13474 research outputs found
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Interference filters for temperature sensing, liquid detection and mode-locked laser applications / Yang Yaoxian
No full textInterference filter, also known as a thin film filter or dielectric filter, is an optical device that selectively transmits or reflects specific wavelengths of light according to the principle of interference. As an advanced optical transmission and sensing technology, optical fiber technology plays a key role in communication, sensing, medical, industrial and scientific fields. This paper aims to discuss the principles and diversified applications of some of these technologies. One of the most widely utilised approaches in substance detection is optical sensor detection. Through the interaction of the sample on the wave characteristics of light, the absorption spectrum, scattering spectrum and transmission spectrum are analyzed to determine the properties of the material composition. This detection method is not only simple to operate, but also has the advantages of high accuracy, non-contact, fast detection speed and high sensitivity. The researchers found that based on the fiber conduction characteristics and the interaction between light and matter, the light signal results can be analyzed to determine the material composition and other properties of the test sample. In this paper, the sensitivity of microfiber sensing technology and Singlemode-Multimode-Singlemode (SMS) fiber structure based on step large-core multimode fiber in temperature and refractive index sensing is discussed. The microfiber ring resonator (MRR) structure based on flame heating conical stretching technology has great research potential in the field of sensing. In this paper, a MRR sensor with a ring diameter of about 400μm and an optical fiber diameter of about 2μm has been successfully prepared. At the same time, the standard single-mode fiber (SMF-28) and the advanced multimode fiber (MMF-S105/125-22A) are fused together, and the SP- DSMSFR sensor is fabricated by side-grinding D-shape grinding in the centre of the multi-mode fiber. The experiments of temperature change, different solution and glycerin solution were carried out on the two sensors respectively. Compared with the experimental results, both sensors have good detection performance and have the potential to be used as solution detectors. In addition, SMS fiber is integrated into the ring cavity of an erbium-doped fiber laser (EDFL) as a saturable absorber (SA). A stable mode-locked pulse laser is obtained
The school-to-work transition, education-job mismatch and the effect on income / Mohd Amirul Rafiq Abu Rahim
No full textThis study investigates the interplay between school-to-work transition (SWT), education-job mismatch, and income among young workers in Malaysia. Using data from the 2018 Survey on School-to-Work Transition of Young Malaysians (SWTS), the research addresses gaps in the literature by analysing characteristics that clarify relationships unique to Malaysia. The study explores determinants and quality of SWT length, education-job mismatch, and their effects on income. The analysis highlights several demographic characteristics playing significant roles in influencing the quality of SWT length and education-job mismatch. The study reveals that tertiary-educated young workers in Malaysia secure jobs faster but face prolonged transition periods. Additionally, overeducated individuals experience significant income penalties, and gender composition influences income differentials, with broader gender income gaps among overeducated workers. The study emphasises the need for comprehensive labour market policies, advocating for a broader perspective beyond economic growth, with a focus on enhancing both passive and active labour market policies for vulnerable populations, particularly the younger generation
Hospital readmission risk prediction of COVID-19 patients using machine learning / Loo Wei Kit
No full textCoronavirus disease (COVID-19) is evolving rapidly and caused the rise in hospital readmission. To mitigate the rate of hospital readmission, a retrospective study was carried out on 1578 COVID-19 patients admitted in Universiti Malaya Medical Centre (UMMC) from May 2020 to January 2022. This study aimed to utilize the technology of machine learning and deep learning in the prediction of readmission risk with three main objectives, to identify potential clinical risk factors leading to COVID-19 readmission, build a predictive model to prognosticate unplanned hospital readmission, and lastly to analyse the characteristics, duration of treatment and recovery rate of readmitted COVID-19 patients in Malaysia. This study consists of three phases, commencing with the preliminary stage, where medical ethics approval was obtained for data collection at UMMC. Following data acquisition, cleaning, and preprocessing, unstructured data underwent Bag of Words analysis through Natural Language Processing (NLP), while statistical analyses and correlation tests were executed on refined patient data. Feature selection, using Recursive Feature Elimination (RFE) technique, preceded the construction and training of three machine learning models: Logistic Regression, Decision Tree Classifier and Support Vector Machine. Logistic Regression performed the best (0.919 accuracy, 0.636 area under curve (AUC)). Advancing to the progressing phase, 443 data was expanded to 1578, with COVID-19 readmission rate of 8.68%. The dataset expansion prompted the re-computation of statistical analyses, feature selection, and machine learning processes. A