Ground penetrating radar (GPR) is a non-destructive tool for subsurface investigation becomes an emerging trend in many applications especially in detecting infrastructure utilities. However, interpreting of GPR data in terms of target’s geometry is remained a challenging task due to the existence intra/inter-class variations and subtle changes of hyperbolic signature pattern in GPR data. To addressed this issue, this paper proposes to classify the basic shape (i.e. cubic, cylindrical and disc) of buried object using multilayer perceptron neural network. The GPR raw data firstly is pre-processed based on A-scan and B- scan GPR data. Then, the combined statistical features with gray level co-occurrence matrix (GLCM) and Hu moment invariants are extracted from A-scan and B-scan. The extracted features are then fed as input to multilayer perceptron to classify the shapes (cubic, cylindrical and disc) of buried object. Based on the experiment conducted, the highest recognition rate has been achieved is about 83.3%. Thus, the proposed method of using combined statistical with GLCM and Hu moment invariants features to classify shape of buried object using multilayer perceptron is promising.

Malaria is categorised as a dangerous disease that can cause fatal in many countries. Therefore, early detection of malaria is essential to get rapid treatment. The malaria detection process is usually carried out with a 100x magnification of thin blood smear using microscope observation. However, the microbiologist required a long time to identify malaria types before applying any proper treatment to the patient. It also has difficulty to differentiate the species in trophozoite stages because of similar characteristics between species. To overcome these problems, a computer-aided diagnosis system is proposed to classify trophozoite stages of Plasmodium Knowlesi (PK), Plasmodium Falciparum (PF) and Plasmodium Vivax (PV) as early species identification. The process begins with image acquisition, image processing and classification. The image processing involved contrast enhancement using histogram equalisation (HE), segmentation procedure using a combination of hue, saturation and value (HSV) color model, Otsu method and range of each red, green and blue (RGB) color selections, and feature extraction. The features consist of the size of infected red blood cell (RBC), brown pigment in the parasite, and texture using Gray Level Co-occurrence Matrix (GLCM) parts. Finally, the classification method using Multilayer Perceptron (MLP) trained by Bayesian Rules (BR) show the highest accuracy of 98.95%, rather than Levenberg Marquardt (LM) and Conjugate Gradient Backpropagation (CGP) training algorithms.

Thermal comfort is a part of indoor environmental quality that should be considered to ensure the occupants' well-being. Unconducive buildings not only bring occupants discomfort but also tend to affect health, disrupt the process of teaching and learning, and reduce work productivity. Thus, this study determines the thermal condition of existing workshop buildings used in Technical and Vocational Education and Training (TVET) implementation. ASHRAE Standard 55 (2017) is referred to in the determination of thermal comfort involving objective measurements and subjective measurements. Observation methods of environmental variables such as air temperature, radiant temperature, air velocity, relative humidity is observed. Evaluations of comfort are based on occupant surveys and environmental measurements. A total of 257 people completed a questionnaire distributed at three technical institutions in Kedah, Malaysia. According to the findings, the average thermal sensation vote is 1.85, which leads to 66.5% of respondents feeling discomfort. Meanwhile, the adaptive model analysis showed that the workshop environmental conditions were out of the comfort zone and did not comply with the ASHRAE 55 standard. Hence, the thermal discomfort factors from the occupants' perspective were identified and widely discussed. As a result, the research findings will benefit parties involved in new building construction or existing building renovations to improve indoor air quality.

Concrete is widely used in for construction purposes due to many advantageous properties. Depending on the density, concrete can be categorized as either conventional or lightweight. However, incorporating sustainable and eco-friendly elements like Expanded Polystyrene (EPS) can reduce the weight of concrete resulting in construction material. The main objective of this research is to investigate the effects of the inclusion of EPS towards the physical characteristics of concrete such as compressive strength, flexural strength, density and water absorption. This research also aim to analyze the soundproofing capabilities of wall panels produced using EPS. The study focuses on evaluating percentages (10%, 15% and 20%) of EPS as aggregates in terms of their impact on mechanical properties, physical properties and soundproofing qualities, in lightweight concrete. A total of 36 cube samples measuring 100 mm x 100 mm x 100 mm were prepared for testing at both 7 day and 28-day curing periods. In addition, 12 wall panel samples measuring 100 mm x 100 mm x 500 mm and another four wall panel samples measuring 600 mm x 600 mm x 40mm for analysis. Findings of the research indicate that the desired targets were met for water absorption (10%) density (15%) and soundproof performance (20%). During the 28-day strength test, the compressive strength decreased by 21.86%, 30.57% and 35.56% when replacing 10%, 15% and 20% of the material respectively. Lightweight concrete achieved a value of 19.45 MPa with a replacement of only 10% EPS. However, the samples, with a replacement of 15% and 20% did not reach this compressive strength level. This study demonstrates that EPS can be effectively utilized in applications. There was a reduction for the flexural strength ranging from 13.42% to 27.89% compared to the control mix when replacing with EPS at rates of 10%, 15% and 20%. This study succeeded in producing the novel discovery of the use of EPS in contributing to reducing overall structure weight, which in turn helps decrease energy consumption during transportation and construction processes.

Hybrid System in Industrialised Building System (IBS) is combining IBS components with conventional method. Delay has become a familiar issue in construction field. The issues pertaining structure stability when using this combination method leads to delay while installing these two different method components. The combination also could cause a defect jointing. In Industrialised Building System (IBS), even though it is one of the technology methods that can save times, cost, and reduce labour in construction, but there still have constraints such as design issues, lack of experienced worker, and internal and external issues that can affect cost problems. In this study, the suitability structure based on combination method is investigated to discover the affected factors of suitability structure by using Hybrid System which is the aim of this study. The data analysis from quantitative survey shows that the top three affecting the building structure are: 1) weather effects with highest mean of 6.25 followed by 2) delay of jointing process at 6.03 and 3) defects from monolithic jointing at 5.93. Therefore, the amount of average data obtained shows that the most affected structure is the Hybrid System.