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Bahasa Kiasan dalam Lirik Lagu Kumpulan Munif Hijjaz: Analisis Semantik Inkuisitif
No full textThis study aims to analyze and describe the meaning of figurative language in the lyrics of the
songs of the group Munif Hijjaz based on an inquisitive semantic approach. This study uses a
qualitative method in the form of a descriptive to identify and explain figurative language in
the lyrics of the songs of the group Munif Hijjaz. The study data was obtained through corpus
data analysis on the YouTube channel Munif Hijjaz. The results of the study show that
inquisitive semantics plays an important role in unraveling the meaning of figurative language.
This can be seen when the production of songs that use a lot of figurative language as a context
in the lyrics of the songs to convey something more polite and gentle. In addition, this study
can also uncover the mind and philosophy from the production of song lyrics. The implication
is that listeners and readers can further appreciate the meaning of the song and the creator
can further improve the documentation of song lyrics that have figurative elements. In
conclusion, this study can provide a little understanding of the context of a song that is
conveyed figuratively and become the main line for future studies to ensure the sustainability
and continuity of the use of figurative language in the futur
ANALISIS PENGGUNAAN KATA KERJA DALAM BAHASA BUGIS BONE DI KAMPUNG SUNGAI IMAM TAWAU, SABAH
No full textThis study aims to analyze the use of verbs in the Bugis Bone language spoken by the Bugis community
in Kampung Sungai Imam Tawau, Sabah. The main objectives of this study are to list the verb
vocabulary, identify the types of verbs, and analyze the processes of verb formation in the Bugis Bone
language. This study employs a descriptive qualitative approach, with data collected through interviews
with four native speakers of Bugis Bone. The verb list used is based on the Swadesh list (1955),
comprising 102 vocabulary items. The findings reveal that verbs in the Bugis Bone language are
categorized into two main groups: transitive verbs (active and passive) and intransitive verbs (with
complements and without complements). Additionally, the study identifies three main processes in verb
formation, namely the formation of root verbs, derived verbs, and reduplicated verbs. The formation of
derived verbs is predominantly characterized by the use of prefixes such as /ma-/, /di-/, and /ta-/. The
study also demonstrates that the morphological system of the Bugis Bone language is unique and rich,
yet it has received limited attention in previous linguistic research. This study is expected to contribute
to the documentation and preservation of the Bugis Bone language and serve as a reference for future
researchers, particularly in the field of verb morphology in minority language
Green-synthesised silver and zinc oxide nanoparticles from stingless bee honey : Morphological characterisation, antimicrobial action, and cytotoxic assessment
No full textThis study investigated the green synthesis of silver nanoparticles (Ag-NPs) and zinc oxide nanoparticles (ZnO-NPs) using an aqueous extract of stingless bee honey (SBH) as a reducing and stabilising agent. The rich compositions of SBH containing flavonoids, phenolics, organic acids, sugars, and enzymes makes the SBH extract an ideal biocompatible precursor for the NPs synthesis. Physicochemical characterisation of the synthesised NPs was performed using UV–Vis spectroscopy, FESEM, TEM, XRD, and FTIR spectroscopy. The results revealed that the Ag-NPs and ZnO-NPs exhibited polydispersity, with size ranges between 25-50 nm and 15–30 nm, respectively. A majority of the NPs possessed a spherical morphology. Furthermore, the study evaluated the antimicrobial activity of the SBH-based NPs against gram-positive (Staphylococcus aureus, ATCC 43300) and gram-negative (Escherichia coli, ATCC 25922) bacteria. The findings demonstrated significantly higher antimicrobial efficacy of the Ag-NPs with a zone of inhibition (ZOI) of 16.91 mm against S. aureus, and 17.43 mm against E. coli compared to the ZnO-NPs which having a ZOI of 13.05 mm and 14.01 mm, respectively. Notably, cytotoxicity assays revealed no adverse effects of the synthesised NPs on normal mouse fibroblast (3T3) and human lung fibroblast (MRC5) cells up to 100 μg/ml of concentration. These findings suggest the potential of SBH-based Ag-NPs and ZnO-NPs as safe and effective antibacterial agents for various applications, including pharmaceuticals, cosmetics, ointments, and lotions
