Adopting Dublin Core with modifications: Challenges and requirements to develop a standard metadata for UM Memory

UM Memory was initiated by the University of Malaya Library to build up digital photo collection. It was officially launched by Royal Professor Ungku A. Aziz on 22 September 2011 and his historical photo in the University was the first online exhibition displayed in UM Memory. The purpose of this initiative is to make the Library photo collection accessible to the public through complete metadata. Metadata of the item must be informative in order to capture the digital user’s interest. Several challenges have been faced by the librarians because no standard has been recorded as a guideline since this project was the pioneer project for historical images repository in the University of Malaya. This paper presents the steps taken by the librarians to produce a proper metadata standard to be used in UM Memory. It compares few established metadata from several institutions worldwide and also discusses the significance of excellence pledge for metadata. Several considerations need to be highlighted to confirm the metadata can represent the images in the portal effectively

Feature Analysis of Numerical Calculated Data from Sweep Frequency Analysis (SFRA) Traces Using Self Organizing Maps

This paper presents a comprehensive investigation of the Self Organizing Map (SOM) classification process of good and defective power distribution transformers. Three main features were extracted from the numerical calculation method of the Sweep Frequency Response Analysis (SFRA) signals acquired from the transformers. These features are the input vectors for the SOM classification. Analysis of the results has shown the capability of the features and the SOM classification method to differentiate between good and defective transformers

Dynamic Mechanical and Gel Content Properties of Irradiated ENR/PVC Blends with TiO2 Nanofillers

Numerous studies reported on irradiated epoxidized natural rubber/polyvinyl chloride (ENR/PVC) blends and the blends were found miscible at all compositional range thus it offers a broad of opportunity in modifying the blend characteristic. Addition of low loading titanium dioxide (TiO2) nanofillers in the ENR/PVC blends has shown a remarkable increment in tensile strength. Thus, this study was initiated to address the effect of TiO2 nanofillers on ENR/PVC blends dynamic mechanical and gel content properties and its morphology upon exposure to electron beam irradiation. ENR/PVC blends with addition of 0, 2 and 6 phr TiO2 nanofillers were first blended in a mixing chamber before being irradiated by an electron beam accelerator at different 0-200 kGy irradiation doses. The influence of TiO2 nanofillers on the irradiation crosslinking of ENR/PVC blends was study based on the dynamic mechanical analysis which was carried out in determining the glass transition temperature and the storage modulus behavior of ENR/PVC blends incorporated with TiO2 nanofillers. Formations of irradiation crosslinking in the blend were investigated by gel content measurement. While, the TiO2 nanofillers distribution were examined by Transmission Electron Microscope (TEM). Upon irradiation, the ENR/PVC/6 phr TiO2 formed the highest value of gel fraction. For dynamic mechanical analysis, it was found that electron beam radiation increased the Tg of all the compositions. The relationship between the crosslinking and the stiffness of the nanocomposites also can be found in this study. The enhancement in the storage modulus and Tg at higher amount of TiO2 in the blend could be correlated to the enhancement of the irradiation-induced crosslinking in the nanocomposites characteristic and also with the higher agglomerations of TiO2 evidence shown from the TEM micrograph examination. Lastly, the dimensions of TiO2 in the blends were found less than 100 nm in diameter which indicates incorporation of TiO2 nanofillers in ENR/PVC blends is potentially to provide the nanocomposites features. Doi: 10.12777/ijse.6.1.24-30 [How to cite this article: Ramlee, N.A., Ratnam, C.T., Alias, N.H., Rahman, M.F.A.. 2014. Dynamic Mechanical and Gel Content Properties of Irradiated ENR/PVC blends with TiO2 Nanofillers. International Journal of Science and Engineering, 6(1),24-30. Doi: 10.12777/ijse.6.1.24-30

Automated external defibrillator (AED) use among paramedics in the Emergency Department – what are the obstacles in using the automated external defibrillator in the pre-hospital care settings?

