## 3 Results and Discussion
### Relationship of the Parameters with Heat Stress and Subclinical Mastitis  
The parameters that directly and indirectly affect heat stress and subclinical mastitisti in dairy cows were focused on in this study. The 21 parameters selected and used in developing the data-mining hub that detect the conditions of the dairy cows reflected the heat stress, subclinical mastitisti, or normal status of the cows more accurately than a single or few parameters alone. As shown in Figure 3, the correlation of temperature and temperature-humidity index (THI) to health conditions ranged from 0.75 to 1.00, while relative humidity (RH) scored a \(-\)0.75 correlation. Other parameters that have shown a positive correlation to health conditions are respiration rate and milk urea nitrogen (correlation = 0.75-1.00) and standing, drinking, and somatic cell count (correlation = 0.25-0.50). The parameters that have shown a high negative correlation to health conditions were body weight, rumen pH, rumination, lying/sitting, milk yield, and feed intake at \(-\)0.75-1.00 correlation, while milk lactose, milk protein, milk fat, milk solids nonfat (SNF), rumen temperature, body temperature, and body weight showed a slightly lower negative correlation at \(-\)0.25-0.50. When dairy cows are affected with heat stress or subclinical mastitisti, physiological body conditions of the animals (body weight, body temperature, rumen temperature, and rumen pH) were reduced. The bodyweight reduction is expected due to reduced feed intake when dairy cows are experiencing discomfort due to heat stress or when cows are affected with subclinical mastitisti. Additionally, rumination of the dairy cows was reduced when cows were affected by heat stress and subclinical mastitisti. The reduced rumination could have affected the reduction of rumen temperature and pH. Interestingly, the resting behavior (lying or sitting) of the dairy cows declined when affected by heat stress or subclinical mastitisti. Normally, dairy cows affected with illnesses or diseases decrease their moving behaviors and increase their resting behavior. The discomfort feeling of the dairy cows due to heat stress or subclinical mastitisti could have made the animals restless, thus increasing their standing behavior (correlation = 0.50). In terms of milk performance indexes, SNF, milk fat, milk protein, milk lactose, and milk yield declined when dairy cows were affected with heat stress or subclinical mastitisti. This result signifies that low-quality milk could diagnose dairy cows. The real-time measurement of milk performance could be a good indicator of heat stress or subclinical mastitisti in dairy cows. The positive correlations of the respiration rate, standing and drinking behaviors, and somatic cell count with the health condition of the dairy cows suggest that the welfare of dairy cows are negatively affected, as evidenced by its increased panting and restlessness, thus affecting the microorganism load in the milk. The findings of the correlation suggest that the parameters selected for the development of the data-mining hub in accurately detecting the health condition of dairy cows can be used as indicators of heat stress and subclinical mastitisti. The selected parameters used in the data-mining hub have proven relevant in health condition detection.  
Figure 2: Theoretical Framework of the proposed ThinkDairy data-mining hub.