1. Java Project Guidance for engineering

Java Project Guidance
Trainer
Rakesh Asileti

Index
• Basics of Java
• Real- Time Applications of Java
• Base Paper Explanation
• Example Project
• Execution Process

BASICS OF JAVA
• Java was developed by James Gosling at Sun Microsystems. It was first released in
1995.
How James Gosling Started Java Programming?
• One day a Project came to James Gosling that he has to install a software in Electronic
devices and it has to be operated with Remote.
• C and C++ languages are platform dependent, then he decided to do this project with
an Extension of Older languages and it should be a platform Independent. Then he
started working on JAVA.

WHAT IS JAVA
• Java is a High level, Object Oriented and Platform Independent Programming language
Platform Independent : Java compilers compiles source code into byte code which is independent on the
systems platform
JAVA APPLICATIONS :
• Standalone applications – desktop applications/window based applications.
• Web applications – server sider
• Enterprise applications – banking
• Mobile applications – android , games
• Business applications
• Artificial Intelligence
• Embedded Systems

Real- time Applications of Java

Desktop GUI Applications
• Java language provides a lot of features that help us to develop GUI
applications. Java provides AWT, Swing API or Java Foundation Classes,
or the latest JavaFX (from Java 8 onwards). These APIs/features help us
develop advanced GUI applications including advanced tree-based or even
3D graphical applications.
Real-world desktop tools developed using Java:
• Acrobat Reader
• ThinkFree

Web Applications
• Java provides features for web development as well as Servlets, Struts,
Spring, hibernate, JSPs, etc. that allow us to develop highly secured easily
program software.
Real-world Web tools developed using Java:
• Amazon
• Broadleaf
• Wayfair

Mobile Applications
• Java language provides a feature named J2ME which is a cross-platform framework to
build mobile applications that can run across Java-supported smartphones and feature
phones.
• One of the popular mobile operating systems Android is developed using Java-based
Android SDK.
Popular Java-based mobile apps:
• Netflix Tinder
• Google Earth Uber

Enterprise Applications
• Java language has the Java Enterprise Edition (Java EE) platform that comes with API
and runtime environment features for scripting and running enterprise software,
network tools, and web services.
• According to Oracle, almost 97% of enterprise computers are running on Java. The
higher performance and faster computing provided by Java have resulted in most
enterprise applications being developed in Java.
Real-time Enterprise Applications using Java:
• Enterprise Resource Planning (ERP) systems
• Customer Resource Management (CRM) systems

Scientific Applications
• Java has powerful security and robustness features that make it popular for
developing scientific applications. Java also provides powerful
mathematical calculations that give the same results on different platforms.
Most popular Java-based scientific tool:
• Mat lab

Web Servers & Applications Servers
• The entire Java ecosystem has numerous applications and web servers as
of today. Among web servers, we have Apache Tomcat, Project Jigsaw,
Rimfaxe Web Server (RWS), Jo! Etc. dominates the space.
• Similarly, application servers like WebSphere, JBoss, WebLogic, etc. are
dominating the industry commercially.

Embedded Systems
• Embedded systems are low-level systems that form a part of the larger
electromechanical systems. These are tiny chips, processors, etc., and are
also called integrated systems.
• Java can produce robust tools that can handle application exceptions
efficiently and are fast too as it is better for developing low-level programs.
Embedded systems applications using Java:
• SIM cards use Java technology
• Blue-ray disc player

Software Tools
• Many software tools used for development are written in Java. For
example, IDEs like Eclipse, IntelliJ IDEA, and Net beans are all written
and developed in Java.
• These are also the most popular desktop GUI-based tools used today.
Earlier swing and AWT were the features that are mostly used to develop
Software but nowadays JavaFx has become more popular.

Trading Applications & J2ME Apps
• The popular trading application Murex, which is used in many banks for
front-to-bank connectivity, is written in Java.
J2ME Apps
• Apart from iOS and android based mobile handsets, there are handsets
from Nokia and Samsung that use J2ME. J2ME is also popular with
products like Blu-ray, Cards, Set-Top Boxes, etc. The popular application
WhatsApp available on Nokia is available in J2ME.

Big Data Technologies
• Big data is the most popular and trending topic in the software industry today. Big data
deals with analyzing and systematically extracting information from complex data sets.
• An open framework that is associated with Big data is called Hadoop and is entirely
written in Java. With features like automatic garbage collection, memory distribution,
and stack provision system, Java gets an edge over other technologies. We can safely
say that Java is the future of Big data.
Real-time Java-based Big data Technologies:
• Hadoop
• Apache HBase
• ElasticSearch
• Accumulo

Real- time Applications of Java- Conclusion

Essentials of Java
• JDK(JAVA DEVELOPMENT KIT) : The JDK is a development environment for building applications ,
applets and components using the java programming language. The JDK includes tools useful for developing
and testing programs written in java programming language and running on the java platform.
• JDK components : javac, jdb, rmic, jar, servlet runner.
• JRE(JAVA RUNTIME ENVIRONMENT) : The JRE is a software that java programs require to run
correctly. Java is a computer language that powers many current web and mobile applications.
• JVM(JAVA VIRTUAL MACHINE) : The compiler is used to compile the code which means The
compiler converts high level language to byte code . Here the job of JVM is to read this byte code and
converts into machine level language.
• JVM is an interpreter for byte code.
• JIT COMPILER : It is used to improve the performance. JIT compiles parts of the byte code that have
similar functionality at the same time and hence reduces the amount of time needed for compilation.

