What Factors Impact a Greenhouse? Modified with permission from Global Climates - Past, Present, and Future, S. Henderson, S. Holman, and L. Mortensen (Eds.). EPA Report No. EPA/600/R-93/126, U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC 47 - 52. Background The earth~s atmospheric "greenhouse effect" is much more complex than the simple greenhouse experiment described in Activity 12. While the earth~s temperature is dependent upon the greenhouse-like action of the atmosphere, the amount of heating and cooling are strongly influenced by several factors. The type of surface that sunlight first encounters is the most important factor. Forests, grasslands, ocean surfaces, ice caps, deserts, and cities all absorb, reflect, and radiate radiation differently. Sunlight falling on a white glacier surface strongly reflects back into space, resulting in minimal heating of the surface and lower atmosphere. Sunlight falling on a dark desert soil is strongly absorbed, on the other hand, and contributes to significant heating of the surface and lower atmosphere. Cloud cover also affects greenhouse warming by both reducing the amount of solar radiation reaching the earth~s surface and by reducing the amount of radiation energy emitted into space. Scientists use the term albedo to define the percentage of solar energy reflected back by a surface. Understanding local, regional, and global albedo effects is critical to predicting global climate change. The following are some of the factors that influence the earth~s albedo. * Clouds: On a hot, sunny day, we usually welcome a big fluffy cumulus cloud passing overhead because we feel cooler immediately. That~s because the top of the cloud reflects sunlight back into space before it ever reaches earth. Depending on their altitude and optical properties, clouds either cool or warm the earth. Large, thick, relatively low-altitude clouds, such as cumulus and cumulonimbus, reflect incoming solar radiation and thereby reduce warming of the surface. The whitewash on plant greenhouses has the same effect on a smaller scale. High-altitude, thinner clouds, such as cirrus clouds, absorb longwave radiation reflected from the earth~s surface, causing increased warming. Cirrus Cumulus Nimbus * Surface albedo: Just as some clouds reflect solar energy into space, so do light-colored land surfaces. This surface albedo effect strongly influences the absorption of sunlight. Snow and ice cover are highly reflective, as are light-colored deserts. Large expanses of reflective surfaces can significantly reduce solar warming. Dark-colored land surfaces, in contrast, are strongly absorptive and contribute to warming. If global temperatures increase, snow and ice cover may shrink. The exposed darker surfaces underneath may absorb more solar radiation, causing further warming. The magnitude of the effect is currently a matter of serious scientific study and debate. * Oceans: From space, oceans look much different than adjacent land areas - they often appear darker, suggesting that they should be absorbing far more sunlight. But unlike dry land, water absorbs energy in a dynamic fashion. Some of the solar energy contacting the surface may be carried away by currents, some may go into producing water vapor, and some may penetrate the surface and be mixed meters deep into the water column. These factors combine to make the influence of the ocean surface an extremely complex and difficult phenomenon to predict. Water also has the capacity to store heat and transport large amounts of heat energy. In addition, oceans are an important sink (storage site) for atmospheric , and their ability to absorb is strongly related to ocean temperature. Because of their enormous size and depth, oceans are extremely important in determining global climate and the future rate of global temperature change. * Forested areas: Like the oceans, the interaction of forests and sunlight is complex. The amount of solar radiation absorbed by forest vegetation depends upon the type and color of vegetation, the time of year, and how well watered and healthy the plants are. In general, plants provide a dark surface, so you might expect high solar absorption. A significant fraction of the solar radiation is captured by the plants and used to make food through photosynthesis (and thus it doesn~t re-radiate as heat); some of the energy is dissipated as water evaporates from plant leaves; and some is absorbed and distributed deep within the forest canopy. These complexities make a simple definition of forest influences impossible. To a lesser extent, the same complexities apply to any relatively continuous-cover ecosystem (for example, grasslands and farmlands). In this exercise, students will form their own conclusions as to how different surface and cover types affect heating using the model bottle systems introduced in Activity 12. Learning Goals 1. Students will be able to identify at least three factors affecting the heat-trapping ability of a greenhouse, including the transparency of the greenhouse cover, color of the surfaces inside the greenhouse, and type of surfaces inside. 2. Students will be able to explain the factors important in the atmosphere~s heat trapping ability. 3. Students will understand the influence of albedo on earth~s temperature. Alignment to National Standards National Science Education Standards * Unifying Concepts and Processes, Grades K to 12, pg. 117: "Models are tentative schemes or structures that correspond to real objects, events, or classes of events and that have explanatory power." * Physical Science, Transfer of Energy, Grades 5 to 8, pg. 155, Item #2: "Heat moves in predictable ways flowing from warmer objects to cooler ones, until both reach the same temperature." * Earth and Space Science, Grades 9 to 12, pg. 189, Item #3: "Heating of earth~s surface and atmosphere by the sun drives convection within the atmosphere and oceans, producing winds and ocean currents." Benchmarks for Science Literacy, Project 2061, AAAS * Common Themes, Models, Grades 6 to 8, pg. 269, Item #1: "Models are often used to think about processes that happen too slowly, too quickly, or on too small a scale to observe directly, or that are too vast to be changed deliberately, or that are potentially dangerous." * The Physical Setting, Energy Transformations, Grades 6 to 8, pg. 85, Item #3: "Heat can be transferred through materials by the collisions of atoms or across space by radiation. If the material is fluid, currents will set up in it that aid the transfer of heat." Grade Level/Time * Grade level: 5 to 9 * Time: o Introduction by teacher: 15 minutes o Student activity (assuming bottle construction already done): 60 minutes Materials for Each Team of Four Students * Six soda bottle experimental chambers (see materials in Activity 12) * Six thermometers * Tape (transparent or light-colored) * White paint * Three cups of dark soil (garden or potting soil) * Three cups of white sand or perlite * Water and dump buckets * One 150-watt floodlight bulb * Portable reflector lamp * Stand to support lamp set-up * Graph paper Procedure 1. To save time, you (or your students) should prepare the model greenhouses prior to class. For each team of four students, you will need six experimental chambers. Paint the upper third of three of the bottles white. 2. Label the bottles A, B, C, D, E, and F with bottles B, D, and F having the white paint. 3. Fill the base of bottles A and B with dark soil, bottles C and D with white sand, and bottles E and F with room-temperature water. 4. Tape a thermometer (using transparent tape or light-colored masking tape) to the inside of each bottle (facing out). 5. Place the bottle tops in the bases. Make sure the bottles are capped. 6. Make sure the bulbs of the thermometers are just above the top of the bases. If the bulbs are below the base, the thermometer may record the heat absorbed directly by the soil or water, complicating the results. 7. Ask students to predict which bottle will get hotter. Why? Record predictions. 8. Have each team set up a graph of time (in minutes) vs. temperature to record their observations. 9. Each student should have a specific responsibility during the experiment, either keeping track of the time or recording the temperature for the different bottles. 10. Place the bottles approximately six inches away from the lamp with the thermometer facing away from the light. Record the baseline temperatures. 11. Turn on the light and begin recording the temperatures every two minutes. Continue for at least 20 minutes. Cautionary Note: If your lamp is not big enough, six bottles may be too many to have under the light at the same time. The ones further from the light may not get the same intensity of heat as the bottles closer to the light thereby compromising the experiment. You may have the students use a sub-set of the bottles at one time. If you make changes in the experiment, make sure you also change the student guide. Observations and Questions 1. Compare the graphed information from the different bottles. 2. Discuss the results and propose some possible explanations. 3. Relate the factors affecting the model greenhouses to the factors affecting the "global greenhouse." Which factors are the same? Which are different? Assessment Ideas * After discussing their findings, ask students to sketch and explain how to set up a model greenhouse (with the light on) with the absolutely coolest possible temperatures. Where might such a condition be found on earth? * Now ask them to sketch and explain a greenhouse designed to generate the maximum possible heat. Where might such a condition really exist? Modifications for Alternative Learners * Team English Language Limited students with more proficient students. When you~re finished with the activity, click on To Student Guide or Back to Activities List at the top of the page to return to the activity menu.

