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Analisis vokal lagu Mengadap Rebab dalam teater Makyung Kelantan / Wan Ismail Naqiuddin Hasbi
No full textMengadap Rebab, sebuah lagu pembuka semasa babak permulaan persembahan bagi teater tradisional Makyung. Ia dipersembahkan lengkap dengan elemen muzik, nyanyian dan seni gerak tari.Pemain watak Pak Yong yang menjadi watak utama di dalam teater ini diberi peranan sebagai vokal utama dan seterusnya setiap rangkap akan disahut oleh sekumpulan suara yang dikenali sebagai Jong-Donde. Tesis ini membentangkan analisis berkaitan dengan vokal atau suara yang dinyanyikan oleh pemain watak Pak Yong dalam lagu Mengadap Rebab. Menerusi analisis yang dijalankan kepada beberapa orang pemain, ia akan merungkai hubung kait nada dan variasi alunan suara yang dinyanyikan serentak bersama alat muzik Rebab. Melalui kajian ini, akan dapat diperhatikan julat suara yang diperlukan bagi melengkapkan nyanyian lagu ini. Perkara yang dibahaskan juga adalah berkaitan dengan tingkat suara yang dimainkan oleh rata-rata pemain watak di dalam lagu ini dan kategori vokal yang diperlukan bagi seorang lelaki dan wanita. Seperkara lagi adalah huraian berdasarkan improvisasi yang dimainkan serta kemahiran yang perlu ada bagi setiap individu yang ingin menyanyikan lagu Mengadap Rebab di dalam teater ini. Sebagai kesimpulan, tesis ini akan merungkai elemen seni suara dalam karakter yang menjadi faktor penyumbang kepada nyanyian lagu Mengadap Rebab ini untuk dipersembahkan
Analysis of photovoltaic panels performance and power output forecasting based on optimized deep learning technique / Muhammad Naveed Akhter
No full textAlternative renewable energy sources have a significant contribution to meet the world’s energy demand due to population climax and reduce global warming. Solar energy is a major alternative energy source to generate electricity through photovoltaic (PV) systems. However, the generated PV power is susceptible to unpredictable climate and seasonal factors, which cause an unfavorable effect on the stability, reliability, and operation of the grid. Therefore, proper monitoring of the PV system and accurate forecasting of PV power output is required to ensure the stability and reliability of the grid. The purpose of monitoring the PV systems is to keep the PV system in continuous functional status with improved performance. In the first part of this work, the performance of three grid-connected photovoltaic systems installed at the rooftop of the engineering tower building, University of Malaya, Kuala Lumpur, Malaysia, is evaluated. The grid-connected PV systems are based on poly-crystalline (p-si), mono-crystalline (m-si), and a-si (amorphous silicon (a-si)) technologies. The performance is evaluated on monthly and annual data monitored from January 2016 to December 2019. A comprehensive analysis is conducted on eleven performance parameters: performance ratio, capacity factor, array yield, final yield, PV array efficiency, PV system efficiency, inverter efficiency, AC energy, array losses, system, and the overall losses. Secondly, an hour ahead forecasting of solar power output is performed on an annual basis for the aforesaid three PV systems over the same period (2016-2019), based on forecasting accuracy measurement parameters such as RMSE, MSE, MAE, r and R2. A deep learning method (RNN-LSTM) is proposed and compared with regression (GPR, GPR (PCA)), machine learning (SVR, SVR (PCA), ANN), and hybrid methods (ANFIS (GP), ANFIS(SC), ANFIS(FCM)) for an hour ahead forecasting of PV power output on an annual basis for the whole period. Moreover, Salp Swarm Algorithm (SSA) is used to tune the hyperparameters of the developed deep learning method on an annual basis over four years to enhance its forecasting accuracy and is compared with RNN-LSTM, GA-RNN-LSTM, and PSO-RNN-LSTM. Performance analysis findings show that p-si PV system performs better with a higher annual average (array yield (1309.7 h), array efficiency (12.17 %), and system efficiency (11.33 %)) accompanied by less degradation in almost all performance parameters compared to a-si and m-si PV systems. Moreover, the composite PV system has the potential to avoid 28143.7 kg of CO2 emissions in four years. The forecasting results show that the proposed deep learning technique (RNN-LSTM) has presented lower (RMSE, MSE) and higher (r and R2) compared to other techniques. Moreover, the proposed hybrid method (SSA-RNN-LSTM) is found (19.14% and 21.57%), (15.4% and10.81%) and (22.9% and 25.2%) better in terms of (RMSE and MAE) than developed (RNN-LSTM) for p-si, m-si and a-si PV systems respectively. Furthermore, the proposed hybrid method (SSA-RNN-LSTM) has shown higher R2 and maximum convergence speed compared to GA-RNN-LSTM and PSO-RNN-LSTM. In addition, the proposed deep learning and hybrid models (SSA-RNN-LSTM) are found to be robust and flexible in the prediction of power output for three different PV systems over four years duration
Prevalence and associated factors of cancer-related fatigue among cancer patients in University Malaya Medical Centre / Tan, Hooi Ling
No full textCancer-related fatigue is a distressing symptom commonly experienced by
our patients diagnosed with cancer. However, there is no data on cancer-related fatigue
among our local population. The objective of this study was to evaluate the prevalence of
cancer-related fatigue and its association with sociodemographic factors, clinical
characteristics of patients, depression, anxiety and demoralisation. Correlation between
cancer-related fatigue, depression, anxiety and demoralization were also studied.
