查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news reporting originating in Wageningen, Netherla nds, by NewsRx journalists, research stated, “Greenhouse production of fruits an d vegetables in developed countries is challenged by labour scarcity and high la bour costs. Robots offer a good solution for sustainable and cost-effective prod uction.” Financial support for this research came from Netherlands Organization for Scien tific Research (NWO).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on Robotics. Acc ording to news reporting out of Seville, Spain, by NewsRx editors, research stat ed, “The ability to avoid collisions with moving robots is critical in many appl ications. Moreover, if the robots have limited battery life, the goal is not onl y to avoid collisions but also to design efficient trajectories in terms of ener gy consumption and total mission time.” Financial supporters for this research include MCIN/AEI, European Union (EU).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Curitiba, Braz il, by NewsRx journalists, research stated, “Air quality is directly affected by pollutant emission from vehicles, especially in large cities and metropolitan a reas or when there is no compliance check for vehicle emission standards. Partic ulate Matter (PM) is one of the pollutants emitted from fuel burning in internal combustion engines and remains suspended in the atmosphere, causing respiratory and cardiovascular health problems to the population.” The news reporters obtained a quote from the research, “In this study, we analyz ed the interaction between vehicular emissions, meteorological variables, and pa rticulate matter concentrations in the lower atmosphere, presenting methods for predicting and forecasting PM2.5. Meteorological and vehicle flow data from the city of Curitiba, Brazil, and particulate matter concentration data from optical sensors installed in the city between 2020 and 2022 were organized in hourly an d daily averages. Prediction and forecasting were based on two machine learning models: Random Forest (RF) and Long Short-Term Memory (LSTM) neural network. The baseline model for prediction was chosen as the Multiple Linear Regression (MLR ) model, and for forecast, we used the naive estimation as baseline. RF showed t hat on hourly and daily prediction scales, the planetary boundary layer height w as the most important variable, followed by wind gust and wind velocity in hourl y or daily cases, respectively. The highest PM prediction accuracy (99.37% ) was found using the RF model on a daily scale. For forecasting, the highest ac curacy was 99.71% using the LSTM model for 1-h forecast horizon wi th 5 h of previous data used as input variables. The RF and LSTM models were abl e to improve prediction and forecasting compared with MLR and Naive, respectivel y. The LSTM was trained with data corresponding to the period of the COVID-19 pa ndemic (2020 and 2021) and was able to forecast the concentration of PM2.5 in 20 22, in which the data show that there was greater circulation of vehicles and hi gher peaks in the concentration of PM2.5. Our results can help the physical unde rstanding of factors influencing pollutant dispersion from vehicle emissions at the lower atmosphere in urban environment.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Robotics are presented in a new rep ort. According to news reporting out of New Delhi, India, by NewsRx editors, res earch stated, “Autonomy offers significant advantages for mobile robots by elimi nating the need for human operators, thereby enhancing safety and cost-effective ness. Path planning is an essential component of achieving autonomy, as it empow ers robots to thoughtfully navigate between different areas.” Our news journalists obtained a quote from the research from Jamia Millia Islami a, “This study explores the most recent developments in automated guided vehicle s (AGVs) and autonomous mobile robots during the previous ten years. It encompas ses a wide range of AGV research topics from both historical and contemporary pe rspectives. AGVs play a vital role in modern logistics networks, offering time s avings and the potential to minimize wear and capital costs through efficient pa th planning. Numerous approaches to aid in the path-planning procedure for mobil e robotics have been suggested and documented in scholarly research. While perfe ction is not guaranteed, these methods have demonstrated impressive efficacy in practical applications. The study evaluates models, optimization benchmarks, and solution techniques employed for charting optimal courses for mobile robots. Bo th field researchers and AGV developers encounter challenges in navigating the e xpanding array of algorithms designed for diverse applications. Digital twins em erge as pivotal tools in AGV systems, contributing to the development and implem entation of control algorithms.