Computer Science

Discussion -wk13 Performing Forensic Analysis and TechniquesThere are a number of Digital forensics tools available. Do some research on both software tools and hardware tools. Choose one of each to present in your Discussion essay. Describe each tool and it’s capabilities and the advantages of having it in your Forensics Toolkit. Considerations should include, functionality, ease of use, reliablity, reputation cost and other factors.Notes: Your essay should be unique, do not duplicate your other classmates selection. (First come first served) If you must write on a tool that another classmate has chosen, be sure to approach your essay from a different angle.These consideration very important in the course functionality, ease of use, reliability, reputation cost and other factors.REFERENCES OR WORKS CITED SHOULD BE INCLUDED.

Data Science for Business project Due Date 04/28/2021Description: The goal of this project is to have students demonstrate the ability to follow the main steps of a Machine Learning project and develop a Machine Learning model. Each student has to select a dataset either from the links that are provided, or you can find yours from any other resource. The final project includes the basic steps that require students to master data science skills to solve a multiclass classification problem.The dataset: the excelProject Requirements: Run the K-Nearest Neighbors model in Python to predict the class label from the different measurements in the dataset.1. Introduction: Start with an introduction of your project. This introduction should introduce (1) the problem you want to solve. (2) Dataset descriptions like the size, the number of measurements, the type of the measurements, and the number of classes and their labels.2. Load the data and discover & visualize it to get insights: generate graphs to discover if there is any relationship between measurements or find any clustering.3. Prepare the dataset: Do preprocessing if your dataset needs for example, dimension reduction, removing outliers, handling text and categorical variables, cleaning the data, and/or data standardization (all of the variables used for K-NN model must be on the same order of magnitude in order to produce accurate results.4. Data partitioning: After preprocessing your dataset, you need now to split the dataset into non-overlap sets to perform training and testing phases.5. Different values of K : Choose three different values of K. Discuss your reasons for choosing the different values of K.6. Training Phase: Run the model using the three different values of K you chose in the previous step. Discuss the three main steps in the K-NN algorithm: calculate the distance, find the nearest neighbors, and making predictions.7. Testing Phase: Compare the accuracy between the training phase and the testing phase. Discuss this results8. Evaluation Phase: Check the accuracy of all models predictions (the different values of K) by creating the confusion matrix, compute Recall score, and Precision score. Discuss the predictions results in terms of the accuracy and the misclassification error.9. Present the best model: choose the best model you found based on the results from the evaluation phase. Think of any improvement that can be made to get better results.10. Conclusion: Discuss your final results and conclusion about the model.Project ReportA narrative description of the all the machine learning model steps, provided with screen shots of the code and output.For every step in the project requirements list above do: (1) Discuss what you did. (2) Provide screen shots of the code. Provide screen shots of the output. (3) Provide any graphs if needs.Submission Checklist:1. Dataset file: original file and the modified one in case if you did any modifications.2. Python file (.py)3. Report document.

1 Preliminary step For all checks that are needed for the following questions, you should use the assert() function. All intermediate and final results should be plotted using the matplotlib package. In order for your results to be reproducible use the following seed np.random.seed(123).2 Fundamental Matrix Linear System (20 points) For this question you are asked to implement the following function:def fundamental_matrix_linear_system(pts1, pts2): “””Create linear equations for estimating the fundamental matrix in matrix form :param pts1: numpy.array(float), an array Nx2 that holds the source image points :param pts2: numpy.array(float), an array Nx2 that holds the destination image points :return:A: numpy.array(float), an array Nx8 that holds the left side coefficients of the linear equations b: numpy.array(float), an array Nx1 that holds the right side coefficients of the linear equations”””Using a number of corresponding points from the source (pts1) and destination (pts2) images as input, this function will return the array AAA 2 RN?8 and vector bbb 2 RN?1 of the linear system AAAxxx = bbb, where xxx 2 R8?1 is a vector that holds the parameters of the fundamental matrix (remember that f33 can be set to 1). You should check that N is at least 8 and that both pts1 and pts2 are two dimensional arrays and that their first dimension is equal to N and the second is equal to 2.3 Compute Epipolar Lines (10 points) In this part of the assignment you need to implement a function that calculates the epipolar lines that correspondto a set of points, under the epipolar constraint. This function should follow the function signature below:def compute_correspond_epilines(points, which_image, F): “””For points in an image of a stereo pair, computes the corresponding epilines in the other image :param points: numpy.array(float), an array Nx2 that holds the image points :param which_image: int, index of the image (1 or 2) that contains the points :param F: numpy.array(float), fundamental matrix between the stereo pair :return:epilines: numpy.array(float): an array Nx3 that holds the coefficients of the corresponding epipolar lines”””According to which image the points belong to, it should calculate the corresponding epilines under the epipolar constraint expressed by the fundamental matrix. You should check that points is a two dimensional array where the second dimension is equal to 2. Also, the which_image parameter should take only one value from the set {1,2} and the fundamental matrix should be a 3 ? 3 array. The epilines should be returned in the format (a,b,c), which are the coefficients of the line l(i) : ax + by + c = 0 that corresponds to the point p(i). Note that the coefficients should be normalized so thatp a2 + b2 = 1.4 Estimate Fundamental Matrix (50 points) For this part, you need to calculate the fundamental matrix for a stereo pair of images. First you need to load thetwo images left.jpg and right.jpg that are found under the data/ directory. Then you will need to extract SIFT features from their grayscale counterparts and find some good correspondences between the left and right image,

