Category: Computer Science

  • Computer Science Question

    Assignment Details COMP 30034 Computer Forensics

    I need a professional and high-quality assignment for the module Computer Forensics (COMP 30034) based on the assignment brief and the teachers detailed explanation.

    Topic:
    Internet of Things (IoT) Security and Digital Forensics in Smart City Environments.

    Requirements:

    • Approximately 20002200 words.
    • APA 7th edition referencing.
    • Minimum 20 academic citations/references.
    • Use the provided Springer article as the main source:
      Forensics and Security Issues in the Internet of Things
    • Include additional academic sources (IEEE, Springer, ACM, ScienceDirect, etc.) for stronger analysis.
    • The work must be written in clear academic English and in original wording (not AI-generated style or copied content).
    • The assignment must include:
      • Title Page
      • Table of Contents
      • Introduction
      • Task 1
      • Task 2(a)
      • Task 2(b)
      • Conclusion
      • At least 2 recommendations
      • Reference list (APA 7)
      • Page numbers

    Formatting:

    • Times New Roman
    • Font size 12
    • Headings size 14, bold, capitalized, and underlined
    • Include suitable diagrams where necessary

    Important:
    The teacher emphasized that the assignment must contain critical analysis, not only description or summary. Strong original contribution is required to achieve high marks.

    Task 1 IoT Forensic Challenges (30 Marks)
    Critically discuss the forensic challenges involved in:

    • Identifying evidence
    • Collecting evidence
    • Preserving evidence

    Scenario:
    A smart city IoT system with smart cameras, vehicle sensors, and cloud analytics experienced abnormal traffic signals and unauthorized access to surveillance feeds.

    The discussion must include:

    • IoT forensics challenges
    • Device heterogeneity
    • Massive data volume
    • Timestamp synchronization issues
    • Distributed evidence across cloud/fog/devices
    • Lack of standardization
    • Chain of custody
    • Impact of these challenges on the investigation process

    Task 2(a) IoT Architecture Models (30 Marks)
    Critically analyze:

    • Three-layer architecture
    • Five-layer architecture
    • CloudFog/Edge architecture

    The answer must include:

    • Architecture explanation
    • Strengths and weaknesses
    • Comparison between architectures
    • Latency discussion
    • Why fog/edge computing is more suitable for smart city environments
    • Critical evaluation, not only description

    Task 2(b) Security Challenges and Hybrid Security Solution (40 Marks)
    Critically analyze:

    • Device heterogeneity
    • Weak authentication mechanisms
    • Privacy concerns
    • Unauthorized access
    • Data breaches
    • Coordinated cyberattacks

    Evaluate the effectiveness of:

    1. Blockchain technology
    2. Machine learning techniques

    Also discuss their practical limitations:

    • Scalability
    • Latency
    • Resource constraints

    Most Important Requirement:
    Create an original high-level hybrid security approach combining technologies such as:

    • Fog/Edge Computing
    • Blockchain
    • Machine Learning

    The proposed solution should explain:

    • Real-time anomaly detection
    • Secure evidence logging
    • Reduced latency
    • Improved resilience and security
    • Lightweight blockchain and edge-based ML concepts

    Conclusion:
    Summarize the findings clearly and provide at least two professional recommendations.

    The final work should be professional, accurate, detailed, and fully aligned with the teachers instructions to achieve a high grade (90%+).

    Additional Expectations for High Distinction Level:

    The assignment should demonstrate advanced academic writing, critical thinking, and deep understanding of IoT security and digital forensics concepts. The analysis should go beyond basic explanation by comparing approaches, evaluating strengths and weaknesses, and justifying arguments using recent academic research.

    The proposed hybrid security framework should be original, realistic, technically justified, and suitable for smart city deployments. Diagrams, comparison tables, and clear architectural illustrations should be included where appropriate to enhance the quality of the report.

    The final submission should reflect the quality of an excellent/distinction-level university assignment capable of achieving the highest possible marks.

  • Database Design Framework

    Prior to beginning work on this assignment, read Chapters 4, 6, 7, 8, and 15 from your textbook Database Systems: Design, Implementation, & Management (14th ed.). These chapters cover ERDs, normalization, SQL, and database connectivity, which are foundational for this project.