Method: A cross-sectional study was conducted using convenience sampling among one
hundred and fifty patients from Oncology Clinic, University Malaya Medical Centre,
Kuala Lumpur from July 2020 until December 2020. Data were collected from self-
administered questionnaire consisted of sociodemographic data, clinical characteristic of
patients, Fatigue Symptom Inventory (FSI), Hospital Anxiety and Depression Scale
(HADS) and Demoralisation Scale. The study participants were also interviewed to assess
fatigue using Proposed ICD-10 criteria for Cancer-related Fatigue (interview was
conducted based on Diagnostic Interview Guide for Cancer-related Fatigue). Chi-square
test, Spearman’s correlation and logistic regression were used to study the relationship
between cancer-related fatigue and its associated factors.
Result: The mean age of the study participants was 63.3 ± 10.29 years old. Majority of
the subjects were female (n=102, 68.0%), of Chinese ethnicity (n=74, 49.3%) and married
(n=135, 90.0%). Most of our patients were diagnosed with solid tumours (n=149, 99.3%),
with breast cancer being the commonest (n=50, 33.3%). Most of the subjects were at
Stage IV (n=68, 45.3%), having had the diagnosis of malignancy between one to five years (n=105, 70.0%). Out of 150 study participants, 58.7% of them were diagnosed to
have cancer-related fatigue. Among patients with cancer-related fatigue, 97.7% of them
were reported to have clinically meaningful fatigue (p<0.001), 17.0% reported anxiety
symptoms (p=0.009), 34.1% had depressive symptoms (p<0.001) and 28.4% had high
demoralisation level (p=0.001). All assessment scales were significantly correlated to
each other (p<0.001). ICD-10 scoring was positively correlated with Total Disruption
Index of FSI (r=0.761, p<0.001) and FSI composite (r= 0.751, p<0.001). Cancer-related
fatigue also correlated positively with anxiety (r= 0.454, p<0.001), depression (r= 0.544,
p<0.001) and demoralisation (r= 0.461, p<0.001). Stages of cancer was the significant
contributing factor to cancer-related fatigue (p=0.021). No significant association was
found between fatigue and sociodemographic data, other clinical characteristics of
patients. In addition, stages of cancer, anxiety, depression and demoralization
independently predict the presence of cancer-related fatigue in our study population.
Conclusion: 58.7% of our cancer patients have reported cancer-related fatigue. Stages of
cancer was identified to be a significant contributing factor. Cancer-related fatigue was
positively associated with depression, anxiety and demoralisation. Routine assessment
should be done to screen for fatigue and related psychological factors in our clinical
practice
Depression, anxiety, perceived social support and associated factors among elderly nursing home residents in the Klang Valley / Pritiss Nair
No full textIntroduction: Depression and anxiety among the elderly brings about various adversities which
affects the physical and psychological state of an individual and is a leading cause of disability
worldwide and a primary contributor to the global burden of disease. Meanwhile, perceived
social support from family members, relatives or friends, may improve an individual’s conduct,
coping, physical and psychological well-being.
Objectives: This study aims to determine the prevalence of depression and anxiety, perceived
social support as well as the socio-demographic correlates among elderly residents residing in
nursing homes in the Klang Valley.
Study Design: It is a cross-sectional study conducted among elderly residents residing in
nursing homes in the Klang Valley. The instruments that were used in this study includes,
socio-demographic questionnaire, Geriatric Depression Scale (GDS-30) was used to assess
depression among elderly residents and Beck’s Anxiety Inventory (BAI) was used to measure
anxiety. Perceived social support was measured using Multidimensional Scale of Perceived
Social Support (MSPSS). Cognition of all residents were screened at the beginning of the study
using Elderly Cognitive Assessment Questionnaire (ECAQ).
