Urgent need for AI ethics education

The recent incident involving a student in Johor allegedly using artificial intelligence (AI) to create and sell lewd images of classmates is a deeply disturbing wake-up call for Malaysia's education system. While technology offers tremendous opportunities, this case highlights a serious gap, revealing that our youth are not being adequately educated on the ethical and responsible use of AI

Teens text, they'd rather not talk

A recent article by Radio New Zealand highlighted a shift in teenagers' communication patterns, in which they choose not to answer incoming calls despite having their phones in hand

More issues in public healthcare to tackle

On July 11, the government announced the exemption of 82,637 healthcare workers from the new 45-hour work week policy under the Public Service Remuneration System (SSPA). This means critical shift-based roles within the Health Ministry will proceed as usual with the 42-hour work week

The smartphone: friend or foe, or both?

There is an urgent need for public attention to focus on a silent crisis affecting our youth, which is the complex, two-way relationship between loneliness and problematic media use (PMU). PMU refers to excessive engagement with social media, gaming, and smartphones - behaviours that are increasingly shaping how young people relate to the world and to themselves

Ensuring sustainable celebrations

The festivals of Chinese New Year, Thaipusam , and Hari Raya will be observed in the coming months. With future generations in mind, we must optimise the opportunity to enjoy celebrations while also taking care of the planet

Development of battery monitoring system for power generators: insights and experience

The increasing dependence on battery monitoring systems (BMS) by power generators highlights the critical role of the former in ensuring continuous power operation and supply in commercial and residential facilities. This paper details the development of a BMS specifically tailored for monitoring Nickel-Cadmium (Ni-Cad) batteries at Jayalax Resources. The system provides near real-time data on essential metrics such as voltage, current, temperature, internal resistance, and state of charge (SOC) for each individual battery cell, all presented through an intuitive online dashboard. Additionally, the BMS features automated email notifications and alerts for critical conditions, including low voltage, high temperature, and significant SOC drops, ensuring timely intervention for remedial actions. The successful deployment of this system across various commercial and residential buildings in the Klang Valley has minimized the need for frequent manual inspections, reduced human error, and generated significant cost savings for Jayalax Resources. Insights gained from this project underscore the importance of robust monitoring solutions in optimizing battery performance and reliability in generator applications

Preparing Malaysia’s health care industry for IFRS sustainability standards

Preparing for these new standards is not merely a compliance exercise; it is a strategic imperative for future-proofing key economic sectors and enhancing the integrity of the entire Malaysian capital market

Automated mold defects classification in paintings: a comparison of machine learning and rule-based techniques.

Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art paintings. The technique leverages a feature extraction method called Derivative Level Thresholding to pinpoint suspicious regions within an image. Subsequently, these regions are classified as mold defects using either morphological filtering or machine learning models such as Classification and Regression Trees (CART) and Linear Discriminant Analysis (LDA). The efficacy of these methods was evaluated using the Mold Features Dataset (MFD) and a separate set of test images. Results indicate that both methods improve the accuracy and precision of mold defect detection compared to no classifier. However, the CART algorithm exhibits superior performance, increasing precision by 32% to 53% while maintaining high accuracy (96%) even with an imbalanced dataset. This innovative method has the potential to transform the approach to managing mold defects in fine art paintings by offering a more precise and efficient means of identification. By enabling early detection of mold defects, this method can play a crucial role in safeguarding these invaluable artworks for future generations

Embrace a circular economy during celebrations

The festivals of Chinese New Year, Thaipusam and Hari Raya will be observed in the coming months. With the future generation in mind, we must optimise the opportunity to enjoy celebrations while also taking care of the planet. Let's not take for granted the various waste or carbon footprints we produce as well as the resources we consume. One way to do this is by embracing the principles of the circular economy. In layman's terms, a circular economy is a system that minimises waste and maximises resource use – it is all about making the most of what we already have