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Bamboo Reimagined : Nature Meets Design
No full textThis book is a Design Compendium showcasing bamboo-based product designs developed through design research. It presents a structured and comprehensive documentation of three categories—furniture, décor and fashion accessories that reveal bamboo’s potential for innovation, sustainability, and cultural expression, integrating traditional values with contemporary design concepts and modern lifestyle applications
The Influence of Internal Organizational Factors on Employee Job Commitment among Academic Staff in Private Universities in Sarawak, Malaysia
No full textThis study investigates the influence of internal organisational factors, technological adoption, job autonomy, supervisor support, and coworker support on employee job commitment among academic staff at private universities in Sarawak, Malaysia. In light of rising challenges in talent retention and job dissatisfaction within the private higher education sector, the study emphasises the need for strategic internal reforms to strengthen organisational commitment. A quantitative research design was employed, and data were collected via a structured survey involving 200 academic staff from three major private universities in Sarawak. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) via SmartPLS. The findings indicate that technological adoption and job autonomy significantly enhance job commitment. However, coworker support and supervisor support were not significantly related to job commitment. Employment status was found to moderate the relationships between job autonomy and technological adoption with job commitment, with permanent employees benefiting more from these factors. Based on these insights, the study recommends that university management prioritise structured technological integration, promote job autonomy, and adopt HR strategies tailored to employment status. These policy recommendations are vital for improving staff retention, enhancing job commitment and sustaining the competitiveness of private universities in Sarawak. The study contributes to literature by addressing contextual gaps and informing HR policy and practice
Chemical Soil Stabilization for Improved Load-Bearing of Road Embankment : A Concise Review
No full textSoil stabilization transforms unsuitable materials into usable ones with desirable engineering properties. It can be categorized into mechanical and chemical stabilization. Mechanical stabilization involves processes like compaction and drainage to change soil characteristics, while chemical
stabilization uses chemicals to alter soil properties via chemical reactions. Soil properties are modified through chemical reactions like hydration and pozzolanic reactions. This results in higher strength, lower permeability, and
reduced plasticity and shrinkage. Chemical stabilization dates back over 5000 years. Ancient civilizations used mixtures like gypsum and lime to construct structures, such as the Egyptian pyramids and the Great Wall of China. In the
US, modern research began in the 1930s. In Malaysia, chemical stabilization for road construction started in the 1980s, known as Cold In-Place Recycling (CIPR). JKR Malaysia has conducted numerous pilot projects to assess the feasibility and performance of chemical soil stabilization. Chemical stabilization can be in-situ or ex-situ. In-situ stabilization improves soil on-site and is divided into surface treatment, shallow mixing, and deep mixing. Exsitu
mixing occurs during transportation or in a batch plant. Cement, lime, fly ash, and bituminous chemicals are widely used. Cement improves soil strength but can be brittle. Lime enhances clayey soils’ strength and reduces plasticity. Fly ash, a by-product of coal power plants, modifies fine-grained soils. Bituminous chemicals add flexibility and prevent cracking. Innovative chemical stabilizers such as ionic stabilizers, enzyme-based stabilizers, microbial induced calcite precipitation (MICP), biopolymers, synthetic
polymers, polymer-modified cementitious stabilizers, and nanotechnology are also explored. These modern solutions offer improved technical effectiveness and commercial efficiency, with potential environmental benefits. In conclusion, chemical soil stabilization significantly enhances the load-bearing capacity of road embankments. This paper provides a critical review of various chemical stabilizing agents and methodologies, highlighting
their mechanisms, advantages, and limitations, and underscores the importance of continuous research and development in this field
Checklist of Wild Betta Fish from Sarawak and Captive Breeding Protocols
No full textThe genus Betta, (commonly known as fighting fish) includes a diverse group of freshwater fishes with significant ecological and economic roles. However, scientific knowledge of wild Betta species in Sarawak remains limited, with most studies focusing on hybrid species for the ornamental trade. This study aimed to update the checklist of wild Betta in Sarawak and establish captive breeding protocols for selected native species. A total of 72 specimens were collected from seven locations across Sarawak. There were 7 species of wild Betta had been recorded namely, B. ibanorum, B. brownorum, B. lehi, B. midas, B. taeniata, B. akarensis
and B. macrostoma. Morphometric comparisons showed that males were generally larger and heavier than females, except in B. ibanorum, where no significant sexual dimorphism
was observed. Successful captive breeding was achieved for B. ibanorum, B. macrostoma, B. taeniata and B. brownorum, with documentation of mating behaviour, larval stages and
growth performance. These findings provide a foundational reference for future conservation programs and sustainable aquaculture efforts involving Sarawak’s indigenous Betta species
Antifungal activity of ten Mapania species (Cyperaceae Juss.) from Sarawak, Malaysia against crop pathogenic fungi
No full textAims: Mapania is found in a wide range of geographical areas, and the chemical compounds of different species within the genus vary. It has attracted attention as a possible source of natural antifungal substances due to its diverse array of secondary metabolites. These variances in secondary metabolites may result in disparities in antifungal efficacy, making Mapania a fascinating subject for further exploration. In this study, the antifungal activities of methanolic root and leaf extracts from 10 Mapania species were evaluated against Colletotrichum musae, Fusarium solani and Pyricularia oryzae (isolate POSA 1 and POSA 2).