prinshu singh   (XII)

Red Rose Berasia Road

“Happiness comes from spiritual wealth, not material wealth. Happiness comes from giving not getting. If we try hard to bring happiness to others we cannot stop it from coming to us also.”

rishabh soni   (I)

Red Rose Lambakheda

a person without dreams is incomplete because untill and unless we don~t know what are the things which we have to achieve we will not able to put our efforts on a straight path and our hard working will be like a ray of light which has no end .By seeing dream it doesn~t mean you are wasting your time in your dreams everytime.Always be energetic to do hard work by remembering your dreams.

Shubham Sahu   (XII)

Red Rose Berasia Road

A man who dares to waste one hour of a time has not discovered the Value of Life.

prashant maithil   (XII)

Red Rose Berasia Road

Although Prime Minister and Congress party leader Indira Gandhi is quoted as saying that corruption is a misuse of power, she also publicly stated "nonchalantly" that "corruption was a global phenomenon" and her government was no different.[4][5][6] Successive central governments and members of India~s famous Nehru-Gandhi political dynasty have often been accused most of corruption and amassing illegal wealth among India~s political class.[4][7][8] The year 2011 has proved to be a watershed in the public tolerance of political corruption in India, with widespread public protests and movements led by social activists against corruption and for the return of illegal wealth stashed by politicians and businessmen in foreign banks over the six decades since independence. Criminalization is also a serious problem in contemporary Indian politics.[9] In July 2008 The Washington Post reported that nearly a fourth of the 540 Indian Parliament members faced criminal charges, "including human trafficking, immigration rackets, embezzlement, rape and even murder".[10] India tops the list for black money in the entire world with almost US$1456 billion in Swiss banks (approximately USD 1.4 trillion) in the form of black money.[11] According to the data provided by the Swiss Banking Association Report (2006), India has more black money than the rest of the world combined.[12][13] To put things in perspective, Indian-owned Swiss bank account assets are worth 13 times the country’s national debt.[14]

priyanka   (X)

