Mosa Muntadher Mohammed Mosa’s scientific contributions

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Publications (1)

Figure 5.25 Scatter Plot of Stress Scores vs Specific Gravity (SG) generated using the Machine Learning classification tools in MATLAB. When data of uncertain accuracy are excluded, it is observed that the closer the specific gravity (SG) value is to 1.00, the higher the stress scores of the subject. However, when these uncertain data are included in the calculation, outliers are excluded, and a direct proportional relationship is observed between stress scores and specific gravity. This observation differs from the results obtained from the Analysis of Variance (ANOVA), which takes all data samples into account and indicates that groups with stress have a higher SG value than the rest. Our hypothesis posits that a high specific gravity is an indication of stress, as the body produces more substances in response to stress. When all data are taken into account, the results align with this hypothesis.
Post-experiment of washing and sterilising the equipment.
Urinalysis for Stress Level Identification
  • Experiment Findings
  • File available

February 2023

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173 Reads

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Mosa Muntadher Mohammed Mosa

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Yu Jia Qi

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Ammar Khaled Salem Saber

The experiment was conducted using Analysis of Variance (ANOVA) and MATLAB. Urine measurements were taken with a CLINITEK Novus device in the Clinical Engineering Simulating lab at Universiti Teknologi Malaysia (UTM). Various samples were selected to examine and analyse the relationship between urinalysis and stress levels, as detailed in the methodology. The findings suggested that higher specific gravity (SG) levels and increased substance production in response to stress are indicative of elevated stress levels. Similarly, high pH or urobilinogen (UBG) levels suggest increased alkaline production, another potential sign of stress. With the use of MATLAB, it was observed that a subject's ability to cope with their environment improved as their stress scores increased. The relationship between urinalysis and stress levels has been a long-standing area of research interest. However, there is still no widely accepted methodology for measuring this relationship. The application of MATLAB in this study also had its limitations, particularly in terms of the number of subjects required. Despite these limitations, this study contributes to the ongoing research in this field and provides a basis for future studies.

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