    For the final assignment of this course, you will analyze user needs to facilitate the development of a database using an SQL server to track the software and hardware assigned to the employees of a given organization. The purpose of this database project is to facilitate the development of data models that can be translated into relational databases.

    Organizations are legally required to track software and ensure that only legally procured software licenses are deployed. As a database architect, your task is to develop a database to track software and hardware for the ConstructCo Company. ConstructCo is a small construction company that employs 50 employees and owns over 80 desktop computers, laptops, and servers. You will be using the SQL Server environment provided during this course. This database will ultimately be used as a basis for a software license management tool to assist the company in tracking how the licenses and workstations/PCs are deployed throughout the organization.

    You must use the template when creating your assignment. For each section of the template, include the content required as listed in the following sections.

    Document History

    The information in this section will be pre-populated in the template. The only required content will be your name in the Revised By column.

    Executive Summary

    For the executive summary,

    • Summarize the project parameters.
    • Describe each of the following sections briefly:
      • Conceptual Design
      • Normalization phase
      • Physical design
      • Data retrieval and connecting to online databases

    There is a sample of an Executive Summary on the Writing Centers page for your reference.

    Conceptual design (ERD creation)

    For the conceptual design,

    • Review the feedback provided for your Week 2 ERD Creation discussion forum.
    • Review the .
    • Revise your Visio conceptual model (or entity-relationship diagram) for your database.
      • Ensure that the following requirements are met:
        • Identify all entities and attributes.
        • Identify all primary keys.
        • Define all relationships between entities.

    Normalization

    Once the ERD is completed for your ConstructCO database project, you will create the Logical Data Model and check the model against 3rd Normal Form (3NF).

    For this phase of the project,

    • Review your existing ERD feedback from your Week 3 assignment where you converted your ERD into a Logical Data Model in 3NF.
    • Revise your Logical Data Model using information from your Week 3 assignment feedback.
    • Describe the three normal forms.
    • Justify how each of your tables meets 1st, 2nd, and 3rd Normal Form.
      • Utilize a minimum of three professional sources to support your statements.

    Physical Design

    In Week 4, you created your database in the SQL server you were provided with within your lab environment and translated this design into SQL server tables with appropriate fields.

    • Select the appropriate data type for every field.
      • The specific data type you select will depend on the size and range of the values that will be stored in the field.
    • Specify all primary keys as identity fields and not as auto-increment.

    After creating the tables, use the insert command to populate the tables with sample data for all the tables. (This will be affirmed in your SQL server in the lab environment.)

    Data Retrieval

    Provide select statements to satisfy the following data requests:

    • List all available laptops assigned laptops to managers.
    • List all available named licenses.
    • List the workstations that are over three years old (from the date of purchase) and assigned to leads.
    • List the names of the leads, workstation IDs, and location.
    • List the names of all the leads in the operations department.
    • List all the workstations with a disk space that is less than the average disk space available in all workstations.
    • List the names of all managers with employees who have not been assigned a workstation.
    • Provide screenshots of the SQL statements used to perform each step and the result sets resulting from the execution of the SQL statements.
    • Describe what you did to complete each step.

    Connect Online Databases with Front-End Interfaces

    In order to connect the database with the front-end interface, you will

    • Modify the Java code provided on the website to retrieve the list of all workstations assigned to managers.
      • The output must include the
        • first name
        • last name
        • department of the managers
        • workstation ID
        • date of purchase
    • Modify the Java Code to insert new workstation records in the workstation table if provided with the WorkstationID, type, location, purchase date, memory, disk space, and CPU speed.
      • Include the modified code by copying and pasting the code as plain text at the bottom of this section.

