Bright Academic Experts

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  • Management Question

    MedTech Solutions is considering expanding their manufacturing capabilities to support a new AI-powered diagnostic device. The leadership team must decide whether to build a new production facility, upgrade the existing facility, or outsource production. Each option carries different costs, probabilities of market demand scenarios, and potential payoffs.

    Option 1: Build New Facility

    • Cost: $1.2 million
    • Strong Demand (60%): Gain $2.5 million
    • Weak Demand (40%): Gain $1.0 million

    Option 2: Upgrade Existing Facility

    • Cost: $600,000
    • Strong Demand (50%): Gain $1.6 million
    • Weak Demand (50%): Gain $900,000

    Option 3: Outsource Production

    • Cost: $300,000
    • Strong Demand (40%): Gain $1.2 million
    • Weak Demand (60%): Gain $500,000

    Part 1: Excel Decision Tree Model

    Build a decision tree in Excel that includes:

    1. All three options
    2. Chance nodes (with demand probabilities)
    3. Associated payoffs (subtracting the cost from revenue)
    4. Expected Monetary Value (EMV) for each branch

    Highlight your final recommendation based on the EMV calculation.

    Part 2: Sensitivity Analysis

    Perform a sensitivity analysis by:

    1. Adjusting the probability of strong demand by 10% for each decision path
    2. Adjusting the strong demand payoff by 20% for at least one option
    3. Recalculating EMVs and determining if the optimal decision changes

    In Excel, clearly show the impact of these changes in a side-by-side comparison.

    Part 3: Video Presentation (1015 Minutes)

    Create a narrated video walkthrough in which you:

    Explain your decision tree step-by-step:

    1. Why each node, branch, and payoff was set up the way it was
    2. How you calculated EMV

    Demonstrate your sensitivity analysis:

    1. Show how the EMVs and decisions change when inputs are modified
    2. Explain which factors had the biggest impact on the final decision

    Discuss stakeholder engagement:

    1. Explain how your analysis and modeling can be used to build stakeholder confidence
    2. Share strategies for communicating your recommendation persuasively and transparently
    3. Use visuals (Excel spreadsheet, PowerPoint if needed), and speak clearly as though presenting to executives or a project team.

    Written Summary (400600 Words)

    Along with your Excel file and video, submit a brief summary that includes:

    • Final decision and rationale
    • Key takeaways from the sensitivity analysis
    • Stakeholder communication strategy

    Submission Checklist:

    Excel file with decision tree and sensitivity analysis

    1015 minute video presentation

    Written summary ( Word)

    Useful Videos for Project:

    Requirements:

    • There is no minimum or maximum required number of pages. Your analysis will be considered complete, if it addresses all the components outlined above.
    • Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited. A minimum of 4 sources (excluding the course textbook) from scholarly articles or business periodicals is required.
    • Include your best critical thinking and analysis to arrive at your justification.

  • Case Studies in Data Protection and Privacy

    Assignment Instructions Summary (Track B: Membership Inference)

    This assignment is based on the official assignment brief document and the materials covered in Weeks 14 lectures and tutorials. The main objective is to perform a security and privacy review of an AI service, focusing on identifying vulnerabilities, testing them practicly, and proposing suitable defences.

    The analysis must follow the structure provided in the assignment file, including:

    • System understanding (architecture and trust boundaries)
    • Identification of assets, attackers, and risks
    • Designing an attack workflow
    • Proposing defence strategies with justification
    • Supporting analysis with figures, tables, and experimental evidence

      I will choos Track B: Membership Inference.This track focuses on analysing whether an attacker can determine if a specific data record was used in training the model, based on the models outputs.The implementation will be based on the provided file:

      • membership_inference_track.py

        Report Requirements

        The final submission will be:

        • One PDF report only
        • No code files will be submitted

        The report must:

        • Be scenario-specific (AI hiring API)
        • Include:
          • Figures (system architecture, attack workflow, defence workflow)
          • Tables (assetattackerharm)
          • Screenshots from code execution as evidence
        • Demonstrate:
          • Understanding of the system
          • Identification of vulnerabilities
          • Clear attack methodology
          • Justified defence design with trade-offs

            Coding Task (Track B)

            The coding task is minimal and only requires completing two missing lines in the provided script, After completing these lines, the script must be executed to generate results for analysis

            Required Screenshots

            Only screenshots are required (NOT full code submission). The report must include:

            1. Code Screenshot

            • Show ONLY the modified lines (the two completed lines in run_mia())

            2. Output Screenshot

            • Show the program output after running the code, including:
              • Baseline case results
              • Defended case results
            • Important values to capture:
              • member_mean_signal
              • nonmember_mean_signal
              • mia_attack_accuracy
              • threshold

            These outputs will be used as evidence in your discussion.