Results: This study involved 224 elderly residents from thirty nursing homes around the Klang
Valley. A majority of the geriatric population residing in nursing homes have both depressive
symptoms (n =211, 94.2%) and symptoms of anxiety (n =182, 81.2%). Subjects with higher
perceived social support were significantly less depressed as compared with older adults who
perceived poor social support. However, lower perceived social support was not a significant
contributor to symptoms of anxiety.
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Conclusion: Depressive and anxiety symptoms are highly prevalent among elderly residents
of nursing homes. Integrating social support to an individual in addition to their existing
treatment plan, helps to improve their overall psychological well-being
The effects of organizational role and flexible work on workers' health and job satisfaction / Abdulrahman Algarnas
No full textThis paper is a study on the health impacts associated with working from home due
to the COVID-19 pandemic. It aims to assess factors relating to flexible work dynamic
and role of organizations in affecting workers' health and job satisfaction. The model of
this research is comprised of four factors related to physical and mental health, job
satisfaction, organizational role, and flexible work arrangement. From these factors, the
study attempts to find direct links between the variables. The study is particularly
important during the COVID-19 pandemic as many businesses and organizations aim to
measure effective work arrangements currently and moving forward. The instrument
used in this research is a questionnaire that was distributed to general workers from
different parts of the world. There were 32 valid participants that took part in the study,
rating their responses on a Likert scale. To answer the research questions, this study
used statistical analysis using SPSS and SmartPLS to test the proposed hypotheses. The
results show that flexible work arrangement positively affects workers' job satisfaction
and physical and mental health at β = 0.156 and β = 0.585 respectively. In addition, the
role of organizations was found to positively correlate with increased job satisfaction, at
β = 0.623, but not with physical and mental health at β = -0.144. Although the study
produced acceptable reliability and validity values, the validity is constrained within the
small sample size
Analysis and forcaset of road safety using big data / Yan Tianyu
No full textWith the rapid development of China's economy and the urbanization advancement
speeding up unceasingly, the motor vehicle ownership across the country are rapidly
expanding and urban road system is also becoming increasingly complex. . Consequently, all kinds of traffic violations and the traffic safety problem is widespread, and this has created great trouble to majority of the people who wish to travel safely. All
the above have brought great challenges to urban public traffic management. Road
traffic behavior safety has a very serious impact on urban traffic running state. It is
desired for the Department of Traffic Management to predict the occurrence of traffic
accidents before they happen. With the advancement of existing positioning and
communication technology, spatiotemporal data of vehicles can be accurately recorded
and stored in the transportation platform. In this project clustering analysis of
spatiotemporal data of vehicles is carried out through unsupervised learning to obtain
normal and abnormal vehicle trajectories. A safety prediction model is established for
the abnormal vehicle trajectory in the mid-term to effectively promote the application of
big data in road traffic safety management, and put forward relevant strategies and
suggestions to improve the efficiency of road traffi
Image based dental impression tray selection from maxillary arches using multifeature with ensemble classifier / Muhammad Asif Hasan
No full textDental impression tray is frequently used in dentistry to record patient’s oral structure for clinical oral diagnosis and treatment planning. Manual procedure of taking impressions is costly, time-consuming, and additionally, no research has been done to select dental impression tray from dental arch images using computer vision in real-life scenarios. In this spirit, an intelligent model is proposed based on computer vision and machine learning to select appropriate dental impression trays from maxillary arch images. A dataset of 52 patients’ maxillary arch images that matches one from 4 sizes of Kurten’s impression tray have been acquired. Various sets features such as, colors, textures, and shapes of the images were extracted to better characterize the maxillary arch images. Considering the importance of the features in describing the maxillary arch object and to improve the classification performance, a method based on multi-feature with ensemble classifier is proposed. Besides, the performance of a deep-learning based
multilayer perceptron neural network is also investigated. The proposed multi-feature with ensemble classifier attained 92.31% precision, 91.75% recall, 91.75% accuracy, respectively, on the dataset. This clearly establishes the feasibility of this study. An illustration of a real-life application of the proposed model is also provided
Use of Syair Aceh as a form of creative teaching in an Acehnese kindergarten / Putri Oktia Rezeki