    The Database Design Framework final project

    • must be 15 to 20 double-spaced pages in length (not including title and references pages) and formatted according to as outlined in the Writing Centers resource.
    • must include a separate title page with the following in title case:
      • title of paper in bold font
        • Space should appear between the title and the rest of the information on the title page.
      • students name
      • name of institution (The University of Arizona Global Campus)
      • course name and number
      • instructors name
      • due date
    • must utilize academic voice.
      • Review the resource for additional guidance.
    • must include an introduction and conclusion paragraph.
      • Your introduction paragraph needs to end with a clear thesis statement that indicates the purpose of your paper.
      • For assistance in writing and , refer to the Writing Center resources.
    • must use at least 2 credible sources in addition to the course text.
      • The table offers additional guidance on appropriate source types. If you have questions about whether a specific source is appropriate for this assignment, please contact your instructor. Your instructor has the final say about the appropriateness of a specific source.
      • To assist you in completing the research required for this assignment, refer to this tutorial, which introduces the University of Arizona Global Campus Library and the research process, and provides some library search tips.
      • You may also refer to the tutorial, which explains keyword searching process in the library to find scholarly articles, or the tip sheet, which provides some tips and strategies to make finding credible online research in a search engine such as Google easier and more efficient.
    • must document any information used from sources in APA Style as outlined in the Writing Centers guide.
    • must include a separate references page that is formatted according to APA Style as outlined in the Writing Center.
      • Refer to the resource in the Writing Center for specifications.
  • Descriptive Statistics Using JASP

    Descriptive Statistics Using JASP (ATTACHED THE REQUIRED FILES)

    Purpose

    This assignment ensures you can successfully open JASP, load the semester dataset, and generate descriptive statistics. These foundational skills are required before we move into correlation, regression, t tests, and ANOVA.

    Instructions

    Step 1

    Open JASP and load the Semester Dataset provided in Week 1.

    Step 2

    Select the following variables:

  • tenure_org_years
  • lead_years
  • job_sat_mean
  • Step 3

    Generate Descriptive Statistics including:

  • Mean
  • Standard Deviation
  • Minimum
  • Maximum
  • Include only the output relevant to this assignment.

    Step 4

    In 1 to 2 well-developed paragraphs, answer the following:

    1. What is the average organizational tenure in this sample?
    2. What is the average leadership experience?
    3. The job_sat_mean variable is measured on a 17 scale, where higher values indicate greater satisfaction. Based on the mean job satisfaction score, would you describe this group as generally satisfied, neutral, or dissatisfied?
    4. Which variable appears to have the greatest variability? Support your answer using the standard deviation.

    Report descriptive statistics in APA format (for example: M = 6.42, SD = 3.15). Round all statistics to two decimal places.

    Step 5

    Copy and paste the JASP output tables and any relevant graphs directly into your Word document.

    Do not submit screenshots. Tables and figures must be clearly readable.

    Submission Requirements

  • 300 words
  • Professional academic tone
  • Round all statistics to two decimal places
  • Proper APA reporting of statistics
  • Copy and paste JASP output tables and graphs (no screenshots)
  • Submit as a Word document (.doc or .docx only)
  • APA Example

    The average organizational tenure was moderate (M = 6.42, SD = 3.15). Leadership experience was slightly lower (M = 4.87, SD = 2.91).

    Grading Criteria (20 Points)

    Statistical Output Accuracy 8 points

    APA Statistical Reporting 4 points

    Interpretation and Application 4 points

    • Professional Writing and Mechanics 4 points
  • Computer Science Question

    The assignment is about designing and evaluating cloud-based information retrieval systems, including data storage, search, retrieval, and security. I will attach the file assignment and please follow the process of the assignment without using AI and word count : 2500

  • Computer Science Question

    Summary:

    Analyze a commonly used application (e.g., a website or mobile app) and create a screen recording with voiceover discussing its Human-Computer Interaction (HCI) design strengths and weaknesses. Upload the recording to YouTube as a private unlisted video and provide a APA format paper (1-2) pages that have the HCI findings and link to your video.

    • Identify the strengths of the application’s HCI design. Consider aspects like usability, visual design, navigation, feedback, and accessibility.
    • Identify the weaknesses of the application’s HCI design. Provide constructive criticism and suggestions for improvement.
    • Write a script for your voiceover that outlines your analysis. Make sure to cover both strengths and weaknesses, and provide specific examples.
    • Use screen recording software (e.g., OBS Studio, Camtasia, QuickTime, Zoom) to capture your screen while you navigate through the application.
    • Record your voiceover while demonstrating the points discussed in your script and ensure your recording is clear, both in terms of audio and video quality while walking through the items on the design side
    • Upload to Youtube and make it public
    • Create APA format (1-2) pages that describes your findings and use at least 2 peer reviewed references.
  • Computer Science Question

    Summary:

    This task aligns with Student Learning Outcome 4 (SLO4), where you will explain how relationships between entities are defined and refined, and Course Learning Objective 4 (CLO4), where you will evaluate entity relationships and incorporate them into a sound database design.

