UTAR Institutional Repository (Universiti Tunku Abdul Rahman)
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Synthesis and characterization of Schiff base liquid crystals with benzothiazole ring
Get PDFA series of benzothiazole ring Schiff base ether liquid crystals (E)-1-(4- (alkyloxy)phenyl)-N-(6-methoxybenzo[d]thiazol-2-yl)methanimine, BRLCn (CnH2n+1O-, where n = 12, 14, 16, and 18) were successfully synthesized, characterized and the mesomorphic properties were investigated. Two major steps were involved for synthesis. The first step is the Schiff base condensation between 2-amino-6-methoxy benzothiazole and 4- hydrobenzaldehyde with the aid of glacial acetic acid formed imine linkage (C=N) between two aromatic benzene rings. The second step is the formation of ether linkage, BRLCn through the etherification between BMB1 and bromoalkane. The molecular structures of the synthesized compounds were determined using Fourier Transform (FTIR), 1D NMR (1H and 13C) and 2D NMR (COSY, HMBC, and HMQC). The mesomorphic properties of synthesized compounds were identified using Differential Scanning Calorimetry (DSC) as well as the photophysical properties using UV-Vis spectroscopy. All the compounds BRLCn (where n = 12, 14, 16, and 18) exhibit two liquid crystal phases
Enhancing house price prediction using hybrid feature selection: A combination of information gain and SVM-RFE
Get PDFAccurate house price prediction is crucial for buyers, investors, and policymakers to make informed decisions. However, real estate datasets often contain high-dimensional features, including redundant and irrelevant attributes, which can negatively impact model performance. This study proposes a hybrid feature selection approach that combines Information Gain (IG) and Support Vector Machine Recursive Feature Elimination to enhance predictive accuracy. The proposed hybrid method significantly improves model performance, achieving a 22.2% reduction in Root Mean Squared Error (RMSE) (from 185,518.52 to 154,403.70) and a 22.7% increase in R-squared (from 0.6522 to 0.8008) compared to using IG alone. While IG is effective in ranking features based on their relevance to the target variable, it does not account for feature interactions and redundancy, which can lead to suboptimal feature selection. The addition of SVM-RFE addresses this limitation by iteratively refining the feature set, ensuring only the most informative attributes are retained. Furthermore, the hybrid approach demonstrated robustness even in the presence of artificially introduced noise. Hyperparameter tuning further optimized the best-performing model, yielding marginal improvements in accuracy. These findings highlight the effectiveness of combining filter and wrapper methods for real estate price prediction, demonstrating that hybrid feature selection leads to more reliable and interpretable models
Assessing biodiversity loss due to environmental changes using artificial intelligence (AI) techniques
Get PDFThis study explores the potential of artificial intelligence (AI) techniques to enhance species distribution modelling (SDM) for assessing biodiversity loss due to environmental change, focusing on Strigiformes (owls) in Malaysia, which remain understudied and vulnerable to climate threats. Traditional SDM methods often struggle to capture complex ecological interactions because they rely on linear assumptions. There is a lack of comprehensive studies focused on predicting the future distribution of these species under varying environmental scenarios in Malaysia.To address these issues, this study proposes the use of machine learning and deep learning models, specifically Random Forests (RF) and Multi-Layer Perceptrons (MLP), complemented by Explainable AI (XAI) techniques, to improve predictive accuracy, robustness, and interpretability of SDMs. The models were developed with eight key environmental variables which are annual mean temperature, mean diurnal range, isothermality, annual precipitation, precipitation of wettest month, primary forest, secondary forest and urban area cover for the genus Ketupa (a genus of Strigiformes) in Malaysia. Data splitting techniques, including random and spatial block were evaluated to address spatial autocorrelation and improve model generalization. Spatial block sampling demonstrated superior performance, with smaller performance gaps in Area Under the Receiver Operating Characteristic curve (AUROC) and Area Under the Precision Recall curve (AUCPR) when tested on East Malaysia independent dataset, confirming its robustness for extrapolation. Environmental analysis identified urban area cover as the most influential predictor of habitat suitability, followed by annual precipitation. Response curve analysis revealed critical environmental thresholds that align with Ketupa’s ecological preferences for tropical lowland and wetland habitats. Habitat suitability mapping under future climate and land-use scenarios indicates a potential loss of high-quality habitat and a flattening of suitability gradients.
