In Tutorial 1, you will start building a Visual C# interface for database management system project with SQL Server. The database, named DBMS, is created. The designed interface in this tutorial will used as the main terminal in accessing other forms. This tutorial will also discuss how to create login form and login table. In Tutorial 2, you will build a project, as part of database management system, where you can store information about valuables in school. In Tutorial 3 up to Tutorial 4, you will perform the steps necessary to add 6 tables into DBMS database. You will build each table and add the associated fields as needed. In this tutorials, you will create a library database project, as part of database management system, where you can store all information about library including author, title, and publisher. In Tutorial 5 up to Tutorial 7, you will perform the steps necessary to add 6 more tables into DBMS database. You will build each table and add the associated fields as needed. In this tutorials, you will create a high school database project, as part of database management system, where you can store all information about school including parent, teacher, student, subject, and, title, and grade.

In chapter one, you will learn to know the properties and events of each control in a Windows Visual C# application. You need to learn and know in order to be more familiar when applying them to some applications in this book. In chapter two, you will go through step by step to build a SALES database using MySQL. You will build each table and add associated data fields (along with the necessary keys and indexes). The first field in the Client table is ClientID. Enter the clien ID in the Name Field and select AutoNumber in the Data Type. You define primary key and other indexes which are useful for quick searching. ClientID is a primary field. You will define FamilyName as an index. You then will create Ordering table with three fields: OrderID, ClientID, and OrderDate. You then will create Purchase table with three fields: OrderID, ProductID, and Quantity. And you will create Product table with four fields: ProductID, Description, Price, and QtySold. Before designing Visual C# interface, you will build the relationships between four tables. The interface will be used to enter new orders into the database. The order form will be used to enter the following information into the database: order ID, order date, client ID, client’s first name and family name, client’s address, product information ordered. The form will have the ability to add new orders, find clients, add new clients. The completed order invoice will be provided in a printed report. In chapter three, you will build a database management system where you can store information about valuables in your warehouse. The table will have seven fields: Item (description of the item), Location (where the item was placed), Shop (where the item was purchased), DatePurchased (when the item was purchased), Cost (how much the item cost), SerialNumber (serial number of the item), PhotoFile (path of the photo file of the item), and Fragile (indicates whether a particular item is fragile or not). The development of this Warehouse Inventory Project will be performed, as usual, in a step-by-step manner. You will first create the database. Furthermore, the interface will be built so that the user can view, edit, add, or add data records from the database. Finally, you add code to create a printable list of information from the database. In chapter four, you will build an application that can be used to track daily high and low pollutant PM2.5 and air quality level. The steps that need to be taken in building Siantar Air Quality Index (SAQI) database project are: Build and test a Visual C# interface; Create an empty database using code; and Report database. The designed interface will allow the user to enter max pollutant, min pollutant, and air quality for any date that the user chooses in a particular year. This information will be stored in a database. Graphical result of the data will be provided, along with summary information relating to the maximum value, minimum value, and mean value. You will use a tab control as the main component of the interface. The control has three tabs: one for viewing and editing data, one for viewing graph of pollutant data, and another for viewing graph of air quality data. Each tab on this control operates like a Visual C# control panel. In chapter five, you will perform the steps necessary to build a MySQL book inventory database that contains 4 tables. You will build each table and add the associated fields as needed. You will have four tables in the database and define the relationship between the primary key and foreign key. You will associate AuthorID (foreign key) field in the Title_Author table with AuthorID (primary key) in the Author table. Then, you want to associate the ISBN (foreign key) field in Title_Author table with ISBN (primary key) in the Title table.