Red Rose Berasia Road

CHAPTER 1 BACK-END, FRONT-END AND THEIR APPLICATION CHAPTER 1 BACK-END, FRONT-END AND THEIR APPLICATION FRONT END Front end software are basically GUI software created for user friendly data entry. A "front-end" application is one that application users interact with directly. Front-end is always graphical system that’s why it is more users friendly. 1) For software applications, front end is the same as user interface. (2) In client/server applications, the client part of the program is often called the front end and the server part is called the back end. (3) Compilers, the programs that translate source code into object code, are often composed of two parts: a front end and a back end. 3/11/2011 Delete I.P CHAPTER=2 System Development Life Cycle The systems development life cycle (SDLC) is a conceptual model used in project management that describes the stages involved in an information system development project, from an initial feasibility study through maintenance of the completed application. Various SDLC methodologies have been developed to guide the processes involved, including the waterfall model (which was the original SDLC method); rapid application development (RAD); joint application development (JAD); the fountain model; the spiral model; build and fix; and synchronize-and-stabilize. Often, several models are combined into some sort of hybrid methodology. Documentation is crucial regardless of the type of model chosen or devised for any application, and is usually done in parallel with the development process. Some methods work better for specific types of projects, but in the final analysis, the most important factor for the success of a project may be how closely the particular plan was followed. In general, an SDLC methodology follows these steps: 1. If there is an existing system, its deficiencies are identified. This is accomplished by interviewing users and consulting with support personnel. 2. The new system requirements are defined including addressing any deficiencies in the existing system with specific proposals for improvement. 3. The proposed system is designed. Plans are created detailing the hardware, operating systems, programming, and security issues. 4. The new system is developed. The new components and programs must be obtained and installed. Users of the system must be trained in its use, and all aspects of performance must be tested. If necessary, adjustments must be made at this stage. 5. The system is put into use. This can be done in various ways. The new system can phased in, according to application or location, and the old system gradually replaced. In some cases, it may be more cost-effective to shut down the old system and implement the new system all at once. Types of System development Life Cycle 2. System analysis The goal of system analysis is to determine where the problem is in an attempt to fix the system. This step involves breaking down the system in different pieces to analyze the situation, analyzing project goals, breaking down what needs to be created and attempting to engage users so that definite requirements can be defined. Requirements analysis sometimes requires individuals/teams from client as well as service provider sides to get detailed and accurate requirements; often there has to be a lot of communication to and from to understand these requirements. Requirement gathering is the most crucial aspect as many times communication gaps arise in this phase and this leads to validation errors and bugs in the software program. 3. Design In systems design the design functions and operations are described in detail, including screen layouts, business rules, process diagrams and other documentation. The output of this stage will describe the new system as a collection of modules or subsystems. The design stage takes as its initial input the requirements identified in the approved requirements document. For each requirement, a set of one or more design elements will be produced as a result of interviews, workshops, and/or prototype efforts. Design elements describe the desired software features in detail, and generally include functional hierarchy diagrams, screen layout diagrams, tables of business rules, business process diagrams, pseudo code, and a complete entity-relationship diagram with a full data dictionary. These design elements are intended to describe the software in sufficient detail that skilled programmers may develop the software with minimal additional input design OBJECTIVES CHOOSE THE CORRECT ANSWER: 1. The answer of HOW and WHAT is given by (a) Analysis 2. Database schema is the output of- (b) Design 3. Data Model are used for- (b) Database Fill in the blanks: 1. Network model is defined by CODASYL in 1971 year. 2. Object oriented database uses feature of Object Oriented language. 3. Table concept is used in Relational language. True and False: 1. SQL is a standard Language for RDBMS: TRUE 2. Feasibility study checks the possibility of system. TRUE 3. Coding Phase is related to programming. TRUE Match the column: 1. ROW Tuple 2. COLUMN Attribute 3. RDBMS Edger codd 4. SDLC Attribute CHAPTER= 3 ENTITY RELATIONSHIP MODEL INTRODUCTION: We have covered the concepts of relational databases in "Introduction to Databases," how to access such databases in "Accessing Databases with SQL," creation of web pages with forms in "Creating Web Pages" and "Web Forms for Database Queries," and CGI programming to interface between web pages and databases and to process data in "CGI Programs and Web Forms" and "CGI Programs in C++ Using the MySQL C API," "In Genomic Data," "Genomic Sequence Comparison," and "Searching Genomic Databases," we studied some of the algorithms to process genomic data and how to use these algorithms in conjunction with the above tasks. Until now, however, we have employed existing databases. The current module, "Relational Database Development," and "Creating and Changing Databases with SQL" discuss how we can design and produce databases. The ability to do so is important for development of databases for our own use or for larger computational science applications. Throughout this discussion, we consider the "College Physics Example" of the module "Computational Science and Web-Accessed Databases" as well as other applications. Entities and Entity Sets • An entity is an object that exists and is distinguishable from other objects. For instance, John Harris with S.I.N. 890-12-3456 is an