This study determined factors that influence usage of automated external defibrillation (AED) on out-of-hospital cardiac arrest among paramedics in Emergency Department of Universiti Kebangsaan Malaysia Medical Centre (UKMMC). It was a cross sectional prospective study conducted between December 2013 and January 2014. Paramedics from Emergency Department were enrolled and assessed using the self-filled questionnaire consisting of multiple sections including knowledge assessment, training and practice. In total, 53 paramedics participated in this study. Only 62% participants used AEDs previously. Not more than 83% participants admitted that they would use it if required. A positive correlation was observed between age and work experience with knowledge on AED usage (p=0.001 and p=0.005, respectively). Government’s institute graduates possess better knowledge and higher confidence level than private institutions graduates (p<0.001). Positive correlation existed between working experience and confidence level in deciding to use (p=0.006), application (p=0.019) and troubleshooting in regards of AED use (p=0.002). The main factor for low confidence level of AED use was lack of training (73.6%) which resulted in reduced confidence to initiate use (45.3%). Eighty eight percent agreed that training is essential before any AED use. Forty one percent felt that Malaysian public is not ready for AEDs use. As a conclusion, AED usage and knowledge among paramedics is still poor and further training is crucial for the improvement of pre-hospital care in Malaysia

Application of response surface methodology for chloride transport properties in nano metaclayed-UHPC

The major concern on the deterioration of reinforced concrete structure is due to the corrosion of steel reinforcement from the aggressive environment such as chloride penetration. Ultra-high performance concrete (UHPC) is an advanced concrete material having ultra-high strength with excellent durability properties. Inclusion of nano metaclay in UHPC is expected to overcome the chloride transport properties in UHPC by providing nano filler effect. Two (2) assessments were conducted which are chloride content and chloride depth were examined. All the concrete specimens were immersed in 3% NaCl solution up to 365 days and the tests conducted were performed at 3, 7, 28, 56, 91, 182 and 365 days. Response surface method (RSM) was performed to evaluate the interaction and relationship between operating variables (compressive strength and nano metaclay content). Based on RSM analysis, inclusion of nano metaclay in UHPC have good relationship towards the chloride resistance characteristics and adequate durability performance in terms of chloride penetration resistance. The results exhibited that inclusion of 1% nano metaclay significantly and positively affect in term of chloride penetration resistance

Thermodynamic evaluation of a solar based kalina cycle

Solar energy has enormous potential in the world. It can produce energy generation several times larger than the overall world energy demand. However, a major challenge to implement it is the high costs of electricity generation from solar sources. These costs can be reduced by improving the conversion efficiency from solar energy to electrical energy. Currently, the Rankine cycle is the most frequently used power cycle for generating electricity from solar energy. An interesting alternative to the commonly used Rankine cycle that uses solar heat energy as its input is the Kalina cycle. The Kalina cycle uses a mixture of ammonia and water as its working fluid. When using a mixture of ammonia and water as a working fluid, temperature varies while heat is added and rejected during phase change. This theoretically would be more efficient than a power cycle who only uses water as its working fluid. This paper examines the performance of a Kalina cycle with solar energy from concentrating solar plant as the input heat. A solution algorithm is developed and programmed to evaluate the thermodynamic properties of a Kalina cycle with inlet turbine temperature of 400 °C. Parametric analysis was done to study the effects of turbine inlet pressure and turbine inlet ammonia concentration on cycle efficiency. Results shows that both parameters have a positive relationship with cycle efficiency. Turbine outlet pressure was found to be a major influence on cycle efficiency. Maximum efficiency was found to be 33% at a turbine inlet pressure of 140 bar and turbine inlet ammonia concentration of 0.8

Renewable energy support policy in Malaysia: a comparative analysis with two successful countries

The world is facing depletion of fossil fuel sources thus urged for alternative and renewable energy sources. The conventional energy production raised a concern regarding greenhouse gases (GHG) emission that has led experts to find ways in reducing it. Energy production from renewable energy sources needs efficient support mechanisms to be successful. Many EU (European Union) countries namely Germany, Sweden, Finland and Denmark have been successful in deploying renewable energy sources by enacting judicial policy support mechanisms. Malaysia too has utilized several policies for promoting renewable energy but its success is yet very low. This paper is aimed to analyze renewable energy policies of Malaysia as to compare with selected EU countries successful policies. RETScreen software is used to analyze policies cases for Solar PV and Biomass sources. A comparative analysis is done for Malaysia with Germany and Sweden to obtain the estimation of net present value, internal rate of return and payback period. The finding provides indication why Malaysia renewable energy policy is not efficient as the two EU countries. The paper also discovers that the proposed policy for Malaysia has shown to a better option for future policies embedment

