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### CmpE226-DB-L10n1

Course: CMPE 138, Fall 2008
School: San Jose State
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Word Count: 777

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Design Dr. Database M.E. Fayad, Professor Computer Engineering Department, Room #283I College of Engineering San Jos State University One Washington Square San Jos, CA 95192-0180 http://www.engr.sjsu.edu/~fayad 2003 SJSU -- CmpE L10-S1 Normalization Lesson 10: Normalization 2 2003 SJSU CmpE --- M.E. Fayad L10-S2 Normalization Lesson Objectives Objectives Understand the goals of normalization Explore...

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San Jose State - CMPE - 138
5 Rules of Data Normalization1. Eliminate Repeating Groups - Make a separate table for each set of related attributes, and give each table a primary key. 2. Eliminate Redundant Data - If an attribute depends on only part of a multi-valued key, remov
San Jose State - CMPE - 138
NORMALIZATION By MATTIE MACGREGOR The aim of normalization is to remove certain kinds of data redundancy, and therefore avoid update anomalies. Update anomalies are difficulties with the insert, update and delete operations on a database due to the d
San Jose State - CMPE - 138
NormalizationWell normalized data makes programming (relatively) easy, and works very well in multi-platform, enterprise wide environments. Non-normalized data leads to heartbreak.Normalization: The first three formsFirst Normal Form: No repeati
San Jose State - CMPE - 138
Database Normalization By Ian Gilfillan By now some of you are familiar with the basics of using in your cgi scripts. Many of your databases will be small, with one or two tables. But as you become braver, tackling bigger projects, you may start find
San Jose State - CMPE - 138
Data Normalization Fundamentals by Luke Chung President of FMS Inc. http:/www.fmsinc.com Introduction The ability to analyze data in Access is a fundamental skill that all developers must master. The better you are at organizing your data and knowing
San Jose State - CMPE - 138
NormalizationT/F 1. Normalization is a design technique that is widely used as a guide in designing relational databases. T/F 2. Normalization is essentially a two step process that puts data into tabular form by removing repeating groups and then r
San Jose State - CMPE - 138
Database Normalization by David Faour A poor database design can cripple an application, producing problems with redundancy, inaccuracy, consistency, and concurrency of your data. Normalization is a process that serves to reduce, if not eliminate, th
San Jose State - CMPE - 138
Database Normalization And Design TechniquesBy: Barry Wise Introduction One of the most important factors in dynamic web page development is database definition. If your tables are not set up properly, it can cause you a lot of headaches down the ro
San Jose State - CMPE - 138
Lesson 12Object-Oriented DatabasesObject-Oriented DatabasesOODBMx xDB is a collection of objects each object represents a physical entity and an idea of interest to the DB application new trend in data modeling and DB processingxsGoal
San Jose State - CMPE - 138
Object Oriented Databases Are Worth a Closer LookObject-oriented databases (OODBs) can offer considerable advantages over relational databases (RDBs), yet application developers often opt for RDBs. Don't shortchange yourself. Learn the pros and cons
San Jose State - CMPE - 138
Object Oriented DatabaseGroup 4Mathieu Metz Palani Kumaresan Napa Gavinlertvatana Kristine Pei Keow Lee Prabhu Ramachandran Outline Object definitions Object Structures Objectoriented concepts OODBS OQL with an example SQL3 with ex
San Jose State - CMPE - 138
0.n Managed Person SSN Name Address 1.1 Manager
San Jose State - CMPE - 138
Database DesignDr. M.E. Fayad, Professor Computer Engineering Department, Room #283I College of Engineering San Jos State University One Washington Square San Jos, CA 95192-0180 http:/www.engr.sjsu.edu/~fayad2003SJSU - CmpEL12-S1Spatiotmpora
San Jose State - CMPE - 138
International Journal of Geographic Information Systems, Special Issue on System Integration, Vol. 12, No 3, 1998O n sp a t i a l d a t a b a s e i n t e g r a t i o nThomas Devogele, Institut Gographique National - COGIT, F 94100 Saint Mand thoma
San Jose State - CMPE - 138
CmpE 226Database Design Project #1Fall 2003_ Express the following queries in SQL using the hospital database. First Question: SQL-Basic 1. Find the weight of Mr. Smith. 2. Find the age of Dr. Hardy. 3. Find the dates (month, day, year) of Mr.
San Jose State - CMPE - 138
University of California, DavisApplication Development MethodologyTechniquesEntity-Relationship Modeling TechniqueOverviewThis section describes the definition of entity types and their relationships. It defines entity and relationship concept
San Jose State - CMPE - 138