In this book, you will learn how to use OpenCV, NumPy library and other libraries to perform signal processing, image processing, object detection, and feature extraction with Python GUI (PyQt). You will learn how to filter signals, detect edges and segments, and denoise images with PyQt. You will also learn how to detect objects (face, eye, and mouth) using Haar Cascades and how to detect features on images using Harris Corner Detection, Shi-Tomasi Corner Detector, Scale-Invariant Feature Transform (SIFT), and Features from Accelerated Segment Test (FAST). In Chapter 1, you will learn: Tutorial Steps To Create A Simple GUI Application, Tutorial Steps to Use Radio Button, Tutorial Steps to Group Radio Buttons, Tutorial Steps to Use CheckBox Widget, Tutorial Steps to Use Two CheckBox Groups, Tutorial Steps to Understand Signals and Slots, Tutorial Steps to Convert Data Types, Tutorial Steps to Use Spin Box Widget, Tutorial Steps to Use ScrollBar and Slider, Tutorial Steps to Use List Widget, Tutorial Steps to Select Multiple List Items in One List Widget and Display It in Another List Widget, Tutorial Steps to Insert Item into List Widget, Tutorial Steps to Use Operations on Widget List, Tutorial Steps to Use Combo Box, Tutorial Steps to Use Calendar Widget and Date Edit, and Tutorial Steps to Use Table Widget. In Chapter 2, you will learn: Tutorial Steps To Create A Simple Line Graph, Tutorial Steps To Create A Simple Line Graph in Python GUI, Tutorial Steps To Create A Simple Line Graph in Python GUI: Part 2, Tutorial Steps To Create Two or More Graphs in the Same Axis, Tutorial Steps To Create Two Axes in One Canvas, Tutorial Steps To Use Two Widgets, Tutorial Steps To Use Two Widgets, Each of Which Has Two Axes, Tutorial Steps To Use Axes With Certain Opacity Levels, Tutorial Steps To Choose Line Color From Combo Box, Tutorial Steps To Calculate Fast Fourier Transform, Tutorial Steps To Create GUI For FFT, Tutorial Steps To Create GUI For FFT With Some Other Input Signals, Tutorial Steps To Create GUI For Noisy Signal, Tutorial Steps To Create GUI For Noisy Signal Filtering, and Tutorial Steps To Create GUI For Wav Signal Filtering. In Chapter 3, you will learn: Tutorial Steps To Convert RGB Image Into Grayscale, Tutorial Steps To Convert RGB Image Into YUV Image, Tutorial Steps To Convert RGB Image Into HSV Image, Tutorial Steps To Filter Image, Tutorial Steps To Display Image Histogram, Tutorial Steps To Display Filtered Image Histogram, Tutorial Steps To Filter Image With CheckBoxes, Tutorial Steps To Implement Image Thresholding, and Tutorial Steps To Implement Adaptive Image Thresholding. In Chapter 4, you will learn: Tutorial Steps To Generate And Display Noisy Image, Tutorial Steps To Implement Edge Detection On Image, Tutorial Steps To Implement Image Segmentation Using Multiple Thresholding and K-Means Algorithm, and Tutorial Steps To Implement Image Denoising. In Chapter 5, you will learn: Tutorial Steps To Detect Face, Eye, and Mouth Using Haar Cascades, Tutorial Steps To Detect Face Using Haar Cascades with PyQt, Tutorial Steps To Detect Eye, and Mouth Using Haar Cascades with PyQt, and Tutorial Steps To Extract Detected Objects. In Chapter 6, you will learn: Tutorial Steps To Detect Image Features Using Harris Corner Detection, Tutorial Steps To Detect Image Features Using Shi-Tomasi Corner Detection, Tutorial Steps To Detect Features Using Scale-Invariant Feature Transform (SIFT), and Tutorial Steps To Detect Features Using Features from Accelerated Segment Test (FAST). You can download the XML files from https://viviansiahaan.blogspot.com/2023/06/learn-from-scratch-signal-and-image.html.

