Computer Science

How can machine learning algorithms be used to
improve Fraud detection in financial transactions?

How do the real-time object detection frameworks; YOLOv8, YOLOv9, and YOLOv10, comparatively perform in terms of model efficiency in detecting various objects in  adverse weather conditions?

How does the use of a priority queue and the implementation of Bellman-Ford and Dijkstra's algorithm affect the time complexity of solving the shortest path problem in weighted graphs?

How does increasing the number of epochs in an image GAN affect the loss values?

How do the two modern encryption algorithms AES and RSA differ in terms of computational efficiency and achieved security level?

How does Kruskal’s algorithm compare to Prim’s algorithm in finding a minimum spanning tree in a graph in terms of running time across graphs with varying densities?

To what extent does password length & variation of characters affect the entropy of a password?

To what extent does the M1 chip outperform its predecessors in terms of efficiency?

To what extent is the CNN diagnosis system effective in diagnosing skin cancer to be malignant or benign?

To what extent does the variance in sample rate, Sample to noise ratio and bit rate impact the file size and thus the practicality for it to be used in a streaming service. 

To what extent is a Fibonacci Heap more efficient than a Binary Heap when using Dijkstra’s Shortest Path Algorithm to calculate the most convenient MTR station from the Hong Kong MTR map?

To what extent may Artificial Intelligence replace human judges in sports?

How does the Convolutional Neural Network (CNN) architecture affect the accuracy, loss and training time of visual facial recognition?

To what extent are Convolutional Neural Networks based on DenseNet and ResNet architectures and Decision Trees efficient at making multi-class morphological classifications of RGB Telescopic Images?

To what extent does the use of backtracking in a binary tree improve the decision-making accuracy in a Tic-Tac-Toe game?

To what extent is the ability of an intelligent agent to operate in unfamiliar scenarios affected by the number of hidden-layer neurons in its neural network and the number of generations it is trained for?

To what degree does a used language in text data influence the compression of Entropy and Dictionary-based encoding using the Huffman and LZW algorithms?

How do different anti-aliasing algorithms (FXAA, TAA) compare to AI aliasing technologies (Deep Super-Sampling) with performance and image quality?

Investigating the Configurable Parameters of K-means Unsupervised Learning

How does the genetic algorithm compare to simulated annealing for solving the Min-Max Vehicle Routing Problem, in terms of time complexity and performance?

To what extent are machine learning models effective in accurately predicting the closing price of stocks?

To What Extent Do AES, RSA and 3DES Vary In Efficiency In Relation to Speed And Memory Usage With Increasing File Size

To what extent is Facebook’s algorithm for removal of hate speech operational in comparison with secondary-school intermediate level Python code?

Efficiency of the Interpolation and Jump Search Algorithm’s runtime in different array sizes based on the positioning of the key

Which facial detection algorithm is the most  appropriate for detecting masked faces?

To what extent can computer vision and convolutional neural networks be used to identify and translate American sign language?

How effective are predictive neural networks when used in reinforcement learning?

Here I basically trained different neural networks and compared how well they predict the sine functions.

To what extent are artificial neural networks successful at predicting the sine function?

Impacto de la multimedia educativa en el proceso de aprendizaje sobre uso de herramientas tecnológicas

Stocks is a type of investment vehicle and is used to represent the percentage of share in a 
company. Investors buy stocks that they think will rise in value over time. Stocks are pieces of 
paper that are made to carve out equity rights in a particular corporation and to divide them into 
smaller pieces so that they can be bought and sold

Comparative Analysis on the Predictive Power of Machine Learning  Algorithms vs. Traditional Time-Series Forecasting for Stock Price  Prediction of Top Five Companies in the KRX

This work aims to answer the question of how two tree structures - splay and AVL -
compare in terms of time complexity upon deleting large sets of values. Time complexity in
this context refers to the amount of time taken to execute a program. The approach chosen
to answer the question takes advantage of the Java nanoTime() method, which returns the
value of the system timer in nanoseconds.

How does the re-balancing algorithm of a splay tree compare to that of an AVL tree in terms of time complexity when deletion of values is carried out?

Assessing the use of machine learning algorithms for predicting the outcome of random number generators.

The EE investigates how the re-balancing algorithm efficiency of an AVL Tree compares to that of a Red-Black Tree in terms of time complexity upon insertion of (ordered) values.

Time complexities of the AVL Tree and Red-Black Tree insertion algorithms

This essay will focus on the insertion function and structure of Binary Search Trees, which links to Topic 5 Abstract Data Structures of the IB Computer Science syllabus The specific Binary Search Trees that this essay will specifically focus on will be the Scapegoat Tree and the Adelson-Velskii and Landis (AVL) Tree. These two trees were specifically chosen as they are commonly used self-balancing binary search trees. The time complexity of inserting a set of values into the two Binary Search Trees will be investigated.

To what extent does the time complexity of inserting values compare between Scapegoat Tree and Adelson-Velskii and Landis Tree’s rebalancing algorithm?

The comparison of accuracy in content filtering  between a custom Naive Bayes Machine Learning  model and pre-trained language models, DistilBERT  and ALBERT

To what extent do L1 and L2 regularization differ in mitigating overfitting in polynomial regression models under limited training samples and varying noise levels?

 To what extent do the different architectures of MongoDB and MySQL when used with Python affect their performance with large amounts of data insertions?

How does the performance of a Bidirectional LSTM neural network compare to that of a LinearSVC in terms of classification accuracy, precision, recall, and F1 Score when analysing sentiments in financial news?

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