total of six machine learning models were developed and trained, namely Logistic Regression, Decision Tree Classifier, Support Vector Machine, Random Forest, eXtreme Gradient Boosting and Category Boosting. Concurrently, six deep learning models were developed and trained after data balancing was executed, namely Multilayer Perceptron, TabNet, Value Imputation and Mask Estimation, TabTransformer, Deep Factorial Machine, and Regularization Learning Model. While machine learning performed better than deep learning, Logistic Regression stood out among the models (0.946 accuracy, 0.639 AUC). For analysis of readmitted patients, most patients had length of stay (LOS) of 7 days or less (76.64%), and majority returned to hospital within a 90-day-interval (70.8%), indicating a good recovery rate for COVID-19 in the observed population. In the finalizing phase, various feature selection techniques were employed to discern the risk factors for COVID-19 readmission. 7 clinical risk factors of COVID-19 readmission are finalized, namely heart rate, cough, age, LOS, diabetes mellitus, hyperparathyroidism, and asthma. Ultimately, a novel Slime Mold Algorithm (SMA) integrated hybrid predictive model was developed. By integrating SMA into Support Vector Machine (SVM), the predictive model achieved an accuracy of 0.946 and AUC of 0.734
Three-dimensional carbon interdigitated ring array with nanofibers as biosensor for dopamine neurotransmitter / Elyana Kosri
No full textDopamine (DA) is one of the crucial neurotransmitters in the central nervous system and is closely linked to various health disorders, whether DA is present in high or low levels, for example Parkinson's disease, which profoundly affects the health of those afflicted. This thesis presents a three-dimensional carbon interdigitated ring array with nanofibers integration (3D C-IDRA NF) for neurotransmitter detection using amperometric method. The methodologies begin with the fabrication of two-dimensional and three-dimensional carbon interdigitated electrode array with nanofibers integration (2D C-IDEA NF and 3D C-IDEA NF) using far-field electrospinning and carbon-microelectromechanical system (C-MEMS) techniques. The 3D C-IDEA NF enlectrode demonstrates better redox cycling results when evaluated using cyclic voltammetry (CV) of KCl-K3Fe(CN)6 solution compared to the 2D C-IDEA NF electrode. Consequently, the 3D C-IDEA NF electrode design is adapted to fabricate the circular ring array, which are the three-dimensional carbon interdigitated ring array with nanofibers integration (3D C-IDRA NF) and 3D C-IDRA electrodes for neurotransmitter sensing using CV and chronoamperometry (CA). The integration of porous carbon nanofibers (CNFs) on the surface of the 3D C-IDRA electrode marks a significant novel approach, enhancing the 3D C-IDRA NF electrode’s surface area, resulting in increased current peaks during CV of DA and overall improved electrode performance compared to the stand-alone 3D C-IDRA electrode. This is evident in the redox amplification factor of 2.94 and the remarkable collection efficiency of 81.1%. These outcomes highlight the advantages of combining porous CNFs with 3D C-IDRA, resulting in a superior 3D C-IDRA NF electrode for electrochemical biosensors for detecting neurotransmitters such as DA
Process parameters optimization via machine learning and properties characterization of ALSI10MG-316L multi-materials produced using laser powder bed fusion / Miao Huan
No full textAlSi10Mg-316L multi-material parts are expected to be used on spacecraft, thereby reducing the weight of the spacecraft and offering more payload section, since AlSi10Mg provides a lightweight structure. However, achieving metallurgical bonding of the AlSi10Mg and 316L using laser powder bed fusion (LPBF) is extremely challenging due to the large differences in their thermal physical properties. This work aims to produce AlSi10Mg-316L multi-material parts with excellent performance using LPBF. Process parameters optimization for powder-mixed AlSi10Mg-316L multi-materials by employing machine learning method was deeply studied. The electrochemical corrosion behavior of AlSi10Mg-316L multi-materials in NaOH solution was evaluated. Interfacial characteristics of AlSi10Mg-316L multi-materials were determined. The experimental process parameters and properties (density and surface roughness) data were used to train a developed multi-output Gaussian process regression (MO-GPR) model to directly predict the multidimensional output to overcome the limitations of the standard Gaussian process regression (GPR) model. Based on the prediction data, process parameter maps were constructed, and optimum process parameters for different compositions were selected from the maps. Optical microscope (OM), scanning electron microscopy (SEM), transmission electron microscope (TEM), energy dispersive spectroscopy (EDS), electron backscattered diffraction (EBSD) and Vickers microhardness tester were used to investigate microstructure, defects, element diffusion, phase formation, grain orientation and microhardness of AlSi10Mg-316L multi-materials. The electrochemical corrosion tests of AlSi10Mg-316L multi-materials in 5 wt% NaOH solution were performed using an electrochemical workstation. The results revealed that MO-GPR model can accurately predict the properties at any set of process parameters of powder-mixed multi-materials due to the low error ratio for density (1.49%) and surface roughness (9.7%). Laser power, scanning velocity and hatching space had important influence on the density and surface roughness of the parts. Electrochemical corrosion tests show that