Nowadays, water pollution has become a global issue affecting most countries in the world. Water quality should be monitored to alert authorities on water pollution, so that action can be taken quickly. The objective of the review is to study various conventional and modern methods of monitoring water quality to identify the strengths and weaknesses of the methods. The methods include the Internet of Things (IoT), virtual sensing, cyber-physical system (CPS), and optical techniques. In this review, water quality monitoring systems and process control in several countries, such as New Zealand, China, Serbia, Bangladesh, Malaysia, and India, are discussed. Conventional and modern methods are compared in terms of parameters, complexity, and reliability. Recent methods of water quality monitoring techniques are also reviewed to study any loopholes in modern methods. We found that CPS is suitable for monitoring water quality due to a good combination of physical and computational algorithms. Its embedded sensors, processors, and actuators can be designed to detect and interact with environments. We believe that conventional methods are costly and complex, whereas modern methods are also expensive but simpler with real-time detection. Traditional approaches are more time-consuming and expensive due to the high maintenance of laboratory facilities, involve chemical materials, and are inefficient for on-site monitoring applications. Apart from that, previous monitoring methods have issues in achieving a reliable measurement of water quality parameters in real time. There are still limitations in instruments for detecting pollutants and producing valuable information on water quality. Thus, the review is important in order to compare previous methods and to improve current water quality assessments in terms of reliability and cost-effectiveness.

Milk is a valuable contributor to a healthy diet as it contains nutritional components such as fats, proteins, carbohydrates, calcium, phosphorous and vitamins. This research aimed to differentiate milk from animal, plant and human sources based on light propagation and random-laser properties. Experimental, statistical and theoretical analyses were used. Light propagation in different types of milk such as almond milk, oat milk, soy milk, fresh milk, goat milk and human breast milk was measured using the spectrometry method. Near-IR and visible light transmission through the diluted milk samples were compared. Soy milk and fresh milk have the highest absorbance and fluorescence of light, respectively, due to a high content of fat, protein and carbohydrates. Principal component analysis was used to determine the accuracy of the experimental results. The research method is comprehensive as it covers light propagation from 350 nm to 1650 nm of wavelength range and non-intrusive as it does not affect the sample. Meanwhile, analysis of milk was also conducted based on random-laser properties such as multiple emission peaks and lasing threshold. Higher fat content in milk produces a lower random lasing threshold. Thus, we found that milk from animals, plants and humans can be analyzed using light absorption, fluorescence and random lasers. The research method might be useful for future study of milk contaminants that change the properties of milk.

Ruby is one of the most precious gemstones on Earth that is always high in demand especially in the jewelry industries. Due to its high value and very expensive, a lot of imitation of ruby has been made. This results in the rising of more complicated issues as gemologists need to perform the grading valuation very carefully and precisely. The current and common grading techniques mostly depend on human vision, which eventually leads to error. This paper aims to analyze the clarity of rubies gemstones using Charge-Coupled Device (CCD). The CCD detects the light intensity and then convert the light intensity value into the voltage value. The CCD sensor is very special in its architecture design, consisting of more than 1000 very small pixels that are sensitive to light sources. Based on the previous research, CCD has high sensitivity to laser light source with wavelength range within 430 nm to 650 nm. This research is going to prove that CCD is able to detect the clarity of various grading of the pink to blood-red ruby stones.

Ultrasonography (US) is one of the procedures to monitor the growth of renal size in diagnose kidney disease. However considering the complexity of renal size, this procedure leads to inter-observer variability and poor repeatability. Given images from Abdominal CT scan, a level set thresholding and combination of logical and arithmetic operation based method was developed to calculate the automated feature description of renal size. This is achieved by applying 2D CT scan image into image segmentation and feature extraction where thresholding and morphological segmentation method are conducted. Then, parameters of the kidney such as perimeter, area, major axis and minor axis were measured and analyzed in classification step. As a result, analysis on the kidney size between subjects who are normal and the results from the studies has shown capability to classify correctly the size of kidneys about accuracy of 80% to 81% in terms of the kidney's relative axis which is the ratio of right kidney and left kidneys. In addition, the method in measurement kidney size is compared between manual method and automated method and results shows that the accuracy of the automated method in terms of compactness is about 91% to 95.

