13474 research outputs found
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Paediatric orthopaedic fracture healing prediction system / Lau Chia Fong
No full textMachine learning methods have been used in this study to analyze and predict the required healing time among paediatric orthopaedic patients. To our best knowledge, there is no study reported using machine learning methods to predict paediatric orthopaedic fracture healing time. In this study, we examined the fracture healing time in children using Random forest (RF), Self-Organizing Feature map (SOM) and support vector regression (SVR) The study sample was obtained from the paediatric orthopaedic unit at University Malaya Medical Centre, radiographs of the upper limb and lower limb fractures from children under twelve years, with ages recorded from the date and time of initial injury. Inputs assessment extracted from radiographic images included the following features: type of fracture, angulation of the fracture, the contact area percentage of the fracture, age, gender, bone type, type of fracture, and the number of bones involved. all of which were determined from the radiographic images. RF and SVR were used to select variables affecting bone healing time. Then, SOM was applied for analysis of the relationship between the selected variables with fracture healing time. Findings from this study identified fracture angulation and distance, age and bone part as important variables in explaining the fracture healing pattern. Root mean square error (RMSE) was used as a performance measure and SOM was used in this study for visualization and ordination of factors associated with healing time. Based on the outcomes obtained from the models it is concluded that SVR and SOM techniques can be used to assist in the analysis of the healing time efficiently especially in paediatric cases as it can additionally signal a non-unintentional injury or abnormal restoration, that affect the time required for bone fracture healing. Predicting healing time can be used as a tool in the treatment process for general practitioners and medical officers and in the follow-up period. We also have developed decision support using the AO trauma guide to determine the type of fracture and its management. The system prototype is available at kidsfractureexpert.com/
Synthesis and characterization of palm-oil-based polymeric surfactant as biocompatible additives for natural rubber latex film / Heng Yi Xin
No full textNatural rubber (NR) is the preferred material in the glove industry with its outstanding characteristics of tensile strength, elasticity and tear resistance. Surfactants are commonly added in latex glove manufacturing to maintain latex stability, wet formers for coagulant dipping and assist smooth film deposition on the former. However, these surfactant molecules tend to migrate to the film surface during drying process and diffuse into the water during leaching process. This will raise the concern of polluting the environment and endangering the aquatic life. Hence, this study focuses on the development of biocompatible polymeric surfactants as an additive to natural rubber (NR) latex and production of dipped films thereafter.In this work, two polymeric surfactants, anionic and non-ionic polymeric surfactants, namely APS and NPS were synthesized from palm oil using polyesterification method. Physicochemical properties of these surfactants were determined. Both APS and NPS were compounded into NR latex to produce latex films. The physical properties of the NR latex films were subsequently studied. Both surfactants are liquid at room temperature and APS has higher viscosity (6750 cps) compared to NPS (1500 cps). Gel permeation chromatography (GPC) result shows that NPS has greater molecular weight but a lower glass transition temperature, -67.11 °C than those ofAPS surfactant. Both surfactants have reasonably good thermal stability with decomposition temperature well above 200 oC, suggesting its suitability to be used in latex compounding for sulfur vulcanization system. In the antimicrobial study, both surfactants shown antibacterial efficacy on Gram-positive bacteria at low concentration but insignificant growth inhibition for Gram-negative bacteria. The outcome of cytotoxicity study is very encouraging with both surfactants exhibited low cytotoxicity at high concentrations, 50 and 100 μg/mL for the first 24 hours, particularly in human keratinocytes and fibroblast cells. Prior to incorporation of the surfactant into the NR latex, surfactants need to be dissolved in water to form solution to reduce its viscosity for better miscibility with NR matrix. The surfactant solutions exhibited excellent wetting property with contact angle < 90°, low critical micelle concentration (CMC) value, low foaming ability and reasonable stable upon storage up to 6 months at storing temperature 40 °C. The results of physical testing demonstrated that the tensile strength of the APS film was about 35 % stronger than control and the low modulus at 300 % elongation also reflected an excellent softness of the film. In the event of thermal aging, both surfactant films exhibited anti-aging properties with no apparent depreciation in the mechanical properties after heat treatment. Collective result from all the tests carried out has demonstrated that APS is an innovation with great potential for NR latex applications, particularly in glove applications such as surgical gloves
A lightweight intrusion detection framework using focal loss variational autoencoder for internet of things / Shapla Khanam
No full textInternet of Things (IoT) generates imbalanced network traffic; thus, the connected objects
in the IoT face security issues, including different and unknown attack types. Even though
traditional learning-based techniques have been used for intrusion detection in IoT, the
detection of low-frequency attacks is lacking due to the imbalanced nature of network
traffic. For example, conventional learning-based techniques suffer from lower detection
accuracy, higher False Positive Rate (FPR), and lower minority-class attacks detection rates.