In chapter one, you will learn to know the properties and events of each control in a Windows Visual C# application. You need to learn and know in order to be more familiar when applying them to some applications in this book. In chapter two, you will build a project so that children can practice basic skills in addition, subtraction, multiplication, and division operations. This Math Game project can be used to choose the types of questions and what factors you want to use. This project has three timing options. Random math problems using values ​​from 0 to 9 will be presented. Timing options are provided to measure accuracy and speed. There are many controls used. Two label controls are used for title information, two for displaying scores. There is a wide label in the middle of the form to display math questions. And, long skinny label is used as separator. Two button controls are used to start and stop question and one button to exit the project. There are three group control boxes. The first group box holds four check box controls that are used to select the type of questions. The second group box holds eleven radio buttons that are used to select values ​​that are used as factors in calculations. The third group box contains three radio button controls for timing options. A scroll bar control rod is used to change the time. In chapter three, you will build Bank Code game. The storage box is locked and can only be opened if you enter the correct digit combination. Combinations can be 2 to 4 non-repetitive digits (range of digits from 1 to 9). After a guess is given, you will be notified of how many digits are right and how many digits are in the right position. Based on this information, you will give another guess. You continue to guess until you get the right combination or until you stop the game. On the left side of the form is a large picture box control. On the right side, two group box controls and two button controls are placed. In the picture box, a control panel is placed. In the panel, there are four label controls (set the AutoSize property to False) and nine button controls. In the first group box control, place three radio buttons. In the second group box control, a text box control is placed. The picture box contains an image of bank and a panel. The label controls in the panel are used to display the combinations entered (the BorderStyle property set to FixedSingle to display the label size). The nine buttons on the panel are used to enter combinations. Radio buttons are used to set options. The buttons (one to start and stop the game and another to exit the project) are used to control game operations. The text box displays the results of the combinations entered. In chapter four, you will build Horse Racing game. This is a simple game. Up to 10 horses will race to the finish line. You guessed two horses that you thought could win the race. By clicking on the Start button, the race will start. All horses will race speed to get to the finish line. Labels are used to display instructions and number of horses in a race. Four button controls are used: two buttons to change number of horses, one button to start the game, and one other button to stop the game. The picture box control is used to load the horse image. A timer control is used to update the horse's movement during the race. In chapter five, you will build Catching Ball game. The bird flew and dropped ball from the sky. Users are challenged to position man under the fallen ball to catch it. Labels are used for instructions and to display game information (remaining time, number of balls captured, and game difficulty level). Two buttons are used to change the game difficulty level, one button to start the game, and another button to stop the game. Picture box controls hold images for man, bird, and ball. In chapter six, you will build Smart Tic Tac Toe game. That said, this is the first game ever programmed on a computer and one that had been programmed by Bill Gates himself when he was a teenager while attending Lakeside School in Seattle. The aim of this game is to win the game on a 3 x 3 grid with the victory of three identical symbols (X or O) on horizontal, diagonal, or vertical lines. The players will play alternately. In this game given two game options: player 1 against player 2 or human player against computer. A smart but simple strategy will be developed for computer logic to be a formidable opponent for humans. In chapter seven, you will build Fighting Plane program. This program can be played by two human players or human player versus computer. The controls of the player are done via the keyboard. Player 1 presses A key to move up, Z key to move down, and S key to throw rudal. When you choose Two players from the Options button, this game can be played by two human players. Player 1 presses the same keys, while player 2 presses key K to move up, M to move down, and key J to throw rudal. All label controls are used for titles and provide scoring and game information. The large panel (Panel1) is the playing field. Three button controls are used to start / stop a program, set options, and exit the program. One timer control is used to control game animation and another is used to represent the computer's decision process. The second control panel (Panel2) is used to select game options. One group box contains radio buttons which are used to select number of players. A group box contains radio buttons to select the level of difficulty of the game, when playing against a computer. A small button is used to close the options panel. The default properties are set for one-player games with the easiest game difficulty.

