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Analyzing watermarking color image channels with wavelet and Schur decomposition technique
No full textThis study explores a digital watermarking
technique that integrates frequency domain transformation with
Schur Decomposition to enhance both imperceptibility and
robustness in grayscale and color images. While grayscale
images are represented by a single channel, color images use
three distinct channels (RGB), offering different opportunities
for watermark embedding. The proposed algorithm applies
Discrete Wavelet Transform (DWT) combined with Schur
Decomposition across individual RGB channels. Experimental
evaluations on three color images reveal that embedding the
watermark in the red channel offers superior robustness,
particularly under noise attacks. Compared to existing methods,
the proposed technique achieves an average PSNR of 69.59 dB
and sustains high Normalized Cross-Correlation (NCC) values
under various distortions. These findings highlight the method’s
effectiveness in achieving an optimal balance between
imperceptibility and robustness in digital watermarking
applications
Preliminary study of ambient radioactive particles in Gebeng Industrial Estate vicinity
No full textThe growing demand for rare earth elements (REEs) has led to an increase in the production of materials that generate radioactive waste as a byproduct, raising the risk of radiation exposure to nearby residents through environmental release. In Malaysia, residents near Gebeng Industrial Estate (GIE) may face such concerns due to the presence of REE processing facilities in the area. This study aimed to assess radioactive particle levels near the GIE and in comparative areas, as well as to analyse cellular turnover in residents of the GIE’s vicinity. This cross sectional study involved environmental sampling at two different areas: exposed areas within 5 km of the GIE (16 sites) and comparative areas approximately 20 km away (16 sites). Ambient radioactive particle levels were measured at each site using a Tracerco Personal Electronic Dosimeter over 30 minutes, between 0900 and 1500, and analysed using Dose Vision software. Demographic data was obtained through a self-administered questionnaire. Buccal cells collected from participants in the exposed areas underwent a micronucleus (MN) assay and were stained with hematoxylin and eosin. Micronuclei were identified through microscopic examination. Data were analysed using SPSS. Ambient radioactive particle levels in the exposed areas ranged from 2.7 x 10-4 µSv to 8.9 x 10-4 µSv, while higher levels were recorded in the comparative areas, ranging from 1.1 x 10-3 µSv to 2.3 x 10-3 µSv. All the recorded levels were well below the permissible radiation exposure limit. The ambient temperature in both areas ranged from 22.2 to 22.3°C, with humidity levels between 63.4% and 63.5%. Micronuclei counts in buccal cells ranged from 2 to 45, which may indicate cellular damage in the analysed samples. A non-significant positive correlation was observed between ambient radioactive particle levels in the exposed areas and the total micronuclei frequency (p-value = 0.779; R2 = 0.01; Pearson Correlation test). This preliminary study provides baseline data on ambient radioactive particle levels in the vicinity of the industrial estate. Elevated levels in comparative areas may be influenced by factors such as demographics, construction, and transportation. The presence of micronuclei in biological samples suggests a possible link between radiation exposure and adverse health outcomes
Smart personal assistant
No full textThe Smart Assistant Application aims to enhance
students' daily lives by providing personalised assistance using
advanced AI technologies. The application focuses on offering
efficient task management, reminders, and information
retrieval to improve user productivity. The development follows
the Rapid Application Development (RAD) to ensure a
structured and user-centred approach. User Acceptance Test
(UAT) was conducted to ensure that the requirements meet
users' expectations, and the results are presented
Cybersense: chrome extension for real-time cyberbullying detection
No full textCyberbullying, the harmful use of digital platforms to harass or humiliate others, has increased significantly since the COVID-19 pandemic, affecting 34% of individuals and causing serious mental health issues. This project, aligned with Sustainable Development Goal (SDG) No. 3 on good health and well-being, focuses on addressing the gap in real-time detection tools for cyberbullying on social media platforms. Using advanced machine learning techniques, a Bidirectional Encoder Representations from Transformers (BERT) model was developed and achieved a high accuracy of 88% in classifying various types of harmful language. The system demonstrates the strength of BERT in analyzing unstructured textual data and handling large datasets effectively, making it more accurate and reliable than traditional methods. Compared to existing solutions, this project uniquely integrates real-time processing for detecting and Imran Hazim Abdullah Salim Department of Computer Science International Islamic University Malaysia Kuala Lumpur, Malaysia [email protected] in 30 countries have experienced online bullying, with nearly 71% of children and teenagers reporting that social media platforms like Facebook and Instagram are