Area of Study: Artificial Intelligence in Ecological Modelling
Keywords: Random Forest, Multi-Layer Perceptron, Species Distribution Modelling, Ketupa, Explainable AI (XAI
Using drawings in picture books for literacy and creativity development of preschool children in a Shandong public preschool, China
Get PDFIn October 2021, the Ministry of Education in China released a recommended reading list of children’s picture books to promote children’s various abilities and language. This saw an increase in the number of preschool teachers who used picture books in their teaching, particularly in reading and drawing activities. In China, there are no designated textbooks for preschool education, and the choice of teaching materials largely depends on collective discussions and decisions made by preschool teachers. While picture books have emerged as the most commonly used teaching tool in preschools in China, preschool teachers face the arduous task of selecting appropriate picture books that align with their teaching objectives. This highlights the need for more guidance and support for preschool teachers in their decision-making process. Existing research has generally examined picture books for children’s reading, and the relationship between that and children’s literacy. While most of the work on teaching by using picture books to date has been at the primary school level with a specific discipline focus, early studies suggested that there are a number of benefits, such as the development of creativity, imagination, cognition, literacy and other abilities, involved in learning with picture books for children. Furthermore, studies on using picture books to teach at the preschool level have, to date, focused on picture book reading activities and language learning in China. However, there is an absence of research on using picture books to teach preschool children in creativity and literacy through drawing. This research’s objective is to explore, through preschool drawing teachers’ experiences and the researcher’s initial observation in a public preschool, elements in picture books which can be used to develop children’s creativity and literacy. Thus, how preschool teachers are able to use children’s picture books in preschool drawing lessons for encouraging children’s creativity and literacy is the main focus of this study Therefore, this research explores the following questions:
1. What elements in picture books can be used to develop preschool children’s
literacy?
2. What elements in picture books can be used to develop preschool children’s
creativity?
3. What are the characteristics of these elements that have been explored?
4. What challenges do preschool teachers face when using picture books in
drawing lessons?
Adopting an ethnography research methodology, participant observation was used to capture the performance of teachers’ teaching and children’s learning by using picture books in drawing lessons. The researcher entered the observation place as a classroom assistant and participated in the observation from the internal perspective adopted by ethnographers. The researcher assisted the preschool teachers in the selected classroom so that the children could get comfortable with the researcher, and used the form of Classroom Observation Recording and Analysis, daily dairies, notes, photos, the electronic recorder, and collected drawings to record. There were also in-depth interviews and semi-structured interviews with preschool teachers to explore the challenges encountered when using picture books to teach in drawing lessons. The data include the recording of one classroom in Grade 3 with 56 children and three teachers for two drawing lessons a week for up to 21 weeks, and 40 recorded interviews. In addition, conversations with selected children, field notes, children’s drawings, examples of picture books, and photos of classroom drawing activities were also collected as additional data.
The findings show that the complete narrative, sentence patterns, diversity of expression, the story plot, words and phrases in picture books are the essential elements to develop children’ literacy, and the composition design, colour tune and colour combination, setting representational skills, straightforward and logical expression, the details of drawing, the resemblance of the shape in picture books are necessary elements to develop children’s creativity when children are learning drawing by using picture books in drawing lessons. The data also point out that, in addition to the need to develop teaching skills in using picture books to teach drawing, a lack of theoretical knowledge about teaching drawing by using picture books and limited teaching evaluation capabilities are also issues that teachers encountered. The results indicate that the elements which can be used to develop children’s literacy and creativity in picture books as mentioned above can support preschool teachers in a practical way in their teaching activities. In addition to being able to better assist preschool teachers to teach drawing by using picture books, it is likely that curriculum settings for cultivating students majoring in preschool education in colleges and universities need to be considerably developed. Furthermore, if preschool teachers acquire a more sophisticated understanding of using picture books to teach, they are likely to be more insightful and skilled teachers. The results of this study will be shared with the preschool teachers in this preschool. This study benefits preschool teachers to identify and classify the elements in picture books which are recommended by the government in China and which can develop children’s creativity and literacy. Thus it can assist preschool teachers in designing feasible thematic teaching activities based on picture books in drawing lessons. The scant existing literature has revealed that picture books have a positive role in develop children’s literacy and creativity, but no details are given as to how this works. This study represents one of the first attempts to fill this important gap by exploring elements in picture books to be used to develop children’s literacy and creativity in drawing lessons, with an eye toward identifying reasons for problems encountered by preschool teachers. Based on the conclusion, it recommend that it is better for the education management department in the field of preschool education to consider setting up related courses and training sessions to support prospective preschool teachers and preschool teachers in using picture books to teach
Effectiveness of a character strengths intervention on emerging adults’ identity formation, self-doubt, and self-efficacy
