Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…Traditional machine learning-based defect prediction models have been built since the early 2000s, and recently, deep learning-based models have been designed and implemented. …”

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

An efficient cache replacement strategy for the hybrid cache consistency approach by Haraty, Ramzi A.

“…Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. …”
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A low degree vertex elimination with high degree vertex selection heuristic for strongly connected dominating and absorbent sets in wireless Ad-Hoc networks. (c2011) by Markarian, Christine Hovsep

“…Experimental results show that our approach outperforms all previously known algorithms for the SCDAS problem.…”
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An efficient cache replacement strategy for the hybrid cache consistency approach in a mobile environment. (c2008) by Zeitunlian, Aline Michel

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On the complexity of various parameterizations of common induced subgraph isomorphism by Abu-Khzam, Faisal N.

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Predicting User Behavior over the Web by Al Safadi, Amal Adnan

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The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”