the corrosion resistance of the LPBFed samples in 5 wt% NaOH solution follows the order: 316L > f=75% > f=50% > f=25% > AlSi10Mg. This indicates that the contributing member 316L significantly improves the corrosion resistance of AlSi10Mg-316L multi-material parts. In addition, using the optimal process parameters, multi-material parts can be produced with a good interface metallurgical bonding without significant defects. The partial Fe- FCC phase in 316L region of multi-materials changed into the Fe-BCC structure, and this shift has also changed the preferred orientation of the grains. Al-Fe icosahedral quasicrystals with five-fold symmetry were found at the boundary of the molten pool, which was caused by an extremely high cooling rate. The microhardness of the Al-Fe interface zone was higher than that of 316L with an average value of 235.57 HV and AlSi10Mg with 124.59 HV, which was caused by the very hard intermetallic compounds Al5Fe2 and AlFe formed at the interface. The metallurgical bonding mechanism of multimaterials was that the dissimilar metals were mixed and in-situ alloyed in the molten pool by the Marangoni convection-induced strong circular flow during LPBF processing. This study provided insights into laser powder bed fusion of multi-materials with dissimilar materials and provided reference for manufacturing functionally graded material parts
Characterization of functionalized support layer performance for surface plasmon resonance sensing platform for viral protein detection / Sharifah Norsyahindah Syed Nor
No full textIn the event of virus outbreak, rapid detection of viral infection is crucial for proper patient management and halting the progress of the disease into a pandemic. The current gold standard of virus detection is the reverse transcription-polymerase chain reaction (RT-PCR), which is time consuming and depends on relative RNA levels to determine the infection status of patients. Investigators have taken interest in surface plasmon resonance (SPR) biosensing for rapid viral detection. Therefore, the objective of this study is to develop a rapid, accurate, and ultra-sensitive SPR sensing platform for virus detection in minimum concentration. Methodologically, the reflectance of the 50 nm gold (Au) coated BK7 prism (Au/BK7 prism) was determined as reference. Next, Au sensing surface was integrated with self-assembled monolayer (SAM) those are 11-Mercaptoundecanoic acid (11-MUA), 3-Mercaptopropionic acid (3-MPA), and mix thiol (11-MUA:3-MPA in 1:10 molar ratio) in addition to transition-metal dichalcogenide (TMDC) carboxyl molybdenum disulfide (MoS2-COOH) layer to enhance the molecular adsorption that consequently enhances the sensitivity of the sensor. The support layers were characterized using Raman spectroscopy, Fourier transform infrared (FTIR) spectroscopy and transmission electron microscopy (TEM) before and after deposition onto the Au surface to study its morphology. Then, SPR measurements were performed for the four configurations (11-MUA/Au/BK7 prism, 3-MPA/Au/BK7 prism, mix thiol/Au/BK7 prism, and MoS2-COOH/Au/BK7 prism) to observe the changes to the SPR curve that proves the interaction of the support layers with Au surface. Consequently, each configuration undergoes refractive index (RI) sensitivity characterization with ethanol at different concentrations (0.01 M, 1 M, 5 M, 10 M, and 16.98 M) as samples to determine the capability of the platform to detect RI changes of the sensing medium. Next, the three most sensitive configurations are validated with testing using severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein (S protein) of various concentrations (10, 20, 30, 40, 50, 60, and 70 ng/mL) with RI variation (1.335, 1.338, 1.341, 1.343, 1.345, 1.347, and 1.350) respectively. Performance parameters such as sensitivity, full width half maximum (FWHM), detection accuracy (DA), figure of merit (FoM), quality factor (QF), and limit of detection (LoD) of the three selected configurations of different sensing element for the detection of SARS-CoV-2 S protein in varying concentration are evaluated and compared. Result shows MoS2-COOH/Au/BK7 prism exhibited the highest sensitivity (203.55 °/RIU) compared to 11-MUA/Au/BK7 prism (89.89 °/RIU) and 3-MPA/Au/BK7 prism (108.90 °/RIU). The LoD for 11-MUA/Au/BK7 prism, 3-MPA/Au/BK7 prism, MoS2-COOH/Au/BK7 prism is 6.55 ng/mL, 6.20 ng/mL, and 5.25 ng/mL respectively. Generally, all three configurations establish good linearity, excellent sensitivity, and LoD in ng/mL range for the detection of SARS-CoV-2 S protein. The findings from this study can be used to aid the future development of non-invasive, rapid, and ultra-sensitive SPR sensing platform for detection of virus infection in the minimum concentration
Downflow sponge biofilm reactor for ammonia removal in raw water treatment / Loi Jia Xing
No full textHigh ammonia levels in Malaysian river water poses a challenge for raw water treatment plants (RWTPs) operation. Current RWTPs rely on conventional treatment methods and lack dedicated ammonia removal capabilities, making the introduction of ammonia treatment critical for safe drinking water supply. The biological ammonia removal (BAR) method shows promising potential for RWTPs but requires a comprehensive understanding of local raw water conditions, including its characteristics, due to potential rate limitations at relatively low NH4+-N concentrations, which differs from wastewater BAR. Achieving a high reaction rate necessitates a short hydraulic retention time (HRT). Sporadic ammonia availability in raw water further complicates the compliance accountability of the BAR process.