    Deliverables:

    1. Review and Refine Relationships: Revisit the following schema and improve the relationships. (attached below the assignment files)
    2. Define Integrity Constraints: Specify primary keys for each table, and establish foreign keys to connect related tables. Define any necessary constraints (such as NOT NULL or UNIQUE) that will help ensure the accuracy of your data.
    3. Use the following video as a reference on how to achieve similar tasks
    4. :
    5. Provide detailed report APA style with 1-2 pages that explain the changes you did with at least 2 peer reviewed resources

    Use the following files (ERD diagram and Schema) [click and right-click then save file] or use the files from the week 4 content

  • Describe the migration process in cloud computing

    this is a cloud computing question. Give the answer in a chronological order

  • CDN Tutorial

    In this tutorial, you will build a small CDN simulation called BuzzStream, a media app whose viral video traffic starts overwhelming a single origin server.

    The lab walks through CDN behavior one layer at a time: first, an origin server; then, an edge cache; then, routing across multiple edge nodes; and finally, resilience features such as stale responses, timeouts, and a backup origin.

    By the end, you should be able to explain what an origin server does, why cache hits are faster than misses, why routing matters for cache locality, and how a CDN can keep serving content when the origin is slow or unavailable.

    Overview PDF: included

    Tutorial Instructions

    Download and extract the tutorial zip file below. Everything needed for the tutorial is included inside the folder.

    Start by opening:

    README.md

    Then work through the steps in order:

    • Step 0: Prerequisites
    • Step 1: Topology Overview
    • Step 2: Origin Only
    • Step 3: Edge Cache
    • Step 4: Routing
    • Step 5: Resilience

    Each step has its own README.md with the commands to run, the files to inspect, and the checks that confirm the lab is working. Run the prerequisite check first, and remember to stop each Docker Compose stack before moving to the next step.

    Lab Files: included


  • PowerPoint , dont use AI my teacher use quetext and quillbot…

    We are approaching the end of the course and you have learned many valuable skills. Think through your progress and identify five business communications skills that you’ve learned for the first time or developed during this course. Create a six-slide presentation, with a title slide and five slides that describe each of the five skills you’ve identified. Be sure to explain how each skill could help you in your career. Use any PowerPoint (or similar software) template and slide graphics you feel appropriate for this assignment. Apply appropriate animations and transitions.

  • Computer Vision System Design, Implementation, and Evaluatio…

    Computer Vision > Final Project

    Assignment due Monday, May 11, 2026, by 11:59pm

    Computer Vision System Design, Implementation, and Evaluation

    Submission:

    Primary submission: Final Report (PDF, max 10 pages excluding references, including video link (with proper sharing settings so that the video is accessible))

    Secondary submission: Zip file containing Jupyter Notebook(s) (.ipynb) and/or Python scripts (Important: you should avoid including large hidden files while copying your code (avoid direct copy of PyCharm projects, which may include large hidden folders)). Do not include the video file in this package.

    1. Overview

    The Final Project is the implementation and evaluation phase of the system proposed in Assignment 2.

    Topic Consistency Requirement:

    The final project is expected to follow the topic proposed in Assignment 2. If a group decides to change its topic, the report must include a justification statement explaining the reason for the change. In such cases, the group is expected to treat the new topic as a fresh project and perform the necessary design, implementation, and evaluation work so that the project goes well beyond a proposal-level description.

    Each group must:

    1. Implement both proposed approaches
    2. Perform structured evaluation
    3. Compare performance across multiple dimensions
    4. Analyze runtime complexity and scalability
    5. Reflect critically on strengths, weaknesses, and real-world applicability

    This project evaluates your ability to apply the full ICS353 pipeline:

    • Image formation & preprocessing
    • Feature detection and matching
    • Motion estimation
    • Reconstruction and depth
    • Segmentation and recognition
    • Evaluation and comparison

    ML-based approaches (e.g., Random Forest, AdaBoost) are optional, not required.

