Tiba Zaki Abdulhameed- Doctor of Philosophy
- Nahrain University
Tiba Zaki Abdulhameed
- Doctor of Philosophy
- Nahrain University
About
10
Publications
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Introduction
Tiba Zaki Abdulhameed currently works as a lecturer at the department of computer science , Al-Nahrain university, and adjunct faculty at Western Michigan University. Tiba does research in Natural Language Processing, Words Embeddings, and Algorithms and Artificial Intelligence.
mainly coding with
Bash scrpits, Python, and C
Skills and Expertise
Current institution
Publications
Publications (10)
Word clustering is a serious challenge in low-resource languages. Since words that share semantics are expected to be clustered together, it is common to use a feature vector representation generated from a distributional theory-based word embedding method. The goal of this work is to utilize Modern Standard Arabic (MSA) for better clustering perfo...
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm designed to identify clusters of various shapes and sizes in noisy datasets by pinpointing core points. The primary challenges associated with the DBSCAN algorithm involve the recognition of meaningful clusters within varying densities datas...
investigate the speed up and efficiency of the parallel algorithms.
Introduction: Coronavirus disease 2019 (COVID-19) is one of the serious infectious diseases that is caused by a specific virus called syndrome coronavirus 2 viruses (SARSCoV-2). The rapid spread of COVID19 raises serious concerns about the globally growing death rate. Currently, cases are doubled in one week around the world. Recorded data shows th...
Utilizing Machine Learning Models to Predict the Car Crash Injury Severity for Elderly Drivers
Abstract—
Car crash can cause serious and severe injuries that impact people every day. Those injuries could be especially damaging for elderly drivers of age 60 or more. The goal of this research is to investigate the risk factors that contribute to cra...
Abstract
Background :Designing accurate predictive models for injury severity prediction of traffic accidents of the elderly population is a critical task for transportation systems.
Objective: A set of influential factors are selected to build five machine learning-based predictive models to classify the severity of injuries.
Methods: Machin...
Neural word embedding, such as word2vec, produces very large features' vectors. In this paper, we are investigating the length of the feature vector aiming to optimize the word representation results, and also to speed up the algorithm by addressing noise impact. Principal Component Analysis (PCA) has a proven record in dimensionality reduction as...