Writing a term paper APA style on:“Overview of Tools used in Digital Forensics”Instructions:10 pages, 1.5 lines spacing, Times new Roman5 referenceTo Include:Abstract:I. IntroductionII. BackgroundIII. Current Issues and Suggest TopicsIV. Methods, Techniques, and EvaluationsV. Future WorksVI. SummaryVII. ReferencesGrading rubric:Comprehension of Assignment (Addressed the question completely and thoroughly. Provided additional supporting evidence, demonstrating a full comprehension of subject matter): 20 percent- Application of Course Knowledge and Content (Thorough technical application of course knowledge and content in a complete and concise manner): 20 percent- Organization of Ideas (Original ideas are effectively developed and presented in a logical, sequential order throughout the entire assignment. Includes adequate and appropriate supporting evidence): 20 percent- Writing Skills (Mechanics (spelling, grammar, and punctuation) are flawless, including proficient demonstration of citations and formatting throughout the entire assignment): 20 percent- Research Skills (Accurate and applicable use of resources relevant to the subject matter that enhance the overall assignment): 20 percent

Analyze the ERD for a student information system provided below. Be alert for the specifications provided for: 1) Entities, 2) Attributes, 3) Primary Key, and 4) Relationships. You will need to have a clear understanding for these components to create your database using MySQL.

Discussion (Chapter 25):How do you define big data? What are the implications from the three industry trends (Three V’s), presented in the textbook, by the Gardner Group? Three V’s presented in the textbook are as follows: Volume, Velocity, and Variety.Need 250 to 300 words with references. No APA format required and the textbook is attached.

Choose a publicly available data visualization. (be sure to provide the link, cite, and reference).Analyze the visualization within the context of the data visualization workflow.Create a proposal of enhancements to create a better user/viewer experience.Use the data visualization workflow as framework for both your analysis and your proposal.Consider the various roles of the project team as specified by Kirk’s concept of “hats”.

This is an individual assignment. You may discuss it with others, but your code and documentation must be written on your own.Linux technical expertise is essential in today’s computer workplace as more and more companies switch to Linux to meet their computing needs. Thus, it is important to understand how Linux can be used, what benefits Linux offers to a company, and how Linux has developed and continues to develop. As Linux system administrator you should be familiar with Linux operating system flavours and their capabilities. Linux may appear different depending on the distribution, your hardware and personal taste, but the fundamentals on which all graphical and other interfaces are built, remain the same.In this assignment, you are required to install Fedora Linux Workstation and Server operating system (Latest Version) on a virtual machine (e.g., Microsoft Hyper-V , VMWare Player or Oracle VM VirtualBox ) on your operating system as a guest. You should also find the minimum hardware requirements for most operating systems on the vendor’s website. For example, the Fedora Linux operating system minimum hardware requirements are documented at docs.fedoraproject.org . You should document the installation process with screenshots.#Task 1 to install Fedora workstation, you should do the following steps: (5 Marks)1. Virtual Machine configuration:a. Allocate 24.5 GB to the virtual machine’s hard diskb. Allocate 2.2 GB to the virtual machine’s memoryc. Configure NAT for IP Address conservation.d. Allocate 2 processor cores to the virtual machine. (Optional)2. pre-Storage configuration:a. You should manually partition the hard disk with the following specification:· 2.5 GiB Swap· 10 GiB root (/)· 500 MiB (/boot)· 11.5 GiB (/home/StudentID)b. Check the disk space command to view system disk usage,c. Create a directory on the Desktop called StudentID_ITC333_202130 .d. The directory icon should be displayed in the Desktop environment.e. You should use a related command to display the hard disk partitions.

The final portfolio project is a three- part activity. You will respond to three separate prompts but prepare your paper as one research paper.Start your paper with an introductory paragraph.Prompt 1 Blockchain (2-3 pages): Explain the major components of blockchain. Be sure to include how blockchain is affecting a global economy and how you see it growing in the future.Prompt 2 Big Data (2-3 pages): Describe your understanding of big data and give an example of how you’ve seen big data used either personally or professionally. In your view, what demands is big data placing on organizations and data management technology? How does big data affect a global economy.Prompt 3 Government and Policies (2-3 pages): Discuss the role government plays in a global economy. Also, look at what policies are currently in place and then discussion what policies should be put in place.Conclude your paper with a detailed conclusion section (1-2 pages long).Your paper should meet the following requirements:Be approximately 8 to ten pages in length, not including the required cover page and reference page.Follow APA7 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.Support your answers with the readings from the course, the course textbook, and at least ten scholarly journal articles to support your positions, claims, and observations, in addition to your textbook.Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.

Description: The purpose of this assignment is to develop skills in problem solving, decision making in complex situations, and learn/use the APA 6.0 style guidelines.Assignment Details:Read the uploaded Case Study: A Hacker Attack: An Ecommerce Nightmare (A). When referencing any outside sources, ensure you properly cite in the body of the text and on the references page.Use the following questions to structure your paper:· How serious is the situation?· What’s at stake here?· What is the most significant problem/challenge faced by the [firm/protagonist]?· Who or what is [responsible/to blame] for the crisis faced by the [firm/protagonist]?· What would you recommend to the [firm/protagonist]?