where it occurs most frequently [2]. The consequences are severe, including anxiety, depression, and, in extreme cases, suicidal tendencies. Another study in 2024 mentions that despite its widespread prevalence, social media platforms struggle to combat this issue effectively, as many lack real-time detection tools powered by artificial intelligence [3]. This gap is especially problematic given that most cyberbullying involves unstructured textual data, making it challenging to analyze and classify harmful language accurately. Addressing this gap is critical to creating safer digital spaces for everyone. This research addresses these gaps by developing an AI-powered managing harmful content on any site, especially social media. Future enhancements include expanding the system to analyze images, memes, and videos, adapting it to other browsers, and developing a user registration feature for personalized experiences. This project not only highlights the potential of AI-driven approaches in addressing cyberbullying but also sets the stage for broader applications, ultimately creating safer online spaces for everyone
Research trends on Maqasid Shariah and Islamic rural banks: a bibliometric investigation
No full textThis study explores the integration of Maqasid Shariah principles into the performance of Islamic Rural Banks (IRBs) and Islamic Microfinance (IsMF) through bibliometric analysis
and systematic literature review. A total of 35 relevant journal articles published between 2006 and 2025 were analyzed using tools such as Publish or Perish (PoP), VOSviewer, and
Mendeley. The findings reveal a growing interest in using Maqasid Shariah not only as a performance measurement tool but also as a guiding philosophy in social impact, governance,
financial inclusion, and integration with Sustainable Development Goals (SDGs). The research trend highlights a shift from conceptual discussions to strategic and operational applications. However, the implementation remains fragmented and underdeveloped. This paper contributes by identifying dominant themes, research gaps, and future research directions to enhance the role of IRBs and IsMFs in achieving ethical, inclusive, and sustainable Islamic finance
Unlocking the potential of in silico approach in designing antibodies against SARS-CoV-2
No full textAntibodies are naturally produced safeguarding proteins that the immune system generates to fight against invasive invaders. For centuries, they have been produced artificially and utilized to eradicate various infectious diseases. Given the ongoing threat posed by COVID-19 pandemics worldwide, antibodies have become one of the most promising treatments to prevent infection and save millions of lives. Currently, in silico techniques provide an innovative approach for developing antibodies, which significantly impacts the formulation of antibodies. These techniques develop antibodies with great specificity and potency against diseases such as SARS-CoV-2 by using computational tools and algorithms. Conventional methods for designing and developing antibodies are frequently costly and time-consuming. However, in silico approach offers a contemporary, effective, and economical paradigm for creating next-generation antibodies, especially in accordance with recent developments in bioinformatics. By utilizing multiple antibody databases and high-throughput approaches, a unique antibody construct can be designed in silico, facilitating accurate, reliable, and secure antibody development for human use. Compared to their traditionally developed equivalents, a large number of in silico-designed antibodies have advanced swiftly to clinical trials and became accessible sooner. This article helps researchers develop SARS-CoV-2 antibodies more quickly and affordably by giving them access to current information on computational approaches for antibody creation
Acute nicotine poisoning in a 2-year-old child – a case report of a near-death event
No full textAcute nicotine poisoning is a devastating condition that occurs when there is an excessive intake
of nicotine, a toxic alkaloid found in tobacco products, mainly e-cigarettes. It impairs respiratory
and neurological functioning due to its massive inflammatory effect. It is mainly related to vaping
activity. Most smokers know about smoking’s adverse effects and implications. However, public
awareness is still poor, and a majority are unable to quit the trending vaping addiction. Nevertheless,
the potential severity of its toxicity to a growing child both in the short and long term is of critical
concern, especially in cases of accidental direct ingestion. We report the case of a 2-year-old child who
presented with acute respiratory failure secondary to liquid nicotine ingestion at home. The child was
first seen by the medical team at primary care and required urgent intubation and paediatric intensive
care unit admission. Her condition was complicated with several episodes of seizure requiring close
monitoring. This case highlights that despite ignorance of adults on the danger of vaping, significant
harm can still occur among children at home when parents engage in vaping. Although adults may
take certain precautions, their harmful habits can indirectly and directly affect children, making the
risk unavoidable. This serves as an urgent call for the government to strictly ban nicotine products and
enact corresponding legislation immediately
