Heat exchangers are used in many industries and power generation applications. The performance of heat exchangers depends on the operating parameters and the types of flow. The sudden pressure drop is one of the major problems encountered in heat exchanger, and this would significantly affect the efficiency and the overall heat transfer coefficient of the heat exchanger. Therefore, this study is aimed at investigating and analyzing the effects of operating parameters that cause pressure fluctuation and affect the overall heat transfer coefficient. Experimental study was carried out for two types of flows: co-current and counter concurrent flows. Comparisons of the overall heat transfer coefficients between shell and tube and spiral coil heat exchangers were made. It was observed that mass flow rate affected the overall heat transfer coefficient. Besides, the counter current flow was more efficient compared to the co-current flow with enhanced overall heat transfer coefficient. The maximum overall heat transfer coefficient for spiral coil heat exchanger counter flow was 2702.78 W/m2.K, showing a higher heat transfer efficiency when compared to the shell and tube heat exchanger. Moreover, the spiral coil heat exchanger occupied less space as opposed to the shell and tube heat exchanger.
Torrefaction is a thermal process to convert biomass into a coal-like material, which has better fuel characteristics than the original biomass. Torrefied biomass has more energy density and hydrophobic which is superior quality for handling and storage. The objective of this research was to develop a simulation model of the torrefied pelletization process from empty fruit bunch (EFB). The process was simulated using ASPEN Plus. Optimization involved a selection of the model option that produced the maximum mass yield and minimum energy requirement, with a converged base case simulation as a starting point. Torrefied biomass pellet offered coal-like properties such as high heating value, brittle, high bulk energy density and more hydrophobic. These properties could potentially avoid costly power plant modifications. On the other hand, Malaysia has issued National Biomass Strategy 2020 with target to solve the problem of under-utilized biomass in this country. Base model was based on previous study. For optimization of mass yield and overall energy consumption, six model options of design configurations were analysed. Design model 0 was used as the base model. For design model 1, flue gas from combustion reactor was channelled to torrefaction reactor. For design model 2, flue gas from combustion reactor was split to dryer and torrefaction reactor. For design model 3, combustion reactor was removed. For design model 4, flue gas was channelled to dryer reactor without combustion reactor. For design model 5, flue gas separator after dryer was removed. Out of five options, results were tabulated for the optimum one. The results showed that the highest mass yield was achieved by simulation Model 5 at 90.76 % and lowest energy requirement was achieved by simulation Model 4 at 411.336 kW. Optimization result meanwhile had shown that Model 4 was selected because it gave the maximum profitability of RM 72834.45 by considering the yield and the energy consumption simultaneously.
This paper presents two gear driven wind turbine generators (WTG) feeding a single three level grid connected NPC inverter. Each component of WTG is made up of wind turbine, 2-mass gear drive, permanent magnet synchronous generator (PMSG), AC-DC-AC power converter. A simple advanced hill climbs search (AHCS) maximum power point tracking algorithm that uses the mechanical power from the Wind turbine was developed to generate proper duty cycle for the control of single stage DC/DC boost converter. The DC link voltages are series interconnected and fed to a sinusoidal pulse width modulation (SPWM) controlled high power inverter. The complete model is simulated using MATLAB/ SIMULINK software under fixed and fluctuating wind speed conditions. Simulation results have shown that WECs exhibit variability in their output power as a result of changes in their prime movers (wind speed).
Detection and identification of text in natural scene images pose major challenges: image quality varies as scenes are taken under different conditions (lighting, angle and resolution) and the contained text entities can be in any form (size, style and orientation). In this paper, a robust approach is proposed to localize, extract and recognize scene texts of different sizes, fonts and orientations from images of varying quality. The proposed method consists of the following steps: preprocessing and enhancement of input image using the National Television System Committee (NTSC) color mapping and the contrast enhancement via mean histogram stretching; candidate text regions detection using hybrid adaptive segmentation and fuzzy c-means clustering techniques; a two-stage text extraction from the candidate text regions to filter out false text regions include local character filtering according to a rule-based approach using shape and statistical features and text region filtering via stroke width transform (SWT); and finally, text recognition using Tesseract OCR engine. The proposed method was evaluated using two benchmark datasets: ICDAR2013 and KAIST image datasets. The proposed method effectively dealt with complex scene images containing texts of various font sizes, colors, and orientation; and outperformed state-of-the-art methods, achieving >80% in both precision and recall measures.
