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Music listening preference and the psychological well-being among urban youth in Klang Valley, Malaysia / Danial Kordy
Get PDFThe main purpose of this is to investigate the youths’ psychological well-being went expose to their music listening preference. The participants are six urban youths ages between 18 to 29 years old living within Klang Valley, Malaysia. The participants are categorized into two different groups, three musicians and three non-musicians. Data was collected through qualitative method semi-structure interview. Due to current global pandemic Covid-19, all the interviews were conducted using Zoom video call during MCO and PKP. The study contributes to the understanding of the relationship of music and urban youth. The findings suggest that the influencing factors of the music listening preference for urban youths are musical background, personality, and musical taste. Furthermore, the reason behind why the urban youths listen to their preference music is entertainment and emotion. Besides, the findings show that the benefits of music listening preference on the well-being of the urban youth are emotional impact and self-reflection. Future studies are recommended to explore various emotions that youths are feeling when they listen to music. From the methodological perspective, future studies are recommended to employ mixed method research with survey and questionnaire with a larger population
Heat flux performance of heterogeneous nanofluid boundary layer flows over an inclined cylinder using variant graphene and carbon-based nanoparticles / Siti Nur Ainsyah Ghani
Get PDFThe heat transfer processes, boundary layer, heat exchangers, nanofluid models are briefly explained in the initial part of study. Then, the laconic preface on magnetohydrodynamic (MHD) and stagnation point flow are also included. The equations of boundary layer assumptions for continuity, momentum and energy are describe generally followed by the selected cylindrical coordinates. The governing partial differential equations (PDEs) are molded according to Tiwari-Das model and reformulated into nonlinear ordinary differential equations (ODEs) by using similarity expressions. A shooting technique is opted to reformulate the ensuing equations into boundary value problems which are then solved numerically by using a finite difference code that executes the three-stage Lobatto IIIa formula in Matlab. Thus, variant graphene-based nanoparticles; graphenes, graphene nanoplatelets (GNPs), graphene oxides (GOs), Single Walled Carbon Nanotubes (SWCNTs) and Multiple Walled Carbon Nanotubes (MWCNTs) in a water-base fluid is the center of interest for the present study. The comparisons between the present and previous published results are presented for accuracy and veracity of the numerical results. The effects of constructive parameters toward the model on dimensionless velocity and temperature disseminations, reduced skin friction coefficient and reduced Nusselt number are presented graphically and discussed in details. Research outcomes show graphenes-water nanofluid has the highest heat flux performance compared to other selected nanofluids across many emerging parameters considered in this study
Experimental and computational studies of fluid structure interaction of tsunami bore on coastal bridges / Iman Mazinani
No full textTo understand the potential effect of the tsunami forces on coastal bridges due to tsunami bore, a series of experimental tests were conducted, and results were compared to those calculated with a fluid-structure interaction (FSI) analysis. Various wave heights and shallow water were utilized in the experiments and computational process. Nine types of 1:40 scale concrete bridge models were placed in a mild beach profile to a 24 m × 1.5 m × 2 m wave flume for the experimental investigation. An Arbitrary Lagrange Euler (ALE) formulation was developed for the propagation of tsunami solitary and bore waves by an FSI package of LS-DYNA using a high-performance computing (HPC) system. The results showed that the fully coupled FSI models could plausibly capture the tsunami wave forces for all ranges of wave heights and shallow depths. It was identified that after ~1.4 s, the wave elevation could potentially reach it's maximum (here, 0.35-0.4 m), which was in good agreement with the results calculated by the Weigel model. Likewise, the Bore height increased with an increase in the wave height, reaching ~0.22 m at a wave height of 0.38 m. The horizontal force reached 180 N after 7.3 seconds and then gradually decreased approaching zero after 8 seconds. The effects of the overturning moment, horizontal force, uplift, and impact force on the pier and deck of the bridge were evaluated. The presence of girders, on a model of a bridge deck with girders, is studied by making a direct comparison by changing the number of girders on the model. It appears that the girders have a significant influence on the uplift and overturning moment. Increasing the number of girders on bridge models significantly increased uplift and overturning moments. However, this variation depended on wave conditions and shallow water. The effect of four different baffle plates on the mitigation of tsunami force is investigated. The result indicated the full baffle plate reduced horizontal and uplift force up to 40 %
