Graduate Studies News

In recent years, deep learning models have provided various applications in various fields, especially in the medical fields such as neuroscience. Thus, ensuring the interpretation of the results predicted by deep learning models has been an important challenge, especially exploring the hidden layers in these models, and this is called black box interpretation.

This research presented two models for classifying data on graduates in general, and data on some specializations in particular, by employment status (employed, unemployed). This was through applying machine learning algorithms to data from the Labor Force Survey carried out by the Palestinian Central Bureau of Statistics.

The researcher created a classification model using five different algorithms - Random Forest, DT, XGBoost, KNN, and AdaBoost for graduate data in general, and three algorithms were applied to classify the data according to university specialization.

In her thesis, the researcher touched on the effect of honey samples depending on the type of blossoms. There were some effects on cell growth in the laboratory. Thus, these samples reduced cancer cell growth, inflammation, and oxidation, in addition to limiting the spread of cancer cells.