The Intensive Care Unit (ICU) ward situation tend to be very intense since the patients who are placed in the wards are usually critical condition patients. These patients need an intensive care by the nurses and physician since their condition are not very stable. Therefore, the nurses and physicians need to monitor them very frequent. So, the idea of this monitoring system is mainly to ease the nurses work by reducing monitoring frequency. This monitoring system also purposely built to make them alert about their patient thus, can minimize the risk of patients who are monitored. This monitoring system is using the microcontroller (Arduino Uno) which is connected to the laptop via Bluetooth to transfer the data of heart rate and body temperature of the respondent. This data was sense through Heart-Rate Grove sensor and LM35 temperature sensor. The data were processed and displayed on the laptop for every minute continuously. Different colour of LED was used as an indicator to notify the condition of the respondent’s pulse or body temperature either it was in high or low condition as a warning. For young adult with fever respondent, it shows the result of 81 bpm of heart rate and 37.63°C of body temperature with 3.83% and 0.65% of the Mean Absolute Percent Error (MAPE) respectively. This monitoring system has successfully built and able to display the data of the heart rate and body temperature of the respondent for every minute and able to facilitate autonomous monitoring tasks in the future.

Background: The emergence of COVID-19 as a pandemic has resulted in the need for urgent development of vaccines and drugs and the conduction of clinical trials to fight the outbreak. Because of the time constraints associated with the development of vaccines and effective drugs, drug repurposing and other alternative treatment methods have been used to treat patients that have been infected by the SARS-CoV-2 virus and have acquired COVID-19.Objective: The objective of this systematic scoping review is to provide an overview of the molecular mechanism of action of repurposed drugs or alternative treatment medicines used to attenuate COVID-19 disease.Method: The research articles or gray literature, including theses, government reports, and official news online, were identified from four databases and one search engine. The full content of a total of 160 articles that fulfilled our inclusion criteria was analyzed and information about six drugs (ritonavir, lopinavir, oseltamivir, remdesivir, favipiravir, and chloroquine) and four Traditional Chinese Medicines (Shuang Huang Lian Kou Fu Ye, TCM combination of Bu Huan Jin Zheng Qi San and Da Yuan Yin, Xue Bi Jing Injection, and Qing Fei Pai Du Tang) was extracted.Results: All of the repurposed drugs and complementary medicine that have been used for the treatment of COVID-19 depend on the ability of the drug to inhibit the proliferation of the SARS-CoV-2 virus by binding to enzyme active sites, viral chain termination, or triggering of the molecular pathway, whereas Traditional Chinese Medicine plays a pivotal role in triggering the inflammation pathway, such as the neuraminidase blocker, to fight the SARS-CoV-2 virus.

Analysing data can be quite a challenge sometimes due to the nature of the data and the vast options of methods and techniques that can be used on the data. In this study, for example, a six years Cleft Lip and Palate dataset were gathered on these patients’ conditions in the quest to identify the contributing factors for a successful pre-graft orthodontic treatment. The challenges faced was in the small number of datasets and imbalance sample class. Therefore, this study had taken a step back and tried to approach the dataset with a combination of unsupervised and supervised learning methods to tackle the challenges by incorporating clustering - for testing records creation and; resampling - for balancing sample class. We also observed if the auto-created testing records are replaceable with the manually selected testing records by looking at the performances of the classification models. Based on the feature that was selected, k-Means and PAM were implemented as the clustering algorithm using the Euclidean formula as the distance measure. Resampling was done using SMOTE and Random Forest as the classification model. When the comparison was done on the models, the ones that were fed by resampled training records showed an increase in the AUC values and decrease in the OOB error. Comparable results were also achieved between the training records produced by PAM and by manual selection as both models, based on the AUC values, was classified as excellent classification models.

Several methods have been used to estimate the generalized extreme value (GEV) distribution namely, the standard method of maximum likelihood (MLE) and the probability-weighted moment (PWM). These methods reported having unreliable estimation of parameters when it is involved in a small sample of an extreme event. This could lead to serious effect especially in civil engineering i.e. estimation of extreme streamflow is needed for dam design calculation. As an alternative, penalty function added to MLE to give a better performance of GEV parameter estimation known as the generalized maximum likelihood (GML). The objective of this study is to model the extreme rainfall observed from several stations in Sabah using an approach of the Bayesian analysis. This method is similar to the GML if the information of the penalty function is the same as the prior of the Bayesian. The results from the Markov Chain Monte Carlo with by Metropolis-Hastings the approach can be used to predict the return level of extreme rainfall.

Background: The emergence of COVID-19 as a pandemic has resulted in the need for urgent development of vaccines and drugs and the conduction of clinical trials to fight the outbreak. Because of the time constraints associated with the development of vaccines and effective drugs, drug repurposing and other alternative treatment methods have been used to treat patients that have been infected by the SARS-CoV-2 virus and have acquired COVID-19. Objective: The objective of this systematic scoping review is to provide an overview of the molecular mechanism of action of repurposed drugs or alternative treatment medicines used to attenuate COVID-19 disease. Data Sources: The research articles or grey literature, including theses, government reports, and official news online, were identified from 4 databases and 1 search engine. The full content of a total of 160 articles that fulfilled our inclusion criteria was analyzed and information about 6 drugs (ritonavir, lopinavir, oseltamivir, remdesivir, favipiravir, and chloroquine) and 4 traditional Chinese medicines ( Shuang Huang Lian Kou Fu Ye , TCM combination of Bu Huan Jin Zheng Qi San and Da Yuan Yin, Xue Bi Jing Injection and Qing Fei Pai Du Tang ) were extracted. Conclusions: All of the repurposed drugs that have been used for the treatment of COVID-19 depend on the ability of the drug to inhibit the proliferation of the SARS-CoV-2 virus by binding to enzyme active sites, viral chain termination, or triggering of the molecular pathway, whereas traditional Chinese medicine has a pivotal role in triggering the inflammation pathway, such as the neuraminidase blocker, to fight the SARS-CoV-2 virus. This review provides an insight to experimental validation of drugs and alternative medicine used for the treatment and control of COVID-19.