Temuan community of Kampung Orang Asli Batu 16, Gombak: Traditional knowledge of medicinal plants and evaluation of anti-inflammatory potential of selected plants / Siti Nor Azreen Abdul Manap
No full textThe utilization of medicinal plants for the treatment of various ailments and health conditions is a common practice among the indigenous people or locally known as Orang Asli in Malaysia. However, traditional knowledge on medicinal plants used by Orang Asli has not been documented extensively. Therefore, the aim of this study was to document all the medicinal plants and their applications in treating ailments or health conditions by the Temuan tribe of Kampung Orang Asli Batu 16, Gombak, Selangor. This valuable traditional knowledge must be documented and preserved before it is lost due to modernization. Assessment of selected medicinal plants for their anti-inflammatory activity was conducted to provide evidence on the effectiveness of the medicinal plants in inflammation treatment. Data were collected from 11 respondents in the village using a semi-structured questionnaire with prior consent. Three medicinal plants such as Molineria latifolia, Tacca integrifolia, and Hymenocallis speciosa were selected for the evaluation of anti-inflammatory potential based on in vitro assay through inhibition of protein denaturation method. A total of 41 medicinal plant species belonging to 28 plant families were documented for their usage in the treatment of 37 ailments or health conditions. Plants of the family Zingiberaceae made up the largest number of medicinal plants (17.1%) followed by Fabaceae (9.8%) and Arecaceae (7.3%). Leaves (34.1%) are the most frequently used plant part for the preparation of herbal remedies. Although a variety of methods have been used for the preparation of herbal remedies, decoction (56.9%) is the most common method of preparation used by the Temuan tribe. In terms of mode of application, oral administration (68%) is the most common followed by being applied topically and bath with 14% and 10%, respectively. Bound topically (8%) is the least typical way of administration. Diabetes and fever are the most common ailments cured using medicinal plants. Parkia speciosa and Ficus deltoidea are the most commonly utilized plant species as remedies for various ailments in this study. The present findings on inhibition of protein denaturation of ethanolic and aqueous extracts of M. latifolia showed concentration-dependent inhibition within the range 65.63 ± 1.56% to 155.91 ± 2.15% of inhibition rate throughout the concentrations tested (100 – 500 μg/mL). Ethanolic extract of T. integrifolia leaves exhibited the highest (86.01 ± 4.04%) anti-inflammatory activity at a concentration of 100 μg/mL compared to their aqueous extract with only 31.88 ± 1.45% at a concentration of 300 μg/mL. Meanwhile, for extract of H. speciosa leaves, the aqueous extract had shown the highest suppression of protein denaturation with 87.18 ± 2.56% at a concentration of 200 μg/mL while only 42.68 ± 0.00% inhibition was observed for its ethanolic extract in the same concentration. All ethanolic extracts of these selected plants showed significant differences in inhibition activity compared to their aqueous extracts. The effect of indomethacin, a common anti-inflammatory drug, was found to be less when compared with these plant extract. Hence, the findings in this study verified the anti-inflammatory activity of the selected plants and support the claim by the Temuan that M. latifolia, T. integrifolia, and H. speciosa could alleviate their inflammation disorders
Proteomic analysis of Pseudogymnoascus spp. From different geographical regions in response to temperature variation / Nurlizah Abu Bakar
No full textThe need for understanding the detrimental effects of environmental stress for soil microorganisms is becoming more significant with current global warming issues. Temperature may alter the abundance of species in soil ecosystems, leading to consequential changes in microbial communities. Under temperature stress, fungi undergo numerous physiological changes in their proteome in order to survive. Understanding the changes in fungal proteomes can give insights into the complex protein responses that occur under high and low temperature stress. Mass spectrometry (MS)-based proteomics is a powerful tool that has helped researchers to identify and quantify complex protein mixtures in various cell systems. Pseudogymnoascus, a soil fungal genus that occurs in polar and temperate regions, is also a known producer of many extracellular hydrolase enzymes that contribute to soil decomposition. It is not known whether the mechanisms of temperature stress response of Pseudogymnoascus spp. differ in strains isolated from different regions and exposed to different environmental conditions. In this study, Pseudogymnoascus was chosen as a model taxon to characterise changes in fungal proteomic profiles in response to temperature stress. Analyses of the thermal tolerance and sensitivity