Sediment has been widely used as a means for assessing the impact of anthropogenic activities on aquatic environment, with metal pollution being the most well-known threat to aquatic environments. Therefore the aim of this study is to identify and determine metal concentrations, specifically that of copper (Cu), chromium (Cr), cadmium (Cd), iron (Fe), and zinc (Zn) on four sediment cores samples of KongKong Laut Masai Johor. The aqua regia method had been used to analyze Cu, Cr, Cd, Fe and Zn concentrations in sediment samples. Metal concentrations had then been determined through the use of flame atomic absorption spectrometry. The degree of metal contamination in sediment core samples had been determined through using Enrichment Factors (EF) and Geoaccumulation Indices (Igeo). From this study, the mean and standard deviation of metal concentrations in each sediment core sample were shown to be lower than the average shale concentration and lower than both the effects-range low (ERL) and effects-range median (ERM) parameters for aquatic toxicity. This information could be useful, serving as a baseline for evaluating the potential impacts of future development in the area.
The present study aims to determine the level of heavy metals in surface soils and street dust from selected urban and peri-urban locations in the metropolitan city of Kuala Lumpur. Samples were collected from 15 different locations, where Kuala Lumpur City Centre (KLCC) served as the centre point while other locations were located at specific distances from the centre. Surface soils and street dust were collected to detect the level of contamination based on five elements (Zn, Cu, Pb, Cd and Fe). Results indicated that the metal distribution displayed a descending trend as follows: [Fe] > [Zn] > [Pb] > [Cu] > [Cd] and [Fe] > [Zn] > [Cu] > [Pb] > [Cd] in the surface soil and street dust samples, respectively. Geoaccumulation index (Igeo), contamination factor (CF) and pollution load index (PLI) were calculated. Based on the Igeo index, Fe in both samples was found to cause no pollution in all study sites. In surface soils, CF showed all sites were contaminated with Cd in both soil and street dust. In conclusion, the soil sample was polluted with metals while no pollution was found in the street dust in all sites sampled. Further intensive studies are recommended in order to determine other factors which may cause contamination.
Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of a watershed. A study was conducted to assess water quality and to establish relationship among water quality parameters in Kelantan River basin. Water quality data was obtained from Department of Environment, (DOE) Malaysia from 2005-2014. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to 15 water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of the watershed. From the results, five PCs were extracted which are collectively accountable for controlling approximately 70% of the watershed’s water quality. Results of cluster analysis indicated that three water quality parameters that included total suspended solids, total solids and turbidity control the water quality of the study area. These parameters were allocated into three clusters based on their similarity. The finding of this study will contribute to existing knowledge of the problems associated with water quality in the basin. This information can be put to use by land use managers and policy makers for future planning and development of the watershed.
Urban green space (UGS) in a city is the foundation of natural productivity in an urban structure. It is also known as a natural cooling device that plays a vital role in the city as an urban lung, discharging oxygen to reduce the city heat and as a wall against harmful air pollution. When urbanization happens, UGS, including the gazetted areas, is essentially converted into an artificial surface due to the population’s demand for new development. Therefore, identifying its significance is a must and beneficial to explore. The purpose of this study is to identify the 10 years of UGS change patterns and analyze the UGS loss, particularly in the affected gazetted zone. The study used available aerial imagery data for 2002, 2012, and 2017, and database record of green space. The study had classified UGS by using the Support Vector Machine (SVM) algorithm. The training area was determined by visual interpretation and aided by a land use planning map as reference. The result validity was then determined by kappa coefficient value and producer accuracy. Overall, the study showed that the city had lost its UGS by about 88% and the total gain in built up area was 114%. The loss in UGS size in the city could be compared to a total of 2,843 units of football fields, transformed forever in just 10 years. The uncontrolled development and lack of advanced monitoring mechanism had negatively affected the planning structure of green space in KL. The implementation of advance technology as a new mitigation tool to monitor green space loss in the city could provide a variety of enhanced information that could assist city planners and urban designers to defend decisions in protecting these valuable UGS.
