UTAR Institutional Repository (Universiti Tunku Abdul Rahman)
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Investigating the accuracy and applicability of authentic materials for Generation Alpha English language learners
Get PDFThe integration of authentic materials in English language classrooms has gained attention as a strategy to improve learner engagement and language acquisition. However, limited research has examined their applicability and accuracy for Generation Alpha learners, particularly in the Malaysian context. Many have ventured the characteristics of the generation but lack evidence that focus on educational application and its learnability towards specific didactic materials. Data were collected from a group of students who fall under the Generation Alpha cohort (e.g., born between 2010 and 2025). We address the issue in three ways. First, we investigate the effectiveness of utilising authentic materials with the focus group. We also look at how the focus group respond to authentic materials before drawing conclusions. Second, we identify the learning strategies most preferred by Generation Alpha learners based on their responses. Finally, we determine how the outcomes of integrating authentic materials in English language learning can assist teachers in material selection. Students’ responses were analysed to study recurring themes related to motivation, learning outcomes, and classroom engagement. We discuss how authentic materials increase learners’ enthusiasm, confidence, and participation. Consequently, catering to learners’ preference for interactive, real-world activities, authentic materials can effectively support English learning. Practically, teachers are urged to select materials that fulfil learners’ interests and needs
Automated parking and payment system using license plate and vehicle attribute recognition with multimodal ai models
Get PDFAs of October 2023, Malaysia recorded over 36.3 million registered vehicles, highlighting the need for more efficient and intelligent parking solutions. Traditional parking systems, which rely on physical tickets, RFID tags, and e-wallets, often lead to congestion, delays, and security vulnerabilities. This project proposes an AI-powered parking payment system that integrates License Plate Recognition (LPR) with Vehicle Attribute Recognition using the Gemini 2.5 Flash multimodal large language model (LLM), complemented by a mobile application designed for drivers, operators, and administrators. The recognition module, developed in Python, was tested using a ground truth dataset of 20 real vehicle images from Roboflow in a simulated environment. Each image was passed directly to the Gemini model to extract license plates and vehicle attributes such as make, model, and color. Recognition was incorporated into two system points: (1) a mobile app feature allowing users to auto-fill vehicle details via photo uploads, and (2) simulated parking facility entry and exit points where vehicle identity was verified against a backend database for automated payment processing. The mobile app was written with Laravel, React Native, and PostgreSQL, and it offers role-based features including vehicle registration, payment tracking, and operational oversight. Testing showed an 85% accuracy for full multi-attribute recognition, with individual accuracies of 95% for license plates, 100% for color and make, and 90% for model detection. Average recognition processing time was 2.495 seconds per image upload. While entry and exit recognition were simulated, the system successfully demonstrated automated vehicle verification and payment workflows. The mobile application facilitated seamless user interactions and system management. Limitations include reliance on free-tier AI services, absence of real-time hardware integration, and limited analytics capabilities. This project illustrates the feasibility of leveraging multimodal LLMs and mobile platforms to create ticketless, contactless, and fraud-resistant parking solutions, contributing to Malaysia’s digital transformation and smart city initiatives.
Keywords: artificial intelligence; license plate recognition; vehicle attribute recognition; smart parking; fraud prevention; multimodal LLMs; smart city
Subject Area: QA75.5–76.95 Electronic computers. Computer scienc
Adaptive cryptography: a transformer neural network-based approach for anomaly detection and secure messaging with signReencryption
Get PDFThe increasing sophistication of cyber threats, particularly in decentralized and resource-constrained environments such as the Internet of Things (IoT), demands adaptive and efficient security solutions. This study introduces SignReencryption, a unified framework that integrates signcryption, proxy re-encryption (PRE), and Transformer-based intrusion detection to deliver both cryptographic assurance and intelligent adaptability. Signcryption ensures confidentiality and authenticity in a single lightweight operation, while PRE enables scalable, fine-grained access control without exposing plaintext. A TabTransformer-based intrusion detection system complements these cryptographic mechanisms, achieving classification accuracies of 94% on CICIDS2017, 99% on CIDDS-001, and 97% on NSL-KDD, with particular strength in detecting minority attack classes traditionally overlooked by baseline models. Optuna-driven hyperparameter optimization revealed dataset-specific configurations, demonstrating the adaptability of the TabTransformer across heterogeneous traffic distributions. Experimental evaluation further shows that SignReencryption reduces ciphertext expansion by up to 50% and lowers per-message execution time by nearly half compared to conventional Sign-Then-Encrypt schemes, confirming its practicality for real-time and bandwidth-limited environments such as intelligent transportation systems. Overall, the framework advances intrusion detection by uniting cryptographic efficiency with adaptive intelligence, offering a scalable, resilient, and operationally viable defense model for modern cybersecurity challenges.