In this book, you will learn how to use NumPy, Pandas, OpenCV, Scikit-Learn and other libraries to how to plot graph and to process digital image. Then, you will learn how to classify features using Perceptron, Adaline, Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN) models. You will also learn how to extract features using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Kernel Principal Component Analysis (KPCA) algorithms and use them in machine learning. In Chapter 1, you will learn: Tutorial Steps To Create A Simple GUI Application, Tutorial Steps to Use Radio Button, Tutorial Steps to Group Radio Buttons, Tutorial Steps to Use CheckBox Widget, Tutorial Steps to Use Two CheckBox Groups, Tutorial Steps to Understand Signals and Slots, Tutorial Steps to Convert Data Types, Tutorial Steps to Use Spin Box Widget, Tutorial Steps to Use ScrollBar and Slider, Tutorial Steps to Use List Widget, Tutorial Steps to Select Multiple List Items in One List Widget and Display It in Another List Widget, Tutorial Steps to Insert Item into List Widget, Tutorial Steps to Use Operations on Widget List, Tutorial Steps to Use Combo Box, Tutorial Steps to Use Calendar Widget and Date Edit, and Tutorial Steps to Use Table Widget. In Chapter 2, you will learn: Tutorial Steps To Create A Simple Line Graph, Tutorial Steps To Create A Simple Line Graph in Python GUI, Tutorial Steps To Create A Simple Line Graph in Python GUI: Part 2, Tutorial Steps To Create Two or More Graphs in the Same Axis, Tutorial Steps To Create Two Axes in One Canvas, Tutorial Steps To Use Two Widgets, Tutorial Steps To Use Two Widgets, Each of Which Has Two Axes, Tutorial Steps To Use Axes With Certain Opacity Levels, Tutorial Steps To Choose Line Color From Combo Box, Tutorial Steps To Calculate Fast Fourier Transform, Tutorial Steps To Create GUI For FFT, Tutorial Steps To Create GUI For FFT With Some Other Input Signals, Tutorial Steps To Create GUI For Noisy Signal, Tutorial Steps To Create GUI For Noisy Signal Filtering, and Tutorial Steps To Create GUI For Wav Signal Filtering. In Chapter 3, you will learn: Tutorial Steps To Convert RGB Image Into Grayscale, Tutorial Steps To Convert RGB Image Into YUV Image, Tutorial Steps To Convert RGB Image Into HSV Image, Tutorial Steps To Filter Image, Tutorial Steps To Display Image Histogram, Tutorial Steps To Display Filtered Image Histogram, Tutorial Steps To Filter Image With CheckBoxes, Tutorial Steps To Implement Image Thresholding, and Tutorial Steps To Implement Adaptive Image Thresholding. You will also learn: Tutorial Steps To Generate And Display Noisy Image, Tutorial Steps To Implement Edge Detection On Image, Tutorial Steps To Implement Image Segmentation Using Multiple Thresholding and K-Means Algorithm, Tutorial Steps To Implement Image Denoising, Tutorial Steps To Detect Face, Eye, and Mouth Using Haar Cascades, Tutorial Steps To Detect Face Using Haar Cascades with PyQt, Tutorial Steps To Detect Eye, and Mouth Using Haar Cascades with PyQt, Tutorial Steps To Extract Detected Objects, Tutorial Steps To Detect Image Features Using Harris Corner Detection, Tutorial Steps To Detect Image Features Using Shi-Tomasi Corner Detection, Tutorial Steps To Detect Features Using Scale-Invariant Feature Transform (SIFT), and Tutorial Steps To Detect Features Using Features from Accelerated Segment Test (FAST). In Chapter 4, In this tutorial, you will learn how to use Pandas, NumPy and other libraries to perform simple classification using perceptron and Adaline (adaptive linear neuron). The dataset used is Iris dataset directly from the UCI Machine Learning Repository. You will learn: Tutorial Steps To Implement Perceptron, Tutorial Steps To Implement Perceptron with PyQt, Tutorial Steps To Implement Adaline (ADAptive LInear NEuron), and Tutorial Steps To Implement Adaline with PyQt. In Chapter 5, you will learn how to use the scikit-learn machine learning library, which provides a wide variety of machine learning algorithms via a user-friendly Python API and to perform classification using perceptron, Adaline (adaptive linear neuron), and other models. The dataset used is Iris dataset directly from the UCI Machine Learning Repository. You will learn: Tutorial Steps To Implement Perceptron Using Scikit-Learn, Tutorial Steps To Implement Perceptron Using Scikit-Learn with PyQt, Tutorial Steps To Implement Logistic Regression Model, Tutorial Steps To Implement Logistic Regression Model with PyQt, Tutorial Steps To Implement Logistic Regression Model Using Scikit-Learn with PyQt, Tutorial Steps To Implement Support Vector Machine (SVM) Using Scikit-Learn, Tutorial Steps To Implement Decision Tree (DT) Using Scikit-Learn, Tutorial Steps To Implement Random Forest (RF) Using Scikit-Learn, and Tutorial Steps To Implement K-Nearest Neighbor (KNN) Using Scikit-Learn. In Chapter 6, you will learn how to use Pandas, NumPy, Scikit-Learn, and other libraries to implement different approaches for reducing the dimensionality of a dataset using different feature selection techniques. You will learn about three fundamental techniques that will help us to summarize the information content of a dataset by transforming it onto a new feature subspace of lower dimensionality than the original one. Data compression is an important topic in machine learning, and it helps us to store and analyze the increasing amounts of data that are produced and collected in the modern age of technology. You will learn the following topics: Principal Component Analysis (PCA) for unsupervised data compression, Linear Discriminant Analysis (LDA) as a supervised dimensionality reduction technique for maximizing class separability, Nonlinear dimensionality reduction via Kernel Principal Component Analysis (KPCA). You will learn: 6.1 Tutorial Steps To Implement Principal Component Analysis (PCA), Tutorial Steps To Implement Principal Component Analysis (PCA) Using Scikit-Learn, Tutorial Steps To Implement Principal Component Analysis (PCA) Using Scikit-Learn with PyQt, Tutorial Steps To Implement Linear Discriminant Analysis (LDA), Tutorial Steps To Implement Linear Discriminant Analysis (LDA) with Scikit-Learn, Tutorial Steps To Implement Linear Discriminant Analysis (LDA) Using Scikit-Learn with