            Expected Analysis (Track B)

            In the report, you will:

            • Compare baseline vs defended model
            • Explain how defence techniques (e.g. regularization, label smoothing, dropout) reduce membership inference risk
            • Use your code results as supporting evidence

              please reffer to the attached files and read the assignment instructions careflly

          • After you finished, provied a (Turnitin + AI) reports. Al

  • Bio article

    Please download the document and answer the questions using a different colored font. Use your own words when answering the questions. DO NOT copy-paste portions of the research paper or quote verbatim – this is considered plagiarism.

    Even if you are working with your team, you are submitting this as an individual assignment.

  • Complex Designs

    Assignment Summary (Module 14: Complex Designs)

    Part 1: Create a Study Using AI

    You need to:

    1. Write a prompt for an AI tool (such as ChatGPT).
    2. Your prompt must ask for:
      • A factorial research study (at least 2 independent variables + 1 dependent variable).
      • A study related to your career .
      • A study that is 150200 words.
      • The AI must NOT identify the type of design and must NOT mention strengths or weaknesses.
    3. Then:
      • Copy and paste:
        • Your prompt
        • The full AI-generated response

    Part 2: Analysis (YOU DO THIS ON YOUR OWN)

    Answer 3 questions (23 sentences each):

    1. Variables
      • What are the independent variables?
      • How many levels does each one have?
      • Write the design notation (example: 2 x 2)
    2. Type of design
      • Is it between-subjects, within-subjects, or mixed?
      • Explain how you know
    3. Advantage and disadvantage
      • One advantage of the design
      • One disadvantage
      • IMPORTANT:

    You must complete this part on your own (no AI)

  • Modifications needed

    This is a follow-up to the previous question.

  • Business Question

    Please put 34 days IF YOU Want to be selected

  • Case Studies in Data Protection and Privacy

    Assignment Instructions Summary (Track B: Membership Inference)

    This assignment is based on the official assignment brief document and the materials covered in Weeks 14 lectures and tutorials. The main objective is to perform a security and privacy review of an AI service, focusing on identifying vulnerabilities, testing them practicly, and proposing suitable defences.

    The analysis must follow the structure provided in the assignment file, including:

    • System understanding (architecture and trust boundaries)
    • Identification of assets, attackers, and risks
    • Designing an attack workflow
    • Proposing defence strategies with justification
    • Supporting analysis with figures, tables, and experimental evidence

      I will choos Track B: Membership Inference.This track focuses on analysing whether an attacker can determine if a specific data record was used in training the model, based on the models outputs.The implementation will be based on the provided file:

      • membership_inference_track.py

        Report Requirements

        The final submission will be:

        • One PDF report only
        • No code files will be submitted

        The report must:

        • Be scenario-specific (AI hiring API)
        • Include:
          • Figures (system architecture, attack workflow, defence workflow)
          • Tables (assetattackerharm)
          • Screenshots from code execution as evidence
        • Demonstrate:
          • Understanding of the system
          • Identification of vulnerabilities
          • Clear attack methodology
          • Justified defence design with trade-offs

            Coding Task (Track B)

            The coding task is minimal and only requires completing two missing lines in the provided script, After completing these lines, the script must be executed to generate results for analysis

            Required Screenshots

            Only screenshots are required (NOT full code submission). The report must include:

            1. Code Screenshot

            • Show ONLY the modified lines (the two completed lines in run_mia())

            2. Output Screenshot

            • Show the program output after running the code, including:
              • Baseline case results
              • Defended case results
            • Important values to capture:
              • member_mean_signal
              • nonmember_mean_signal
              • mia_attack_accuracy
              • threshold

            These outputs will be used as evidence in your discussion.

            Expected Analysis (Track B)

            In the report, you will:

            • Compare baseline vs defended model
            • Explain how defence techniques (e.g. regularization, label smoothing, dropout) reduce membership inference risk
            • Use your code results as supporting evidence

              please reffer to the attached files and read the assignment instructions careflly

          • After you finished, provied a (Turnitin + AI) reports. Al

  • math talk

    Please follow the instructions down below!

  • Writing Questions

    Question-1:

    Rent control laws, like minimum wage laws, apply broadly to everyone, not just low-income individuals. Should there be provisions to limit rent control benefits only for those who truly need lower rent?

    Note: Your answer should be a minimum of 5-6 pages in total and include a minimum of 3-4 references. APA format, and no plagiarism or AI content is allowed.

    Question-2:

    Calculating the present value of external benefits and comparing it to the present value of additional costs is a purely economic way to evaluate Head Start. Is this the only approach? Is it the right one, or are there other ways to assess the program?