Keywords: Signcryption; Cryptography; Transformer Neural Network; Intrusion Detection System; Internet of Things
Subject Area: QA75.5-76.9
Inventory management dashboard for tracking of sports equipment and facilities in a secondary school's sport centre
No full textManual inventory management in secondary school sports centres often results in misplaced equipment, overbooked facilities, and inefficient maintenance tracking. This project aims to address these issues by developing an Inventory Management Dashboard that digitalizes the management of sports equipment and facilities. The system integrates QR code-based tracking, real-time updates, and a centralized booking platform to enhance operational accuracy and accountability. Using a prototyping methodology, the system was iteratively designed, developed, and refined through continuous user feedback from stakeholders, including administrators, quartermasters, teachers, and students. The solution was implemented as a web-based application using React.js for the frontend, Laravel for the backend, and a MySQL database for persistent storage. Key features include role-based access control, QR code generation and scanning for equipment check-in and check-out, real-time inventory and facility booking, maintenance scheduling, and an analytics dashboard for performance insights and decision-making. The system underwent comprehensive unit testing, integration testing, and user acceptance testing, confirming its functionality, usability, and effectiveness in meeting user requirements. Results demonstrate significant improvements in inventory accuracy, booking transparency, and maintenance monitoring. The developed dashboard offers a scalable and user-friendly solution that reduces manual workload, minimizes errors, and promotes data-driven management of sports resources. Future improvements may include the integration of predictive maintenance, automated reporting, and multi-school scalability to broaden its impact across educational institutions.
Keywords: inventory management; sports facilities; QR code tracking; web application; React.js; Laravel; MySQL; prototyping methodology
Subject Area: QA76.76 Computer softwar
Self-hosted multi-agent RAG system for contextual document processing
No full textThe increasing use of Artificial Intelligence (AI) in document processing faces persistent challenges such as hallucination, privacy risks, and limited adaptability. This study presents a self-hosted multi-agent Retrieval-Augmented Generation (RAG) system designed to address these limitations by enhancing accuracy and preserving data privacy through a fully local and modular architecture. Built using Marker, Ollama, LangGraph, and Weaviate, the system enables flexible deployment and coordination between agents. Evaluation using the SQuAD dataset measured retrieval and generation performance through metrics such as Recall@3, Mean Reciprocal Rank (MRR), Context Recall, Faithfulness, and Answer Correctness. Two evaluation methods were employed: a calculation-based approach on 100 samples for quantitative assessment, and an LLM-as-Judge approach using GPT-4o on 20 samples for qualitative, human-like evaluation. Results show strong retrieval performance with a Recall@3 of 90%, MRR of 75%, and Context Recall of 100%, demonstrating accurate and consistent grounding. The generation results indicate improved faithfulness and contextual relevance, though challenges remain in scalability and factual precision. Overall, the findings show that the proposed multi-agent RAG system effectively mitigates hallucination and privacy concerns while maintaining adaptability, making it a promising approach for secure and accurate AI-driven document processing.
