions, management, public administration, municipal and state government, and veterinary medicine It also encompasses staff development for K 12 and higher education personnel because activities under this rubric, though designed to improve faculties and institutions, are client oriented, not pro t oriented A broader de nition of continuing education would include training that is intended exclusively or primarily to bene t an organization for its own sake or pro t for example, training that prepares an employee to perform his or her job more ef ciently in order to increase the employer s pro t margin, or training that teaches an employee new skills that he or she will apply in the workplace to improve service or productivity That type of education is taken up in 8, under careers in business and industry

(a)0n thebasisof a linear regression this data,determine of cunent a voltage of 35 V Plot the line and the data for and evaluate fit the (b)Redo regressionand force the interceptto be zero the

rol-,l,,

DROP FULLTEXT STOPLIST ArcanesStoplist;

This chaptertakesthe conceptoffitting a straightline and extends to (d) fitting a it polynomialand (D)fitting a variablethat is a linear function of two or more independent variables will then show how suchapplications be generalized applied a We can and to Finally, we will illustratehow optimizationtechniques be broadergroup of problerns can usedto implementnonlinearregression Specilicobjectives and topicscoveredare o o o o Knowing how to implementpolynomial regression Knowing how to implementmultiple linear regression Understanding formulation of the generallinear least-squares the model Understanding how the generallinear least-squares model can be solvedwith MATLAB usingeitherthe normalequations left division or Understanding how to implementnonlinearregression with optimization techniques

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This covers the basic use of stopwords and stoplists in 2008. Let s take a moment now to look at some advanced queries that will help you manage your stopwords and stoplists.

In Chap13, a procedurewas developedto derive the equationof a straightline using the least-squares criterion Some data, although exhibiting a marked pattern such as seen in FiglrtfispoorlyrepresentedbyastraightlineForthesecases,acurvewouldbebetter suited to fit the dataAs discussed Chap 13, one method to acconrplish in this objective is to use transformations Another alternativeis to fit polynomialsto the datausingpolynotnial regression procedurecan be readily extendedto fit the data to a higher-order The least-squares polynomial For example,suppose polynomial or quadratic: that we fit a second-order ,y:uotalr+ a z r :+ e (141)

I4 FIGURE I (b i h regression)l n d i c o i i otn o io p o r o b o l os for leost-squores (o)Doto is ill-suited lineor ihot preferoble

Our first query returns a list of all the user-defined stoplists in our database:

\142)

fit, the To generate least-squares we take the derivativeof Eq (142) with respectto coefficientsof the polynomial, as in eachof the unknown

SELECT stoplist_id, name FROM sys.fulltext_stoplists;

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Our next query returns a list of stopwords for our user-defined stoplists in the database. Note the linking to get the associated stoplist name and language:

-c'ltt -a,'t,

-t'1*;)

SELECT sl.name as StoplistName , sw.stopword as StopWord, lg.alias as LanguageAlias , lg.name as LanguageName, lg.lcid as LanguageLCID FROM sys.fulltext_stopwords sw JOIN sys.fulltext_stoplists sl ON sl.stoplist_id = sw.stoplist_id JOIN master.sys.syslanguages lg ON lg.lcid = sw.language_id;

.

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This next query gets a list of all of the stopwords that ship with SQL Server 2008:

a2xl)

- a0 - a1x1 - u7tl)

SELECT ssw.stopword, slg.name FROM sys.fulltext_system_stopwords ssw JOIN sys.fulltext_languages slg ON slg.lcid = ssw.language_id;

These equationscan be set equal to zero and reananged to develop the following set of normal equations:

So far we ve learned how to create catalogs and full-text indexes, along with a variety of ways to get information back out of our indexes. All are great tools for the database developer. If you re a database administrator, though, there are few more tricks you can use to administer and take care of your full-text indexes.

zz (n)ao+ It')ar + (f -t''a) :Lvi ( (I r') oo+ (I-t,t) n' + (t ti) a2: lxiYi (Ir, ) oo+ (T",1)"' + (I-'1) tL2: lx!)'i

where all summationsare from i : I through n Note that the precedingthreeequations are can linear and have three unknowns:a0, ctt, anda2 The coefficientsof the unknowns be calculateddirectly from the observed data For this casewe see that the problem of determininga least-squares second-order polynomial is equivalentto solving a systemof three simultaneous The linear equations two-dimensional to casecan be easily extended an mth-orderpolynomial as in + ! : aotdlx f a2x2 a ax'' I e Thus,wecan The foregoinganalysiscan be easily extended this more generalcase to polynomial is equivalent to recognize that determining the coefficients of an mth-order enot For this case,the standard solving a systemof m I I simultaneous linear equations is formulatedas

Let s start with a few basic queries. First, let s retrieve a list of the catalogs that are associated with the current database.

n - (m -l1)

(143)

SELECT fulltext_catalog_id, name, is_default FROM sys.fulltext_catalogs;

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