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Author: Vivian Siahaan
Publisher: SPARTA PUBLISHING
ISBN:
Category : Computers
Languages : en
Pages : 527
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Book Description
The lessons in this book are a highly organized and well-indexed set of tutorials meant for students and programmers. Netbeans, a specific IDE (Integrated Development Environment) is used to create GUI (Graphical User Interface applications).The finished product is the reward, but the readers are fully engaged and enriched by the process. This kind of learning is often the focus of training. In this book, you will learn how to build from scratch a SQLite database management system using Java. In designing a GUI and as an IDE, you will make use of the NetBeans tool. Gradually and step by step, you will be taught how to use SQLite in Java. In chapter one, you will learn: How to create SQLite database and six tables In chapter two, you will study: Creating the initial three table projects in the school database: Teacher table, TClass table, and Subject table; Creating database configuration files; Creating a Java GUI for viewing and navigating the contents of each table; Creating a Java GUI for inserting and editing tables; and Creating a Java GUI to join and query the three tables. In chapter three, you will learn: Creating the main form to connect all forms; Creating a project will add three more tables to the school database: the Student table, the Parent table, and Tuition table; Creating a Java GUI to view and navigate the contents of each table; Creating a Java GUI for editing, inserting, and deleting records in each table; Creating a Java GUI to join and query the three tables and all six tables. In chapter four, you will study how to query the six tables. In chapter five, you will create Bank database and its four tables. In chapter six, you will learn the basics of cryptography using Java. Here, you will learn how to write a Java program to count Hash, MAC (Message Authentication Code), store keys in a KeyStore, generate PrivateKey and PublicKey, encrypt / decrypt data, and generate and verify digital prints. In chapter seven, you will learn how to create and store salt passwords and verify them. You will create a Login table. In this case, you will see how to create a Java GUI using NetBeans to implement it. In addition to the Login table, in this chapter you will also create a Client table. In the case of the Client table, you will learn how to generate and save public and private keys into a database. You will also learn how to encrypt / decrypt data and save the results into a database. In chapter eight, you will create an Account table. This account table has the following ten fields: account_id (primary key), client_id (primarykey), account_number, account_date, account_type, plain_balance, cipher_balance, decipher_balance, digital_signature, and signature_verification. In this case, you will learn how to implement generating and verifying digital prints and storing the results into a database. In chapter nine, you will create a Client_Data table, which has the following seven fields: client_data_id (primary key), account_id (primary_key), birth_date, address, mother_name, telephone, and photo_path. In chapter ten, you will create Crime database and its six tables. In chapter eleven, you will be taught how to extract image features, utilizing BufferedImage class, in Java GUI. In chapter twelve, you will be taught to create Java GUI to view, edit, insert, and delete Suspect table data. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. In chapter thirteen, you will be taught to create Java GUI to view, edit, insert, and delete Feature_Extraction table data. This table has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. All six fields (except keys) will have a BLOB data type, so that the image of the feature will be directly saved into this table. In chapter fourteen, you will add two tables: Police_Station and Investigator. These two tables will later be joined to Suspect table through another table, File_Case, which will be built in the seventh chapter. The Police_Station has six columns: police_station_id (primary key), location, city, province, telephone, and photo. The Investigator has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. Here, you will design a Java GUI to display, edit, fill, and delete data in both tables. In chapter fifteen, you will add two tables: Victim and File_Case. The File_Case table will connect four other tables: Suspect, Police_Station, Investigator and Victim. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The File_Case has seven columns: file_case_id (primary key), suspect_id (foreign key), police_station_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. Here, you will also design a Java GUI to display, edit, fill, and delete data in both tables.