Keywords: Artificial Intelligence (AI), Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Self-Hosted AI
Subject Area: Q300-390 Cybernetic
论唐代制度和文化——以唐传奇中的士子和娼妓为例 : Tang dynasty intitutions and culture - A study of scholars and courtesans in Tang Chuanqi
No full text唐代是中国古代社会与文化发展的重要时期，科举制度的完善使士子群体在社 会生活中的地位日益显著。与此同时，都市经济的繁荣与文学文化的兴盛，也使妓女 群体频繁进入文学与文化场域。士子与妓女虽身份悬殊，却在唐传奇中形成丰富的交 集，二者的互动不仅构成文学作品如唐传奇等重要的叙事主题，也凸显出出唐代社会 的制度结构与文化。 本研究以唐传奇中的士子与妓女关系为切入点，探讨唐代制度与文化之间的相 互作用。首先从史料与制度史出发，分析唐代士子在科举取士、经济条件与地域参差 等方面的现实处境及其心态困境。其次梳理妓女群体的来源、文化功能与所处地位， 揭示其在文学创作中的特殊意义。本研究结合《李娃传》、《霍小玉传》等代表性文 本，重点剖析士子与妓女关系的叙事模式与文化意涵。 本研究发现，唐传奇中的士子形象常与“科举失意、功名追求、异乡漂泊”相 关联，而妓女则兼具才情与风尘的双重特质。两者之间的交往，反映了士人在仕途与 情感之间的挣扎，这些皆展现在士子们的作品上。 本文综合运用史料文献考据与文学作品文本分析法，通过分析士子与妓女关系， 旨在探讨士子与妓女、是如何与唐代的制度、文化，相互影响，又是如何影响整个唐 代社会。 【关键词】唐传奇、士子、妓女、唐代科举制度、唐代社会文
A mobile application to assist Alzheimer’s patients and caregivers
No full textAlzheimer's disease (AD) is a progressive neurological disorder that severely impacts memory, cognitive functions, and daily living abilities, posing significant challenges not only for patients but also for caregivers and society. With no known cure, there is a critical need for supportive solutions to alleviate these difficulties. This project aims to develop a mobile application that assists Alzheimer's patients and their caregivers. Therefore, MemoraCare was developed, and it is a Flutter-based mobile application that helps caregivers and patients stay connected, safe, and recognized in real time by integrating functionality such as real-time face detection and recognition, safe-distance navigation, communication channels, AI assistance, diaries, and NFC info cards, with Firebase as a backend service. There are three models, which are the custom CNN model, Siamese Network, and MobileFaceNet.. The fine-tuned MobileFaceNet achieved 80.5% testing accuracy, which clearly outperformed the other models and emerged as the most suitable for this project. Compared to the custom CNN, which suffered from overfitting, and the Siamese network yielded modest results. Firstly, the app delivers an end-to-end, on-device face pipeline designed specifically for caregiver–patient workflows: a lightweight embedding-based recognizer by using the MobileFaceNet to enable open-set identification, indicating that new people can be added without retraining, while the ML Kit is used for face detection. Secondly, by coupling recognition with a person-linked memory repository, MemoraCare enables the recall of the patient's memory. Thirdly, the app provides a safety stack combining geolocation by allowing the caregiver to set a customized safe zone, Haversine distance for geofencing to calculate the shortest distance between the patients and caregiver, and walking-route retrieval to guide the patient return to the designated locations for real-world caregiving scenarios by integrating the Google Cloud APIs: Maps API, Directions API, and Places API to display the locations on the Google Maps, suggest a route between two points, and search for places. Fourthly, the app increases the relationship between the patient and caregivers by integrating a communication chat room that employs deterministic pairwise chat IDs and voice-note peak compaction for achieving 1 to 1 chat room for the users and supports voice messaging. Also, a role-conditioned OpenAI assistant that is driven by carefully designed prompts to respond
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Faculty of Information and Communication Technology (Kampar Campus), UTAR
with an expected reply. Fifthly, the app writes a minimal public-profile URL to an NFC NTAG213 tag to enable tap-to-view access so bystanders can quickly contact caregivers if the patient becomes lost. Sixthly, the app encourages the patient to write and record a diary about their valuable and interesting memories by storing it in the cloud instead of their brain, so that they can review and recall the memories if needed. Hence, the application attempts to enhance daily living, promote memory recall, improve communication, ensure patient safety, and reduce caregiver burden
Critical success factors for building information modelling (BIM) implementation: developers' perspective
No full textBuilding Information Modelling (BIM) is known as the new disruptive technology that is currently transforming Malaysia’s traditional practices of the construction industry towards digitalization adoption. After more than a decade of its introduction, the adoption rate remains
low in the industry. There is very little information regarding the critical factors influencing the decision of developers whether to implement BIM. Thus, this research aims to identify critical success factors (CSFs) of BIM among the developers and assessing the most and least
significant factors.