Water- and food-related health issues have received a lot of attention recently because food-poisoning bacteria, in particular, are becoming serious threats to human health. Currently, techniques used to detect these bacteria are time-consuming and laborious. To overcome these challenges, the colorimetric strategy is attractive because it provides simple, rapid and accurate sensing for the detection of Salmonella spp. bacteria. The aim of this study is to review the progress regarding the colorimetric method of nucleic acid for Salmonella detection. A literature search was conducted using three databases (PubMed, Scopus and ScienceDirect). Of the 88 studies identified in our search, 15 were included for further analysis. Salmonella bacteria from different species, such as S. Typhimurium, S. Enteritidis, S. Typhi and S. Paratyphi A, were identified using the colorimetric method. The limit of detection (LoD) was evaluated in two types of concentrations, which were colony-forming unit (CFU) and CFU per mL. The majority of the studies used spiked samples (53%) rather than real samples (33%) to determine the LoDs. More research is needed to assess the sensitivity and specificity of colorimetric nucleic acid in bacterial detection, as well as its potential use in routine diagnosis.

Nowadays, the innovation and production of prayer seats can widely be seen around the world particularly in a nation or region with a majority of Muslim population. Demands on this assistive device are everywhere in order to ease and help disabled Muslims to conduct their daily prayers. Most of the existing devices consist of basic systems and sometimes do not accurately meet disabled Muslims’ requirement. The main objective of this research is to design and develop a Solah chair using electronic sensor to assist disabled Muslims to perform Solah and other ritual activities comfortably. This research uses four types of electrical and electronic systems namely the ultrasonic system, DF player system, counter system and IR sensor system to assist disabled Muslims to perform Solah and other ritual activities such as zikir and listening to Quran recitation. Arduino Uno is used to integrate these four subsystems. Arduino as the main micro-controller for this system is chosen for its convenience and capabilities to read and run C-language. It is also a simple platform which is suitable for many IT projects in general.

This research aims to explore and develop methods for extracting wax from cocoa beans, their components, and potential applications. The study focused on extracting wax from cocoa pods from Lees farm in Malaysia,by using response surface methodology (RSM) to optimize wax yield and validate its active ingredient. The highest wax yield was recorded at 20.4%, with the density of cocoa pod wax ranging from 0.94 to 0.98 grams per milliliter

Efficient electrical connections are critical for maintaining the reliability of aerial bundled cable (ABC) systems, where Insulation Piercing Connectors (IPC) play a vital role. This study focuses on predicting torque values in IPC installations using machine learning techniques to enhance mechanical performance and reduce failure risks. Three mechanical tests were conducted, including Shearhead, Continuity, and Body tests, using IPC samples provided by TeknoBumi. The data were analyzed using Random Forest, Decision Tree, and Artificial Neural Network models.Data preprocessing included normalization, and model performance was evaluated using R-squared, Mean Squared Error, Root Mean Squared Error, and Mean Percentage Error. Among the models, Random Forest showed the highest accuracy across all tests. In addition, anomaly detection methods including Isolation Forest, One-Class Support Vector Machine, and Local Outlier Factor were applied to identify abnormal torque values that could indicate potential installation issues or defects. Isolation Forest proved to be the most consistent and reliable method for detecting outliers. The findings of this study demonstrate that integrating AI-based predictive modeling and anomaly detection can support early identification of mechanical inconsistencies, improve IPC installation quality, and enhance the overall reliability of low-voltage overhead distribution systems.