CmpE 226Database Design Project 2Fall 20031. Design an MLPQ/PReSTO constraint database with at least 6 constraint tables. The constraint tables should use the full power of linear constraints. (For example, the equality constraint x =1 does not
San Jose State - CMPE - 138
CmpE 226: Database Systems &amp; Design1. Team Project Submission Guidelines:1. All team project materials must be submitted on time. 2. All team project submission must be handed in as hardcopies and must be submitted electronically. 3. For Electroni
San Jose State - CMPE - 138
Diagramming Techniques http:/www.nickerson.to/visprog/ch2/diagtech.htm Diagram-Tech.pdf
San Jose State - CMPE - 138
Object-Oriented Database Links: http:/www-2.cs.cmu.edu/People/clamen/OODBMS/ http:/www.service-architecture.com/object-oriented-databases/articles/index.html http:/www.service-architecture.com/object-oriented-databases/articles/odbms_faq.html http:/b
San Jose State - CMPE - 138
MyBusTeam Members: Kiran Patel Radhika Rajgopal Rajesh Dorairajan Abstract: In this project we propose to build a web-based tool called MyBus for the ACME Transportation Authority (ATA). This tool will help user plan a trip on ATA routes. It will al
San Jose State - CMPE - 138
UML Notation Guide3This guide describes the notation for the visual representation of the Unified Modeling Language (UML). This notation document contains brief summaries of the semantics of UML constructs, but the UML Semantics chapter must be c
San Jose State - CMPE - 138
XML &amp; Database Links http:/www.dwinfocenter.org/ http:/db.cs.sfu.ca/sections/publication/kdd/kdd.html http:/db.cs.sfu.ca/ http:/www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining .htm http:/tech.irt.org/articles/js215/in
San Jose State - CMPE - 138
begin%Face%Head(i, x, y, t) :-i = 0,x &gt; 100,x - y &gt; -450,y &lt; 650,x + y &lt; 1250,x &lt; 700,2x - y - 2t &lt; 1150,y &gt; 0,2x + y + 2t &gt; 450,t &gt;= 0,t &lt;= 20.Hair(i, x, y, t) :-i = 501,x &gt; 200,y &lt;
San Jose State - CMPE - 138
begin %mtaufik%face(i, x, y) :- i = 1, -x &lt;= 0,-y &lt;= 0, x +0.16 y &lt;= 10, x +0.51 y &lt;= 11.09, x + y &lt;= 13.97, x +1.97 y &lt;= 21.82, x +6.31 y &lt;= 63.1.face(i, x, y) :- i = 1, x &lt;= 0, -y &lt;= 0, -x +0.16 y &lt;= 10, -x +0.51 y &lt;= 11.09, -x + y &lt;= 13.97, -x
San Jose State - CMPE - 138
begin%test%/* * County defined by name, id (for ease of use later) * County(name, cid) */County_id(name, cid):-name=&quot;Alameda&quot;, cid = 1.County_id(name, cid):-name=&quot;Marin&quot;, cid = 2.County_id(name, cid):-name=&quot;San Francisco&quot;, cid = 3.County_id(
San Jose State - CMPE - 138
Neeta Tomar CMPE-226 Project 1 Updated Problem StatementINTRODUCTIONThis project aimed at implementing a database representing the Real Estate Economics of five different Bay area counties based on the MLPQ system. The goal is to be able to do que
San Jose State - CMPE - 138
begin%Route%Current_Pos(road, x, y) :- road = 880, -x &lt;= -221,x &lt;= 229, -y &lt;= -110, y &lt;= 118.Route(road, x, y):- road = 680, 10x - 3y = 2500, x &gt;= 250 ,
San Jose State - CMPE - 138
Binbin Lai and Tong LiCMPE226 Project#1 Problem Statement Title: Travel Information System Binbin Lai and Tong Li DescriptionThe objective of our project is to find the information of restaurants, shopping centers, gas stations, hotels, cities nea
San Jose State - CMPE - 138
begin%animation%head(id, x, y) :- x +0.41 y &lt;= 10,x +2.41 y &lt;= 24.14,-x +2.41 y &lt;= 24.14,-x +0.41 y &lt;= 10,-x -0.41 y &lt;= 10,-x -2.41 y &lt;= 24.14,x -2.41 y &lt;= 24.14,x -0.41 y &lt;= 10.hair(id, x, y) :- id = 1,x -0.09 y = 0.66,-x &lt;= -1.51,x
San Jose State - CMPE - 138
begin %hospital%patient(name, id, cm, kg) :- name=&quot;Anderson&quot;, id=100, cm=200, kg=130.patient(name, id, cm, kg) :- name=&quot;Brown&quot;, id=111, cm=150, kg=50.patient(name, id, cm, kg) :- name=&quot;Davis&quot;, id=222, cm=190, kg=90.patient(name, id, cm, kg)
San Jose State - CMPE - 138
begin%animation%head(id, x, y) :- x +0.41 y &lt;= 10,x +2.41 y &lt;= 24.14,-x +2.41 y &lt;= 24.14,-x +0.41 y &lt;= 10,-x -0.41 y &lt;= 10,-x -2.41 y &lt;= 24.14,x -2.41 y &lt;= 24.14,x -0.41 y &lt;= 10.hair(id, x, y) :- id = 1,x -0.09 y = 0.66,-x &lt;= -1.51,x
San Jose State - CMPE - 138
begin%SD% face(x,y):- x&gt;=0, x&lt;1, y&gt;=-4, y&lt;=4.face(x,y):- x&gt;=1, x&lt;2, y&gt;=-12.46, y&lt;=12.46.face(x,y):- x&gt;=2, x&lt;3, y&gt;=-16.008, y&lt;=16.008.face(x,y):- x&gt;=3, x&lt;4, y&gt;=-18.848, y&lt;=18.848.face(x,y):- x&gt;=4, x&lt;5, y&gt;=-21.266, y&lt;=21.266.
San Jose State - CMPE - 138
x hH}phV3Vh7 3pp hVep p5 p }p hV}pV7}h}a}pp}hh} PW d d Y W d f PWW ` UW `b d S PY Sg g YW U Si W d Pb d S Ug }3 XUTf5WRgVVRti}egVXa`BQhp9xV3VD}aH(VVR}1RWhVX}aPf dP3aPV&amp;m5dB59eg`bVhUhXYaVR5aahacP`}Rgg~TW3Vx
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Spectra Extracted from tstart=-1.070 tstop=4.950(Trigger Time, GPS=798091925.000000, Redshift, z=0.0)Power-Law Model FitNorm@15keV 6.1256e-03 (2.8320e-03 1.0653e-02)alpha -1.2461 (-1.7291 -0.7486)Energy Fluence (15-350 keV) 1.7188e-07 (1.2382e
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