Working in a virtual team presents many challenges. Communication is one of the most important challenges, especially when a virtual team includes members from different countries and background. Virtual project management enables organizations to save on resources such as cost and time. Organizations often struggle with poor communication in their geographically dispersed teams and ineffective communication have been identified as one of the main causes project failure. The aim of this study is to determine the most critical barriers to effective communication in virtual teams. A mixed method of data collection was adopted using semi structured interview with communication and construction experts, and questionnaire approach with construction companies that are G5-G7 rated. Data were analyzed using pareto and exploratory factor analysis for the development of a strategy for enhancement of communication management within virtual teams. The result shows that lack of trust and misunderstanding are the most important barrier to communication within virtual teams. However, managing communication process has been identified to have more impact on the barriers, while planning communication has the least impact. Establishing rule for response and changing focus from individual to group were identified as the two most important factors required in order to sustain trust within virtual teams.
A large scale of investigation had been carried out to predict the personality, or in precise, the behaviour of online users through user-generated texts, such as Tweets and status messages. Nevertheless, only a handful of machine learning (ML) studies have applied the personality model to assess criminality behaviour, particularly within the context of Malay social network messages. Based on the concept of sentiment valence, this study annotated a list of Malay Tweets that might be subjected to crime or illicit messages from the stance of Psychoticism trait. Consequently, the supervised-based text classification method was conducted by using Naïve Bayes (NB), Sequential Minimal Optimisation (SMO), and Decision Tree (DT) on Tweets using several features determined via Chi Square (x2). The analyses outcomes signified that SMO outperformed other classifiers insignificantly by achieving 92.85% of accuracy. Based on x2, several swear terms, such as bontot, melancap, and kote, displayed significant correlation with Psychoticism Tweets due to the nature of the trait that has been subjected to criminality behaviour, for instance, aggressive and antisocial attributes. The findings illustrate the possibilities to adapt several personality aspects in order to enhance the effectiveness in detecting illicit social network messages.
Known for its plain and dry content, tajweed learning is often tedious, particularly for children. Our preliminary study confirmed that most of the learners were uninterested to learn tajweed and this fact was agreed by their educators. Currently, technological advancement helps learning enormously and it has been widely utilised, especially for the digital native generation. Therefore, we highlighted the use of augmented reality and gamification as an attempt to attract children to learn tajweed. Based on experience and motivational theory, tajweed augmented reality-based gamification learning model (TARGaLM) was implemented in the tajweed learning. To investigate the effectiveness of the proposed approach in terms of their emotional engagement (enjoyment) potential and learning performance, 198 children constituted four groups participated in the learning activities. TARGaLM successfully gained positive results of autonomy, challenge, points, badges, leader board, progression, immersion, and feedback, which are crucial for enjoyment. In the post-activity interviews, the students mentioned that the proposed approach was interesting. Furthermore, the proposed approach group indicated the highest decrease in articulation errors from the post-test compared to other groups. The use of current technology and approach not only has potential in bringing enjoyment, but also gives a positive impact on the learning outcomes.