This thesis aims to develop a low-energy, high hydraulic rate, and robust sponge-core BAR system, known as the Downflow Sponge Biofilm (DSB) reactor for raw water treatment. A river water quality assessment was conducted to establish BAR operational guidelines, with DSB system applicability evaluated in lab-scale reactors under varying HRTs and feast-famine conditions. Additionally, microbial community dynamics were investigated to ensure safe and efficient reactor operation.
Ammonia levels at the raw water intakes of three major river basins in Selangor, prone to water disruption, ranged from 0 to 6 mg N L−1. The range of ammonia concentrations served as a guideline for DSB reactor operation. Two DSB reactors were operated under short HRTs of 60-, 30-, 20-, and 15-min. The designed ammonia concentrations of DSB-1 and DSB-2 are 5 and 2.5 mg NH4+-N L−1, respectively. Both DSB reactors demonstrated high ammonia removal efficiencies at all four HRTs and their effluents met the recommended raw water quality standards (≤ 1.5 mg NH4+-N L−1). The shortest HRT for effluent compliance was 15 min. The short HRT operation had no adverse effects on the nitrifying microbial communities for safe reactor operation due to excellent biomass retention of the DSB system. The successful enrichment of nitrifiers affiliated with Nitrosomonas and Nitrospira was the key to achieve stable nitrification performance. Further phylogenetic analysis revealed the presence of putative complete ammonia oxidation Nitrospira associated with higher ammonia affinity in DSB-2, operating at low NH4+-N.
DSB-2 was continuously operated under a feast-famine regime. Four famine periods were investigated, comprising two 14-days partial famine phases, one 56-day phase involving both partial and complete famine, and one 90-day complete famine phase. Repeated 14-day partial famine phases had no impact on nitrification. A shift from partial to complete famine resulted in a delay in NOx−-N production. After 174 days of famine, the robust DSB reactor successfully restored ammonia and nitrite removal performance in 5 and 29 days, respectively. Under famine conditions, Candidatus Nitrosotenuis predominated while Nitrospira persisted throughout the study. Ca. Nitrosotenius, Nitrosomonas, and Nitrospira co-existed to contribute stable ammonia removal performance.