Moreover, due to the constrained nature of IoT, the conventional heavyweight intrusion
detection models are not suitable for IoT. To overcome these issues, this research aims
to establish and evaluate a lightweight intrusion-detection framework using Class-wise
Focal Loss Variational Autoencoder (CFLVAE) for IoT. In establishing the proposed
framework, a data generation model was developed using CFLVAE. Precisely, the CFLVAE
model utilizes an efficient and cost-sensitive objective function called Class-wise Focal
Loss (CFL) to train Variational AutoEncoder (VAE) to solve the data imbalance problem.
Additionally, a highly imbalanced NSL-KDD intrusion dataset is employed to conduct
extensive experimentation of the proposed model. Furthermore, a Lightweight Deep
Neural Network (LDNN) model is established for intrusion detection in the IoT and
trained using the balanced intrusion dataset created from the CFLVAE model to improve
the intrusion detection performance. To maintain lightweight criteria, feature reduction
using Mutual Information (MI) method and network compression using the Quantization
technique are applied. The results demonstrate that the proposed CFLVAE with LDNN (CFLVAE-LDNN) framework obtains promising performance in generating realistic new
intrusion data samples and achieves superior intrusion detection performance. Specifically,
the CFLVAE-LDNN achieves 88.08% overall intrusion detection accuracy and 3.77%
false positive rate. It also achieved 79.25%, and 67.5% for Root to Local (R2L) and User
to Root (U2R) low-frequency attacks detection rates, respectively. More significantly,
low memory and CPU time consumption confirm that the proposed model is suitable for
resource-constrained IoT. Overall, the proposed model benefits researchers and practitioners
with intrusion detection in IoT
Effect of Covid-19 pandemic period on pattern of substance usage among people who use drugs (PWUD) receiving treatment at University Malaya Medical Centre (UMMC) in Malaysia / Amir Zulhilmi Yahaya
No full textCOVID-19 (Coronavirus Disease 2019) was announced by World Health Organization
(WHO) as a global pandemic and is rising in the number of infections around the globe.
