Kidney is one of the vital organs in a human body while ironically, chronic kidney disease (CKD) is one of the main causes of death in the world. Due to the low rate of loss of kidney function, the disease is often overlooked until it is in a really bad condition. Dysfunctional kidney may lead to accumulation of wastes in blood which would affect several other systems and functions of the body such as blood pressure, red blood cell production, vitamin D and bone health. Machine learning algorithms can help in classifying the patients who have CKD or not. Even though several studies have been made to classify CKD on patients using machine-learning tool, not many researchers perform pre-processing and feature selection technique to obtain quality and dependable result. Machine learning used with feature selection techniques are shown to have better and more dependable result. In this study, feature selection methods such as Random Forest feature selection, forward selection, forward exhaustive selection, backward selection and backward exhaustive selection were identified and evaluated. Then, machine learning classifiers such as Random Forest, Linear and Radial SVM, Naïve Bayes and Logistic Regression were implemented. Lastly, the performance of each machine-learning model was evaluated in terms of accuracy, sensitivity, specificity and AUC score. The results showed that Random Forest classifier with Random Forest feature selection is the most suitable machine learning model for classification of CKD as it has the highest accuracy, sensitivity, specificity and AUC with 98.825%, 98.04%, 100% and 98.9% respectively which outperformed other classifiers.

Electromyography is a study of muscle function through the analysis of electrical signals emanated during muscular and muscle contractions. In the post-stroke rehabilitation process, monitoring of muscle activity is very important to know the developments of muscle strength. EMG signals, which produced by muscle activity have information such as muscle contractions, muscle strength and muscle weakness. Rehabilitation process that takes a long period of time can cause muscle fatigue, and the rehabilitation becomes inefficient. The objective of this research is to analyze the muscle fatigue during arm movements by using EMG signals. In this study, deltoid and biceps are monitored by using EMG and the signal are analyzed by using MATLAB. Five healthy subjects are selected to perform the rehabilitation in the experiments. Functional and fundamental movements are used in the data collections. The mean as a feature from a frequency domain is proposed to be used in the analysis. The results show that the signal contractions from deltoid and biceps muscles decreased constantly by the time. In the process of rehabilitation, the stroke sufferers should not do the exercise in a long period of time.

Halloysite nanotubes (HNTs) reinforced polylactic acid (PLA) nanocomposite films were utilized for different applications, such as packaging, drug recover and other applications. The incorporation of plasticizer into polymer nanocomposites modifies some of their functional and physical properties, such as increasing flexibility, moisture sensitivity, in addition to other functional properties. However, the effects of Polyethylen glycol (PEG) and sesame oil (SO) on selected physical properties (moisture content (MC), contact angle (CA) and water vapor permeability (WVP)) of PLA)/HNTs bionanocomposite films were examined. The plasticized PLA/HNTs (5 wt % HNTs loading) bionanocomposite films were prepared using the solution casting method at room temperature. The concentrations of each plasticizer that used indivisually were (0, 10, 20 and 30 wt %). Results show that the increasing of PEG content led to increase in moisture content and water vapor permeability and decrease in contact angle of the films. On the contrary, the increasing of SO levels led to decrease in moisture content and water vapor permeability and increase in contact angle of the films. Differences in measured physical properties of films with plasticizer type and concentration may be attributed to differences in the hydrophilic and hydrophobic properties of the plasticizers. SO was the plasticizer that showed the most interested effect (low moisture content and water vapor permeability) on PLA/HNTs films for food packaging applications compared to PEG.

An operation theatre (OT) is a special room inside the hospital where medical surgery is carried out by a surgeon with the help of medical personnel. Technical standards or requirements which have been set for heating, ventilation and air conditioning (HVAC) inside an operation theatre is important not only for the comfort of surgeon, patient, and medical personnel, but also to reduce the risk of surgical site infection during surgery. This research focus on Minor Operation Theatre (MOT) which is dental surgery room at Universiti Malaysia Perlis Health Centre with room dimensions of 2.89 m(H)×3.12 m(W)×3.4 m(L) is used for numerical analysis. The air flow supplied to the MOT is from single unit air-conditioning system. Computational Fluid Dynamics (CFD) analysis is a part of an investigation to determine the air flow and temperature distribution inside the MOT. A simulation conducted by using ANSYS Fluent only consider dry air inside MOT. Therefore, the main aim of this research is to compare and analyze the simulation of dry air conducted with previously obtained experimental data of humid air distribution inside the MOT. The comparison of humid and dry air temperature throughout the MOT shows that the difference is 25.3%. The average temperature of humid air inside the MOT is 21.8 °C while for dry air is 16.3 °C. Moreover, the cooling capacity of humid air and dry air are 2.23 kW and 1.64 kW respectively. Thus, the difference between humid air and dry air-cooling capacity is 26.5%. However, the dry air simulation and humid air simulation is the same if only the process is considered as simple cooling.

This paper is presented to document a development process of automated system for the spray-painting process and for the purpose of advantage of implementation of automation to the production line instead of manual spray process and know-how of thickness control when applying three spray guns compared to single gun as normally implemented in automated spraying system. Three spraying could reduce the process time to spray the workpieces, in this case, is airplane wing’s parts built from composite material. But these three guns automations system comes with challenging tasks in order to find an even thickness of overlapping spray pattern coming from these three separated guns. Ultimately, various studies on atomization parameters and other factors resulted in successful mass production.