of six isolates of Pseudogymnoascus spp. were carried out using temperature-dependent growth studies and colony morphological changes. Description of proteome profiles of Pseudogymnoacus spp. cultured at a non-stressful temperature (15°C) was carried out using liquid chromatography tandem mass spectrometry (LC MS/MS) to provide baseline information and knowledge of the phenotypic diversity of all six isolates. Bioinformatic analyses of differentially expressed proteins and Gene Ontology (GO) enrichment were used to identify the pathways that were significantly enriched in response to temperature variation (cold and heat stress studies). All six isolates were characterised as psychrotolerant fungi with lower and upper temperature limits for growth of 5°C and 25°C, respectively. The proteome profiles of all six isolates showed that the majority of proteins identified were clustered into groups representing metabolic functions and catalytic activities. Temperature stress response of Pseudogymnoascus spp. involved a wide range of pathways being enriched, with no suggestion of response mechanisms following specific geographical patterns. The data obtained in this study provide new information on how Pseudogymnoascus spp. respond to temperature variation in their environment and increase our understanding of how these temperature stress responses in the context of global climate change may affect decomposition processes in soi
Spectral interrogation technique for tilted fibre Bragg Grating devices in refractometry and immunoassay / Waldo Udos
No full textFibre Bragg grating (FBG) has been an important optical device since its discovery in 1978. Today, FBG is well known for its capability as a sensor and its wide-spread usage in various industrial and biomedical sectors. Tilted fibre Bragg grating (TFBG) is one of the FBGs that has superior sensitivity to ambient refractive index. This has attracted the curiosity and attention among the researchers. However, the comprehension and analysis for the sophisticated output spectrum of TFBG remains a challenge to researchers and users. Hence, there is a pressing need for the development of suitable and robust spectral interrogation technique for the TFBG’s output spectrum. Thus, as part of the research, its spectral interrogation technique in refractometry and immunoassay was studied. In this research, gold (Au) was deposited on TFBG to form gold-coated TFBG (Au-TFBG) by using the electron beam evaporation method. However, the ability to form an even thickness of gold film was limited due to the absence of a rotatory mechanism in the machine. Deposition schemes based on one-step, two-step and three-step deposition schemes were simulated and experimentally studied. The characteristics of deposition profile for each deposition scheme and remediation of shortcomings were discussed. The simulation was proven based on FESEM images of the deposited gold film on Au-TFBG. The characterization of the tilt plane of TFBG was studied to determine the effect of the uneven gold thickness to the optical transmission spectra of TFBG. The deposition angle, α was defined as the angle between the deposition direction and the tilt plane. The deposition angles of interest were 0º, 30º, 60º, 70º, 80º and 90º. It was worth noting that the deposition angle affected the transmission spectra of Au-TFBG in the aspect of the attenuation of cladding resonance in the longer wavelength range, cut-off wavelengths and the SPR resonance bandwidth. The optical transmission spectra of TFBG and Au-TFBG are complicated. It is hard to make data analysis due to the complexity of the spectrum. Besides that, the spectra characteristics depend on some fabrication parameters and affecting the technique of data acquisition. In this research, the optical transmission spectra was studied, and a new analytical method was developed to ease the signal demodulation. Lastly, Au-TFBG were employed as biosensors for the detection of EV-A71 virus, one of the causative agents for hand foot and mouth disease (HFMD). The biofunctionalization methods and the incorporation of Monoclonal antibodies (MAb) as the bio-receptor were introduced and discussed. It was noteworthy that MAb was responsible for the immobilization of EV-A71 virus and this contributed to the change in SPR mode intensity. LOD of the Au-TFBG was 0.343 × 10-6 g/ml. The bio-sensor was also proven to be sensitive to EV-A71 virus while non-reactive to other HFMD virus strains in the specificity tests
Application of material flow analysis and water quality modelling to facilitate the efficiency of leachate management system / Tengku Nilam Baizura Tengku Ibrahim
