When you create a case in EnCase you add your information either by a template or enter it individually for each case. Where is this header information contained?
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When you create a case in EnCase you add your information either by a template or enter it individually for each case. Where is this header information contained?
It is stored in the header in the first evidence file since it does not have to be written to again
It is stored in each data block before the CRC for the next file
It is stored in the last section of the evidence file right before the MD5 hash
It is stored in the header in each of the subsequent evidence files added to the evidence file
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- Open your text editor and create a new document named model.php model.php will contain functions that will connect to a database potentially return PDO statementobjects to the controller for processing. updateMessagesfunction updateMessages($id)This method will take a single parameter of id which is the saved id from the last or latest message displayed. It will conditionally select from the table “messages”, id, name, message, and time. The condition is that the field id is greater than the parameter for id. The return is the PDOStatement object with the row data from the query.The Save Transaction button depicted in the screen attached is used to save relevant data to the sales table and the salesdetails tables from the depicted schema. When this button is clicked it calls the saveTransaction() function that is within the PosDAO class, it passes to this function an ArrayList of salesdetails object, this list contains the data entered into the jTable which is the products and qty being sold.Write the saveTransaction function. You are to loop through the items and get the total sales, next you are to insert the current date and the total sales into the sales table. Reminder that the sales table SalesNumber field is set to AUTO-INCREMENT, hence the reason for only entering the total sales and current date in sales table.2. load_friendsdb This function does the reverse of save_friendsdb -- it takes a single argument, filename, and opens that specified file for reading. Then it reads the file one line at a time and creates a new friends database to return. Like in the previous function, each line will contain a friend's name followed by a tab, then the friend's height, and then a newline. Sample calls should look like this: >>> load friendsdb("friendsdb.tsv") [{'name': ' bimmy', 'height': 600}, {'name': 'Ian Donald Calvin Euclid Zappa', height': 175}]
- 2. load_friendsdb This function does the reverse of save_friendsdb -- it takes a single argument, filename, and opens that specified file for reading. Then it reads the file one line at a time and creates a new friends database to return. Like in the previous function, each line will contain a friend's name followed by a tab, then the friend's height, and then a newline. Sample calls should look like this: >>> load_friendsdb("friendsdb.tsv") [{'name': ' bimmy', 'height': 600}, {'name': Ian Donald Calvin Euclid Zappa', height': 175}]For on ordered file based on key attribute, the following index can be created: O Clustering. O Primary. Secondary.0 1 import pandas as pd examclub = pd.read_csv ("exama.csv") examclub.info() 2 3 RangeIndex: 10 entries, 0 to 9 Data columns (total 6 columns): # Column Give the following dataframe(examclub), write the statements that will complete the following dataset memory optimization. 1. Set the "Member Join Date" to a date object. 2. Set any Dues Paid and Dues Owed NaN values to zeros. Then set them to floats. 3. Show the unique column values, then set Club Use and Member Level to categories. 4. Display the sum of the Dues Paid. 1 5. Display all members that are Gold Member Level. 6. Display all member that are Silver Member level and Club use is Pool. 7. Display all members that are Gold and Silver member levels. Use the isin method. 8. Display all members that Dues Paid is between 2500 and 6000. 2 3 examclub.head() Member Name Member Level Dues Paid Member Join Date 10 non-null club Use 10 non-null 4 5 Dues Owed dtypes: int64(2), object(4) memory usage: 608.0+ bytes Non-Null Count Dtype ---…
- The file that contains ordering attributes that are not key in nature is referred to as theSBN Title Author 12345678 The Hobbit J.R.R. Tolkien 45678912 DaVinci Code Dan Brown Your student ID DBS311 Your Name use the following statement to Write the MongoDB Shell code to remove the Title Key Value from the 3rd document fromWhat precisely is metadata? An answer to this question may be found in the result set's metadata. Result set information may be beneficial in a variety of situations.
- classification classification number classification name 1 food 2 food 3 raw material Products product number product name classification number 11 tires 2 22 cheesy 33 pills 1 44 gas 3 use microsoft access 1.Create a database in the name of food products 2. Check the above table with the identification of data types and key keys. 3. During design, the following points must be applied: lookup wizard. a. The classification name must be a drop-down list entered by the lookup wizard b. The size of the product name field must be 100. The value must be entered for the field and should not be empty (required). 4. Enter the data into the tables as shown flags.Population Database You will find a program named CreateCityDB.java in Starting Out with Java: Early Objects (6th Edition) Chapter 15 Source Code. Compile and run the program (SEE BELOW). The program will create a Java DB database named CityDB. The CityDB database will have a table named City, with the following columns: Column Name Data Type CityName CHAR (50) Primary Key Population DOUBLE The CityName column stores the name of a city, and the Population column stores the population of that city. After you run the CreateCityDB.java program, the City table will contain 20 rows with various cities and their populations. Next, write a JavaFX application called PopulationDemo that connects to the CityDB database and allows the user to click any of the following operations: Sort the list of cities by population, in ascending order. Sort the list of cities by population, in descending order. Sort the list of cities by name. Get the total population of all the cities. Get the…Fast Food Analysis For the purposes of Questions 10 to 19, we are interested in trying to predict the number of calories in fastfood items, given other information about their nutritional content. You will need to open Rstudio, and then write and run some code, in order to answer these questions. You should attach the .r file used to answer these questions to your submission. Whilst not directly used for assessment, it may be used as evidence in the case of a marking dispute, as well as evidence of plagiarism should it be necessary. Before you start, you will need to install the openintro library via install.packages ("openintro") Then, load library openintro and look at the help file for fastfood. library ("openintro") ?fastfood Please let me know (by email) sooner rather than later if you have technical issues installing the package and loading the data. Now, we are going to be interested in a subset of this data. Start by generating a new dataframe ffood that you are to use…