Rice plays a crucial part in Cambodia’s agricultural landscape, serving as a primary food source for the population. The limited water in dry season becoming an increasing concern in the region,optimizing irrigation methods is to modify water consumption in rice production. This study was conducted to investigate the effect of three irrigation methods on the grain yield and water use efficiency of rice crops in soil columns under a nethouse with

Oleoresin is a semi-solid mixture of volatile and nonvolatile compounds that can be extracted from plants, herbs, and spices. Red pepper is widely used as a spice in food products and herbal medicine due to the presence of various bioactive substances such as phenolics and flavonoids. The experimental design for oleoresin extraction was done to define the optimum condition that could offer the highest yield of oleoresin. This study aims to optimi

The peel of key lime is regarded as a byproduct that contains a substantial amount of bioactive components, including essential oil. The extraction of essential oils from key lime peel typically involves conventional techniques such as hydro-distillation or solvent extraction, which are known for their time-intensive and energy-intensive. The employing of microwave pretreatment has emerged as a conventional approach in the extraction of essential

The issue of traffic congestion in Phnom Penh, exacerbated by rapid population growth and construction of flyovers, underscores the need for effective traffic management strategies. In particular, efforts to mitigating congestion during flyover construction, is equally critical for ensuring smoother traffic flow and minimizing disruptions for commuters. This study proposed and evaluated several alternative solutions to minimize traffic congestion

Soybean oil extracted from different methods contains impurities and undesirable substances such as soap residues, free fatty acids, phosphatides, trace metals, coloring pigments, and other impurities that negatively impact the soybean oil's quality including testability, appearance, smell, and shelf life. To enhance the quality of soybean oil, the removal of these undesirable substances is commonly carried out through the bleaching process, whic

Efficient public transportation systems are critical for urban mobility, requiring precise bus arrival time predictions to enhance service quality and passenger satisfaction. This study thoroughly investigates predictive modeling utilizing machine learning methodologies to forecast bus arrival times along a specific route in Phnom Penh, Cambodia. The dataset contains historical bus arrival data from a specific route, including journey duration, h

Identifying the writer of handwritten text poses a significant challenge due to the diversity and variability inherent in handwriting styles. This paper proposes a novel approach based on Siamese neural network (SNN) for the task of writer identification in Khmer handwriting. The SNN architecture was leveraged for training and testing on a dataset specifically collected for this purpose. The dataset comprised 1400 samples collected from students

Despite significant improvement in education levels within Cambodia over recent decades, high school failure rates remain a persistent concern. A quick intervention through the usage of digital transformation is needed. Business Intelligence (BI) and Educational Data Mining (EDM), which offer powerful tools for extracting valuable insights from raw data, hold notable potential to address this challenge within the education domain. This research i

As artificial intelligence has grown, a large language model is a model train with a vast quantity of textual data. This model can be tailored to a particular task, such as chatbots, text production, and question-answering. However, most of the existing pre-trained models nowadays were trained with English datasets, leading to limited support and low performance in other languages, especially low-resource languages like Khmer. To address the imba

Artificial intelligence, fueled by machine learning and deep learning techniques, is revolutionizing various domains. Reinforcement learning (RL) stands out as a potent method for training agents to navigate complex environments and make informed decisions. Our focus is on applying RL techniques, specifically Convolutional Neural Networks (CNNs) combined with policy gradient methods, to enhance the gameplay experience of Khmer chess. Our goal is