No full textLeachate from landfills is known to be one of the major environmental impacts, particularly those constructed near rivers. Therefore, this study is conducted to assess the impact of discharged leachate, using SL Landfill and Sembilang River as the case study. Solid waste generated from 2015-2016 served as input data on volume and composition of the solid waste that was sent to SL Landfill. A material flow analysis (MFA) is employed to trace the fate of solid waste that has been disposed and leachate that is produced at SL Landfill using STAN software. Six parameters in Water Quality Index (WQI), viz. DO, pH, BOD, COD, NH3N, TSS were used to define the quality of the river water. A total of 80 water samples were collected monthly for 1 year from 10 sampling stations. In order to predict and assess the pollutant transport in Sembilang River basin, QUAL2K was used as a simulation model. Water quality parameters (DO, BOD and NH3-N) were chosen to model the impact from the SL landfill effluent towards Sembilang River. The findings showed that the highest composition of waste that was present at the landfill can be categorized as food waste with 32% of the total waste input. Results from the MFA model showed that the amount of leachate generated from SL landfill was 123,386 m3/year. The finding had also successfully identified the input and output flow of SL Landfill, with an overall input values of 948,505 ton per year and the output at 393,292 ton per year. From 3 different possible scenarios that were chosen, results from the MFA showed that composting was the most effective method in terms of reducing leachate production in SL Landfill which expected to reduce leachate production by up to 92%. The Sembilang River water quality results show that it falls in Class III of the WQI, which ranges from 43.46 to 68.03 mg/L. Different water quality model scenarios were simulated in order to assess the pollutant transport on the Sembilang River water quality and it was found that the effects of different scenarios for water quality parameters were particularly noticeable for DO and BOD. However, for the NH3N parameters there were no significant change and had remained in Class IV and V. This was due to the high NH3N concentration from a few points along the river. These findings showed that the MFA, water quality assessment and modeling were found to be the best methods to predict and analyzed the composition of waste to the leachate production and the effect to the river water pollution
A visual analysis of the Kelantan shadow play puppets / Fiona Wong E Chiong
No full textWayang Kulit Kelantan, or Kelantan shadow play, is a traditional Malay folk theatre form in the northern part of peninsular Malaysia, and parts of southern Thailand. It performs the Hikayat Maharaja Wana, a localised version of the famous Indian epic, Ramayana. However, with the diminishing state of Wayang Kulit Kelantan performances in recent years, there is lesser demand and necessity for puppeteers and puppet-makers in Kelantan to produce puppets. There is a lack of scholarship and in-depth research particularly on the visual analysis of the Wayang Kulit Kelantan puppets. From the visual analysis of the puppets, it is evident that most puppets are designed to portray the characters in keeping with Indonesian-Malay aesthetics terms of their refinement or coarseness. These principles apply to the characters, as well as in the manner that they are portrayed in puppets. However, the puppets are designed in such a manner that certain refined characters appear coarse-looking, and vice versa. In most instances such figures are not gods or human beings. An outstanding example is Hanuman Kera Putih. The puppets tend to conform to a certain structure or ‘formula’ consisting of a head in side-profile; upper torso en face; lower torso and limbs in side-profile; with ornamentation including headdress, clothing, and accessories filled with intricate motifs and patterns; as well as a platform or vehicle. Certain puppets of the same classification, though appearing very similar, can still be distinguished from each other based on certain features of characterization. In addition, the puppets also reflect Indian, Thai or Javanese influences. The principal characters—Seri Rama, Siti Dewi, Maharaja Wana, and Hanuman Kera Putih—tend to draw parallels with their counterparts in Indian, Thai and Javanese cultural iconography and visual manifestations. The puppets are portrayed differently by the puppet-maker according to his individual style, preference, interpretation, and artistry, based on the details of the puppets passed down from their teachers. Instead of following a certain ‘standard template’ of design, changes are often made to the overall structure of the puppet’s figure to accommodate the physical attributes of the puppet-making materials during the crafting process. Over time, each dalang and puppet-maker has developed a personalized design style for his puppets based on his understanding of the character, different from those made by his predecessors or teachers, and peers. A visual comparison among the stylistic variations of the puppets has been made in this study. The puppet-maker produces his own desired motifs and patterns in his puppets’ design, which amalgamate on a single surface reflecting a strong sense of eclectic appeal. These motifs and patterns—deriving from nature and thus carry localised names, including their symbolisms—resemble those in local traditional material cultures in Kelantan, such as textiles, woodcarving, silverwork, and wau. The level of intricacy and detailing in the motifs reflect the puppet-maker’s skill and perfection. In conclusion, this study shows the significance of the visual aspects of the Wayang Kulit Kelantan puppets as a means of preserving a highly important example of Malaysian cultural heritage