Water is an essential element for every plant to survive, absorb nutrients, and perform photosynthesis and respiration. If water is polluted, plant growth can be truncated. The aim of this research is to develop a water quality monitoring system for agriculture purposes based on integration of sensing framework with a smart decision support method. This research consists of three stages: (1) the first stage: developing sensing framework which has four different water quality parameter sensors such as potential hydrogen (pH), electrical conductivity (EC), temperature, and oxidation-reduction potential (ORP), (2) the second stage: developing a hardware platform that uses an Arduino for sensor array of data processing and acquisition, and finally (3) the third stage: developing soft computing framework for decision support which uses python applications and fuzzy logic. The system was tested using water from many sources such as rivers, lakes, tap water, and filtered machine. Filtered water shows the highest value of pH as the filtered machine produces alkaline water, whereas tap water shows the highest value of temperature because the water is trapped in a polyvinyl chloride (PVC) pipe. Lake water depicts the highest value of EC due to the highest amount of total suspended solids (TSS) in the water, whereas river water shows the highest value of ORP due to the highest amount of dissolved oxygen. The system can display three ranges of water quality: not acceptable (NA), adequate (ADE) and highly acceptable (HACC) ranges from 0 to 9. Filtered water is in HACC condition (ranges 7–9) because all water quality parameters are in highly acceptable ranges. Tap water shows ADE condition (ranges 4–7) because one of the water quality parameters is in adequate ranges. River and lake water depict NA conditions (ranges 0–4) as one of the water quality parameters is in not acceptable ranges. The research outcome shows that filtered water is the most reliable water source for plants due to the absence of dissolved solids and contaminants in the water. Filtered water can improve pH and reduce the risk of plant disease. This research can help farmers to monitor the quality of irrigated water which eventually prevents crop disease, enhances crop growth, and increases crop yield.

Milk is a dairy product that contains dissolved proteins, carbohydrates, fat, and many minerals. Milk enhances body growth and provides vital energy and fatty acids. Milk can turn bad after being kept at room temperature for several days. The endurance of milk could depend on its fat and protein composition. Our work aims to compare the quality of milk after being kept at room temperature for several days using spectroscopy methods. Modeling based on scattering theory is also provided to compare the light propagation in milk, water, and air. A VIS-NIR spectrometer was used to observe the light absorption, transmission, and reflectance whereas a modeling approach was applied to study the scattering, absorption, and extinction efficiencies. The milk samples consist of full cream milk kept at room temperature for 8 days, 11 days, 14 days, and 17 days. The results show that milk without fermentation has higher light absorbance and lower transmission compared to milk with fermentation, due to changes in milk composition after the fermentation process. Milk scatters more light compared to water and air due to its fat globule and protein ingredients. The output of this study can be used as a reference for studies involving bacteria or microorganisms in milk. It also can be used to compare the quality of milk with and without air exposure.

The coronavirus disease 2019 (COVID-19) pandemic is a worldwide health anxiety. The rapid dispersion of the infection globally results in unparalleled economic, social, and health impacts. The pathogen that causes COVID-19 is known as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A fast and low-cost diagnosis method for COVID-19 disease can play an important role in controlling its proliferation. Near-infrared spectroscopy (NIRS) is a quick, non-destructive, non-invasive, and inexpensive technique for profiling the chemical and physical structures of a wide range of samples. Furthermore, the NIRS has the advantage of incorporating the internet of things (IoT) application for the effective control and treatment of the disease. In recent years, a significant advancement in instrumentation and spectral analysis methods has resulted in a remarkable impact on the NIRS applications, especially in the medical discipline. To date, NIRS has been applied as a technique for detecting various viruses including zika (ZIKV), chikungunya (CHIKV), influenza, hepatitis C, dengue (DENV), and human immunodeficiency (HIV). This review aims to outline some historical and contemporary applications of NIRS in virology and its merit as a novel diagnostic technique for SARS-CoV-2.

This research presents an application of Charge-Coupled Device (CCD) linear sensor and laser diode in an optical tomography system. Optical tomography is a non-invasive and non-intrusive method of capturing a cross-sectional image of multiphase flow. The measurements are based on the final light intensity received by the sensor and this approach is limited to detect solid objects only. The aim of this research is to analyse and demonstrate the capability of laser with a CCD in an optical tomography system for detecting objects with different clarity in crystal clear water. Experiments for detecting transparent objects were conducted. The object's diameter and image reconstruction can also be observed. As a conclusion, this research has successfully developed a non-intrusive and non-invasive optical tomography system that can detect objects in crystal clear water. � Penerbit UTHM.