This pandemic virus causes a certain vulnerable population to have higher morbidities
and mortalities, for example; Substance Use Disorder patients or people who use
alcohol/illicit substances which in turn, causes a change of pattern of substance usage
among them during this COVID-19 pandemic period. This study aims to determine the
effects of the Covid-19 Pandemic Period on the Pattern of Substance Usage Among
People Who Use Drugs ( PWUD) Receiving Treatment in the University Malaya Medical
Centre (UMMC) as well as levels of anxiety and depression among them together with
their coping mechanism as well as other associating factors that affected it. This is a cross sectional study among 130 peoples who use drugs/alcohol (PWUD),
receiving treatment in University Malaya Medical Centre and convenient sampling was
used for recruitment. The participants who agreed to participate in this study will answer
an online questionnaire which include socio – demographic questionnaire, The Mini –
European Web Survey On Drugs (EWSD) : COVID 19, Hospital Anxiety and Depression
Scale (HADS) and Brief COPE Scale (both validated Malay and English version). The data collection took place from 6 July 2020 – 31 October 2021. The prevalence and
pattern of each of the substance/alcohol use was determined. Univariate and multivariate
analysis were done to determine the association between different change in the pattern
of substance use with isolation status during COVID-19, depression, anxiety, and coping skills. 130 people who use drugs/alcohol (PWUD) completed the online survey. There were
36.2% of PWUDs had not used/stop the usage of illicit drugs/alcohol, 26.2% increased
their usage, 20% of them decreased, and 14.6% of them used the same amount of illicit
substances/alcohol during the COVID-19 Pandemic Period/ Restrictions. Most of the
PWUD in UMMC used multiple substances (14.6%), followed by heroin, alcohol, and
amphetamine-type stimulant (12.3% for each of them), and lastly cannabis (6.9%). Most
of the PWUD increased their illicit substances/alcohol usage during the COVID-19
Pandemic Period/restrictions because of boredom (23.1%) and anxiety to cope with
COVID-19 (11.6%). Around 48.5% of the PWUDs experienced physical and home
isolation, 26.6% had physical isolation and 6.2% of them had physical and home isolation
as well as being quarantined. There were 28.5% of PWUDs had an increased intention to
seek professional support for drug counseling/treatment during the COVID-19 Pandemic
Period. The prevalence of PWUD who had anxiety and depression symptoms in HADS
were 33% and 41.5% respectively, with depression being associated with an increase in
alcohol/illicit substance use. PWUD who experienced isolation during the COVID-19
pandemic have significantly higher odds of increasing their alcohol/illicit substances
usage. There were also noted increased odds of maintaining the alcohol/illicit substance
usage during the COVID-19 Pandemic Period among PWUDs who practices dysfunctional coping. PWUDs who has to increase their intention to seek professional
support does have significantly higher odds of reducing their alcohol/illicit substances
usage during the COVID-19 Pandemic Period. COVID-19 Pandemic does significantly affect the population of substance users in
Malaysia. Our study highlighted that anxiety and depression were prevalent among
PWUD. Depression, isolation status, dysfunctional coping, and intention to seek
professional support does affect the pattern of alcohol/illicit substance use during the
COVID-19 Pandemic Period. A more vast prospective longitudinal study is imminent to
highlight these associating factors and causal relationships among them
Inter-regional market clearing of a power system with high PV penetration during a mid-day over-generation / Deepak Yadav
No full textWith the rapid growth of renewable energy (REs) resources in the electricity sector, the
system operators (SOs) are facing some major challenges related to security, market, and
operations in power transmission. Since the government policies are providing subsidized
and favorable terms; therefore, the investors are highly keen on the installation of REs in the
power networks. Altogether, the REs wouldn’t be available 24 hours. Hence, the modern and
upcoming power markets need to exchange power between different networks or regions
(inter-regional) to meet the growing demands. The higher penetration of REs could cause
overgeneration into the system due to low demands on the power systems, especially during
mid-days. Therefore, inter-regional or inter-power markets strategies are the need in the
present power systems to address the market clearing problems during the mentioned
situation. In the present work, the locational marginal pricing (LMP) based solution
methodology has been proposed to resolve the problem of market clearing in the power
system during overgeneration. The objective function for the identified problem has been
formulated using optimal power flow technique and solved through Interior Point Method
(IPM). The interconnection of IEEE-9 & IEEE-5 bus systems and IEEE-118 & IEEE-57 bus
