查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news reporting from Menoufia, Egypt, by NewsRx journalist s, research stated, “Object tracking is one of the major tasks for mobile robots in many real-world applications. Also, artificial intelligence and automatic co ntrol techniques play an important role in enhancing the performance of mobile r obot navigation.” Financial support for this research came from Deanship of Scientific Research at Shaqra University.
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 Machine Learn ing - Support Vector Machines have been published. According to news reporting f rom Shanghai, People’s Republic of China, by NewsRx journalists, research stated , “Al-Mg-Si (6xxx series) aluminum alloys are widely employed in the automotive industry for lightweight applications, but crack formation during thermal formin g remains a common issue. To address the problem and enhance the mechanical prop erties of these materials, an in-depth study of the flow stress is crucial.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of China (NSFC), Natural Science Foundation of Shanghai, Program of Foundation of Science and Technology Commission of Shanghai Municipality, Shanghai Professional Technical Service Pl atform for Intelligent Operation and Maintenance of Renewable Energy.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Ottawa, Canada, by NewsRx editors, research stated, “Despite the potential of artificial intell igence (AI) in enhancing cardiovascular care, its integration into clinical prac tice is limited by a lack of evidence on its effectiveness with respect to human experts or gold standard practices in real-world settings. The purpose of this study was to identify AI interventions in cardiology that have been prospectivel y validated against human expert benchmarks or gold standard practices, assessin g their effectiveness, and identifying future research areas.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on robotics are presented i n a new report. According to news reporting out of Asan, South Korea, by NewsRx editors, research stated, “This paper proposes a novel adaptive law that uses a quasi-convex function and a novel sliding variable in an adaptive sliding mode c ontrol (ASMC) scheme for robot manipulators.” Financial supporters for this research include Soonchunhyang University Research Fund; Ministry of Education.
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 are pre sented in a new report. According to news reporting from Vigo, Spain, by NewsRx journalists, research stated, “Cognitive and neurological impairments are very c ommon, but only a small proportion of affected individuals are diagnosed and tre ated, partly because of the high costs associated with frequent screening. Detec ting pre-illness stages and analyzing the progression of neurological disorders through effective and efficient intelligent systems can be beneficial for timely diagnosis and early intervention.” Financial supporters for this research include Xunta de Galicia, Spanish Governm ent, University of Vigo/CISUG.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics is now availab le. According to news reporting out of Witzenhausen, Germany, by NewsRx editors, research stated, “The demand for efficient and sustainable agricultural practic es has fostered the development of advanced technologies for pest management. Th is paper presents a research study on the detection of slugs on lettuce and the 3D localization (x,y,z\documentclass[ 12pt]{minimal} \usep ackage{amsmath} \usepackage{ wasysym} \usepackage{amsfonts} \ usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \ usepackage{upgreek} \setlength { \oddsidemargin}{-69pt} \ begin{document}$$x,y,z$ $\end{document} coordinate s) of the detected slugs, with the goal of enabling a robotic arm to collect the m in a horticultural application.” Financial support for this research came from Federal Ministry of Food and Agric ulture of Germany.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting originating from Urmia U niversity by NewsRx correspondents, research stated, “Predictions of total disso lved solids (TDS) in water bodies including rivers and lakes are challenging but essential for the effective management of water resources in agricultural and d rinking water sectors.” The news correspondents obtained a quote from the research from Urmia University : “This study developed a hybrid model combining Grey Wolf Optimization (GWO) an d Kernel Extreme Learning Machine (KELM) called GWO-KELM to model TDS in water b odies. Time series data for TDS and its driving factors, such as chloride, tempe rature, and total hardness, were collected from 1975 to 2016 to train and test m achine learning models. The study aimed to assess the performance of the GWO-KEL M model in comparison to other state-of-the-art machine learning algorithms. Res ults showed that the GWO-KELM model outperformed all other models (such as Artif icial Neural Network, Gaussian Process Regression, Support Vector Machine, Linea r Regression, Classification and Regression Tree, and Boosted Regression Trees), achieving the highest coefficient of determination (R2) value of 0.974, indicat ing excellent predictive accuracy. It also recorded the lowest root mean square error (RMSE) of 55.75 and the lowest mean absolute error (MAE) of 34.40, reflect ing the smallest differences between predicted and actual values.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on robotics have been pr esented. According to news originating from Carnegie Mellon University by NewsRx correspondents, research stated, “Electrolytes play a critical role in designin g next-generation battery systems, by allowing efficient ion transfer, preventin g charge transfer, and stabilizing electrode-electrolyte interfaces.” Funders for this research include Doe | Advanced Research Projects Agency - Ener gy. The news journalists obtained a quote from the research from Carnegie Mellon Uni versity: “In this work, we develop a differentiable geometric deep learning (GDL ) model for chemical mixtures, DiffMix, which is applied in guiding robotic expe rimentation and optimization towards fast-charging battery electrolytes. In part icular, we extend mixture thermodynamic and transport laws by creating GDL-learn able physical coefficients. We evaluate our model with mixture thermodynamics an d ion transport properties, where we show improved prediction accuracy and model robustness of DiffMix than its purely data-driven variants. Furthermore, with a robotic experimentation setup, Clio, we improve ionic conductivity of electroly tes by over 18.8% within 10 experimental steps, via differentiable optimization built on DiffMix gradients.”
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 Machine Learn ing have been published. According to news reporting from Beijing, People’s Repu blic of China, by NewsRx journalists, research stated, “Green buildings represen t a promising solution for advancing high-quality development in the building se ctor to combat climate change. Selecting appropriate credits from the rating sys tem based on the distinct characteristics of buildings is a crucial step in the green building certification process.”Funders for this research include National Natural Science Foundation of China ( NSFC), Beijing Building Research Institute Corporation Limited of CSCEC.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in robotic s. According to news reporting from Busan, South Korea, by NewsRx journalists, r esearch stated, “Since the emergence of ChatGPT, research on large language mode ls (LLMs) has actively progressed across various fields. LLMs, pre-trained on va st text datasets, have exhibited exceptional abilities in understanding natural language and planning tasks.” Financial supporters for this research include Ministry of Trade, Industry, And Energy; Ministry of Education. Our news reporters obtained a quote from the research from Dong-A University: “T hese abilities of LLMs are promising in robotics. In general, traditional superv ised learning-based robot intelligence systems have a significant lack of adapta bility to dynamically changing environments. However, LLMs help a robot intellig ence system to improve its generalization ability in dynamic and complex real-wo rld environments. Indeed, findings from ongoing robotics studies indicate that L LMs can significantly improve robots’ behavior planning and execution capabiliti es. Additionally, vision-language models (VLMs), trained on extensive visual and linguistic data for the vision question answering (VQA) problem, excel at integ rating computer vision with natural language processing. VLMs can comprehend vis ual contexts and execute actions through natural language. They also provide des criptions of scenes in natural language. Several studies have explored the enhan cement of robot intelligence using multimodal data, including object recognition and description by VLMs, along with the execution of language-driven commands i ntegrated with visual information.”
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