Radio over Free Space Optics (RoFSO) is believed to be the most reliable technology in future communication as it provides high speed, high bandwidth and low consumption energy for data transmission. However, some turbulence weather factor such as fog, haze and rain may cause data attenuation in the FSO network. This project presents the effect of haze attenuation on RoFSO transmission system for Orthogonal Frequency Division Multiplexing (OFDM) modulation technique with Quadrature Amplitude Multiplexing (QAM) scheme. The data obtained was referring to the Air Pollution Index (API) from the region of Sepang, one of the town in Malaysia. The system is modelled and simulated using a software called OptiSystem. The result performance of RoFSO system when being modulated by OFDM is compared in terms of the BER value, received optical power and constellation diagram

Ninety percent of the ruby stones available worldwide come from Myanmar. Malaysia is known to be one of the countries that have been importing ruby stones for precious stone industries, manufacturing industries, medical and dentistry applications. There are several gemology tools which are used to investigate the grading of ruby stones such as loop, microscope, and dichroscope. Nevertheless, these tools are highly dependable on human visual assessment and require years of experience that may lead to error since ruby stone quality is evaluated based on its clarity and transparency. Hence, this paper addresses a simulation study on the optical properties of ruby stones via Charge-Coupled Device (CCD) Tomography approach. This paper indicates the capability of CCD and tomography system to analyze the ruby stone optical properties through image reconstruction based on the previous research. Linear Back Projection (LBP) algorithm will be used to construct two-dimensional image reconstruction of varieties ruby stones. From these image reconstructions, the transparency and blemishes of ruby stones can be analyzed.

Real life phenomena found in various fields such as engineering, physics, biology and communication theory can be modeled as nonlinear higher order ordinary differential equations, particularly the Duffing oscillator. Analytical solutions for these differential equations can be time consuming whereas, conventional numerical solutions may lack accuracy. This research propose a block multistep method integrated with a variable order step size (VOS) algorithm for solving these Duffing oscillators directly. The proposed VOS Block method provides an alternative numerical solution by reducing computational cost (time) but without loss of accuracy. Numerical simulations are compared with known exact solutions for proof of accuracy and against current numerical methods for proof of efficiency (steps taken).

This research discusses an application of Couple-Charge Device (CCD) linear sensor and laser diode in an optical tomography (OPT) system. Tomography is a system that could capture a cross-sectional image based on sensor data scattered across the periphery of the examining device in the non-invasive and non-intrusive framework. This project focuses on quantifying the level of object transparency based on CCD and mathematical modelling assessment. The objective of this project is to investigate the light refraction, reflection and absorption effect on object transparency. The study will include a discussion on the light parameters and its mathematical expression. The voltage output measured by CCD defines the degree of intensity of light obtained after penetrating through different object transparency. In conclusion, this research has successfully proved the potential of CCD in OPT configuration to detect different size diameters of a targeted transparent object, which is an air bubble in non-flowing crystal-clear liquid.

Presently, Malaysia is fostering growth in the green energy sector in order to reduce its carbon emissions and contribute in the fight against global warming. Renewable Energy (RE) such as solar cell could no longer be considered as a green technology because at the end of their lifecycle, they become non- biodegradable waste which in turn constitutes pollution and contributes to global warming. Thus, the aim of this research is to study a self-sustaining solar module produced by upcycling solar cells from non- biodegradable waste. Several solar cells from electronic devices were reused in this study. The results obtained show that a combination of 4V, 3V and 2V reused solar cells produced 10.20V and 47.9mW of power. This indicates that the proposed upcycled solar module is feasible and has the potential to aid in the promotion of clean and renewable energy use in order to attain the desired sustainable development goals.

For the first time, we demonstrated a wide range operation of an all-optical non-return-to-zero(NRZ)- differential-phase-shift-keying (DPSK)-to-return-to-zero(RZ)-DPSK waveform-wavelength conversion with exible picosecond width-tunablity and regenerative functionality. The scheme is based on a Raman amplifier soliton compressor (RASC) and a ber-based four-wave mixing (FWM) AND-gate. In the first demonstration, we demonstrated waveform-wavelength conversion of a 10-Gb/s DPSK signal without input signal degradation over 54-nm input-output wavelength ranges. The measurement results of the converted RZ-DPSK signal are pedestal-free, and its converted pulse width from 13.0 to 2.87-ps can be adjusted by tuning the Raman pump power between 0.20 and 0.90-W. An investigation of the regenerative waveform-wavelength conversion is further conducted at different Raman pump power settings over 40-km standard single-mode bers without dispersion compensation. Error-free operation with a low power penalty less than -1:95-dB is obtained for the RZ-DPSK regenerated converted signal.