相关论文: From Bytes to Bites: Using Country Specific Machin…
Food recognition is an important task for a variety of applications, including managing health conditions and assisting visually impaired people. Several food recognition studies have focused on generic types of food or specific cuisines,…
The instability of power generation from national grids has led industries (e.g., telecommunication) to rely on plant generators to run their businesses. However, these secondary generators create additional challenges such as fuel leakages…
As the use of Lithium-ion batteries continues to grow, it becomes increasingly important to be able to predict their remaining useful life. This work aims to compare the relative performance of different machine learning algorithms, both…
The issue of food waste is a major problem contributing to the emission of greenhouse gases into the environment in addition to causing illness in humans. This research aimed to develop a correlation between the amount of time until a food…
One third of food produced in the world for human consumption -- approximately 1.3 billion tons -- is lost or wasted every year. By classifying food waste of individual consumers and raising awareness of the measures, avoidable food waste…
Identifying and addressing poverty is challenging in administrative units with limited information on income distribution and well-being. To overcome this obstacle, small area estimation methods have been developed to provide reliable and…
Homelessness is a humanitarian challenge affecting an estimated 1.6 billion people worldwide. In the face of rising homeless populations in developed nations and a strain on social services, government agencies are increasingly adopting…
The automotive industry is under growing pressure to reduce its environmental impact, requiring accurate predictive modeling to support sustainable engineering design. This study examines the factors that determine vehicle fuel consumption…
Malnutrition is a major public health concern in low-and-middle-income countries (LMICs). Understanding food and nutrient intake across communities, households and individuals is critical to the development of health policies and…
Sepsis is a severe condition responsible for many deaths in the United States and worldwide, making accurate prediction of outcomes crucial for timely and effective treatment. Previous studies employing machine learning faced limitations in…
This transformation of food delivery businesses to online platforms has gained high attention in recent years. This due to the availability of customizing ordering experiences, easy payment methods, fast delivery, and others. The…
Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, were overweight. Of these, over 600 million were obese. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges…
This study presents a machine learning framework for forecasting short-term faults in industrial centrifugal pumps using real-time sensor data. The approach aims to predict {EarlyWarning} conditions 5, 15, and 30 minutes in advance based on…
Accurate prediction of crop yield before harvest is of great importance for crop logistics, market planning, and food distribution around the world. Yield prediction requires monitoring of phenological and climatic characteristics over…
Diabetes has emerged as a significant global health issue, especially with the increasing number of cases in many countries. This trend Underlines the need for a greater emphasis on early detection and proactive management to avert or…
The world is becoming more globalized every day and people can buy products from almost every country in the world in their local stores. Given the different food and feed safety laws from country to country, the European Union began to…
Agricultural research is essential for increasing food production to meet the requirements of an increasing population in the coming decades. Recently, satellite technology has been improving rapidly and deep learning has seen much success…
Drought threatens food and water security around the world, and this threat is likely to become more severe under climate change. High resolution predictive information can help farmers, water managers, and others to manage the effects of…
Many aging individuals encounter challenges in effectively tracking their dietary intake, exacerbating their susceptibility to nutrition-related health complications. Self-reporting methods are often inaccurate and suffer from substantial…
Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate…