Where are artificial neural networks applied?

The artificial neural networks have been applied to a number of problems in diverse fields such as engineering, finance, medical, physics, medicine, and biology and so on. 

- All these applications are based on the fact that these neural networks can simulate the human brain capabilities. 

- They have found a potential use in classification and prediction problems. 

- These networks can be classified under the non-linear data driven self adaptive approaches. 

- They come handy as a powerful tool when the underlying data relationship is not known. 

- They find it easy to recognize and learn the patterns and can correlate between the input sets and the result values.

- Once the artificial neural networks have been trained, they can be used in the prediction of the outcomes of the data. 

- They can even work when the data is not clear i.e., when it is noisy and imprecise. 

- This is the reason why they prove to be an ideal tool for modeling the agricultural data which is often very complex. 

- Their adaptive nature is their most important feature.

- It is because of this feature that the models developed using ANN is quite appealing when the data is available but there is a lack of understanding of the problem.

- These networks are particularly useful in those areas where the statistical methods can be employed. 

- They have uses in various fields:

    1. Classification Problems:

a)   Identification of underwater sonar currents.

b)   Speech recognition

c)   Prediction of the secondary structure of proteins.

d)   Remote sensing

e)   Image classification

f)    Speech synthesis

g)   ECG/ EMG/ EEG classification

h)   Data mining

i)     Information retrieval

j)    Credit card application screening

2. Time series applications:

a)   Prediction of stock market performance

b)   ARIMA time – series models

c)   Machine robot/ control manipulation

d)   Financial, engineering and scientific time series forecasting

e)   Inverse modeling of vocal tract

3. Statistical Applications:

a)   Discriminant analysis

b)   Logistic regression

c)   Bayes analysis

d)   Multiple regression

4. Optimization:

a)   Multiprocessor scheduling

b)   Task assignment

c)   VLSI routing

5. Real world Applications:

a)   Credit scoring

b)   Precision direct mailing

6. Business Applications:

a)   Real estate appraisal

b)   Credit scoring: It is used for determining the approval of a load as per the applicant’s information.

c)   Inputs

d)   Outputs

7. Mining Applications

a)   Geo-chemical modeling using neural pattern recognition technology.

8. Medical Applications:

a) Hospital patient stay length prediction system: the CRTS/ QURI system was developed using a neural network for predicting the number of days a patient has to stay in hospital. The major benefit of this system was that money was saved and better patient care. This system required the following 7 inputs:

Ø  Diagnosis

Ø  Complications and comorbidity

Ø  Body systems involved

Ø  Procedure codes and relationships

Ø  General health indicators

Ø  Patient demographics

Ø  Admission category

9. Management Applications: Jury summoning prediction: a system was developed that could predict the number of jurors that were actually required. Two inputs were supplied: the type of case and judge number. The system is known to have saved around 70 million.
10. Marketing Application: A neural network was developed for improving the direct mailing response rate. This network selected those individuals who were likely to respond to the 2^nd mailing. 9 variables were given as the input. It saved around 35 % of the total mailing cost.
11. Energy cost prediction: A neural network was developed that could predict the price of natural gas for the next month. It achieved an accuracy of 97%. 

What is virtual user script? Why do you need to parametrize fields in your virtual user script?

Nowadays, the concept of the virtual user is quite common in the field of load testing. 

What is a Virtual User?

- Virtual user is one of the quite useful tools have been ever invented in the field of software engineering. 

- Virtual users can be used in a number of ways for testing load, stress or capacity of any software system or application you want. 

- It will be the easiest to define a virtual user as a virtualized representation of a real world user which has been specifically designed for simulating the same interactions and behaviors with the software system or application or web site to be tested in a way that a real world user would do exactly. 

Let us take an example, suppose at a peak your web site got 100 users over a particular hour. It becomes quite easy for you to simulate the same behavior using 100 virtual users making use of the scripts that invoke quite similar interaction and the navigation exactly as your real users do. Today such virtual users are also available that can playback the recorded scripts. 

In this article we discuss about what a virtual user script is and what is the need for parameterizing the fields in a virtual user script.  

What is a Virtual User Script & Need to Parametrize fields?

The fact that almost all of the scripts of the virtual user are automated is quite common. 

- For each and every automated script a particular entry point is marked by the script statement in virtual user. 

- From this point, the actions of the automated scripts are much similar to that of the real world users. 

- At any point these virtual user scripts can be made to click on any of the buttons or the windows, type some words, and move the mouse around and so on.

- Not only scripts, there are certain functions that are supported well by the virtual user and these functions can act as an extension to the virtual user scripts. 

- These functions have been given a general name called “tasks”. 

- These tasks consist of a procedure along with a list of parameters and in some cases they may also include an optional return value. 

- The information regarding the environment of the target computer is also collected by the virtual user with help of a statement called the match statement. 