Methodology and results: Secondary metabolites extraction using methanol was performed on the root and leaf
samples of 10 Mapania species. These methanolic crude extracts were used in an antifungal assay against C. musae, F. solani and two isolates of P. oryzae using an in vitro agar dilution assay to measure fungal growth inhibition. Five methanolic root crude extracts and one methanolic leaf crude extract showed a significant inhibition effect against C. musae, with inhibition zone ranging from 0.477 ± 0.222 cm - 0.644 ± 0.038 cm. One methanolic root crude extract and three methanolic leaf crude extracts showed a significant inhibition effect against P. oryzae isolate POSA 1 (0.402 ± 0.014 cm - 0.442 ± 0.028 cm) while two leaf methanolic crude extracts significantly inhibited isolate POSA 2 (0.504 ± 0.038 cm - 0.509 ± 0.043 cm). The inhibition effects of crude extracts were fungal species-dependent and isolate dependent.
Conclusion, significance and impact of study: The findings of this study provide valuable insights into the antifungal properties of Mapania species, enhancing our understanding of their bioactive potential and supporting conservation efforts. This knowledge contributes to promoting the sustainable utilization of Mapania species in natural product development and agricultural disease management
Assessing the Interplay between Economic Vulnerability and Health Resilience: A Multidimensional Analysis of Malaysia
No full textFollowing periods of economic growth, nations often encounter various challenges, as evidenced by the diverse crises affecting Malaysia’s economy. In this context, addressing economic vulnerability and health resilience is crucial for ensuring that government policies are effectively aligned to enhance societal well-being. However, these concepts are inherently abstract and difficult to measure objectively. This study aims to address this gap by first constructing indexes for economic vulnerability and health resilience, grounded in the Economic Vulnerability Theory and the Social Determinants of Health framework. Subsequently, the study examines the interaction between these two dimensions. In addition to integrating data representing external economic conditions, the study successfully recruited 389 respondents from diverse socioeconomic backgrounds. Across three versions of the economic vulnerability and health resilience indexes, findings indicate that Malaysian society exhibits moderate levels of both economic vulnerability and health resilience. Moreover, results suggest that higher-income groups demonstrate greater economic vulnerability and health resilience. Additionally, indicators of economic vulnerability appear to influence the overall health resilience of Malaysian society. Ultimately, the computed indexes and their subsequent analysis provide a valuable benchmark for policymakers. By leveraging these findings, policymakers can refine existing strategies to better address societal needs, promote long-term sustainability, and enhance overall well-being
A DNA Based Lightweight Cryptography Framework Integrating ECC and RNN Based Deep Learning for IoT Security
No full textThe exponential growth of Internet-of-Things (IoT) networks and connected devices has highlighted critical challenges in ensuring high security, low latency, and low energy consumption for sensitive data exchange in resource-constrained environments. Traditional cryptographic systems often struggle to meet these demands, necessitating innovative solutions tailored to IoT. This study proposes a novel DNA-Based Lightweight Cryptographic System (DNA-LWCS) integrating the inherent randomness of DNA sequences with Elliptic Curve Cryptography (ECC) to enhance security and efficiency. Leveraging the robustness of DNA sequences and ECC’s computational efficiency, DNA-LWCS provides robust protection against attacks like Distributed Denial-of-Service (DDoS) and Man-in-the-Middle (MITM), addressing IoT vulnerabilities. Deep learning models, including Recurrent Neural Networks (RNN) and Gated Recurrent Units (GRU), achieve remarkable precision of 99.62% for RNN and 98.61% for GRU in key strength estimation, optimizing encryption processes. Experimental results demonstrate DNA-LWCS outperforms 3DES, AES, ECC, and benchmarks in critical security and efficiency metrics. DNA-LWCS achieves a correlation coefficient of 0.025, ensuring high confidentiality and data integrity, fast encryption times (e.g., 0.800 seconds for Photographer), high throughput (12.00 Bps at 50 data points), and low energy consumption (10.00–15.00 J), ideal for resource-constrained IoT devices like smart meters and smart homes. DNA-LWCS demonstrates superior entropy values (7.800 for Lena, 6.500 for Photographer) and avalanche effect (52.99% for Lena, 50.99% for Photographer), meeting stringent randomness and input sensitivity criteria for applications like autonomous vehicles and patient monitoring. This research advances IoT security by combining DNA-based encryption with deep learning, delivering a scalable, efficient, and resilient cryptographic framework that bolsters data protection and fulfills the essential requirement for lightweight, energy-efficient encryption in contemporary interconnected systems
Practices of EFL Teachers on Metacognition: A Case Study of a Saudi University
No full textstudy examined teachers' metacognitive processes in non-native English contexts. Data collected through classroom observations, semi-structured interviews, and stimulated recall interviews from the teachers at a Saudi university. Classroom observations conducted to capture authentic teaching practices, while semi-structured interviews provided insights into teachers' beliefs and experiences. Stimulated recall interviews allowed for a deeper exploration of specific teaching moments. Qualitative data analysis techniques, including open, axial, and selective coding, employed to identify patterns in teacher behavior and thought processes. Atlas.ti9 used to facilitate data management and analysis. Findings indicate that teachers' metacognitive awareness significantly influences their teaching practices and student outcomes. Participants demonstrated a range of metacognitive strategies, such as planning, monitoring, evaluation, and regulation. These strategies were evident in various classroom activities, including lesson planning, instructional delivery, and student feedback. The study highlights the importance of fostering metacognitive development among teachers to enhance overall teaching effectiveness.
