Practice B.4 Communication modelling and simulation with authentic IB Computer Science (CS) exam questions for both SL and HL students. This question bank mirrors Paper 1, 2, 3 structure, covering key topics like programming concepts, algorithms, and data structures. Get instant solutions, detailed explanations, and build exam confidence with questions in the style of IB examiners.
Machine translators are regularly used to translate text from one language to another. In spite of the advances that have been made in this field, the output may still need to be proofread by a human.
Describe two problems that these translators may encounter when translating from one language to another.
Google Translate is an algorithm whose function is to translate text from one language to another. One of the resources that it uses is the body of documents produced by the United Nations which are routinely translated by humans into various languages.
Discuss the reasons why Google Translate takes a probabilistic approach in preference to a cognitive rule-based approach.
An autonomous vehicle company uses neural networks to detect and respond to pedestrians and obstacles.
Outline two challenges that a neural network might face in accurately detecting pedestrians.
Explain one advantage of using neural networks in autonomous vehicles over rule-based systems.
An image processing system analyses colour images of architectural landscapes. The system compares any new images with existing ones stored in a knowledge base. The purpose of the system is to extend the knowledge base with images of the same scenes taken either from different perspectives or at different times of the year or with different weather conditions.
Explain how cluster analysis can be used to achieve the aims of the system that is described above.
Discuss the appropriateness of using genetic algorithms to compare the processed images with those stored in the knowledge base.
A wildlife conservation organization uses neural networks to track animal populations in a national park through camera trap images.
Outline how neural networks can identify different species in camera trap images.
Describe two potential limitations of using neural networks for this application.
Climate is cyclical as well as being affected by other factors.
(a) Explain what is meant by the term "climate". [2]
(b) Describe how the Earth's climate has changed over the past 800,000 years. [3]
(c) Explain how the Milankovitch cycles affect the Earth's climate. [4]
(d) Discuss the extent to which human activities have contributed to climate change. [6]
Identify four factors that could be used to define the current weather in a particular area on a particular day.
Suggest how values for these factors could be presented to show weather patterns over one year.
Outline how a computer system could be used to detect displacement trends in climate change.
Discuss the advantages and disadvantages of using the results from a computer simulation to predict long term climate change.
A finance company uses supervised learning in a neural network to assess creditworthiness of loan applicants.
Describe how supervised learning works in the context of credit assessment.
Discuss one ethical consideration related to using neural networks in credit assessment.
A social media platform uses unsupervised learning to identify user interests and recommend content.
Describe how unsupervised learning works in the context of user interest identification.
Explain one advantage and one limitation of using unsupervised learning for content recommendations.
A healthcare system uses a neural network to detect tumors in medical images.
Define the term "pattern recognition" and explain its role in this application.
Identify two factors that could impact the accuracy of tumor detection.
A parasite is destroying olive trees in a region in southern Europe. This area is monitored by taking aerial digital images at midday each day. A neural network is then used in the analysis of these images.
Many companies now use an automated response system when answering basic telephone queries from customers. This system uses speech analysis together with recorded messages.
Explain why the content of the messages given by these systems must be carefully chosen.
Outline why neural networks need to be trained before they can be used in this analysis.
Genetic algorithms follow an iterative process in developing a solution to a problem.
Outline the steps involved in this iterative process.
Explain why supervised learning may be preferred to unsupervised learning for training these networks to make predictions on the progress of this parasitic disease.