systems have been chosen to create the inter-regional marketplaces. The proposed LMP based solution methodology has been implemented on these marketplaces. The obtained test results show that the proposed methodology provides an economic and efficient solution for
the highly PV penetrated power system
A high efficiency and low noise magnetron cathode using gallium nitride and silicon carbide polymers for modulated microwave power transmission / Leong Wen Chek
No full textMicrowave Power Transmission is one of the potential fantastic technologies in Wireless Power Transmission apart from Inductive Coupling, Resonant Inductive Coupling, Capacitive Coupling, Magnetic Resonant, Radio Frequency, Laser Power and Laser Light Wireless Power Transmission. Microwave Power Transmission performs better for low power applications due to its far-field transmission distance. However, due to safety and health concerns, the research on Microwave Power Transmission has been reduced and requires high costs to conduct the experimental investigation. The Magnetron is one of the most commonly used microwave power generators for commercial or industrial applications. The system's efficiency is mainly affected by factors such as the building materials, resonant cavity size, operation space size, anode structure, and operating frequency. Previous researchers have emphasized implementing GaN on SiC polymer in various power device applications such as high electron-mobility transistors, power diodes, and microwaves. However, the solution proposed in this thesis is the first reported for implementing the same polymer in a magnetron’s cathode surface. This thesis proposes the modification of magnetron cathode for high frequency and low power applications using Silicon Carbide (SiC) and Gallium Nitride (GaN) coated cathode polymer replacing traditional Barium Oxide (BaO) substrate through an annealing process. The highlighted optimization is intended to modify the control of magnetron electron flow velocity to reduce heat dissipation. Sudden temperature rise during magnetron operation reduces its efficiency because it loses its stability. Simulation and experimental results have been extracted at 2,45MHz to generate 5W microwave power and tested for over 10 m. of power transmission using a rectenna interface, which results in an efficiency of 87%, compared to 36% using a BaO coat
Assessing the quality of life of urban residents in greater Kuala Lumpur / Siti Nurul Munawwarah Roslan
No full textQuality of life in urban areas has become an important factor for sustaining urban living. A wide range of factors contribute to quality of life, and neighbourhood satisfaction is one such factor that has been highlighted by many researchers. Households located in urban areas can benefit from a variety of urban infrastructure and services provided by the public sector to achieve a better standard of living. However, an increase in the number of urban population has resulted in higher rates of unemployment, poor residential and environment quality, climate change, and poor provisions for shelter, and amenities in urban areas. The high rate of migration will also generate a demand for more affordable housing, development of new residential areas, acceptable cost of living, employment and job opportunities, good environment, and physical features. This gap, addressed in the study, proposes pertinent environment and housing attributes relevant to improving urban quality of life. This study aims to explore the level of neighbourhood satisfaction and the quality of life perceived by urban residents, assess the influence of neighbourhood attributes and housing attributes in elucidating neigbourhood satisfaction, and examine the role of neighbourhood satisfaction to facilitate the relationship between neighbourhood attributes and urban quality of life. Primary data, collected through a survey involving 530 respondents, were utilised in this study and SEM–AMOS was used for data analysis. This study covers seven local authorities in the Greater Kuala Lumpur namely Kuala Lumpur City Hall, Petaling Jaya City Council, Shah Alam City Council, Klang Municipal Council, Sepang Municipal Council, Subang Jaya Municipal Council and Selayang Municipal Council. The study revealed three significant findings: (1) quality of life is influenced by the satisfaction towards the neighbourhood which, in turn, is dependent on the gratification obtained from the socio/physical attributes, economics attributes, environment attributes, and housing attributes, (2) neighbourhood attributes and housing attributes considerably affect neighbourhood satisfaction, and (3) neighbourhood satisfaction partially mediates the relationship between neighbourhood attributes and quality of life. These findings are beneficial to the government and authorities for future urban planning. It can also be concluded that the local authorities and government should introduce improvements to the neighbourhood environment as this will greatly benefit the society by enhancing their quality of life
Challenges to adopt circular economy in the Malaysian construction industry / Asma'u Abdulwahab Muhammad
