Browsing Computing Dissertations and Theses by Date Published
Now showing items 1-20 of 93
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A new approach for the prevention of sinkhole attack in mobile wireless sensor networks
(2023)RESEARCH QUESTIONS Main research question is: Is it possible to prevent a sinkhole attack on MWSN using a combination of Blowfish and RSA algorithms? Then it was broken down into the following questions: Q1: What would ... -
A development framework for software integration projects – case study: Web app Integration with OpenWeather API
(2023)RESEARCH QUESTIONS Q1. What are the key stages of the Software Development Life Cycle (SDLC) implementation in software integration projects, and how do they contribute to the successful integration of software systems? Q2. ... -
Critical comparison of statistical and deep learning models applied to the New Zealand Stock Market Index
(2022)RESEARCH QUESTIONS 1. What are the critical fundamental determinants of the NZX 50 Index movements? 2. How can effective forecasting models based on HWES and ARIMA methodologies be devised and applied with high precision ... -
New Zealand Stock Market prediction using sentiment analysis
(2022)In this research, I addressed this gap and tried to focus on the New Zealand Stock Exchange (NZX). For the proposed model, I used the financial news only, for the SA and for the stock data I took five of the biggest New ... -
Identification of queen-less beehives using signal enhancement techniques and neural networks
(2021)Beekeeping has a long history of about 180 years in New Zealand. The first group of honey bees introduced has expanded to approximately one million registered beehives by now. An increasing number of residents have been ... -
A CNN-based identification of honeybees' infection using augmentation
(2021)RESEARCH QUESTIONS: [Are standard images classified accurately using Convolutional Neural Network (CNN) or transfer learning method?] Can varroa destructor mite be identified correctly from a small number of low-quality ... -
Deep correlation learning for urban air quality: Analysis and prediction in New Zealand
(2021)RESEARCH QUESTIONS: • RQ1: Can we relate all the variables involved in air-quality monitoring to establish which ones have dependencies on the others? • RQ2: Can we further model this inter-relationship and automate ... -
A framework for analysis and comparison of deepfakes detection methods
(2021)With the rise of AI (Artificial Intelligence), people can already utilise Deepfakes technology to generate fake pictures and videos increasingly. Similar to all technologies, while bringing benefits, this technology also ... -
A hybrid intelligent intrusion detection system for advanced persistent threats
(2020)RESEARCH MOTIVATION: The objective of this research is to investigate how to increase the detection rate and increase the tracking rate of APT and TA in their early attack phases within an environment of distributed ... -
Activity recognition and resident identification in smart home environment
(2020)World’s population is ageing rapidly. There have been various efforts to improve the quality of life for elderly. Ambient assisted living is one possible solution which enables elderly or disabled people to live a better ... -
Analysis and evaluation of quantum key distribution protocols
(2020)Quantum Key Distribution (QKD) which is the name of cryptography in quantum environment act as the highest developed area in quantum communication and computing technology (QCIT). QKD is inventive technology which utilize ... -
Analysis of the metrics that influence the performance of SOAP/XML message routing in ESB Applications
(2020)RESEARCH QUESTION: What are the key performance metrics that influence the performance of SOAP/XML message routing tasks in ESB Applications?\ TASKS: Finding ESB performance evaluation set up and method from existing ... -
Visualising vein pattern based on sparse auto-encoder algorithm
(2020)RESEARCH QUESTIONS: Q1: How is it possible to apply deep learning algorithms such as Autoencoder (AE) instead of current simple neural networks with limited capabilities for uncovering vein pattern? Q2: Can deep learning ... -
Automatic assessment of dysarthric severity level using audio-video cross-modal approach in deep learning
(2020)Dysarthria is a speech disorder disease that can have a significant impact on a person's daily life. Early detection of the disease can put the patient into therapy sessions more quickly. Researchers have established various ... -
Intelligent beehive status monitoring in noisy environment
(2020)Artificial neural network (ANN) based bee-hive monitoring algorithm does not perform very efficiently in noisy environments. Although an ANN based bee-hive monitoring algorithm using audio signals of a beehive could perform ... -
An edge-based steganography algorithm for hiding text into images
(2019)RESEARCH QUESTIONS: • How can I improve existing steganography methods in terms of capacity and transparency? • How can I reduce the complexity of existing steganography methods? • How can I increase the robustness ... -
Detecting Sybil attack in mobile wireless sensor networks using observer nodes
(2019)RESEARCH QUESTIONS: What lightweight, scalable algorithm can be developed to detect the Sybil nodes in MWSNs? Then, I broke it to more detailed questions as follows: How many observer nodes would be enough for a ... -
Support Vector Machine (SVM) aggregation modelling for spatio-temporal air pollution analysis
(2019)RESEARCH QUESTIONS: 1. Dealing with long term historical data of spatio-temporal is always challenging. SVM ensemble and other methods are used to handle long term historical data, but these methods result in slow ... -
Modelling wear patterns on footwear outsoles
(2019)ABSTRACT: The outsoles of footwear develop nicks, cuts, and tears via repeated exposure to the abrasive forces that occur between the outsole and the ground. These abrasions result in the formation of characteristics ... -
Incremental and parallel learning algorithms for data stream knowledge discovery
(2018-02)Incremental and parallel are two capabilities for machine learning algorithms to accommodate data from real world applications. Incremental learning addresses streaming data by constructing a learning model that is updated ...