This research demonstrated the DSB system’s potential for highly efficient ammonia removal in raw water treatment, especially under challenging conditions like short HRTs and sporadic ammonia availability. Implementing DSB reactors could alleviate operational strains and ensure the security of water treatment systems
Experiences, attitudes, and prospects of Malaysian Muslim and Christian students on dialogue / Simon Herrmann
No full textWhat are prospects for Muslim-Christian dialogue among those who are likely to be in positions of influence in the future? This is the question behind the original research on which this dissertation is based. Postgraduate Muslim and Christian students of various universities and seminaries in Malaysia were interviewed about their experiences with people of the other faith, the benefits, need and difficulties in regard to dialogue and their personal interest in it. Analysis took place by basic statistical methods, content analysis and comparative analysis. Results show that there are obstacles that have a detrimental effect on dialogue. Among them are that students have limited contact with those of the other faith, Muslims do not want to be accused of taking steps towards compromising their faith and Christian students are concerned that their contact with Muslims could be interpreted in a way of propagating their faith to Muslims. Nevertheless, the students are not interested in living segregated lives. Openness on both sides for various modes of dialogue is high – higher than they would think it is. This dissertation concludes that the students find open doors for dialogue among those of the other faith and that they as prospective future leaders of their religious communities have many opportunities to move dialogue forward if they desire to do so. By laying open the attitudes, hopes, interests and concerns the findings of this study can be used to find ways how dialogue can be conducted successfully. In the Conclusion some steps toward implementation are suggested. The findings have significance for the students themselves, the religious communities they are part of and for all those who are interested in Muslim-Christian dialogue in Malaysia
Lightweight security schemes for internet of things resource-constrained devices / Usman Ali
No full textThe implementation of efficient security mechanisms for Internet of Things (IoT) environments based on Radio Frequency Identification (RFID) and Wireless Sensor Networks (WSN) has always been a constant challenge due to limited computing resources and communication over insecure wireless channels. Several authentication schemes have been proposed in recent years. However, some schemes are more focused on lightweight performance features using cryptographic operations with the lowest computational cost. The use of this operation affects important security requirements. Other authentication schemes that meet security requirements have unsatisfactory lightweight characteristics. To address these issues, three different authentication schemes are proposed, namely: Signcription-based Authentication Scheme for RFID termed SAS-RFID, Signcription-based Certificateless Authentication Scheme for WSN termed SCAS-WSN, and Enhanced Lightweight and Secure Certificateless Authentication for WSNs termed ELWSCAS-WSN. ELWSCAS-WSN is based on the concept of Authenticated Encryption with Associated Data (AEAD). The proposed solutions namely SAS-RFID, SCAS-WSN and ELWSCAS-WSN are based on elliptic curve cryptography (ECC) with Curve25519. The key exchange (KE) protocol X25519 is also used in the proposed solution to create a secure session key (SK) with reduced computational cost. The security of the proposed solution is evaluated using two different methods: formal analysis and informal analysis. Formal security analysis is conducted using the Real or Random (RoR) model and the Automated Validation of Internet Security Protocols and Applications (AVISPA) toolkit. The efficiency of the proposed solution is evaluated and compared with existing related schemes. The results obtained show that the proposed solution is generally more efficient and resistant to known attacks. Further, the proposed solution fulfills all the required security features and is faster compared to the related existing authentication schemes
Compressive strength and microstructural characterization of porous nickel brazed to copper and stainless steel / Ramizah Rozaimay
No full textHeat exchangers are fascinating devices with an important role in many aspects of daily lives and widely used in heat supply systems. It is suggested to design heat exchangers with porous metals to enhance the heat efficiency in the application of heat exchangers. However, utilizing porous metal, is challenging job, since it involves joining of base metals with porous metal. The way of fabrication is essential to ensure high thermal conduction at the interfaces. Since base metals and porous metals are dissimilar materials, an appropriate method must be adopted to create a tight bond for reducing the resistance at the contact surface. Thus, brazing has been regarded as an effective technique for joining dissimilar materials because it neither distorts base metal nor porous metal. In this study, brazing process of joining porous nickel to copper and stainless steel using copper-based brazing filler metal (VZ2250) was investigated. The brazing process parameters (brazing temperatures and times) as well as different brazing filler metals were assessed. A high vacuum furnace is used to braze the samples. The resultant joints were evaluated for compressive strengths (Instron Universal Testing machine) to determine the rigidity and extent of diffusion of VZ2250 brazing filler metal into the porous nickel. The characteristics of the joint interface were investigated to evaluate the performance of the brazed samples by using scanning electron microscope (SEM) and energy-dispersive X-Ray spectroscope (EDS). It was found that the compressive strength declined linearly with the increases in the brazing temperature from 680 °C to 740 °C. The maximum compressive strength of 27.64 MPa is achieved at the brazing condition of 680 °C for 15 minutes of brazing time. This means that the molten VZ2250 brazing filler metal has effectively and evenly diffused into the struts at the specified brazing condition. SEM images revealed microstructure flaws such as cracks and voids started to appear with the increasing brazing time. EDS analysis have shown that nickel and phosphorus elements are able to diffuse at brazing temperature of 680 °C for 15 minutes. These elements contribute to high compressive strength of porous nickel after brazing. Therefore, from the investigated parameters, including the analysis from the structure of porous nickel, brazed joint strength and the microstructure; it can concluded that using VZ2250 brazing filler metal at 680 °C for 15 minutes is the most suitable parameter for brazing porous nickel to copper and stainless steel