No full textCircular Economy (CE) has developed as a result of increasing environmental consciousness, environmental legislation, and the need for social responsibility. In Malaysia, however, an unclear financial case were also deemed the most significant economic challenges. Another significant challenge was the construction industry's structure, which was seen as having a fragmented supply chain and a general lack of interest, awareness, and knowledge. The practises are further behind than they should be due to a dearth of research on the subject. This study aims to investigate the current awareness levels and CE-related practises in the Malaysian construction industry. The study employs a quantitative survey questionnaire and a convenience sample technique. Through the FAME database, personal contacts, and LinkedIn, 100 individuals from various aspects of the construction industry were contacted directly over the course of 40 days. There were 71 completed responses to the survey. Given the exploratory nature of the study, descriptive statistics were primarily used to analyse the data. A correlation, ANOVA, and descriptive analysis were also conducted to validate the aim. The research findings indicate that as governing bodies around the world place a greater emphasis on corporate social responsibility, organizations are becoming more aware of CE practises. The analysis also reveals some valuable CE insights. Furthermore, our findings indicate that the factors of CE are to develop strategies to eliminate the perceived risk of contamination. In addition, and given their lack of shift, industries should develop educational and awareness campaigns to assist workers in overcoming their negative perceptions of circular econom
Modified polyacrylamide by incorporating silica for drilling fluid technology / Koh Jin Kwei
No full textDrilling is a process to remove the cutting in the excavations and offshore industry. Polyacrylamide (PAM) is a commercial additive in the drilling industry nowadays, but PAM has poor thermal, chemical, and pile stability in the geotechnical industry. Therefore, the functionalised material is required to be involved in the PAM-based drilling fluid. This study focuses on the modification of PAM incorporated with silica (SiO2). The rheological investigation was optimised using various PAM concentrations (500-2000 ppm) for the subsequent testing with the effect of SiO2, sodium dodecyl sulphate (SDS), temperature, and pH. Meanwhile, the promising formulation of modified PAM was identified via the rheological study with the effect of SiO2 and SDS. This formulation further studied the effect of temperature and pH. The drilling fluids were characterised by Fourier Transform Infrared Spectroscopy (FTIR), tensiometer, and contact angle. The results showed that 1000 ppm PAM was the critical association concentration as the rheological properties were better below 1000 ppm PAM. Further, 0.5 wt% SiO2 and 0.2 wt% SDS are promising formulations because both demonstrated better rheological performance than others. All modified PAM had better rheological performance than bare PAM. The rheological performance of PAM and modified PAM were significantly affected by temperature, which showed a better performance after heating to 60 °C and 40 °C, respectively. PAM and modified PAM had a better rheological performance at pH 10. Future studies can demonstrate the modified PAM in the bored pile construction to investigate the frictional resistance
An enhanced fully automatic ventricular heartbeat classification inspired by cyclic echo state networks / Qurat-Ul-Ain Mastoi
No full textAbnormal conduction (arrhythmia) in the lower chamber of the heart (ventricular) can cause cardiac diseases. Premature ventricular contraction (PVC) is a type of ventricular arrhythmia that is quite dangerous due to the frequent occurrence of premature beats in the ECG cycle. Accurate detection of premature ventricular contractions is not easy due to the multiform nature and interpatient variability issues in the heartbeat. The most challenging part of ECG signal analysis is to design an approach that accepts the multiform and interpatient variation in ECG signals for PVC arrhythmia feature extraction. This study develops a fully automatic model for PVC arrhythmia classification that helps to identify the accurate pattern of PVC arrhythmia. In the first part of the experiment, this research conducts extensive experiments to extract the features from ECG signals, such as inverse R-peaks, QRS, P-wave, and T-wave identification, and proposes a template matching technique to verify the abnormality from ECG signals. In the final stage, a cyclic echo state network classification model is proposed to classify abnormal and normal heartbeat conditions. To enhance the efficiency of the proposed model, a classifier is scaled according to the dimension of the proposed feature vector set and tuned accordingly. Three datasets are utilized to conduct this experiment: MIT-BIH-SVDB, AHA (for the experiment), and MIT-BIH-AR (for evaluation). This study follows the standard k-fold cross-validation technique and standard metrics to evaluate the performance of the model. Hence, it is observed that the proposed method achieved remarkable results, which are approximately 99.19% accuracy in SVEB cases and 99.24% accuracy in VEB cases