查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Artificial Intelligence are discussed in a new report. According to news originating from Rio de Janeiro, Brazil, by NewsRx editors, the research stated, “The aim of this study was to identify and analyze the main constituent elements of text generated by ChatGPT in response to questions on an emerging topic in the academic literature in Portuguese - health literacy - and discuss how the evidence produced can contribute to improving our understanding of the limits and challenges of using artificial intelligence (AI) in academic writing. We conducted an exploratory descriptive study based on responses to five consecutive questions in Portuguese and English with increasing levels of complexity put to ChatGPT.” Our news journalists obtained a quote from the research from Oswaldo Cruz Foundation (FIOCRUZ), “Our findings reveal the potential of the use of widely available, unrestricted access AI-based technologies like ChatGPT for academic writing. Featuring a simple and intuitive interface, the tool generated structured and coherent text using natural-like language.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting out of Bari, Italy, by NewsRx editors, research stated, “Drinking water infrastructures are systems of pipes which are generally networked. They play a crucial role in transporting and delivering clean water to people.” Our news journalists obtained a quote from the research from the Polytechnic University of Bari, “The water quality analysis refers to the evaluation of the advective diffusion of any substance in drinking water infrastructures from source nodes. Such substances could be a contamination for the system or planned for the disinfection, e.g., chlorine. The water quality analysis is performed by integrating the differential equation in the pipes network domain using the kinetics of the substance decay and the Lagrangian scheme. The kinetics can be formulated using a specific reaction order depending on the substance characteristics. The basis for the integration is the pipes velocity field calculated by means of hydraulic analysis. The aim of the present work is to discover the intrinsic mechanism of the substance transport in drinking water infrastructures, i.e., their pipes network domain, using the symbolic machine learning, named Evolutionary Polynomial Regression, which provides ‘synthetic’ models (symbolic formulas) from data. We demonstrated, using one real network and two test networks, that the concentration at each node of the network can be predicted using the travel time along the shortest path(s) between the source and each node.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting originating from Davis, California, by NewsRx correspondents, research stated, “This work aims to address the challenge of developing interpretable ML-based models when access to large-scale compu- tational resources is limited. Using CoMoFeNiCu high-entropy alloy catalysts as an example, we present a cost-effective workflow that synergistically combines descriptor-based approaches, machine learning-based force fields, and low-cost density functional theory (DFT) calculations to predict high-quality adsorption energies for H, N, and NH ( = 1, 2, and 3) adsorbates.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on robotics are discussed in a new report. According to news originat- ing from the University of Louisiana at Lafayette by NewsRx correspondents, research stated, “The flexible and adaptable nature of continuum soft robots makes them applicable to a wide range of operations not easily obtainable with conventional rigid-body robots. Thus, soft robots can be used in various operations such as manipulation tasks, minimally invasive surgery operations, robotic rehabilitation/wearable devices, inspection, and surveillance tasks.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial intelligence have been published. According to news reporting originating from Hangzhou, People’s Republic of China, by NewsRx correspondents, research stated, “The recently developed Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2), furnished with the Advanced Terrain Laser Altimeter System (ATLAS), delivers considerable benefits in providing accurate bathymetric data across extensive geographical regions. By integrating active lidar-derived reference sea- water depth data with passive optical remote sensing imagery, efficient bathymetry mapping is facilitated.” Funders for this research include National Natural Science Foundation; National Key Research And Development Program of China; Key Special Project For Introduced Talents Team of Southern Marine Science And Engineering Guangdong Laboratory; Donghai Laboratory Preresearch Project; Key Research And Development Program of Zhejiang Province.
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligence is the subject of a new report. According to news reporting from Faisalabad, Pakistan, by NewsRx journalists, research stated, “In text applications, pre-processing is deemed as a significant parameter to enhance the outcomes of natural language processing (NLP) chores. Text normalization and tokenization are two pivotal procedures of text pre-processing that cannot be overstated.” Our news editors obtained a quote from the research from National Textile University: “Text normal- ization refers to transforming raw text into scriptural standardized text, while word tokenization splits the text into tokens or words. Well defined normalization and tokenization approaches exist for most spoken languages in world. However, the world’s 10th most widely spoken language has been overlooked by the research community. This research presents improved text normalization and tokenization techniques for the Urdu language. For Urdu text normalization, multiple regular expressions and rules are proposed, including removing diuretics, normalizing single characters, separating digits, etc. While for word tokeniza- tion, core features are defined and extracted against each character of text. Machine learning model is considered with specified handcrafted rules to predict the space and to tokenize the text. This experiment is performed, while creating the largest human-annotated dataset composed in Urdu script covering five different domains.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in artificial intelligence. According to news reporting from Selangor, Malaysia, by NewsRx journalists, research stated, “Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout’s distributed machine-learning environment.” Our news correspondents obtained a quote from the research from Universiti Kebangsaan Malaysia: “The study taps into Apache Hadoop’s robust tools for data storage and processing, including HDFS and MapReduce, to effectively manage and analyze big data challenges. The preprocessing phase utilizes Canopy clustering to expedite the initial partitioning of data points, which are subsequently refined by K- means to enhance clustering performance. Experimental results confirm that incorporating the Canopy as an initial step markedly reduces the computational effort to process the vast quantity of parallel power load abnormalities. The Canopy clustering approach, enabled by distributed machine learning through Apache Mahout, is utilized as a preprocessing step within the K-means clustering technique. The hybrid algorithm was implemented to minimise the length of time needed to address the massive scale of the detected parallel power load abnormalities. Data vectors are generated based on the time needed, sequential and parallel candidate feature data are obtained, and the data rate is combined.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting out of Guangzhou, People’s Republic of China, by NewsRx editors, research stated, “Cocrystal engineering, which involves the self-assembly of two or more components into a solid-state supramolecular structure through non-covalent interactions, has emerged as a promising approach to tailor the physico- chemical properties of active pharmaceutical ingredient (API). Efficient coformer screening for cocrystal remains a challenge.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on robotics. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Robotic friction stir welding has become an important research direction in friction stir welding technology.” Funders for this research include National Key Research And Development Program of China; “qihang Programme” For The Faculty of Materials And Manufacturing, Bjut. The news editors obtained a quote from the research from Beijing University of Technology: “However, the low stiffness of serial industrial robots leads to substantial, difficult-to-measure end-effector deviations under the welding forces during the friction stir welding process, impacting the welding quality. To more effectively measure the deviations in the end-effector, this study introduces a digital twin model based on the five-dimensional digital twin theory. The model obtains the current data of the robot and six-axis force sensor and calculates the real-time end deviations using the robot model. Based on this, a virtual welding model was realized by integrating the FEA model with the digital twin model using a co-simulation approach. This model achieves pre-process simulation by iteratively cycling through the simulated force from the FEA model and the end displacement from the robot model.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting orig- inating from Wageningen, Netherlands, by NewsRx correspondents, research stated, “Accurate field-scale estimates of the actual evapotranspiration (ETact) based on readily available input data is indispensable to optimize irrigation in (semi-)arid regions. In this study, at an irrigated pecan orchard in Northwest Mexico we explored the potential for three different machine learning algorithms to improve upon the 30-min ETact estimates provided by the FAO Penman-Monteith method (FAO-PM) when trained and tested on multi-year eddy-covariance measurements.” Funders for this research include WIMEK graduate school (Wageningen University and Research, Netherlands), MEXCID.
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