Keywords: Practices, metacognition, metacognitive strategies, observation, semi-structured interview
Rethinking FDI and Growth in China: The Role of Technology Spillovers
No full textChina has consistently attracted the highest foreign direct investment (FDI) inflows among developing nations for three decades. However, transitioning to a high-income economy requires a shift from relying on FDI for poverty alleviation to leveraging it for wealth creation. This study investigates the impacts of technology spillover on China's economic growth, focusing on its direct, indirect, and spatial effects. Based on Neoclassical and Exogenous growth theories, technology spillover and FDI are the key variables, with trade openness, government expenditure, and total population as control variables, and economic growth as the dependent variable. This study employs a panel dataset from 30 Chinese provinces spanning 2000-2022, sourced from the China Statistical Yearbook. Methodologically, the Cross-Section Dependence test, Augmented Mean Group (AMG) model, and Spatial model are used. Findings confirm cross-sectional dependence, validating the AMG model. Direct effects reveal that research and development (R&D) and real government expenditure significantly drive economic growth, while real FDI and trade openness are both insignificant and negatively correlated. Indirect effects highlight R&D's significant role in the relationship between FDI and economic growth. Spatial analysis reveals positive and significant coefficients for R&D, FDI, and government expenditure, emphasizing that neighbouring provinces exert a considerable influence on their growth. The implications of these findings are: first, fostering R&D investment is critical to magnifying the benefits of FDI and enhancing economic growth. Second, policies should focus on strengthening inter-provincial cooperation to maximize spatial spillover effects. Finally, aligning trade openness with sustainable growth strategies is important
A Dynamic Malaysian Sign Language Dataset for Sign Language Recognition and Translation
No full textSign languages all around the world are unique and diverse. Each sign language shows the differences in cultural nuances of its origin locale giving it is distinctive nature. Thus, despite the positive outcomes of sign language recognition and translation research that has been widely conducted worldwide, there are still notable limitations to each system which are mainly caused by data limitations. The sign language recognition and translation research in Malaysia especially has been set back by the limited size and nature of datasets available that are concurrent with current technological developments. The current datasets available for Malaysian Sign Language (BIM – Bahasa Isyarat Malaysia) are small and limited to fingerspelling of alphanumeric characters and several dynamic words and short phrases. However, given the continuous nature of the sign language communication, these data are not enough to properly train machine learning models to recognize and translate continuous real-world signs. Therefore, in order to address this issue, we introduce a dynamic BIM dataset which comprises of video, gloss, and translation data consisting of alphanumeric characters, dynamic words and short phrases, and continuous sentences. The dataset is split into two versions. The first version, BIM-SSD-V1 dataset comprises of 4,858 parallel video (RGB frames), gloss, and translation data while the second version, BIM-SSD-V2 dataset comprises of 3,143 parallel video (RGB frames), keypoints and gloss data for recognition purposes, and 4,900 parallel gloss and translation data for translation purposes. The raw videos are also available in the dataset. The dataset was developed and compiled with the help of the Deaf and Hard-of-Hearing community. This process also included the development of a Sign Language Module (translations for the video and gloss data) to assist in the development of the dataset. The image and video data were collected using smartphones and the respective gloss annotations for the data were prepared with the help of a BIM expert. The data collection process and participant selection were guided by criteria that ensured data diversity and used a setup similar to real-world scenarios. These criteria and sample differences were set to help models trained on the dataset adapt to different individuals, signing styles, backgrounds, attire, and other contextual variations. The total number of participants involved in the data collection process was four. There are also four samples for every character, word, phrase or sentence in the Sign Language Module. The dataset can mainly be reused by researchers who would like to conduct sign language recognition and translation research using the Sign-to-Gloss-to-Text framework. However, the dataset is not limited to only one framework and can be used for other sign language recognition and translation research frameworks accordingly