PyQt, Tutorial Steps To Implement Kernel Principal Component Analysis (KPCA) Using Scikit-Learn, and Tutorial Steps To Implement Kernel Principal Component Analysis (KPCA) Using Scikit-Learn with PyQt. In Chapter 7, you will learn how to use Keras, Scikit-Learn, Pandas, NumPy and other libraries to perform prediction on handwritten digits using MNIST dataset. You will learn: Tutorial Steps To Load MNIST Dataset, Tutorial Steps To Load MNIST Dataset with PyQt, Tutorial Steps To Implement Perceptron With PCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Perceptron With LDA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Perceptron With KPCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Logistic Regression (LR) Model With PCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Logistic Regression (LR) Model With LDA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Logistic Regression (LR) Model With KPCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement , Tutorial Steps To Implement Support Vector Machine (SVM) Model With LDA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Support Vector Machine (SVM) Model With KPCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Decision Tree (DT) Model With PCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Decision Tree (DT) Model With LDA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Decision Tree (DT) Model With KPCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Random Forest (RF) Model With PCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Random Forest (RF) Model With LDA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement Random Forest (RF) Model With KPCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement K-Nearest Neighbor (KNN) Model With PCA Feature Extractor on MNIST Dataset Using PyQt, Tutorial Steps To Implement K-Nearest Neighbor (KNN) Model With LDA Feature Extractor on MNIST Dataset Using PyQt, and Tutorial Steps To Implement K-Nearest Neighbor (KNN) Model With KPCA Feature Extractor on MNIST Dataset Using PyQt.

This book aims to develop a database-driven desktop application that readers can develop for their own purposes to implement database-oriented digital image processing, machine learning, and image retrieval applications. In Tutorial 1, you will perform the steps necessary to add 6 tables using Visual C# into ImageProc database. You will build each table and add the associated fields as needed. In this tutorial, you will also build such a form for Officer table. This table has sixteen fields: OfficerID, FirstName, LastName, RegNumber, BirthDate, AppDate, Gender, Status, Rank, Address, Mobile, Phone, Email, Description, PhotoFile, and FingerFile). You need seventeen label controls, two picture boxes, ten text boxes, two comboxes, one check box, two date time pickers, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, eight buttons for utilites, one button for searching officer’s name, one button to upload officer’s photo, and one button to upload officer’s fingerprint. In Tutorial 2, you will perform the steps necessary to create and implement police station form. In this tutorial, you will build such a form for PoliceStation table. This table has seven fields: PSID, OfficerID, PSName, City, Address, Phone, and Description. You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need eight label controls, six text boxes, two comboxes, one check box, and one printpreviewdialog. You also need four buttons for navigation, eight buttons for utilites, and one button for searching officer’s name. Place these controls on the form. In Tutorial 3, you will build such a form for Accused table. This table has thirteen fields: AccusedID, FullName, MotherName, CrimeCase, BirthDate, Gender, Address, Mobile, Phone, Email, Description, PhotoFile, and FingerFile). You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need fourteen label controls, two picture boxes, nine text boxes, two comboxes, one date time picker, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, eight buttons for utilites, one button for searching accused’s name, one button to upload accused’s photo, and one button to upload accused’s fingerprint. In Tutorial 4, you will build such a form for Witness table. This table has thirteen fields: WitnessID, FullName, MotherName, CrimeCase, BirthDate, Gender, Address, Mobile, Phone, Email, Description, PhotoFile, and FingerFile). You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need fourteen label controls, two picture boxes, nine text boxes, two comboxes, one date time picker, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, eight buttons for utilites, one button for searching witness’s name, one button to upload witness’s photo, and one button to upload witness’s fingerprint. In Tutorial 5, you will build such a form for Victim table. This table has thirteen fields: VictimID, FullName, MotherName, CrimeCase, BirthDate, Gender, Address, Mobile, Phone, Email, Description, PhotoFile, and FingerFile). You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need fourteen label controls, two picture boxes, nine text boxes, two comboxes, one date time picker, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, eight buttons for utilites, one button for searching victim’s name, one button to upload victim’s photo, and one button to upload victim’s fingerprint. In Tutorial 6, you will build such a form for CrimeReg table. This table has fourteen fields: CRID, CRNumber, PSID, VictimID, AccusedID, DateReport, DateCrime, Arrested, CaseStatus, Description, Feature1, Feature2, Feature3, and Feature4. You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need thirty two label controls, seven text boxes, ten comboxes, one check box, two date time pickers, six picture boxes, and one printpreviewdialog. You then need four buttons for navigation, eight buttons for utilites, and one button for searching crime register number. You also need button to save every feature.