Systematic Literature Review of Speaker Diarization Techniques : Toward Bridging Gaps in Low-resourced Languages using Machine Learning
Get PDFSpeaker diarization, the process of segmenting audio into speaker-specific regions, plays a critical role in various speech technologies by determining "who spoke when" in a conversation. This technique is particularly valuable for enhancing automatic speech recognition (ASR) and conversational artificial intelligent systems. However, its application to low-resourced languages remains underexplored, limiting not only the performance of speaker diarization among low-resourced languages, but also stagnating the advancements of ASR to low-resourced languages. This is due to the fact that speaker diarization enables speaker adaptation in ASR, crucial for maximizing the performance of ASR itself. This lack of digital resources of speaker diarization to low-resourced languages, as well as the scarcity of its implementation presents a gap between low-resourced languages and popular languages in terms of the advancements of speech technologies involving the particular languages. This paper focuses on Sarawak Malay, a low-resourced language, and presents conversational data collected through a crowd-sourced approach, which needs speaker turns and transcripts. These missing annotations create challenges for building accurate acoustic models. To address this, we conducted a systematic review of recent speaker diarization research and related machine learning techniques. Using the PRISMA methodology, we reviewed 42 articles published between 2018 and 2023. Our findings identify key machine learning models, such as i-vectors and x-vectors, and open-source tools like Pyannote, which offer promising advancements in diarization performance. Besides that, these tools have shown potential to be implemented in developing speaker diarization models for low-resourced language. By highlighting the gaps in current research for low-resourced languages, we provide a pathway for improving speaker diarization models in these underrepresented languages through machine learning techniques
Sensitivity Analysis of COVID-19 Transmission Dynamics in Pakistan Using Mathematical Modelling
Get PDFCOVID-19 has profoundly impacted all countries' lives, social habits, and economies, resulting in a swift health system breakdown. This immense effect has caused worldwide research to assess its impact on various healthcare, socio-economic and demographic factors. This paper focuses on evaluating the impact of COVID-19 in Pakistan by adopting a mathematical model consisting of five population compartments: Susceptible (S), Vaccinated (V), Exposed (E), Infected (I), and Recovered (R) b y utilising COVID-19 data specific to Pakistan. The primary objective is to analyse the influence of various parameters within the model. Numerical simulations were obtained using the higher-order Runge-Kutta method for dependent variables and the basic reproduction number by varying the parameters. The sensitivity analysis was then performed to assess the effect of the parameters. From the analysis, it is revealed the key parameters, including death rate, vaccination rate, and vaccine wane rate are more sensitive to the proposed SVEIR model. The simulation of basic reproduction was also carried out by observing the simultaneous effect of the five parameters, which includes the probability of susceptibility to becoming infectious per contact, isolated infectious cases, infectious period, the average number of contacts per day per case and death rate. The simulations show that the death rate produces more variations in almost all classes of the population. Vaccination rate reveals a higher number of recovered populations and reduced infected populations, and vaccine wane rate is suitable for intermediate values of the selected interval. The basic reproduction number also remains significant for the combination of probability of susceptibility to becoming infectious per contact and death rate. These insights contribute to the understanding of the sensitivity of disease dynamics under the influence of various interaction parameter
International Resilience Symposium 2025 (IReS'25)
Get PDFThe International Resilience Symposium 2025 (IReS’25) aims to provide a platform for sharing insights, research, and practices on resilience both in Malaysia and globally. The symposium aspires to serve as a hub for discussions on resilience theories, models, and approaches to nation-building.