entity, as he can be uniquely identified as one particular person in the universe. • An entity may be concrete (a person or a book, for example) or abstract (like a holiday or a concept). • An entity set is a set of entities of the same type (e.g., all persons having an account at a bank). • Entity sets need not be disjoint. For example, the entity set employee (all employees of a bank) and the entity set customer (all customers of the bank) may have members in common. • An entity is represented by a set of attributes. o E.g. name, S.I.N., street, city for ``customer~~ entity. o The domain of the attribute is the set of permitted values (e.g. the telephone number must be seven positive integers). • Formally, an attribute is a function which maps an entity set into a domain. o Every entity is described by a set of (attribute, data value) pairs. o There is one pair for each attribute of the entity set. o E.g. a particular customer entity is described by the set {(name, Harris), (S.I.N., 890-123-456), (street, North), (city, Georgetown)}. An analogy can be made with the programming language notion of type definition. • The concept of an entity set corresponds to the programming language type definition. • A variable of a given type has a particular value at a point in time. • Thus, a programming language variable corresponds to an entity in the E-R model. Figure 2-1 shows two entity sets. We will be dealing with five entity sets in this section: • branch, the set of all branches of a particular bank. Each branch is described by the attributes branch-name, branch-city and assets. • customer, the set of all people having an account at the bank. Attributes are customer-name, S.I.N., street and customer-city. • employee, with attributes employee-name and phone-number. • account, the set of all accounts created and maintained in the bank. Attributes are account-number and balance. • transaction, the set of all account transactions executed in the bank. Attributes are transaction-number, date and amount. Attributes It is possible to define a set of entities and the relationships among them in a number of different ways. The main difference is in how we deal with attributes. • Consider the entity set employee with attributes employee-name and phone-number. • We could argue that the phone be treated as an entity itself, with attributes phone-number and location. • Then we have two entity sets, and the relationship set EmpPhn defining the association between employees and their phones. • This new definition allows employees to have several (or zero) phones. • New definition may more accurately reflect the real world. • We cannot extend this argument easily to making employee-name an entity. Mapping Constraints An E-R scheme may define certain constraints to which the contents of a database must conform. • Mapping Cardinalities: express the number of entities to which another entity can be associated via a relationship. For binary relationship sets between entity sets A and B, the mapping cardinality must be one of: 1. One-to-one: An entity in A is associated with at most one entity in B, and an entity in B is associated with at most one entity in A. (Figure 2.3) 2. One-to-many: An entity in A is associated with any number in B. An entity in B is associated with at most one entity in A. (Figure 2.4) 3. Many-to-one: An entity in A is associated with at most one entity in B. An entity in B is associated with any number in A. (Figure 2.5) 4. Many-to-many: Entities in A and B are associated with any number from each other. (Figure 2.6) The appropriate mapping cardinality for a particular relationship set depends on the real world being modeled. (Think about the CustAcct relationship...) Keys Differences between entities must be expressed in terms of attributes. • A superkey is a set of one or more attributes which, taken collectively, allow us to identify uniquely an entity in the entity set. • For example, in the entity set customer, customer-name and S.I.N. is a superkey. • Note that customer-name alone is not, as two customers could have the same name. • A superkey may contain extraneous attributes, and we are often interested in the smallest superkey. A superkey for which no subset is a superkey is called a candidate key. • In the example above, S.I.N. is a candidate key, as it is minimal, and uniquely identifies a customer entity. • A primary key is a candidate key (there may be more than one) chosen by the DB designer to identify entities in an entity set. An entity set that does not possess sufficient attributes to form a primary key is called a weak entity set. One that does have a primary key is called a strong entity set. For example, • The entity set transaction has attributes transaction-number, date and amount. • Different transactions on different accounts could share the same number. • These are not sufficient to form a primary key (uniquely identify a transaction). • Thus transaction is a weak entity set. For a weak entity set to be meaningful, it must be part of a one-to-many relationship set. This relationship set should have no descriptive attributes. (Why?) The idea of strong and weak entity sets is related to the existence dependencies seen earlier. • Member of a strong entity set is a dominant entity. • Member of a weak entity set is a subordinate entity. A weak entity set does not have a primary key, but we need a means of distinguishing among the entities. The discriminator of a weak entity set is a set of attributes that allows this distinction to be made. The primary key of a weak entity set is formed by taking the primary key of the strong entity set on which its existence depends (see Mapping Constraints) plus its discriminator. To illustrate: • Transaction is a weak entity. It is existence-dependent on account. • The primary key of account is account-number. • Transaction-number distinguishes transaction entities within the same account (and is thus the discriminator). • So the primary key for transaction would be (account-number, transaction-number Objectives: Q1 Choose the correct answer: 1. Key attributes represents: Primary Key 2. ER Model is a: Conceptual: Model 3 Only one entity set is used in: Ternary Q2. Fill in the blanks: 1. Mapping is used to show the Association of entities. 