Author: Vivian Siahaan
Publisher: SPARTA PUBLISHING
ISBN:
Category : Computers
Languages : en
Pages : 527
Get Book Here
Book Description
The lessons in this book are a highly organized and well-indexed set of tutorials meant for students and programmers. Netbeans, a specific IDE (Integrated Development Environment) is used to create GUI (Graphical User Interface applications).The finished product is the reward, but the readers are fully engaged and enriched by the process. This kind of learning is often the focus of training. In this book, you will learn how to build from scratch a SQLite database management system using Java. In designing a GUI and as an IDE, you will make use of the NetBeans tool. Gradually and step by step, you will be taught how to use SQLite in Java. In chapter one, you will learn: How to create SQLite database and six tables In chapter two, you will study: Creating the initial three table projects in the school database: Teacher table, TClass table, and Subject table; Creating database configuration files; Creating a Java GUI for viewing and navigating the contents of each table; Creating a Java GUI for inserting and editing tables; and Creating a Java GUI to join and query the three tables. In chapter three, you will learn: Creating the main form to connect all forms; Creating a project will add three more tables to the school database: the Student table, the Parent table, and Tuition table; Creating a Java GUI to view and navigate the contents of each table; Creating a Java GUI for editing, inserting, and deleting records in each table; Creating a Java GUI to join and query the three tables and all six tables. In chapter four, you will study how to query the six tables. In chapter five, you will create Bank database and its four tables. In chapter six, you will learn the basics of cryptography using Java. Here, you will learn how to write a Java program to count Hash, MAC (Message Authentication Code), store keys in a KeyStore, generate PrivateKey and PublicKey, encrypt / decrypt data, and generate and verify digital prints. In chapter seven, you will learn how to create and store salt passwords and verify them. You will create a Login table. In this case, you will see how to create a Java GUI using NetBeans to implement it. In addition to the Login table, in this chapter you will also create a Client table. In the case of the Client table, you will learn how to generate and save public and private keys into a database. You will also learn how to encrypt / decrypt data and save the results into a database. In chapter eight, you will create an Account table. This account table has the following ten fields: account_id (primary key), client_id (primarykey), account_number, account_date, account_type, plain_balance, cipher_balance, decipher_balance, digital_signature, and signature_verification. In this case, you will learn how to implement generating and verifying digital prints and storing the results into a database. In chapter nine, you will create a Client_Data table, which has the following seven fields: client_data_id (primary key), account_id (primary_key), birth_date, address, mother_name, telephone, and photo_path. In chapter ten, you will create Crime database and its six tables. In chapter eleven, you will be taught how to extract image features, utilizing BufferedImage class, in Java GUI. In chapter twelve, you will be taught to create Java GUI to view, edit, insert, and delete Suspect table data. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. In chapter thirteen, you will be taught to create Java GUI to view, edit, insert, and delete Feature_Extraction table data. This table has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. All six fields (except keys) will have a BLOB data type, so that the image of the feature will be directly saved into this table. In chapter fourteen, you will add two tables: Police_Station and Investigator. These two tables will later be joined to Suspect table through another table, File_Case, which will be built in the seventh chapter. The Police_Station has six columns: police_station_id (primary key), location, city, province, telephone, and photo. The Investigator has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. Here, you will design a Java GUI to display, edit, fill, and delete data in both tables. In chapter fifteen, you will add two tables: Victim and File_Case. The File_Case table will connect four other tables: Suspect, Police_Station, Investigator and Victim. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The File_Case has seven columns: file_case_id (primary key), suspect_id (foreign key), police_station_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. Here, you will also design a Java GUI to display, edit, fill, and delete data in both tables.
Author: Vivian Siahaan
Publisher: SPARTA PUBLISHING
ISBN:
Category : Computers
Languages : en
Pages : 539
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Book Description
This book is SQLite-based python programming for database-driven desktop projects. Deliberately designed for various levels of programming skill, this book is suitable for students, engineers, and even researchers in various disciplines. There is no need for advanced programming experience, and school-level programming skills are needed. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six, you will create dan configure database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter seven, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have VARBINARY(MAX) data type. You will also create GUI to display, edit, insert, and delete for this table. In chapter eight, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In the last chapter, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.
Author: Vivian Siahaan
Publisher: SPARTA PUBLISHING
ISBN:
Category : Computers
Languages : en
Pages : 333
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Book Description
In this book, you will learn how to build from scratch a criminal records management database system using Java / SQLite. All Java code for digital image processing in this book is Native Java. Intentionally not to rely on external libraries, so that readers know in detail the process of extracting digital images from scratch in Java. In the first chapter, you will be shown how to create SQLite database and tables with Java. In second chapter, you will be taught how to extract image features, utilizing BufferedImage class, in Java GUI. Digital image techniques to extract image features used in this chapted are grascaling, sharpening, invertering, blurring, dilation, erosion, closing, opening, vertical prewitt, horizontal prewitt, Laplacian, horizontal sobel, and vertical sobel. For readers, you can develop it to store other advanced image features based on descriptors such as SIFT and others for developing descriptor based matching. In the third chapter, you will be taught to create Java GUI to view, edit, insert, and delete Suspect table data. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. In the fourth chapter, you will be taught to create Java GUI to view, edit, insert, and delete Feature_Extraction table data. This table has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. All six fields (except keys) will have a BLOB data type, so that the image of the feature will be directly saved into this table. In the fifth chapter, you will add two tables: Police_Station and Investigator. These two tables will later be joined to Suspect table through another table, File_Case, which will be built in the seventh chapter. The Police_Station has six columns: police_station_id (primary key), location, city, province, telephone, and photo. The Investigator has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. Here, you will design a Java GUI to display, edit, fill, and delete data in both tables. In the sixth chapter, you will add two tables: Victim and Case_File. The File_Case table will connect four other tables: Suspect, Police_Station, Investigator and Victim. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File has seven columns: case_file_id (primary key), suspect_id (foreign key), police_station_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. Here, you will also design a Java GUI to display, edit, fill, and delete data in both tables. Finally, this book is hopefully useful for you.