- A specific environment element is searched by this match statement with the help of some descriptor traits like the following:

1. Static text
2. Edit text
3. Pictures
4. Icons
5. User items and so on.

- There is one more kind of statement that is used and is called the collect statement.

- It is used to collect all elements of a certain type in to the list.

- Afterwards the virtual user interacts with the software system or application environment using certain keywords like:

1. Select
2. Drag
3. Type
4. Close
5. Click and so on.

- Common objects of the operating system like windows, buttons, bars, menus and scrolls are accessed by the virtual users. 

- The virtual user software package comes with a log file feature using which one can write out all the information from within a script. 

- This feature also provides the scripter with information regarding the current run time state of the virtual user scripts. 

- These virtual user scripts can also be debugged whenever required by logging with the printh statement. 

Another fact about virtual user is that there exists no type checking which serves as a very good idea to log the parameters that serve as input to every task.

What are different characteristics of Capability Maturity Model (CMM)?

Capability maturity model or CMM as it is often abbreviated. It is a development model developed after a prolonged study of the data collected from various organizations from all over the world.

Characteristics of Capability Maturity Model
1.The development of this model was funded by the USDD (United States department of defence).

2.The capability maturity model became the foundation for the development of software engineering institute or SEI as it is popularly known as.

3.The term “maturity” emphasises process optimization and level of formality.

4.Processes are optimized from ad-hoc practices to steps that have been formally defined.

5.Nowadays this model is being used effectively for management of result metrics.

6.Capability maturity model has proved to be great help in active optimization of the processes.

7.This model allows improvement in the development processes of an organization.

8.It is an effective and good approach towards improvement of any organization’s development processes.

9.This model is securely based upon the frame work of process maturity which was developed in 1989.

10.Initially it was used for objective assessment of the processes carried out by the contractors of the government to keep a track on the project.

11.CMM is not only used in the field of software engineering but, it is also applied to organizational processes of a business.

12.It is used in other fields like:
- Software development
- System engineering
- Software maintenance
- Project management
- System acquisition
- Risk management
- Information technology
- Human capital management and
- Services

Where is Capability Maturity Model used?

Capability maturity model is being extensively used in various organizations like in commerce, government offices, software development organizations and industry.

What was the need for Capability Maturity Model?
- In the 20th century the use of computers was wide spread.

- Computerized processes were thought to be less costly, effective and flexible way to carry out tasks.

- As more and more organizations started adopting computerized processing systems, the demand for software development eventually rose.

- As a result CMM was developed, of course with lots of failures.

- The computers were a new technology at that time and so there was a lot of pressure on developers to deliver quality products within a stipulated period of time.

- The US military was in havoc that because all their projects were running out of budget and time.

- So in order to know the reason behind all this, they funded the study at SEI. Active study started at SEI.

- It was watts Humphrey who actually came up with the actual idea of CMM.

- He based his approach on the evolution of software development practices.

- He concentrated on all the processes as one instead of concentrating on just one software development process.

- Since then the CMM has become popular among various organizations and is used as a powerful tool for improving overall performance of the business.

Though CMM proved to be a very effective tool for business but many times it caused problems in software development.

- CMM didn’t allow use of multiple software development practices. It was superseded by CMMI.

- These days still the capability maturity model is being used as the model with the capability of handling general processes when it comes to public domain.

Some Important Facts About CMM
1.CMM is still maintaining its position as a model of maturity of process.

2.CMM provides a place to start the development.

3.It uses a common language and the development is based upon a shared vision.

4.It effectively develops a frame work for actions according to their priority.

5.For an organization it defines the ways for improvement.

6.It is used an aid for better and effective understanding.

CMM has 5 aspects:
- Maturity level
- Key process area
- Goal
- Features
- Practices.

Introduction to Integration testing? What are approaches used in integration testing?

Unit testing is useful to test the modules individually. Problem arises when these modules are put together, which is also called interfacing. There is a huge chance that data is lost across an interface or one module can affect the functionality of the other module or global data structures can present problems.

Integration testing is a technique that is used for constructing software architecture while at the same time conducting tests to uncover errors that arise because of interfacing. There are two approaches to integration testing :

- Taking the big bang approach (all components are combined in advance and then testing is done) to integration is a lazy strategy that is bound to fail. One should integrate in an increment manner and do testing as you go. In big bang approach, cause of fail is not easily tracked and hence the complexity increases.

- Incremental approach can be started early and controlled easily. Incremental testing is usually better for large, complex systems. Two related modules are combined and tested and check whether they are working in the correct manner. Then, another module is added and checked.

Integration testing follows unit testing and precedes system testing. It helps in verifying functional, performance and reliability requirements. Reasons for integration testing includes:
- Fields are defined differently in different modules.
- Different perceptions and understanding of business requirements.
- Field content can have different assumptions.
- There are few errors that can be left uncovered during unit testing.