An expert system is designed to diagnose a medical condition based on symptoms. The system uses the following certainty factors (CF) for two symptoms:

    1. Symptom One: Fever (CF = 0.9)

    2. Symptom Two: Cough (CF = 0.6)

The expert system then checks a final symptom:

    3. Symptom Three: Body ache (CF = 0.7)

The school has introduced an online ticketing app to make it easier for students to book and pay for tickets to school drama and band performances. Students use the app to browse available performances and book tickets. After selecting the tickets, they make payments directly through the app to the bank. Once the payment is processed, they receive a confirmation email with their ticket(s).

A teacher has set up a spreadsheet to calculate the average mark for each student based on their results from the three tasks completed during the course. This average mark is then used to calculate a course grade using the Grade Table. It then checks the grade and if the student has received an A for the course, they will be receiving an award at the end-of-course presentations night.

A medical centre has decided to implement a new appointment management system to replace their paper-based appointment book.

Stimulus for Question 13(b)

The following shows an extract of the information stored in the system’s Patient table:

A local sports club is updating the system that manages its membership. They want to employ a specialist software development company to design a working model of the updated system.

ShopSmart is a global e-commerce company that collects vast amounts of data from its customers. The data includes purchase history, user behaviour on the website, customer feedback, product reviews, and location data. ShopSmart has been expanding rapidly and operates in multiple regions, leading to an increasing amount of data being generated daily. The company aims to utilise this data to improve customer experience, optimise inventory, predict trends, and personalise product recommendations.

To manage this growing volume of data, ShopSmart has implemented a data warehousing solution that consolidates data from multiple sources into a central repository. The company also uses advanced simulation and data modelling tools to predict future sales trends and to optimise its supply chain operations. Additionally, the company has automated its inventory management system to ensure timely stock replenishment based on the predicted demand.

A medical expert system can use a flowchart to determine possible causes of a fever based on symptoms. The system follows the following IF-THEN rules to guide decision-making:

1. IF the patient has a fever → THEN check for a sore throat.
2. IF the patient has a sore throat → THEN check for white spots in the throat.
3. IF white spots are present → THEN diagnose strep throat and recommend a doctor visit. 
4. IF no white spots → THEN diagnose flu and suggest rest and fluids. 
5. IF no sore throat but a runny nose and sneezing → THEN diagnose common cold and recommend home care 
6. IF no sore throat and no runny nose and sneezing → THEN run further tests

A company has implemented a new customer relationship management (CRM) system.

During the testing and evaluation phase, the project team must verify and validate the system to ensure it is effective and reliable.

A book shop tracks its monthly sales performance using spreadsheet software. The dataset below records sales revenue, expenses, profit, units sold, and customer satisfaction across different regions and products over three months. The company relies on this data to identify trends and improve decision-making.

Please refer to the following sample spreadsheet to answer Question 20.

HealthPlus, a healthcare provider, is adopting an enterprise computing system to manage patient records, appointments, and medical histories. The system will integrate data from various sources, including electronic health records (EHR), wearable devices, and lab results. HealthPlus plans to use machine learning and statistical modelling to analyse big data for predicting patient outcomes, identifying trends, and improving treatment plans.

The implementation plan involves ensuring data privacy and compliance with legal regulations, as well as training staff to use the new system effectively.

A large city museum uses advanced technologies to enhance its operations and visitor experience. The museum employs online analytical processing (OLAP) to analyse visitor data and uses intelligent systems incorporating virtual reality (VR) and touch and gesture interfaces in its interactive exhibits.

A data scientist is undertaking a project that analyses player statistics from a local football app used for game and team management. The data visualisations will be used to predict future representative players.

A large e-commerce company collects personal data from millions of users, including their purchasing habits, location, and browsing history. The company uses this data to create personalised advertisements and optimise its services. However, concerns have been raised about the privacy of users, the ethical implications of data collection, and the environmental impact of maintaining large-scale data centres.

A healthcare organisation is developing a data visualisation tool to track patient recovery rates from various treatments. The tool aggregates patient data from electronic health records (EHRs), surveys, and follow-up assessments. However, the data collection process is focused primarily on patients from urban hospitals, with limited data from rural or remote healthcare facilities.