The sago starch industry is one of the major revenue sources of the Malaysian state of Sarawak. This state is currently among the world’s leading producers of sago starch, exporting more than 40,000 tons every year to different Asian countries. This number is expected to rise since starch production and export value have been increasing 15.0%– 20.0% each year. Sago palm is subjected to various processes to obtain starch from its trunk. During processing, a huge amount of residual solid wastes is generated, such as bark and hampas, and in general, is burned or washed off to nearby streams. Along with the rising sago starch demand, the sago starch industry is now facing waste management problems, which have resulted in environmental pollution and health hazards. These wastes comprise starch, hemicellulose, cellulose, and lignin; hence, can be valorized into feedstock as value-added products. To date, these wastes have been utilized in the production of many materials like adsorbents, sugars, biofuels, nanomaterials, composites, and ceramics. This review article aims to summarize the various methods by which these wastes can be utilized besides to enlighten the major interest on sago hampas and bark.
Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of a watershed. A study was conducted to assess water quality and to establish relationship among water quality parameters in Kelantan River basin. Water quality data was obtained from Department of Environment, (DOE) Malaysia from 2005-2014. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to 15 water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of the watershed. From the results, five PCs were extracted which are collectively accountable for controlling approximately 70% of the watershed’s water quality. Results of cluster analysis indicated that three water quality parameters that included total suspended solids, total solids and turbidity control the water quality of the study area. These parameters were allocated into three clusters based on their similarity. The finding of this study will contribute to existing knowledge of the problems associated with water quality in the basin. This information can be put to use by land use managers and policy makers for future planning and development of the watershed.
The use of biometric features, to authenticate users of different applications, is growing rapidly in recent years, according to the high sensitivity of the protected information and the good security that biometric authentication provides. In this study, a method is proposed to measure the similarity between two fingerprint images, using convolutional neural networks, instead of classifying them. Thus, modifying the users that the proposed method can recognize is a matter of adding or removing model images of the users’ fingerprints. The similarity between the fingerprint image and every model image was measured in order to select the user with the highest similarity to the input image as the recognized user, where that similarity measure was compared to a threshold value in order to authenticate that user. The evaluation results of the proposed method, using FVC2002_DB1 and FVC2004_DB1 showed that the proposed method had 99.97% accuracy with 0.035% False Acceptance Rate (FAR) and 0% False Rejection Rate (FRR). Hence, the proposed method has been able to maintain high accuracy while eliminating the vulnerabilities of biometric authentication systems imposed by the use of separate stages for features extraction and similarity measurement.
This study evaluates the spatiotemporal distribution of aerosol optical thickness (AOT) over Malaysia. The significance of aerosols in regional and global climate change assessment has become a pressing topic in recent climate discussions. Two different approaches are used in measuring AOT; satellite imagery and ground measurement approaches. However, the satellite approach is deemed the best way for monitoring the patterns and transport of aerosols largely due to its extensive spatial coverage and reliable repetitive measurements. The data in this study were obtained from a Sea-viewing Wide Field-of-view Sensor (SeaWiFS), a Multi-angle Imaging Spectroradiometer (MISR), and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors based on a NASA-operated Giovanni portal. Ground-based Aerosol Robotic Network (AERONET) datasets from two sites over the study area were also used. The results show that the highest AOT ground values of 1.93 and 2.00 were recorded in September 2015, at USM station and Kuching station, respectively. Throughout the 15 years of recorded data, the monthly average value of AOT reached its highest values in September, October, and November. In these months, the value of AOT went above 0.40, unlike in other months of the year. Significantly, the results indicate that Malaysian air quality can be evaluated based on AOT values, as these show the variation in optical properties of aerosol.
Referring to the existing model that considers the image boundary as the image background,
the model is still not able to produce an optimum detection. This paper is introducing
the combination features at the boundary known as boundary components affinity that is
capable to produce an optimum measure on the image background. It consists of contrast,
spatial location, force interaction and boundary ratio that contribute to a novel boundary
connectivity measure. The integrated features are capable to produce clearer background
with minimum unwanted foreground patches compared to the ground truth. The extracted
boundary features are integrated as the boundary components affinity. These features were
used for measuring the image background through its boundary connectivity to obtain the
final salient object detection. Using the verified datasets, the performance of the proposed
model was measured and compared with the 4 state-of-art models. In addition, the model
performance was tested on the close contrast images. The detection performance was
compared and analysed based on the precision, recall, true positive rate, false positive
rate, F Measure and Mean Absolute Error (MAE). The model had successfully reduced
the MAE by maximum of 9.4%.