2. Weak entity set is associate with Owner entity set. 3. Value of Derived Attribute is determined by Base Attribute. Q3. Stay true or false: 1. Ternary relationship has three entity set: True 2. Weak entity sets may have primary key: False 3. ER Model could be converted in to Relation Model: True Q4. Match the column: 1. Composite Attribute Sub Attribute 2. Multi valued Attribute Many values 3. Binary Relationship Two entity set 4. Weak Entity Owner Entity Chapter= 4 RDBMS & DBMS The tables in the following sections provide a functional summary of SQL statements and are divided into these categories: • Data Definition Language (DDL) Statements • Data Manipulation Language (DML) Statements • Transaction Control Statements • Session Control Statements • System Control Statement • Embedded SQL Statements 1. Data Definition Language (DDL) Statements Data definition language (DDL) statements let you to perform these tasks: • Create, alter, and drop schema objects • Grant and revoke privileges and roles • Analyze information on a table, index, or cluster • Establish auditing options • Add comments to the data dictionary The CREATE; ALTER, and DROP commands require exclusive access to the specified object. For example, an ALTER TABLE statement fails if another user has an open transaction on the specified table. The GRANT, REVOKE, ANALYZE, AUDIT, and COMMENT commands do not require exclusive access to the specified object. For example, you can analyze a table while other users are updating the table. Oracle Database implicitly commits the current transaction before and after every DDL statement. Many DDL statements may cause Oracle Database to recompile or reauthorize schema objects. For information on how Oracle Database recompiles and reauthorizes schema objects and the circumstances under which a DDL statement would cause this, see Oracle Database Concepts. DDL statements are supported by PL/SQL with the use of the DBMS_SQL package. 2.Data Manipulation Language (DML) Statements Data manipulation language (DML) statements access and manipulate data in existing schema objects. These statements do not implicitly commit the current transaction. The data manipulation language statements are: CALL DELETE EXPLAIN PLAN INSERT LOCK TABLE MERGE SELECT UPDATE The SELECT statement is a limited form of DML statement in that it can only access data in the database. It cannot manipulate data in the database, although it can operate on the accessed data before returning the results of the query. 3.Transaction Control Statements Transaction control statements manage changes made by DML statements. The transaction control statements are: COMMIT ROLLBACK SAVEPOINT SET TRANSACTION All transaction control statements, except certain forms of the COMMIT and ROLLBACK commands, are supported in PL/SQL. For information on the restrictions, see COMMIT and ROLLBACK . 4.Session Control Statements Session control statements dynamically manage the properties of a user session. These statements do not implicitly commit the current transaction. PL/SQL does not support session control statements. The session control statements are: 1. ALTER SESSION 2. SET ROLE 5.System Control Statement The single system control statement, ALTER SYSTEM, dynamically manages the properties of an Oracle Database instance. This statement does not implicitly commit the current transaction and is not supported in PL/SQL. 6.Embedded SQL Statements Embedded SQL statements place DDL, DML, and transaction control statements within a procedural language program. Embedded SQL is supported by the Oracle recompiles and is documented in the following books: • Pro*COBOL Programmer~s Guide • Pro*C/C++ Programmer~s Guide • Oracle SQL*Module for Ad a Programmer~s Guide Embedded SQL statements are: OPEN CLOSE DECLARE CONNECT FET Objectives: Ques: 1 Choose the correct answer: 1. SQl is a standard language by- Ans- ANSI 2. PL/SQL commands by- Ans-Embedded SQL 3. Alter modifies Ans-Table Structure Q2. Fill in the blanks: 1. DDL Commands are specially made for database objects. 2. All operations are cancelled by ROLLBACK commands. 3. DML statements are used for data. Q3. STAY TRUR OR FALSE:: 1. COMMIT is used to save all operations-(TRUE) 2. Session control statements are not supported in PL/SQL (TRUE) 3. DROP command is used to drop a column-(FALSE) Q4. MATCH the column: 1. GRANT DDL 2. MERGE DML 3. SAVEPOINT TCS 4. DECLARE Embedded .Meta data- Meta data are ‘data about data’ of any sort in any media. An item of metadata may describe an individual datum, or content item, or content item, or a collection of data including multiple content items. The word Meta comes from the Greek, where it means ‘after’ or ‘beyond’. Metadata are used facilitate the understanding, characteristics, use and management of data. .Data Dictionary- A data structure which stores meta-data is called Data dictionary. Usually it means a table in a data base that stores the names, fields, types, length, and other Characteristics of the field in the database tables. An active data dictionary is automatically updated as changes occur in the database. A passive data dictionary must be annually updated. The data dictionary is a more general software utility used by designers, users, and administrator for information recourses management. The data dictionary may maintain information on system hardware, software, documentation, users and other aspects . .Data Warehouse- Abbreviated DW, a collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. Development of a data warehouse includes development of systems to extract data from operating systems plus installation of a warehouse database system that provides managers flexible access to the data. The term data warehousing generally refers to the combination of many different databases across an entire enterprise. Contrast with data mart. .Data Mining- Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. The three major data mining techniques are:- • Classes: Stored data is used to locate data in predetermined groups. For example, a restaurant chain could mine customer purchase data to determine when customers visit and what they typically order. This information could be used to increase traffic by having daily specials. • Clusters: Data items are grouped according to logical relationships or consumer preferences. For example, data can be mined to identify market segments or consumer affinities. • Sequential patterns: Data is mined to anticipate behavior patterns and trends. For example, an outdoor equipment retailer could predict the likelihood of a backpack being purchased based on a consumer~s purchase of sleeping bags and hiking shoes 6/23/2011