No full textThe issue about engaging local wisdom in education in Indonesia brought a kind of understanding of how this practical teaching experience worked among Indonesian teachers. This study explored the use of Acehnese’s local wisdom which is syair Aceh in the teaching activity of private preschool located in Banda Aceh, Indonesia, by identifying the syair Aceh used, teacher’s self-past parenting life, and challenges encountered were listed as the research objectives. The purposive sampling was assigned to one urban private kindergarten and three experienced teachers were interviewed and observed, where the school's document was reviewed as well. A pilot study has been conducted and Nvivo 10 was the tool in the data collection process by adopting Miller Huberman. The results revealed themes depicted on research questions. Overall, there were seven syair Aceh used in teaching activity and the use was linked to the theory given that syair Aceh was a form of creative teaching with given elements; bring about the topic, pertinent action, self-determination, and assisting genuinely. The syair practiced linked to teachers' self-parenting style whereby used and believed as a way to develop a child’s spiritual value, moral value, and language. However, some challenges were encountered by children by pronouncing, environment, and by teachers from source, less-motivation, and pronunciation. Thus, it can be concluded that syair Aceh remains to exist in 2020, and it is applicable for creative teaching among pre-schoolers especially in Aceh, Indonesia
Information and communication technology usage for holistic development of children with dyslexia: A case study / Muhammed Zivali
No full textInformation and communication technology (ICT) usage among children has been increasing excessively in these days because of the portable devices, new life-styles and maternity ways. ICT usage and its effects towards the development has not been researched for the children with dyslexia. This study aimed to identify the positive and negative effects of ICT usage, as well as the perspectives of parents and teachers on ICT usage towards the holistic development of children with dyslexia. It was a single case study conducted in a private center at Kuala Lumpur which offers services to children with dyslexia. Three parents for children with dyslexia and their teachers participated in the study. The data was collected through interviews and document analysis. Atlas.ti, was adopted for the qualitative data analysis. Findings of the study revealed that ICT usage among the children with dyslexia had positive effects on the holistic development. It was seen that the children sustained longer attention, easy and fast learning, more confidence, and less struggles in reading and spelling. Moreover, ICT were good for language learning and for emotions sharing of the children with family and parents in addition to help to communicate with school friends while they felt better and happy. It was also seen that ICT kept children active when it improved their hand and finger motors. Nevertheless, the findings illustrated that the ICT usage had negative effects on certain aspects of the development of the children with dyslexia. Some children showed focus problem as ICT easily distracted them. Moreover, ICT caused mis-language usage and unwanted words in addition to the less interaction and communication with parents and peers as they preferred to use ICT in their spare time. The children had some emotional problems like throwing tantrum, bad and unwanted behaviors after using ICT in addition to the physical problems like less movement and problems in motor development. Furthermore, the parents and teachers are advised to control and limit the ICT usage among children by balancing with other activities as they were aware of the benefits and harmful side of the ICT usage. The study concluded that the correct ICT usage among children with dyslexia is important because it has positive and negative impact on the holistic development of these children
Analisis terjemahan fitur parataksis Arab Melayu dalam novel Kalilah dan Dimnah berdasarkan linguistik fungsional sistemik / Abdul Hadi Marosadee
No full textBinaan ayat bahasa Arab seringkali terbentuk melalui cantuman sejumlah klausa dalam satu ayat yang dihubungkan oleh waw al-‘aṭf (kata hubung waw). Majoriti sarjana bahasa Arab menakrifkan kata hubung waw ini dengan makna penggabungan antara klausa. Penggunaan kata hubung waw yang berlebihan boleh menimbulkan kekeliruan dalam memahami makna dan fungsi yang disebabkan oleh pertindihan makna. Kajian ini meneliti makna-makna bagi kata hubung waw yang terdapat dalam novel Kalilah Dan Dimnah dengan membandingkan teks sumber (TS) dengan teks terjemahan (TT). Novel ini merupakan novel bahasa Arab yang telah diterjemahkan ke bahasa Melayu terbitan syarikat Alasfiyaa, Malaysia. Bagi meneliti makna kata hubung waw, teori klausa kompleks daripada Linguistik Fungsional Sistemik (LFS) oleh Halliday &Matthiessen (2014) diaplikasi bersesuaian dengan fungsi asal kata hubung waw yang berperanan untuk membentuk klausa kompleks. Hasil kajian mendapati majoriti kata hubung waw dalam TS memberi makna peluasan sebanyak 66%, diikuti makna peningkatan untuk menerangkan alur cerita sebanyak 28.6% dan makna perincian sebanyak 5.4%. Penterjemahan kata hubung waw didapati tidak terhad kepada “dan”, tetapi terjemahan seperti “kerana” dan “tetapi” juga digunakan oleh penterjemah. Hasil kajian mendapati bahawa penterjemah menggunakan strategi tertentu dalam menterjemahkan klausa kompleks melalui kata hubung waw seperti pengguguran dan penambahan klausa, mengalih makna dan keterikatan klausa melalui strategi peralihan taksis, makna dan jumlah klausa. Kesimpulannya, teori LFS sesuai diaplikasi untuk meneroka kajian terjemahan Arab-Melayu secara lebih luas lagi dan tidak terhad kepada peringkat klausa semata-mata