Bringing together professional counselors, psychologists, ESG experts, students, community leaders, government and NGO representatives, and other stakeholders, IReS’25 offers opportunities to exchange ideas and deepen understanding of resilience and counseling. Key topics include human development, effective counseling practices, and strategies for fostering well-being and happiness in individuals and communities
Comparison between single-chamber and dual-chamber photocatalytic fuel cell on synthetic dye removal efficiency and power generation
No full textPhotocatalytic fuel cell (PFC) is the combination of photocatalysis and fuel cell that can be used to treat wastewater and produce electrical energy simultaneously. Dual-chamber photocatalytic fuel cell (DCPFC) has been reported to have better performance than single-chamber photocatalytic fuel cell (SCPFC) because of the ability to prevent the electron-hole recombination in DCPFC. But there was not many side-by-side studies found in the literature to compare the performance in between SCPFC and DCPFC. This study presents a comprehensive comparison at different parameter between typical SCPFC and DCPFC for the synthetic methyl red dye degradation and power generation under different conditions. The performance of PFC influenced by the electron transfer driven by potential difference between two electrodes. SCPFC system suffers from the fast recombination of electron-hole pairs. In the present study, a DCPFC setup was setup by separating the photoanode and cathode into two different chambers to prevent the rapid electron-hole recombination. Both types of PFC used ZnO/Zn as photoanode to treat the 10 ppm synthetic methyl red dye solution at pH 4. The DCPFC achieved a highest power generation (130.24 mW/cm2) and 100% dye degradation, significantly outperforming than SCPFC which obtained the highest power generation (59.85 mW/cm2) and 12.23% dye degradation. The ZnO/Zn photoanode can be reused twice in DCPFC but only once in SCPFC. This study highlights the advantages of DCPFC in its’ performance and hence the design can be served as a model for the future reference. Indeed, the output of the research aligns with SDGs in clean water, clean energy, and life below water
End-to-End Security Mechanism Using Blockchain for Industrial Internet of Things
Get PDFThe urgent penetration of the Industrial Internet of Things (IIoT) in industrial sectors has
fostered unmatched benefits in terms of efficiency, productivity, and overall performance. Although current
security frameworks already offer a sound level of protection, they do not adequately scale to the growing
diversity and number of devices integrated into the Industrial Internet of Things. They rely on static,
centralized network organization and management, which cannot ensure data integrity across a huge number
of highly distributed devices. The proposed research provides insight into an innovative end-to-end security
solution model, which caters to the needs of IIoT via the introduction of the blockchain. The current security
solutions seem to fail in terms of security, scalability, data efficiency, integrity, and the actual needs of IIoT.
As a result, the top chance of a cyberattack or similar threat remains high. The proposed work demonstrates
that IIoTs may benefit from blockchain frameworks because blockchains reuse existing security mechanisms,
enable transaction validation without central trust, and implement appropriate authorization. Additionally,
the IIoT environment can benefit from implementing security frameworks that reflect their characteristics.
In this paper, an overall solution that employed the decentralized setup of blockchain was proposed for
authentication, authorization, and data integrity for all devices. Our approach is free from the need for any
central authority. That mechanism is based on smart contracts that enforce security policies. Our framework
allows for the switching of any access rule at any time, as well as it can immediately react to some suspicious
behavior. In our paper, we proposed some lightweight cryptographic schemes, and Data management
overhead which could fit any device. Moreover, our algorithm for the blockchain implementation is hybrid
because this approach incorporates all the best features of the private and public implementation due to the
individual blocks containing feasible information rather than the entire history
Deciphering Property Crime Through OLS Regression : A Demographic Study
Get PDFThis study explores the correlation between property crime and demographic factors in Kuala Lumpur and Putrajaya using spatial autocorrelation (SA) and ordinary least squares (OLS) regression from 2015 to 2020. The 2016 SA analysis shows a significant increase in Moran's I index (0.012905), with a positive z-score of 2.020088 and a p value of 0.043374, indicating spatial clustering of crime. The study examines how factors like total population, household areas, residential areas, male populations and female populations influence number of property crime cases, revealing varying relationships year by year. By highlighting fluctuations in R-squared and F-statistic values, this research challenges static crime models, advocating for adaptable, data-driven strategies in crime prevention. These findings emphasize the importance of continuous policy adjustments to address the evolving socioeconomic dynamics of urban areas