Get PDFThis study explored the impact of a single-session character strengths intervention (CSI) on improving identity formation and self-efficacy, as well as reducing self-doubt among Malaysian emerging adults attending tertiary education. A randomized active-controlled trial including pretest, posttest, and a 2-week follow-up was administered. A total of 133 undergraduate students, aged 18 to 25, were randomly allocated to either the CSI or a control group that attended a gatekeeper training for suicide prevention. Data from emerging adults and perceived adults were examined separately using a mixed-design analysis of variance (ANOVA). The results revealed that CSI did not have a unique effect on improving emerging adults’ identity formation, self-efficacy, and self-doubt when compared to the control group. However, the study revealed incidental findings that highlighted the developmental differences between emerging adults and perceived adults. At pretest, emerging adults demonstrated significantly lower identity formation and self-efficacy and significantly higher self-doubt compared to perceived adults. These findings suggest that emerging adults might require more tailored, purpose-driven interventions to address their specific developmental needs. Despite the current results not being significant, this study revealed the developmental challenges faced by emerging adults, and highlighted the need for more support strategies to facilitate their identity development
Facetrack: Personalized information retrieval through face recognition
Get PDFThis project addressed the challenge of managing and recalling personal information in scenarios involving high-volume interactions, infrequent encounters, and age-related memory decline using face recognition. Existing face recognition solutions were primarily limited to government applications, such as national identification systems, suspect tracking, and border control [1], [2], highlighting the need for accessible, personalized tools for everyday users. The system employed OpenCV and YuNet for face detection and movement analysis with a sharpness threshold above 1.8, while DeepFace (FaceNet512) enabled face matching with a similarity threshold of 0.7. WebSocket facilitated low-latency communication between the frontend and backend, supported by user interaction modules with form validation and notifications, and PostgreSQL handled database operations. The system was tested across multiple stages, including initialization, detection, recognition, user interaction, and database management. It achieved an end-to-end latency of 2–5 seconds and a recognition accuracy of 98.54% for known faces under controlled lighting. The novelty of this system lay in its movement-adaptive processing, which cleared the recognition queue during rapid motion. This allowed the system to quickly process new faces entering the camera view, as high movement often indicated a change in person. Additionally, its sharpness-based image capture mechanism ensured that only high-quality images were processed. Combined with WebSocket-driven pause/resume functionality, these features enabled a seamless and uninterrupted user experience. Overall, the system demonstrated the feasibility and scalability of a personalized face recognition solution for everyday environments such as kindergartens, hotels, and events
InterviewAI: Real-time questions generator using LLM
Get PDFInterviewAI is an advanced AI-driven platform designed to transform the recruitment process by integrating emotion detection, automated CV analysis, and dynamic question generation powered by large language models (LLMs). The primary goal of this Final Year Project (FYP2) is to enhance recruitment efficiency, fairness, and personalization by extracting critical information from CVs, analyzing candidates’ real-time emotional states, and generating tailored interview questions based on these insights. The system employs a sophisticated combination of machine learning models, including a Convolutional Neural Network (CNN) for real-time emotion detection from video feeds and the Llama3 model for context-aware question generation, seamlessly integrated into a unified framework. Leveraging Artificial Intelligence for data processing and Human-Computer Interaction principles for user-centric design, the methodology ensures robust handling of multimodal data, enabling the system to adapt dynamically to each candidate’s emotional and professional profile.
Compared to its initial development in FYP1, InterviewAI in FYP2 has been significantly refined to improve accuracy in emotion detection, enhance CV extraction capabilities, and optimize question relevance through iterative model training and user feedback. Final results demonstrate the system’s ability to reduce recruitment bias, streamline the interview process, and provide HR professionals with an intelligent tool that adapts to individual candidate responses, thereby fostering a more inclusive and equitable interview experience. By alleviating the administrative burden on recruiters and promoting objective evaluations, InterviewAI showcases substantial potential to revolutionize modern recruitment practices, making them more efficient, unbiased, and tailored to the unique needs of each candidate
Government expenditure and economic growth in Malaysia: Aggregate and disaggregate perspectives
Get PDFThis study investigates the relationship between government development expenditure and economic growth in Malaysia from 1990 to 2023, using both aggregate and disaggregate perspectives. A step-by-step econometric approach is adopted, beginning with the analysis of total development expenditure, followed by aggregate social sector spending, and finally the disaggregated components: education and training, health, and housing. This layered model progression allows for a more detailed understanding of how different types of government spending influence real GDP. Time series econometric methods, including the Johansen Cointegration Test and the Vector Error Correction Model (VECM), are employed to estimate both shortrun and long-run relationships. In Model 1, aggregate development expenditure is found to have a significant and positive long-run effect on economic growth, though its short-run effect is statistically insignificant. In Model 2, social sector expenditure demonstrates a negative significant long-run relationship with GDP, but short-run effects remain weak. In Model 3, which disaggregates the social sector, it found that health and housing expenditures have positive and significant long-run effects, whereas education and training shows a negative and significant impact in the long run. However, in the short run, education shows a delayed positive impact. The short-run effects of health and housing are negative effects but some lag periods showing statistical significance and others remain insignificant. These variations are possibly due to policy inefficiencies or delayed returns.