Multi-feature fusion framework for automatic sarcasm identification in Twitter data / Christopher Ifeanyi Eke
No full textRecently, sentiment analysis in social network research has gained much recognition. The notion behind sentiment analysis is to determine the polarity of the emotion word in an expression. Analysis of people’s sentiments is a process of identifying subjective information in source documents. The process of identifying people’s opinions (sentiments) about products, politics, services, or individuals brings a lot of benefits to the organizations. For example, sarcasm is a type of sentiment where people express their negative emotions using positive words or intensified positive words in a text. In a sarcastic utterance, the expressed statement usually deflects the different meanings than their actual composition. Various feature engineering techniques such as Bag-of-words (BoWs), N-gram, and word embedding have been investigated to detect sarcasm in textual data automatically. However, the use of the features mentioned above results in the loss of contextual information due to the methods ignoring the context of words in the text. Furthermore, there are issues bothering on the sparsity of training data in sarcasm expression. This issue makes a feature vector for each sample constructed by BoW mostly null due to the microblog's word limit. Moreover, many deep learning methods in Natural Language Processing uses word embedding learning as a standard approach for feature vector representation. Nevertheless, one of the major drawbacks of word embedding is that it does not consider the sentiment polarity of the words. Consequently, words with opposite polarities are mapped into a close vector. To address the above-named problems and enhance the predictive performance in sarcasm identification, a Multi-Feature Fusion Framework for sarcasm identification is proposed using two classification stages. The first classification stage is constructed with a lexical feature only, extracted using the BoW technique and trained using five standard classifiers, including Support Vector Machine, Decision Tree, K-Nearest Neighbor, Logistic Regression, and Random Forest to predict the sarcastic tendency based on the lexical feature. In stage two, the extracted lexical feature is fused with the length of microblog, hashtag, discourse markers, emoticons, syntactic, pragmatic, semantic (GloVe embedding), and sentiment related features to form a feature fusion and modelled using various classifiers, including Support Vector Machine, Decision Tree, K-Nearest Neighbor, Logistic Regression, and Random Forest. The developed Multi-feature framework effectiveness is tested with various experimental analysis, which was performed to obtain classifiers’ performance. The evaluation shows that the constructed classification models based on the developed framework obtained results with the highest precision of 94.7% using a Random Forest classifier. Finally, the obtained results were compared with baseline approaches, and the proposed Multi-feature fusion framework attained the average detection precision between 11.2% - 27.1% compared to the baseline methods. The comparison outcomes show the significance of the proposed framework for sarcasm identification. Thus, the data sparsity issue can be resolved by selecting the discriminative features from the sparse training set before the modelling phase and bolstering the content-based feature with contextual information can enhance the predictive performance of sarcasm classification in textual data
EEG-based IQ and learning style classification model using artificial neural network / Muhammad Marwan Anoor
No full textIntelligence and learning styles are among most widely studied traits in cognitive psychology. Currently, both aspects of cognition can only be assessed using paper-based psychometric tests. The methods, however, are exposed to inconsistency issues due to the variation of examination format and language barriers. Hence, this study proposes an intelligent system for assessing intelligence quotient (IQ) level and learning style from the resting brainwaves using artificial neural network (ANN). Eighty-five individuals from varying highest educational backgrounds have participated in this study. Resting electroencephalogram (EEG) is recorded from the left prefrontal cortex using NeuroSky. Control groups are established using Kolb’s Learning Style Inventory (LSI) and a model developed based on Raven’s Progressive Matrices (RPM). Subsequently, theta, alpha and beta power ratio is extracted from the pre-processed EEG. Distribution and pattern of features show a correlation with the Neural Efficiency Hypothesis of intelligence and Alpha Suppression Theory. The power ratio features are then used to train, validate and test the ANN model. The system has demonstrated satisfactory performance for IQ classification with accuracies of 98.3% for training and 94.7% for testing. The proposed model is also able to classify learning style with accuracies of 96.9% for training and 80.0% for testing