anshul   (XII)

Red Rose Berasia Road

The only true wisdom is in knowing you know nothing. A wise man does not need advice and a fool won~t take it.

nikita verma   (XII)

Red Rose Berasia Road

“To be always thinking about your manners is not the way to make them good; the very perfection of manners is not to think about yourself”

priya tiwari   (XII)

Red Rose Berasia Road

That men should live honestly, quietly, and comfortably together, it is needful that they should live under a sense of God~s will, and in awe of the divine power, hoping to please God, and fearing to offend Him, by their behaviour respectively.

nikita verma   (XII)

Red Rose Berasia Road

CHAPTER=2 System Development Life Cycle The systems development life cycle (SDLC) is a conceptual model used in project management that describes the stages involved in an information system development project, from an initial feasibility study through maintenance of the completed application. Various SDLC methodologies have been developed to guide the processes involved, including the waterfall model (which was the original SDLC method); rapid application development (RAD); joint application development (JAD); the fountain model; the spiral model; build and fix; and synchronize-and-stabilize. Often, several models are combined into some sort of hybrid methodology. Documentation is crucial regardless of the type of model chosen or devised for any application, and is usually done in parallel with the development process. Some methods work better for specific types of projects, but in the final analysis, the most important factor for the success of a project may be how closely the particular plan was followed. In general, an SDLC methodology follows these steps: 1. If there is an existing system, its deficiencies are identified. This is accomplished by interviewing users and consulting with support personnel. 2. The new system requirements are defined including addressing any deficiencies in the existing system with specific proposals for improvement. 3. The proposed system is designed. Plans are created detailing the hardware, operating systems, programming, and security issues. 4. The new system is developed. The new components and programs must be obtained and installed. Users of the system must be trained in its use, and all aspects of performance must be tested. If necessary, adjustments must be made at this stage. 5. The system is put into use. This can be done in various ways. The new system can phased in, according to application or location, and the old system gradually replaced. In some cases, it may be more cost-effective to shut down the old system and implement the new system all at once. Types of System development Life Cycle 2. System analysis The goal of system analysis is to determine where the problem is in an attempt to fix the system. This step involves breaking down the system in different pieces to analyze the situation, analyzing project goals, breaking down what needs to be created and attempting to engage users so that definite requirements can be defined. Requirements analysis sometimes requires individuals/teams from client as well as service provider sides to get detailed and accurate requirements; often there has to be a lot of communication to and from to understand these requirements. Requirement gathering is the most crucial aspect as many times communication gaps arise in this phase and this leads to validation errors and bugs in the software program. 3. Design In systems design the design functions and operations are described in detail, including screen layouts, business rules, process diagrams and other documentation. The output of this stage will describe the new system as a collection of modules or subsystems. The design stage takes as its initial input the requirements identified in the approved requirements document. For each requirement, a set of one or more design elements will be produced as a result of interviews, workshops, and/or prototype efforts. Design elements describe the desired software features in detail, and generally include functional hierarchy diagrams, screen layout diagrams, tables of business rules, business process diagrams, pseudo code, and a complete entity-relationship diagram with a full data dictionary. These design elements are intended to describe the software in sufficient detail that skilled programmers may develop the software with minimal additional input design OBJECTIVES CHOOSE THE CORRECT ANSWER: 1. The answer of HOW and WHAT is given by (a) Analysis 2. Database schema is the output of- (b) Design 3. Data Model are used for- (b) Database Fill in the blanks: 1. Network model is defined by CODASYL in 1971 year. 2. Object oriented database uses feature of Object Oriented language. 3. Table concept is used in Relational language. True and False: 1. SQL is a standard Language for RDBMS: TRUE 2. Feasibility study checks the possibility of system. TRUE 3. Coding Phase is related to programming. TRUE Match the column: 1. ROW Tuple 2. COLUMN Attribute 3. RDBMS Edger codd 4. SDLC Attribute CHAPTER= 3 ENTITY RELATIONSHIP MODEL INTRODUCTION: We have covered the concepts of relational databases in "Introduction to Databases," how to access such databases in "Accessing Databases with SQL," creation of web pages with forms in "Creating Web Pages" and "Web Forms for Database Queries," and CGI programming to interface between web pages and databases and to process data in "CGI Programs and Web Forms" and "CGI Programs in C++ Using the MySQL C API," "In Genomic Data," "Genomic Sequence Comparison," and "Searching Genomic Databases," we studied some of the algorithms to process genomic data and how to use these algorithms in conjunction with the above tasks. Until now, however, we have employed existing databases. The current module, "Relational Database Development," and "Creating and Changing Databases with SQL" discuss how we can design and produce databases. The ability to do so is important for development of databases for our own use or for larger computational science applications. Throughout this discussion, we consider the "College Physics Example" of the module "Computational Science and Web-Accessed Databases" as well as other applications. Entities and Entity Sets • An entity is an object that exists and is distinguishable from other objects. For instance, John Harris with S.I.N. 890-12-3456 is an entity, as he can be uniquely identified as one particular