Author: Aditya Gupta
Publisher: Packt Publishing Ltd
ISBN: 178328899X
Category : Computers
Languages : en
Pages : 209
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Book Description
This is an easy-to-follow guide, full of hands-on and real-world examples of applications. Each of the vulnerabilities discussed in the book is accompanied with the practical approach to the vulnerability, and the underlying security issue. This book is intended for all those who are looking to get started in Android security or Android application penetration testing. You don’t need to be an Android developer to learn from this book, but it is highly recommended that developers have some experience in order to learn how to create secure applications for Android.
Author: Tomonobu Senjyu
Publisher: Springer Nature
ISBN: 9811641773
Category : Technology & Engineering
Languages : en
Pages : 802
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Book Description
This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Fifth International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2021), held in Ahmedabad, India. The book is divided into two volumes. It discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.
Author: Chet Haase
Publisher: Pearson Education
ISBN: 0132715694
Category : Computers
Languages : en
Pages : 706
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Book Description
Filthy Rich Clients refers to ultra-graphically rich applications that ooze cool. They suck the user in from the outset and hang on to them with a death grip of excitement. Filthy Rich Clients: Developing Animated and Graphical Effects for Desktop JavaTM Applications shows you how to build better, more effective, cooler desktop applications that intensify the user experience. The keys to Filthy Rich Clients are graphical and animated effects. These kinds of effects provide ways of enhancing the user experience of the application through more attractive GUIs, dynamic effects that give your application a pulse, and animated transitions that keep your user connected to the logical flow of the application. The book also discusses how to do so effectively, making sure to enrich applications in sensible ways. In-depth coverage includes Graphics and GUI fundamentals: Dig deep into the internals of how Swing and Java 2D work together to display GUI applications onscreen. Learn how to maximize the flexibility of these libraries and use them most effectively. Performance: Follow in-depth discussions and tips throughout the book that will help you write high-performing GUI applications. Images: Understand how images are created and used to make better Java applications. Advanced graphics: Learn more about elements of Swing and Java 2D that are of particular benefit to Filthy Rich Clients. Animation: Discover general concepts of animation, as well as how to use the facilities provided in the Java platform. Learn new utility libraries that vastly simplify animations in Java. Effects: Learn how to create, customize, and use static and animated effects—the mainstays of Filthy Rich Clients. Code examples illustrate key concepts, and the book’s companion Web site, http://filthyrichclients.org, includes extensive demos, utility libraries, additional information on related technologies, and more. Informal, fun, and, most of all, useful, this book is great for any developer working with Java to build desktop applications.
Author: Grant Allen
Publisher: Apress
ISBN: 1430232269
Category : Computers
Languages : en
Pages : 363
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Book Description
Outside of the world of enterprise computing, there is one database that enables a huge range of software and hardware to flex relational database capabilities, without the baggage and cost of traditional database management systems. That database is SQLite—an embeddable database with an amazingly small footprint, yet able to handle databases of enormous size. SQLite comes equipped with an array of powerful features available through a host of programming and development environments. It is supported by languages such as C, Java, Perl, PHP, Python, Ruby, TCL, and more. The Definitive Guide to SQLite, Second Edition is devoted to complete coverage of the latest version of this powerful database. It offers a thorough overview of SQLite’s capabilities and APIs. The book also uses SQLite as the basis for helping newcomers make their first foray into database development. In only a short time you can be writing programs as diverse as a server-side browser plug-in or the next great iPhone or Android application! Learn about SQLite extensions for C, Java, Perl, PHP, Python, Ruby, and Tcl. Get solid coverage of SQLite internals. Explore developing iOS (iPhone) and Android applications with SQLite. SQLite is the solution chosen for thousands of products around the world, from mobile phones and GPS devices to set-top boxes and web browsers. You almost certainly use SQLite every day without even realizing it!
Author: Jay Kreibich
Publisher: "O'Reilly Media, Inc."
ISBN: 0596521189
Category : Computers
Languages : en
Pages : 526
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Book Description
Explains how to build database-backed applications for the Web, desktop, embedded systems, and operating systems using SQLite.