The key selection criteria were identified through a detailed literature review. Three main categories encompassing Technology Readiness, Organization Readiness and Environment Readiness and four sub-criteria for each category were confirmed for this study. Subsequently, a survey questionnaire was distributed to developers from REHDA and gather insights into their decision-making processes regarding the CSFs of BIM. The Analytic
Hierarchy Process (AHP) method were utilized to prioritize the CSFs based on the collected data. The findings revealed that Environment Readiness is the main CFS to developer in
deciding the adoption of BIM. The sub-criteria of Ownership & Copyright, Coordination & Cooperation, and Competitor Pressure was the CSF for the respective category. The highest weightage was calculated in Competitor Pressure factor, which indicated the developer needs to remain on par with the industry benchmark and stay competitive in ensuring the profitability of the organization. It also revealed varying priorities among different stakeholders. This
pioneering research has provided valuable insights into the CSFs influencing the implementation of BIM in the industry, specifically from the developers’ perspective.
Keywords: Building Information Modelling, Critical Success Factors, Construction, Developer, Technology Readiness, Environment Readiness, Organizational Readiness
HD9715-9717.5 Construction industr
Statutory adjudication as a means for changing payment culture in the Malaysian construction industry
No full textDisputes and payment defaults are two prominent issues face by stakeholders in the Malaysian construction industry, yet resolving them through legal means is the last resort as arbitration and litigation are costly and time-consuming.
Despite much research efforts and enactment of the Construction Industry Payment and Adjudication Act 2012 (CIPAA), disputes are still on the rising due to lack of in-depth understanding on root causes of disputes and statutory
adjudication. This study aims to develop a practical approach model for effective application of CIPAA via questionnaire survey among registered adjudicators (N=280) from Asian International Arbitration Centre, and
analysed by Statistical Packages for Social Science and Relative Importance Index, and verified via online interviews with six industry experts.
The objectives are (a) to identify the common types of payment and contractual disputes; (b) to determine the right types of disputes suitable to resolve by CIPAA; (c) to examine the effectiveness of CIPAA 2012; and (d) to ascertain whether CIPAA adjudication is able to change existing mind-sets on payment default culture.
The results identified twelve common payment disputes and eighteen contractual disputes. Only eight payment disputes: interim payment; payment certificate; withholding monies; final account; retention sum; variation order; certified value; professional fees; and one contractual dispute: imposition of liquidated damages are suitable to resolve by CIPAA. It verified that there is no statistically significant difference in the findings among diverse professions of the adjudicators. CIPAA concluded as an effective, cheap and speedy payment dispute resolution. The Act can influence the existing mind-sets to an ethical
payment culture in the industry.
This study contributes to existing knowledge in construction disputes, effective CIPAA application, and references for reforms. It serves as a practical guide for construction stakeholders in selecting CIPAA to resolve suitable disputes and achieve finality while mitigating legal challenges to adjudication decisions.
Keywords: CIPAA; alternative dispute resolution; payment culture; statutory adjudication; construction
Subject Area: K7690 Arbitration and awar
The pirate fairy as a powerful means for engaging audiences of all ages in societal and cultural discourses
Get PDFChildren's media is primarily designed to entertain, educate younger audiences, typically expressed through TV shows, short animations, and storybooks. These purposes can be illustrated by the example of The Pirate Fairy (2014), which feature bright visuals and straightforward narrative elements. However, to argue the assertion that this type of media is solely for entertainment and limited to children, this study, particularly through the film mentioned and Peter Pan (1953) (supporting source), aims to investigate how children’s media serves as a powerful tool in engaging audiences of various age groups within contemporary societal and cultural discussions, proving to be more impactful than other media channels like news and social media. By applying Social Identity Theory (SIT) and Media Narratives (MNs), this research finds that both films incorporate the social and cultural themes of gender and class, leadership and profession roles, group membership that could significantly contribute to individuals' cognitive, emotional, and social growth. Additionally, Comparative Historical Analysis (CHA) is utilized to highlight these themes, revealing whether stereotypes are reinforced or diminished within the narratives, thus allowing viewers of all ages to process and reinterpret their perspectives based on their knowledge and experiences. This analysis confirms that children’s narratives (as of the two movies) possesses the characteristics of universality, multilayered storytelling, and fantastical settings that are seldom found in other media forms, which can spark meaningful commitment from children, teenagers, and adults regarding social and cultural progress