In chapter one, you will learn to know the properties and events of each control in a Windows Visual C# application. You need to learn and know in order to be more familiar when applying them to some applications in this book. In chapter two, you will go through step by step to build a SALES database using Microsoft Access and SQL Server. You will build each table and add associated data fields (along with the necessary keys and indexes). The first field in the Client table is ClientID. Enter the clien ID in the Name Field and select AutoNumber in the Data Type. You define primary key and other indexes which are useful for quick searching. ClientID is a primary field. If the small lock symbol is not displayed next to the ClientID row, then you need to place it there. Right click on ClientID row and select Primary Key. A small key is now displayed next to the entry indicating it is the primary key. You will define FamilyName as an index. Select the FamilyName line. On the General tab, set the Indexed property to Yes (Duplicates OK). You then will create Ordering table with three fields: OrderID, ClientID, and OrderDate. You then will create Purchase table with three fields: OrderID, ProductID, and Quantity. And you will create Product table with four fields: ProductID, Description, Price, and QtySold. Before designing Visual C# interface, you will build the relationships between four tables. In chapter three, you will build a Visual C# interface for the database. The interface will be used to enter new orders into the database. The order form will be used to enter the following information into the database: order ID, order date, client ID, client’s first name and family name, client’s address, product information ordered. The form will have the ability to add new orders, find clients, add new clients. The completed order invoice will be provided in a printed report. In chapter four, you will build a database management system where you can store information about valuables in your warehouse. The table will have seven fields: Item (description of the item), Location (where the item was placed), Shop (where the item was purchased), DatePurchased (when the item was purchased), Cost (how much the item cost), SerialNumber (serial number of the item), PhotoFile (path of the photo file of the item), and Fragile (indicates whether a particular item is fragile or not). The development of this Warehouse Inventory Project will be performed, as usual, in a step-by-step manner. You will first create the database. Furthermore, the interface will be built so that the user can view, edit, add, or add data records from the database. Finally, you add code to create a printable list of information from the database. In chapter five, you will build an application that can be used to track daily high and low pollutant PM2.5 and air quality level. You will do this in stages, from database development to creation of distribution packages. These steps are the same as those used in developing a commercial database application. The steps that need to be taken in building Siantar Air Quality Index (SAQI) database project are: Build and test a Visual C# interface; Create an empty database using code; and Report database. The designed interface will allow the user to enter max pollutant, min pollutant, and air quality for any date that the user chooses in a particular year. This information will be stored in a database. Graphical result of the data will be provided, along with summary information relating to the maximum value, minimum value, and mean value. You will use a tab control as the main component of the interface. The control has three tabs: one for viewing and editing data, one for viewing graph of pollutant data, and another for viewing graph of air quality data. Each tab on this control operates like a Visual C# control panel. In chapter six, you will perform the steps necessary to build a SQL Server book inventory database that contains 4 tables using Microsoft Visual Studio 2019. You will build each table and add the associated fields as needed. You will have four tables in the database and define the relationship between the primary key and foreign key. You will associate AuthorID (foreign key) field in the Title_Author table with AuthorID (primary key) in the Author table. Then, you want to associate the ISBN (foreign key) field in Title_Author table with ISBN (primary key) in the Title table.