person in the universe. • An entity may be concrete (a person or a book, for example) or abstract (like a holiday or a concept). • An entity set is a set of entities of the same type (e.g., all persons having an account at a bank). • Entity sets need not be disjoint. For example, the entity set employee (all employees of a bank) and the entity set customer (all customers of the bank) may have members in common. • An entity is represented by a set of attributes. o E.g. name, S.I.N., street, city for ``customer~~ entity. o The domain of the attribute is the set of permitted values (e.g. the telephone number must be seven positive integers). • Formally, an attribute is a function which maps an entity set into a domain. o Every entity is described by a set of (attribute, data value) pairs. o There is one pair for each attribute of the entity set. o E.g. a particular customer entity is described by the set {(name, Harris), (S.I.N., 890-123-456), (street, North), (city, Georgetown)}. An analogy can be made with the programming language notion of type definition. • The concept of an entity set corresponds to the programming language type definition. • A variable of a given type has a particular value at a point in time. • Thus, a programming language variable corresponds to an entity in the E-R model. Figure 2-1 shows two entity sets. We will be dealing with five entity sets in this section: • branch, the set of all branches of a particular bank. Each branch is described by the attributes branch-name, branch-city and assets. • customer, the set of all people having an account at the bank. Attributes are customer-name, S.I.N., street and customer-city. • employee, with attributes employee-name and phone-number. • account, the set of all accounts created and maintained in the bank. Attributes are account-number and balance. • transaction, the set of all account transactions executed in the bank. Attributes are transaction-number, date and amount. Attributes It is possible to define a set of entities and the relationships among them in a number of different ways. The main difference is in how we deal with attributes. • Consider the entity set employee with attributes employee-name and phone-number. • We could argue that the phone be treated as an entity itself, with attributes phone-number and location. • Then we have two entity sets, and the relationship set EmpPhn defining the association between employees and their phones. • This new definition allows employees to have several (or zero) phones. • New definition may more accurately reflect the real world. • We cannot extend this argument easily to making employee-name an entity. Mapping Constraints An E-R scheme may define certain constraints to which the contents of a database must conform. • Mapping Cardinalities: express the number of entities to which another entity can be associated via a relationship. For binary relationship sets between entity sets A and B, the mapping cardinality must be one of: 1. One-to-one: An entity in A is associated with at most one entity in B, and an entity in B is associated with at most one entity in A. (Figure 2.3) 2. One-to-many: An entity in A is associated with any number in B. An entity in B is associated with at most one entity in A. (Figure 2.4) 3. Many-to-one: An entity in A is associated with at most one entity in B. An entity in B is associated with any number in A. (Figure 2.5) 4. Many-to-many: Entities in A and B are associated with any number from each other. (Figure 2.6) The appropriate mapping cardinality for a particular relationship set depends on the real world being modeled. (Think about the CustAcct relationship...) Keys Differences between entities must be expressed in terms of attributes. • A superkey is a set of one or more attributes which, taken collectively, allow us to identify uniquely an entity in the entity set. • For example, in the entity set customer, customer-name and S.I.N. is a superkey. • Note that customer-name alone is not, as two customers could have the same name. • A superkey may contain extraneous attributes, and we are often interested in the smallest superkey. A superkey for which no subset is a superkey is called a candidate key. • In the example above, S.I.N. is a candidate key, as it is minimal, and uniquely identifies a customer entity. • A primary key is a candidate key (there may be more than one) chosen by the DB designer to identify entities in an entity set. An entity set that does not possess sufficient attributes to form a primary key is called a weak entity set. One that does have a primary key is called a strong entity set. For example, • The entity set transaction has attributes transaction-number, date and amount. • Different transactions on different accounts could share the same number. • These are not sufficient to form a primary key (uniquely identify a transaction). • Thus transaction is a weak entity set. For a weak entity set to be meaningful, it must be part of a one-to-many relationship set. This relationship set should have no descriptive attributes. (Why?) The idea of strong and weak entity sets is related to the existence dependencies seen earlier. • Member of a strong entity set is a dominant entity. • Member of a weak entity set is a subordinate entity. A weak entity set does not have a primary key, but we need a means of distinguishing among the entities. The discriminator of a weak entity set is a set of attributes that allows this distinction to be made. The primary key of a weak entity set is formed by taking the primary key of the strong entity set on which its existence depends (see Mapping Constraints) plus its discriminator. To illustrate: • Transaction is a weak entity. It is existence-dependent on account. • The primary key of account is account-number. • Transaction-number distinguishes transaction entities within the same account (and is thus the discriminator). • So the primary key for transaction would be (account-number, transaction-number Objectives: Q1 Choose the correct answer: 1. Key attributes represents: Primary Key 2. ER Model is a: Conceptual: Model 3 Only one entity set is used in: Ternary Q2. Fill in the blanks: 1. Mapping is used to show the Association of entities. 