Java Features
• Simple
• Secured
• Portable
• Object Oriented
• Robust
• Multi Threaded
• Platform Independent
• Interpreted
• High Performance
• Distributed

Java Features
• Simple : Java is very easy to learn and its syntax is simple clean and easy to understand.
• Secured : Java is secured. It supports firewalls.
• Portable : Java is portable because it facilitates due to carry the java byte code to any platform.
• Object Oriented : Everything in java is an object. Object oriented means we organize our software as a
combination of different types of an objects that incorporates both data and behaviors.
• Robust : Java is strong because it is allowing exception handling and memory management(through
garbage collection.)
• Multi Threaded : A thread is like a separate program executing concurrently

Java Features
• Platform Independent : Java is platform independent because there is no
implementation of dependent features.
• Interpreted : Java compiler translates source code into byte code instructions. Then
java interpreter generates machine code that can be directly executed by the machine
that is run in java code.
• High Performance : Introducing JIT compiler.
• Distributed : Java is distributed because of facilitates as to create distributed applications
in java.

Java Editions
• Java SE(Standard Edition)
• Java EE(Enterprise Editions)
• Java ME(Micro Edition)
• JAVA SE : The SE stands for Java Standard Edition is a computing platform in which
we can execute software, and it can be used for development and deployment of
portable code for desktop and server environments. It has the Java programming
language in use. It is part of Java software-platform family.
• The following are the few APIs which Java SE has –
Applet,AWT,JDBC,Swing,Collections.

Java Editions
• JAVA EE : The Java EE stands for Java Enterprise Edition, which was earlier known as
J2EE and is currently known as Jakarta EE. It is a set of specifications wrapping around
Java SE (Standard Edition). The Java EE provides a platform for developers with
enterprise features such as distributed computing and web services. Java EE applications
are usually run on reference run times such as microservers or application servers.
• Specifications of JAVA EE – Servlet,Web socket,JSON,Java Server Faces.
• JAVA ME : The Java ME stands for Java Micro Edition. It is a development and
deployment platform of portable code for embedded and mobile devices (sensors,
gateways, mobile phones, printers, TV set-top boxes). It is based on object-oriented Java.
The Java ME has a robust user interface, great security, built-in network protocols, and
support for applications that can be downloaded dynamically

Base Paper
• Abstract
• Index Terms
• Introduction
• Literature survey
• Software Environment
• Methodology (Modules)
• System Design (UML Diagrams, Architecture, Class Diagrams)
• Testing
• Conclusion
• References

Abstract
• Educational Data Mining (EDM) is used by an educational organization to enhance the
academic progress of students. For predicting the academic achievement of the
student, EDM comes with many features selection and Machine Learning techniques.
The purpose of using these features selection techniques is to remove the unwanted
elements from the student academic datasets that have not required for performance
prediction. By using feature selection techniques, the quality of students' datasets has
improved, and with it, the predictive accuracy of various data mining techniques has
also enhanced. Taking these facts into consideration analysis of four feature selection
and six classification techniques are implemented on student datasets to check the
predictive accuracy. After the implementation of FS and classification techniques only
CfsSubsetEval, GainRatioAttributeEval feature selection gave improved efficiency up
to 5%.

Existing System
• The given section is a short review of work done in the area of feature
selection algorithm by a different researcher. Many authors used feature
selection (FS) algorithms in combination with classification algorithms to
compare the prediction accuracy of varying student dataset. Some of the
exciting work in this field of EDM has reviewed. Siva Kumar S,
Venkataraman S, et al., "Predictive Modeling of Student Dropout
Indicators in Educational Data Mining using Improved Decision Tree,"
proposed an improved version of decision tree algorithm which will
predict the dropout students. The dataset of 240 students has been
collected by the authors via survey and then applied the correlation-based
feature selection algorithm for preprocessing of the dataset.

Disadvantages of Existing System
• Here, four FS algorithms such as CfsSubsetEval, GainRatioAttributeEval,
InfoGainAttributeEval and ReliefAttributeEval are evaluated.
Classifications algorithms Naive Bayes (NB), Logistic Regression (LR),
DecisionTable (DT), JRip, J48 and Random Forest (RF) has evaluated
through academic algorithms. cfsSubsetEval: Attributes subsets are
evaluated based on both the predictive ability and the degree of
redundancy of each feature.

Proposed System
• The principal purpose of these FS algorithms is to select the most predictive features
from the chosen dataset for analysis and ignore the rest of the attribute, which is non
predictive. It means that non-predictive elements are not affecting the actual result, but
it reduces the complexity of the analysis results. The accuracy and effectiveness of the
student's performance prediction model can have improved with the help of these
feature selection algorithms. These feature selection algorithms can have further
divided into three different groups, namely filter, wrapper and integrated methods.
The filtering methods of feature selection algorithms is one of the primary techniques
which depends on the general characteristics of the learning data and get performed
during the pre-processing phase of the dataset. The Wrapper method is used to
evaluate functions using learning algorithms. Embedded methods are executed during
the classifier's learning process and be more specific to learning algorithms.

Advantages of Proposed System
• The proposed methodology implements Hashing techniques method which is more
fast and reliable method to process the data.
• The proposed system implemented Clustering chain techniques based on Hashing
for improving the system performance.

System Requirements
• Processor - Pentium –IV
• RAM - 4 GB (min)
• Hard Disk - 20 GB
• Key Board - Standard Windows Keyboard
• Mouse - Two or Three Button Mouse
• Monitor - SVGA

Software Requirements
• Operating System - Windows XP
• Coding Language - Java/J2EE(JSP,Servlet)
• Front End - J2EE
• Back End - MySQL

Establishing Database Connection

Conclusion
• Basics of Java
• Real- Time Applications of Java
• Base Paper Explanation
• Example Project
• Execution Process

1. Java Project Guidance for engineering

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