    Note: Your answer should be a minimum of 5-6 pages in total and include a minimum of 3-4 references. APA format, and no plagiarism or AI content is allowed.

    Note:

    • Content should be clear, concise, and understandable in APA format
    • No plagiarism or AI content is allowed.
    • Please follow the minimum number of pages and include a minimum number of references.
    • Check for any grammatical errors and sentence structure.

  • Psychology Question

    Inquiry and analysis is a systematic process of refining our understanding of issues, objects, and works through a cycle of questions and evaluation.

    Purpose: Students will use course information on research methods and psychological research studies to design an experimental study testing a research question that is meaningful to college students.

    Task: Students will write responses that address the following prompts:

    1. Define a specific research question that will address one of the following:

    • What will improve grades?
    • What will reduce stress?
    • What will improve sleep?
    • What will improve self-esteem?

    Example research question: Does warm milk before bedtime improve sleep?

    2. Develop a specific hypothesis for your proposed research question. Which group will have better or worse outcomes?

    Example hypothesis: People who drink a cup of warm milk before bedtime will sleep longer than people who drink water before bedtime.

    3. Find two sources to support your hypothesis (e.g., from class, lecture, textbook, or approved source). Discuss previous research findings that suggest why your chosen variable will affect the outcome.

    Supporting hypotheses with past research: Several empirical studies have demonstrated the impact of drinking milk before bedtime. In one study, adults over 60 who drank fermented milk experienced reduced nighttime wakings (Yamamura et al., 2009). In a different study, adults over 65 who drank milk before bedtime fell asleep more quickly than those who did not consume milk before bed (Kitano et al., 2014).

    4. Describe how you would conduct your study, which includes:

    • a description of who you will sample (the participants)
    • a description of your procedure, which includes a description of your experimental conditions (independent variable) and how you will measure the outcome (dependent variable).

    Sample: I will recruit college students who report difficulty getting a good night’s sleep. Participants will be recruited for a study on “drink consumption before bedtime.” Participants would need to meet the following criteria: (1) cannot be lactose intolerant, (2) are okay to consume cow’s milk, (3) have a microwave to warm the milk provided, and (4) are willing to wear a sleep activity watch.

    Procedure: I would randomly assign participants to one of two groups: (1) drink warm milk before bed or (2) drink water before bed.

    • Participants in the milk condition would be provided with six 8oz bottles of milk for the week. They will be instructed to microwave their milk for 45 seconds and consume it 60 minutes before going to bed. Before going to sleep, the participants will put on the sleep activity watch to monitor their sleep (wakings; length of sleep). The sleep activity watch will track and store their nightly sleep over the six days of the study.
    • Participants in the control condition would be provided with six 8oz bottles of water for the week. They will be instructed to consume the room temperature water 60 minutes before going to bed. Before going to sleep, the participants will put on the sleep activity watch to monitor their sleep (wakings; length of sleep). The sleep activity watch will track and store their nightly sleep over the six days of the study.

    Independent Variable: Milk consumption (I manipulated whether participants drank warm milk or water)

    Dependent Variable: Sleep length (I measured the participants’ length of sleep using the sleep activity watch which recorded sleep time in hours and minutes over six days).

    5. Describe your expected resultsthat is, how participants will react or behave in each condition.

    Expected results: Participants who drank warm milk will sleep about 45 minutes longer than those who did not consume milk before bed.

    6. Which groups or populations would be most interested to learn about your results and why?

    Recommended populations:

    • People who have a difficult time sleeping could benefit from knowing easy remedies to improve their sleep.
    • Doctors and pediatricians could recommend this simple solution to their patients who want improved sleep.
    • Researchers may want to test whether alternative forms of milk have the same benefits (e.g., soy milk; almond milk; oat milk).

    7. Include your references using APA 7.

    • Yamamura, S., Morishima, H., Kumano-go, T., Suganuma, N., Matsumoto, H., Adachi, H., Sigedo, Y., Mikami, A., Kai, T., Masuyama, A., Takano, T., Sugita, Y., & Takeda, M. (2009). The effect of Lactobacillus helveticus fermented milk on sleep and health perception in elderly subjects. European Journal of Clinical Nutrition, 63(1), 100105.
    • Kitano, N., Tsunoda, K., Tsuji, T., Osuka, Y., Jindo, T., Tanaka, K., & Okura, T. (2014). Association between difficulty initiating sleep in older adults and the combination of leisure-time physical activity and consumption of milk and milk products: A cross-sectional study. BMC Geriatrics, 14, 118.

    Submission Guidelines:

    • Enter your answers to each prompt in a text entry box.
    • Be sure to provide enough detail to fully answer each prompt.
    • Include your APA 7 citations at the end of your assignment.