Keywords: government expenditure; economic growth; social sector expenditure; Johansen Cointegration test; VECM; Malaysia
Subject Area: HJ7461-7980 Expenditures. Government spendin
Exploring critical reading of poetry in utar undergraduate students: An eye-tracking case study
Get PDFCritical reading is an important skill and is regarded as crucial in this era of globalisation. It is defined as the ability to analyse, interpret, and evaluate the contents of any written text. However, critical reading levels in Malaysian schools have been unsatisfactory. This paper aims to discover the challenges faced when applying critical reading in poetry. By examining a sample of EDEL students in how they read and analyse poems, this research aims to discover the effect of critical reading on students’ poetry comprehension. Using purposive sampling, 7 Year 3 students from the FAS faculty of UiTM were chosen to read two Malaysian English poems while their visual patterns were tracked using eye-tracking equipment before a semi-structured interview that tested their comprehension and their knowledge of critical reading. The eye-tracking results were analysed using a set of five pre-determined reading categories, while the interview transcripts were set to undergo thematic analysis. The research’s results indicated that the visual patterns of the respondents whilst they read the poems were affected by a combination of objective, length and arrangement of poems as well as the complexity of language in the poem. The researcher also discovered that language proficiency and poetic devices were the main challenges the readers faced when critically analysing poems. At the end of the paper, the research notes down several limitations encountered in this experiment’s design as well as a few recommendations when reimplementing this research in future studies
A study of social, marketing and personal aspects towards private retirement scheme (PSR) in Malaysia
Get PDFThe increasing interest in Private Retirement Schemes (PRS) in Malaysia highlights a changing retirement planning environment influenced by demographic changes, economic factors, and shifting societal norms. PRS is a crucial element of Malaysia's multi-tiered pension system, intended to complement the mandatory pension fund, the Employee Provident Fund (EPF). The study aims to develop a comprehensive understanding of the social, marketing,
and personal aspects of PRS in Malaysia. Specific objectives of the study include investigating the determinants within social, marketing, and personal dimensions that influence attitudes and intentions towards PRS participation in Malaysia, analysing the relationship among firm-created social media, user-generated social media communication, and social influence of the social aspects and attitudes
towards PRS, examining the relationship among transaction costs, advertisement, and brand image of the marketing aspects and attitudes towards PRS, and examining the relationship among financial literacy, financial risk tolerance, personal trust, and investment experience of the personal aspects and attitudes towards PRS. The study also explores the mediating effect of attitudes towards PRS
and the moderating effects of government support, age, and income. This research is guided by theoretical frameworks such as Theory of Planned Behaviour, Symbolic Interaction Theory, and Life Cycle Theory. A quantitative study with 501 respondents in Klang Valley was conducted using convenience
sampling. Statistical methods like SPSS and SmartPLS were employed to test hypotheses. The results reveal significant mediating effects of social influence, transaction costs, advertisements, financial literacy, risk tolerance, personal trust, and investment experience on attitudes towards PRS. Additionally, income significantly moderates the relationship between attitudes and PRS participation.
Contrary to the initial assumption that PRS would serve as an alternative to EPF, the findings suggest that while PRS contributes to diversification in retirement
planning, it does not present itself as a standalone substitute for EPF. Rather, it complements the EPF by offering more flexibility to certain segments of the
population. The findings also highlight critical policy implications: to encourage broader participation in PRS, targeted government incentives, enhanced financial
literacy programs, and marketing strategies that reduce perceived transaction costs are essentials.
Keywords: Social aspects, marketing aspects, personal aspects, private retirement scheme, Malaysi