2. Weak entity set is associate with Owner entity set. 3. Value of Derived Attribute is determined by Base Attribute. Q3. Stay true or false: 1. Ternary relationship has three entity set: True 2. Weak entity sets may have primary key: False 3. ER Model could be converted in to Relation Model: True Q4. Match the column: 1. Composite Attribute Sub Attribute 2. Multi valued Attribute Many values 3. Binary Relationship Two entity set 4. Weak Entity Owner Entity Chapter= 4 RDBMS & DBMS The tables in the following sections provide a functional summary of SQL statements and are divided into these categories: • Data Definition Language (DDL) Statements • Data Manipulation Language (DML) Statements • Transaction Control Statements • Session Control Statements • System Control Statement • Embedded SQL Statements 1. Data Definition Language (DDL) Statements Data definition language (DDL) statements let you to perform these tasks: • Create, alter, and drop schema objects • Grant and revoke privileges and roles • Analyze information on a table, index, or cluster • Establish auditing options • Add comments to the data dictionary The CREATE; ALTER, and DROP commands require exclusive access to the specified object. For example, an ALTER TABLE statement fails if another user has an open transaction on the specified table. The GRANT, REVOKE, ANALYZE, AUDIT, and COMMENT commands do not require exclusive access to the specified object. For example, you can analyze a table while other users are updating the table. Oracle Database implicitly commits the current transaction before and after every DDL statement. Many DDL statements may cause Oracle Database to recompile or reauthorize schema objects. For information on how Oracle Database recompiles and reauthorizes schema objects and the circumstances under which a DDL statement would cause this, see Oracle Database Concepts. DDL statements are supported by PL/SQL with the use of the DBMS_SQL package. 2.Data Manipulation Language (DML) Statements Data manipulation language (DML) statements access and manipulate data in existing schema objects. These statements do not implicitly commit the current transaction. The data manipulation language statements are: CALL DELETE EXPLAIN PLAN INSERT LOCK TABLE MERGE SELECT UPDATE The SELECT statement is a limited form of DML statement in that it can only access data in the database. It cannot manipulate data in the database, although it can operate on the accessed data before returning the results of the query. 3.Transaction Control Statements Transaction control statements manage changes made by DML statements. The transaction control statements are: COMMIT ROLLBACK SAVEPOINT SET TRANSACTION All transaction control statements, except certain forms of the COMMIT and ROLLBACK commands, are supported in PL/SQL. For information on the restrictions, see COMMIT and ROLLBACK . 4.Session Control Statements Session control statements dynamically manage the properties of a user session. These statements do not implicitly commit the current transaction. PL/SQL does not support session control statements. The session control statements are: 1. ALTER SESSION 2. SET ROLE 5.System Control Statement The single system control statement, ALTER SYSTEM, dynamically manages the properties of an Oracle Database instance. This statement does not implicitly commit the current transaction and is not supported in PL/SQL. 6.Embedded SQL Statements Embedded SQL statements place DDL, DML, and transaction control statements within a procedural language program. Embedded SQL is supported by the Oracle recompiles and is documented in the following books: • Pro*COBOL Programmer~s Guide • Pro*C/C++ Programmer~s Guide • Oracle SQL*Module for Ad a Programmer~s Guide Embedded SQL statements are: OPEN CLOSE DECLARE CONNECT FET Objectives: Ques: 1 Choose the correct answer: 1. SQl is a standard language by- Ans- ANSI 2. PL/SQL commands by- Ans-Embedded SQL 3. Alter modifies Ans-Table Structure Q2. Fill in the blanks: 1. DDL Commands are specially made for database objects. 2. All operations are cancelled by ROLLBACK commands. 3. DML statements are used for data. Q3. STAY TRUR OR FALSE:: 1. COMMIT is used to save all operations-(TRUE) 2. Session control statements are not supported in PL/SQL (TRUE) 3. DROP command is used to drop a column-(FALSE) Q4. MATCH the column: 1. GRANT DDL 2. MERGE DML 3. SAVEPOINT TCS 4. DECLARE Embedded .Meta data- Meta data are ‘data about data’ of any sort in any media. An item of metadata may describe an individual datum, or content item, or content item, or a collection of data including multiple content items. The word Meta comes from the Greek, where it means ‘after’ or ‘beyond’. Metadata are used facilitate the understanding, characteristics, use and management of data. .Data Dictionary- A data structure which stores meta-data is called Data dictionary. Usually it means a table in a data base that stores the names, fields, types, length, and other Characteristics of the field in the database tables. An active data dictionary is automatically updated as changes occur in the database. A passive data dictionary must be annually updated. The data dictionary is a more general software utility used by designers, users, and administrator for information recourses management. The data dictionary may maintain information on system hardware, software, documentation, users and other aspects . .Data Warehouse- Abbreviated DW, a collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. Development of a data warehouse includes development of systems to extract data from operating systems plus installation of a warehouse database system that provides managers flexible access to the data. The term data warehousing generally refers to the combination of many different databases across an entire enterprise. Contrast with data mart. .Data Mining- Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. The three major data mining techniques are:- • Classes: Stored data is used to locate data in predetermined groups. For example, a restaurant chain could mine customer purchase data to determine when customers visit and what they typically order. This information could be used to increase traffic by having daily specials. • Clusters: Data items are grouped according to logical relationships or consumer preferences. For example, data can be mined to identify market segments or consumer affinities. • Sequential patterns: Data is mined to anticipate behavior patterns and trends. For example, an outdoor equipment retailer could predict the likelihood of a backpack being purchased based on a consumer~s purchase of sleeping bags and hiking shoes

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