Multiwall carbon nanotube polyvinyl alcohol-based saturable absorber in passively Q-switched fiber laser

In this work, we demonstrated a compact Q-switched erbium-doped fiber laser capable of generating high-energy pulses using a newly developed multiwall carbon nanotube (CNT) polyvinyl alcohol (PVA) thin film based saturable absorber. Q-switched pulse operation is obtained by sandwiching the thin film between two fiber ferrules forming a saturable absorber. A saturable absorber with 1.25 wt. % of PVA concentration shows a consistency in generating pulsed laser with a good range of tunable repetition rate, shortest pulse width, and produces a high pulse energy and peak power. The pulse train generated has a maximum repetition rate of 29.9 kHz with a corresponding pulse width of 3.49 μs as a function of maximum pump power of 32.15 mW. The maximum average output power of the Q-switched fiber laser system is 1.49 mW, which translates to a pulse energy of 49.8 nJ. The proposed method of multiwall CNT/PVA thin film fabrication is low in cost and involves uncomplicated processes

IoT-based Machine Learning Comparative Models of Stream Water Parameters Forecasting for Freshwater Lobster

Water quality parameters such as dissolved oxygen, pH, and mineral content are important factors for aquaculture. Predictive analytics can predict water conditions in aquaculture and significantly reduce the mortality probability of aquaculture products. This paper applied stream predictive analytics to the freshwater lobster farming dataset where its real-time data supplied by End Node Unit (ENU) which integrated with dissolved oxygen (DO), potential hydrogen (pH), electrical conductivity (EC), and total dissolved solids (TDS). The real-time data of ENU in Structured Query Language (SQL) is normally displayed for remote monitoring and the analytics will only be done after in different processing platform called batch analytics. Instead of batch, this paper demonstrates capability of stream analytics where the real-time data query from ENU streaming through Structured Query Language (SQL) right into R Studio and Autoregressive Integrated Moving Average (ARIMA) predictions executed on the query table simultaneously on the same processing platform. Previously, ARIMA, Neural Network Autoregressive (NNETAR), and Naïve Bayes, were run and evaluated in R Studio to identify the best algorithm for stream analytics. Prediction procedure in R studio start with importing real-time data stored in SQL database and stream into R Studio using command of “dbGetQuery(con,sql)”. These three models evaluated the performance of freshwater lobster water conditions, dissolved oxygen (DO), potential hydrogen (pH), electrical conductivity (EC), and total dissolved solids (TDS). The data was collected for six months, and 70% was used as training data and 30% as test data. Compared to NNETAR and Naïve Bayes, ARIMA fits the entire data set well for 7 days; the ARIMA model exhibited lower absolute errors for pH and electrical conductivity, with errors ranging from 0.04 to 1.7 across days, while the NNETAR model had generally lower errors for TDS, with errors ranging from 0.3 to 0.7; however, the Naïve Bayes model's performance varied, with the lowest error for DO on day (5) 0.15 but higher errors for other parameters and days, including the highest error for electrical conductivity on day (6) 6.2. In conclusion, the average absolute errors for DO, pH, EC, and TDS are 0.163, 0.064, 0.705, and 0.498, respectively. Our findings underscore the efficacy of ARIMA for comprehensive water quality via stream prediction while highlighting the nuanced strengths and weaknesses of each model in forecasting specific parameters. This study contributes to the aquaculture literature by providing a nuanced comparative analysis of predictive models tailored to freshwater lobster farming, emphasizing the imperative role of stream predictive modelling. It enables real-time monitoring of water quality parameters, ensuring prompt interventions to maintain optimal conditions, thereby minimizing risks, enhancing aquaculture productivity, and ultimately contributing to sustainable and efficient freshwater lobster farming practices

Novel algorithm for mobile robot path planning in constrained environment

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested in several working environments with different degrees of complexity. The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. The results revealed that the proposed method has shortest path length, less computational time and the best smooth path. As an average, GLS is faster than A∗ and LS by 7.8 and 5.5 times, respectively and presents a path shorter than A∗ and LS by 1.2 and 1.5 times. In order to verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot (WMR) platform in labs and roads. The experimental work investigates a complete autonomous WMR path planning in the lab and road environments using a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of the analogous-road in lab or real-road environments. The study shows that the proposed method is able to generate shortest path and best smooth trajectory from start to goal points in comparison with laser simulator