    2. Learning Outcomes Alignment

    This project assesses all course learning outcomes:

    #LO1_image: Describe the foundation of image formation and image processing.

    #LO2_visionmethods: Compare various computer vision methods used for feature detection, edge computation, motion estimation, reconstruction, and recognition.

    #LO3_visiontechniques: Evaluate appropriate computer vision techniques.

    #LO4_imageprocessing: Apply image processing techniques to solve computing problems related to object detection and image segmentation for real-world applications.

    3. Project Requirements

    A. Implementation Requirements

    You must implement:

    • Sub-team A pipeline
    • Sub-team B pipeline
    • Complete preprocessing
    • Parameter tuning experiments
    • Structured evaluation
    • Runtime complexity analysis

    B. Required Evaluation Dimensions

    Your comparison must include:

    1. Quantitative accuracy metrics (pick those suit your task)
      • Precision / Recall
      • IoU
      • Matching accuracy
      • Tracking error
      • Depth error
      • F1-score (if applicable)
    2. Runtime performance
      • Execution time per image/frame
      • FPS (for video tasks)
    3. Robustness analysis (how does your system behave under variation of various factors)
      • Noise sensitivity
      • Illumination variation
      • Parameter sensitivity
    4. Failure case analysis
      • Where and why the method fails

    4. Final Report Structure (Max 10 Pages)

    Your report must include:

    1. Title Page

    • Project Title
    • Group members
    • Sub-team assignments
    • Course code
    • Notebook links
    • Submission date

    2. Abstract ( 300 words)

    • Concise summary including:
    • Problem
    • Approaches
    • Main results
    • Key conclusion

    3. Introduction ( 5 references)

    • Problem context
    • Relevance
    • Application domain
    • Challenges

    4. Literature Review ( 5 additional references)

    • Summary of related work
    • Comparison table of existing solutions
    • Strengths and weaknesses of previous approaches

    5. Methodology

    Dataset Description

    • Include a summary table.

    Sub-team A Pipeline

    • A flowchart/diagram is required
    • Preprocessing
    • Algorithms
    • Justification

    Sub-team B Pipeline

    • A flowchart/diagram is required
    • Preprocessing
    • Algorithms
    • Justification

    Improvement Declaration

    Each group must include a short statement explaining how the final system represents a substantial improvement over the proposal submitted in Assignment 2. The statement should clearly describe what was expanded, redesigned, or implemented beyond the proposal stage, including additional experiments, implementation details, evaluation depth, or methodological refinements.

    6. Results

    Include:

    • Quantitative comparison table
    • Runtime comparison table
    • Robustness tests
    • Example outputs (visuals)
    • Parameter tuning experiments

    Clarity and conciseness are essential.

    7. Discussion

    You must analyze:

    • Why one method performed better
    • Trade-offs (accuracy vs runtime)
    • Sensitivity analysis
    • Real-world feasibility
    • Limitations
    • Potential improvements

    Include:

    Curriculum Mapping Table: Technique Used and Session that covered the technique. For example:

    • Optical Flow; Session 1820
    • Stereo matching; Session 2228
    • Feature Detection; Session 78

    etc.

    8. Conclusion

    Summary of findings

    Member contributions

    3 key learnings for the group

    Future work

    9. References

    Minimum 10 academic references.

    Proper citation required.

    5. Code and Video Submission Requirements

    You must submit clean Jupyter notebook(s) that include the following:

    • Organized sections
    • Clear comments
    • Parameter tuning
    • Evaluation metrics
    • Output visualization
    • Runtime measurement

    The notebook must be readable and reproducible.

    Project Demonstration Video:

    Each group must create a brief demonstration video (maximum 6 minutes) presenting the implemented system, key results, and a short walkthrough of the pipeline. The video should clearly demonstrate the system running and highlight the comparison between the two approaches. The video link must be included in the final report (with proper sharing settings so that it is accessible by the instructor).

    7. Academic Integrity

    No generative AI-written text

    Code must reflect your understanding

    You may be asked to explain any part of your code

    Attached is the original proposal along with the professors’ comments that need to be made and adjusted to the final.