A non-coastal cockle farming area such as an estuaries zone might become an alternative for continuous and sustainable cockle supply in the future. The main objective of this research is to determine the growth and mortality rate of Tegillarca granosa (T. granosa) within an estuary area. Three cockle plots were allocated along the estuary area of Kongkong Laut (P1, P2, P3) based on the geographical area, from upper to lower part of estuaries. Cockle monitoring activity was conducted from August to December 2015 for both in-situ water parameters and the cockles’ growth increments. This study shows that within a brackish estuarine environment, the highest cockle growth increment was recorded within the highest water salinity trend area (26.92 ± 4.79 ppt; P2), with a shell increment of 2.70 ± 0.52 mm per month, while the lowest cockle growth increment was recorded within the lowest water salinity trend area (17.65 ± 5.73 ppt; P1) with the shell increment of 2.05 ± 0.86 mm per month. One-way ANOVA shows that there was significant difference (p
A number of different studies were reviewed to investigate the functionality of splitter plates for the
purpose of drag reduction and vortex elimination behind a circular cylinder. The studies were carried
out numerically or experimentally in different combinations of Reynolds range, 2D or 3D dimensions,
with intention of drag reduction, vortex suppression or both. Results were compared to discover the
generalities of a splitter plate’s applications and its performance in drag reduction and vortex control.
The reduction of 12% up to 38.6% in drag coefficient suggests that all reviewed studies verified the
effectiveness of upstream plate in drag reduction. Varied upstream plate’s gap ratios (gap between the
plate and cylinder) were tested and the optimum position was obtained. For the finite cylinder case,
however, the studies discovered that the effectiveness of upstream plate decreased severely and thus, are
barely considered as a drag reductive tool for shorter cylinders. Although downstream plate influences
drag force, its prominent application is found to be vortex shedding elimination (up to 14.7%). The
length ratio and gap ratio of downstream plate were varied in these studies and it was found that the
length ratio was a more important factor compared with the gap ratio in the case of vortex suppression.
The use of the Light Rail Transit (LRT) system is currently preferred because LRT is sustainable,
improves travel options and facilitates swift mobility in urban areas. Hence, the structural stability
and safety of this public transportation system against seismic occurrences are indispensable. Given
that these structures cannot be considered conventional frames because of their complex architectural
design, focussing meticulously on reliable seismic design codes and structural rehabilitation techniques
is vital for the design of the lateral resistance system. One Malaysian LRT station is considered in this
study, and the seismic response of this train station when equipped with supplementary viscous damper
devices is evaluated. Thus, the LRT station is modelled through finite element simulation. The methods
of seismic analysis are limited to linear seismic analyses, namely, response spectrum and time history
analyses. Results derived in this study show a significant improvement in structural response when the
station is fitted with dampers; approximately 40% reduction in displacement is observed at the top joint
of the roof. Furthermore, the lateral base shears decrease by approximately 70%.
Viscosity, peel strength, shear strength and tack of styrene-butadiene rubber (SBR)-based pressuresensitive
adhesive were studied using silica as the filler. The silica content was varied from 10-50 parts
per hundred parts of rubber (phr). The tackifying resin, solvent and coating substrate used were gum rosin,
toluene and poly(ethylene terephthalate) (PET) respectively. Viscosity of the adhesive was determined by
a Brookfield Viscometer. Both peel strength, shear strength and tack were measured by a Lloyd Adhesion
Tester operating at 10-60 cm/min. Results show that viscosity increases with silica loading due to the
concentration effect. Peel strength, shear strength and tack passes through a maximum value at 20 phr
silica loading, an observation which is attributed to the culmination of wettability at the optimum silica
content. Peel strength decreases with the angle of testing at a fixed silica loading and coating thickness.
Both peel strength, shear strength and tack increases with coating thickness and testing rates.