Author: Mayur Ramgir
Publisher: Packt Publishing Ltd
ISBN: 1787122301
Category : Computers
Languages : en
Pages : 391
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Book Description
Best practices to adapt and bottlenecks to avoid About This Book Tackle all kinds of performance-related issues and streamline your development Master the new features and new APIs of Java 9 to implement highly efficient and reliable codes Gain an in-depth knowledge of Java application performance and obtain best results from performance testing Who This Book Is For This book is for Java developers who would like to build reliable and high-performance applications. Prior Java programming knowledge is assumed. What You Will Learn Work with JIT compilers Understand the usage of profiling tools Generate JSON with code examples Leverage the command-line tools to speed up application development Build microservices in Java 9 Explore the use of APIs to improve application code Speed up your application with reactive programming and concurrency In Detail Finally, a book that focuses on the practicalities rather than theory of Java application performance tuning. This book will be your one-stop guide to optimize the performance of your Java applications. We will begin by understanding the new features and APIs of Java 9. You will then be taught the practicalities of Java application performance tuning, how to make the best use of garbage collector, and find out how to optimize code with microbenchmarking. Moving ahead, you will be introduced to multithreading and learning about concurrent programming with Java 9 to build highly concurrent and efficient applications. You will learn how to fine tune your Java code for best results. You will discover techniques on how to benchmark performance and reduce various bottlenecks in your applications. We'll also cover best practices of Java programming that will help you improve the quality of your codebase. By the end of the book, you will be armed with the knowledge to build and deploy efficient, scalable, and concurrent applications in Java. Style and approach This step-by-step guide provides real-world examples to give you a hands-on experience.
Author: Vivian Siahaan
Publisher: BALIGE PUBLISHING
ISBN:
Category : Computers
Languages : en
Pages : 286
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Book Description
In this comprehensive project, "COVID-19: Analysis, Classification, and Detection Using Scikit-Learn, Keras, and TensorFlow with Python GUI," the primary objective is to leverage various machine learning and deep learning techniques to analyze and classify COVID-19 cases based on numerical data and medical image data. The project begins by exploring the dataset, gaining insights into its structure and content. This initial data exploration aids in understanding the distribution of categorized features, providing valuable context for subsequent analysis. With insights gained from data exploration, the project delves into predictive modeling using machine learning. It employs Scikit-Learn to build and fine-tune predictive models, harnessing grid search for hyperparameter optimization. This meticulous process ensures that the machine learning models, such as Naïve Bayes, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Extreme Gradient Boosting, Multi-Layer Perceptron, AdaBoost, and Logistic Regression, are optimized to accurately predict the risk of COVID-19 based on the input features. Transitioning to the realm of deep learning, the project employs Convolutional Neural Networks (CNNs) to perform intricate image classification tasks. Leveraging Keras and TensorFlow, the CNN architecture is meticulously crafted, comprising convolutional and pooling layers, dropout regularization, and dense layers. The project also extends its deep learning capabilities by utilizing the VGG16 pre-trained model, harnessing its powerful feature extraction capabilities for COVID-19 image classification. To gauge the effectiveness of the trained models, an array of performance metrics is utilized. In this project, a range of metrics are used to evaluate the performance of machine learning and deep learning models employed for COVID-19 classification. These metrics include Accuracy, which measures the overall correctness of predictions; Precision, emphasizing the accuracy of positive predictions; Recall (Sensitivity), assessing the model's ability to identify positive instances; and F1-Score, a balanced measure of accuracy. The Mean Squared Error (MSE) quantifies the magnitude of errors in regression tasks, while the Confusion Matrix summarizes classification results by showing counts of true positives, true negatives, false positives, and false negatives. These metrics together provide a comprehensive understanding of model performance. They help gauge the model's accuracy, the balance between precision and recall, and its proficiency in classifying both positive and negative instances. In the medical context of COVID-19 classification, these metrics play a vital role in evaluating the models' reliability and effectiveness in real-world applications. The project further enriches its analytical capabilities by developing an interactive Python GUI. This graphical user interface streamlines the user experience, facilitating data input, model training, and prediction. Users are empowered to input medical images for classification, leveraging the trained machine learning and deep learning models to assess COVID-19 risk. The culmination of the project lies in the accurate prediction of COVID-19 risk through a combined approach of machine learning and deep learning techniques. The Python GUI using PyQt5 provides a user-friendly platform for clinicians and researchers to interact with the models, fostering informed decision-making based on reliable and data-driven predictions. In conclusion, this project represents a comprehensive endeavor to harness the power of machine learning and deep learning for the vital task of COVID-19 classification. Through rigorous data exploration, model training, and performance evaluation, the project yields a robust framework for risk prediction, contributing to the broader efforts to combat the ongoing pandemic.