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news reporting originating from Col lege Station, Texas, by NewsRx correspondents, research stated, “Monitoring acti vities of daily living (ADLs) plays an important role in measuring and respondin g to a person’s ability to manage their basic physical needs.” Financial supporters for this research include National Science Foundation. Our news reporters obtained a quote from the research from Texas A& M University: “Effective recognition systems for monitoring ADLs must successful ly recognize naturalistic activities that also realistically occur at infrequent intervals. However, existing systems primarily focus on either recognizing more separable, controlled activity types or are trained on balanced datasets where activities occur more frequently. In our work, we investigate the challenges ass ociated with applying machine learning to an imbalanced dataset collected from a fully in-the-wild environment. This analysis shows that the combination of prep rocessing techniques to increase recall and postprocessing techniques to increas e precision can result in more desirable models for tasks such as ADL monitoring .”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting from the Universitas Nahdlatu l Ulama Sunan Giri by NewsRx journalists, research stated, “Ease of access to in formation is both an advantage and a challenge for today’s young generation. Stu dents who are faced with easy access to information must be able to analyze and filter the information they receive from an early age.” The news reporters obtained a quote from the research from Universitas Nahdlatul Ulama Sunan Giri: “The development of this technology also needs to be balanced with efforts to develop Indonesian human resources. Through the independent cur riculum, it is hoped that the quality of Indonesian human resources will be high er. The Merdeka Curriculum has an essential difference by combining science and social studies at the elementary school level to become science. In this researc h, science subjects were collaborated with a technology-based learning model usi ng Artificial Intelligence, with the aim of describing students’ abilities when taking part in the learning. This research was conducted using a descriptive qua litative approach. Four data collection techniques were used to describe this re search, including interviews, observation, questionnaires, and documentation. Th e results of this research show that science and science learning in elementary schools using Artificial Intelligence is very interesting for students with 95% indicators of learning interest.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning - Intel ligent Systems are presented in a new report. According to news reporting out of Hubei, People’s Republic of China, by NewsRx editors, the research stated, “Thi s paper proposes a hybrid model to improve Information Content (IC) related metr ics of semantic similarity between words, named IC+SP, based on the essential hy pothesis that IC and the shortest path are two relatively independent semantic e vidences and have approximately equal influences to the semantic similarity metr ic. The paradigm of IC+SP is to linearly combine the IC-related metric and the s hortest path.” Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Hubei Provincial Nat ural Science Foundation, China, Open Research Fund of Key Laboratory of Digital Cartography and Land Information Application, Ministry of Natural Resources, Chi na.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Hunan, People’s Republ ic of China, by NewsRx correspondents, research stated, “The screening and desig n of ‘green’ biochar materials with high adsorption capacity play a pivotal role in promoting the sustainable treatment of Cd(II)-containing wastewater. In this study, six typical machine learning (ML) models, namely Linear Regression, Rand om Forest, Gradient Boosting Decision Tree, Cat- Boost, K-Nearest Neighbors, and B ackpropagation Neural Network, were employed to accurately predict the adsorptio n capacity of Cd(II) onto biochars.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Bern, Switzerl and, by NewsRx journalists, research stated, “The accuracy of movement determina tion software in current activity trackers is insufficient for scientific applic ations, which are also not open-source. To address this issue, we developed an a ccurate, trainable, and open-source smartphone-based activity-tracking toolbox t hat consists of an Android app (HumanActivityRecorder) and 2 different deep lear ning algorithms that can be adapted to new behaviors.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news originating from Al Kharj, Saudi Arabia , by NewsRx correspondents, research stated, “This paper proposes an accurate ha rmonic identification strategy for microgrids and distributed power systems.” Financial supporters for this research include Prince Sattam Bin Abdulaziz Unive rsity As Part of Funding For Its Sustainable Development Goals Roadmap Research Funding Program.
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