Improving combustion efficiency and reducing flue gas emissions in coal-fired power plants (CFPPs) have become critical priorities amid growing global pressure to mitigate the environmental impact of the energy sector. Machine learning (ML) has demonstrated strong potential in predicting flue gas parameters, yet systematic reviews mapping algorithmic trends, implementation challenges, and integration opportunities with CFPP operations remain limited. This study presents a systematic literature review (SLR) of 31 selected articles published between 2019 and 2024 across Scopus, IEEE Xplore, and ScienceDirect databases, utilizing the PICOC framework for selection. The analysis shows that LSTM is the most frequently applied model for temporal prediction of flue gas temperature, while Random Forest is widely adopted for estimating NOx emissions. However, most studies are constrained to single-plant datasets, and real-time control system integration is still uncommon. These findings highlight the need for hybrid approaches that emphasize not only predictive accuracy, but also model interpretability via Explainable AI methods such as SHAP, and adaptability across diverse operational conditions. This study advocates future development directions by embedding predictive models within digital twin frameworks to enhance decision-making and optimize system performance sustainably. As such, the review contributes to bridging academic research with practical industrial demands in coal-based energy generation.
This study examines the effectiveness of the Indonesian National Police’s (Polri) digital services in Depok City, focusing on information dissemination, implementation challenges, and public perceptions. Using a qualitative case study approach with interviews, observations, and documentation, the findings reveal that Polri's digital services have improved communication, accelerated information delivery, and simplified administrative access. However, challenges remain, including limited infrastructure, low digital literacy among some groups, insufficient personnel skills, and poor system integration. While public perception is generally positive especially among younger users elderly and marginalized communities still face access barriers. The study concludes that although Polri’s digital transformation shows promise, further improvements in infrastructure, human resources, and inclusive outreach are needed to ensure equitable and effective public service.
The management of end-of-life vehicles (ELVs) in the automobile industry is a pressing issue due to their substantial impact on environmental pollution and resource scarcity. While the European Union successfully implemented the ELV Guidelines in 2000, Malaysia has not yet enacted such laws, indicating a slower pace of advancement compared to other industrialized nations. The study seeks to conduct a comprehensive analysis of ELV management in Malaysia, to identify the difficulties, opportunities, and gaps within this industry. The study employed a mixed-method approach, integrating a systematic literature survey with a cross-sectional survey of 630 Malaysian individuals. The findings indicate that the ELV management system is now in its nascent phase. The report offers specific suggestions for enhancing Malaysia’s ELV management infrastructure, including the enforcement of rules, the reinforcement of public awareness programs, and the establishment of recycling facilities. The research model employs structural equation modeling and is examined using the WarPLS 7.0 software package. It encompasses various variables, including recycling concepts, consumer knowledge, solid waste data, management strategies, budget concerns, attitudes, motivations, and preferences for behavioral change. This model accurately forecasts the dissemination of ELV policy in Malaysia by discerning meaningful correlations among these variables. As an illustration, the idea of recycling has a beneficial impact on attitude (β = 0.13, p < 0.001) and motivation (β = 0.17, p < 0.001). Consumer knowledge has a strong impact on attitude (β = 0.57, p < 0.001) and motivation (β = 0.50, p < 0.001). The results indicate a complete mediation effect: recycling concepts and consumer knowledge influence management strategies and budget concerns only through attitudes and motivations. In other words, without positive attitudes and strong motivation, knowledge and recycling concepts alone do not directly shape acceptance of ELV policies. The model compliance index validates the strength and reliability of the model, demonstrating its ability to appropriately portray public approval of the ELV policy. The findings of this study will be advantageous for policymakers, automobile manufacturers, and other parties involved in the ELV business in Malaysia and other emerging nations. These results will establish a basis for enhancing ELV management systems.
In 2025, the Republic of Indonesia marks its 80th anniversary, offering a critical moment to evaluate the nation’s collective performance across key sectors. This study provides a comprehensive and reflective assessment of Indonesia’s political, economic, social, educational, cultural, environmental, and global development trajectories. Using a qualitative-descriptive approach and a systematic literature review, the analysis draws on official government documents, international institutional reports, scholarly publications, and credible media investigations. The findings show that although Indonesia has made notable progress—emerging as the world’s third-largest democracy and Southeast Asia’s largest economy—substantial structural challenges remain. Democratic consolidation is hindered by ethical violations in judicial institutions, increasing oligarchic influence, and stagnation in anti-corruption efforts. Economic growth has not fully translated into equitable distribution, evidenced by persistent inequality, governance failures in social assistance, and continued labor-market mismatches. The education and health sectors demonstrate improved access yet uneven quality, while environmental degradation and a slow clean-energy transition pose urgent threats to sustainability. Globally, Indonesia plays an active diplomatic role, but institutional constraints limit its international effectiveness and innovation capacity. The study aims at arguing that Indonesia’s 80-year milestone should serve as a catalyst for reaffirming constitutional ideals and strengthening governance, equity, and sustainability as essential foundations for realizing the vision of 2045 Golden Indonesia.
Modern biotechnological approaches in technology for cassava propagation depend on somatic embryogenic calli (SEC) induction and somatic embryo (SE) regeneration techniques. Consequently, it is essential to develop SEC induction and SE regeneration for cassava genotypes. By assessing the effects of different auxins and explant types, this study aims to develop efficient techniques for inducing cassava SEC and SE. Callus induction medium (CIM) supplemented with 10 mg l-1 2,4-dichlorophenoxyacetic acid (2,4-D) or 12 mg l-1 Picloram was used to cultivate five different types of cassava explants. Subsequently, the induced calli were maintained on CIM until the formation of SEC, which were sub-cultured on the same CIM to promote proliferation and induce SE formation. These SEs subsequently germinated and developed into shoots, which were rooted to produced complete plantlets . These findings indicate that culturing-induced axillary bud explants on CIM supplemented with 12 mg l-1 Picloram is an effective method for inducing SEC in cassava. Histological analyses and cryogenic electron microscopy observations confirmed the development of SECs and SEs on CIM. Our finding, in which up to 202.3 SEs were regenerated from 10 induced axillary bud explants on CIM supplemented with 12 mg l-1 Picloram in the Menti genotype, highlights the effects of auxin and explant types on SEC and SE induction. Although further research is required, the methods developed in this study will contribute to the successful breeding and micropropagation of cassava.
