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 artific ial intelligence. According to news reporting out of the Universiti Tenaga Nasio nal by NewsRx editors, research stated, “This study highlights drought forecasti ng for understanding the semi-arid area in India, where drought phenomena play v ital role in the irrigation, drinking water supplies, and sustaining the ecologi cal with economic balance for every nation. Therefore, drought forecasting is im portant for the future drought planning based on the machine learning (ML) model s. Hence, The Standardized Precipitation Index (SPI) at 3- and 6-month periods h ave been selected and used for future drought forecasting scenarios in area.”
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 the Chi nese Academy of Agricultural Sciences by NewsRx correspondents, research stated, “[Purpose/Significance] Accurately measur ing the influence of technical topics is crucial for decision-makers to understa nd the developmental trends in the technology sector. It is also an important li nk in identifying emerging, cutting-edge, and disruptive technical topics.” The news journalists obtained a quote from the research from Chinese Academy of Agricultural Sciences: “Traditional methods of measuring technical topic influen ce are significantly affected by the latency of patent data approval and citatio ns, lack a forward-looking perspective on the potential influence of technical t opics, and suffer from insufficient semantic richness in the extraction of techn ical topics. This paper presents a method for measuring technical topic influenc e based on PhraseLDA-SNA and machine learning. It aims to mitigate the impact of delays in patent data approval and citation, while improving the interpretabili ty and accuracy of the results in assessing technical topic influence. [Method/Process] In this study the explicit and implicit deter minants of technical topic influence were first analyzed, based on which an inde x system for measuring technical topic influence was constructed. Then, the Phra seLDA model was used to extract semantically rich technical topics from a large corpus of pre-processed patent texts and to compute the topic-patent association probabilities. PhraseLDA-SNA enhances the semantic richness of technical topic extraction and deepens the analysis of topic content. Machine learning methods l everage their robust data processing and analysis capabilities to predict the hi gh citation potential of patents related to the topics. This research integrates PhraseLDA-SNA and machine learning methods to accurately measure the significan ce and advanced nature of technical topics in promoting field development,there by achieving an accurate measurement of the influence of technical topics. Final ly, an empirical study was conducted in the field of cellulose biodegradation to compare the high-impact technical topics identified by the proposed method with those identified by the traditional method. Several experts with high academic influence and extensive experience in cellulose biodegradation research were inv ited to evaluate the high-impact technical topics identified in this study, thus validating the effectiveness of the proposed method. [Result s/Conclusions] Compared with the traditional method, the tech nical topic influence measurement approach based on PhraseLDA-SNA and machine le arning reveals more in-depth content.”
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 new report. According to news reporting out of Guangxi, Pe ople’s Republic of China, by NewsRx editors, research stated, “With the advancem ent of technology in recent years, the application of artificial intelligence in real life has become more extensive. Graphic recognition is a hot spot in the c urrent research of related technologies.” The news correspondents obtained a quote from the research from College of Infor mation Science and Engineering: “It involves machines extracting key information from pictures and combining it with natural language processing for in-depth un derstanding. Existing methods still have obvious deficiencies in fine-grained re cognition and deep understanding of contextual context. Addressing these issues to achieve high-quality image-text recognition is crucial for various applicatio n scenarios, such as accessibility technologies, content creation, and virtual a ssistants. To tackle this challenge, a novel approach is proposed that combines the Mask R-CNN, DCGAN, and ALBERT models. Specifically, the Mask R-CNN specializ es in high-precision image recognition and segmentation, the DCGAN captures and generates nuanced features from images, and the ALBERT model is responsible for deep natural language processing and semantic understanding of this visual infor mation. Experimental results clearly validate the superiority of this method.”
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 out of Ourense, Spain, b y NewsRx editors, research stated, “The shiitake mushroom has gained popularity in the last decade, ranking second in the world for mushrooms consumed, providin g consumers with a wide variety of nutritional and healthy benefits.” The news correspondents obtained a quote from the research from University of Vi go: “It is often not clear the origin of these mushrooms, so it becomes of great importance to the consumers. In this research, different machine learning algor ithms were developed to determine the geographical origin of shiitake mushrooms (* * Lentinula edodes* * ) consumed in Korea, based on experimental data reporte d in the literature (d13C, d15N, d18O, d34S, and origin). Regarding the origin of shiitake in three categories (Korean, Ch inese, and mushrooms from Chinese inoculated sawdust blocks), the random forest model presents the highest accuracy value (0.940) and the highest kappa value (0 .908) for the validation phase. To determine the origin of shiitake mushrooms in two categories (Korean and Chinese, including mushrooms from Chinese inoculated sawdust blocks in the latter ones), the support vector machine model is chosen as the best model due to the high accuracy (0.988) and kappa (0.975) values for the validation phase. Finally, to determine the origin in two categories (Korean and Chinese, but this time including the mushrooms from Chinese inoculated sawd ust blocks in the Korean ones), the best model is the random forest due to its h igher accuracy value (0.952) in the validation phase (kappa value of 0.869). The accuracy values in the testing phase for the best selected models are acceptabl e (between 0.839 and 0.964); therefore, the predictive capacity of the models co uld be acceptable for their use in real applications.”
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 Ro botics - Androids. According to news reporting originating from Jinan, People’s Republic of China, by NewsRx correspondents, research stated, “This article pres ents a reactive planning and control framework to enhance the robustness of huma noid robots locomotion against external disturbances. The framework comprises tw o main modules, reactive planning and motion optimization.” Financial support for this research came from National Natural Science Foundatio n of China.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on robotic systems a re discussed in a new report. According to news originating from Beijing, People ’s Republic of China, by NewsRx correspondents, research stated, “At present, tr aditional analysis methods sometimes show incompatibility when analyzing the deg ree of freedom (DOF) of parallel mechanisms.” Our news reporters obtained a quote from the research from School of Mechanical and Electrical Engineering: “In this research, a new DOF analysis method (MV-DOF method) based on primary-ancillary motion theory is developed. The 4PPRRR serie s-parallel mechanism is taken as an example, the analysis results by using the M V-DOF method are compared with those of traditional inverse helix theory and mod ified Grubler-Kutzbach formula, respectively. The comparison shows that this MV- DOF method can always analyze the DOF of the 4PPRRR series-parallel mechanism ac curately, while the other two traditional methods show inapplicability sometimes . During the analysis, an important rule is also found that the ancillary motion is equivalent to local constraint helix motion, but it is not always true in tu rn. Based on this MV-DOF method, a DOF cutting analysis way is also suggested. A ny output point on a complex mechanism can be taken as a cutting point, along wh ich the mechanism can be cut into two independent sub-mechanisms.”
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 originating from Donostia San Sebastian, Spain, by NewsRx c orrespondents, research stated, “The cost landscape in advanced technology syste ms is shifting dramatically.” Funders for this research include Elkartek Research Program of The Basque Govern ment; Fundacion Tecnalia Research And Innovation. Our news journalists obtained a quote from the research from TECNALIA: “Traditio nally, hardware costs took the spotlight, but now, programming and debugging com plexities are gaining prominence. This paper explores this shift and its implica tions, focusing on reducing the cost of programming complex robot behaviors, usi ng the latest innovations from the Generative AI field, such as large language m odels (LLMs).”
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 from Raleigh, North Carolina, by NewsRx journalists, research stated, “Granular activated carbon (GAC) adsorp tion is frequently used to remove recalcitrant organic micropollutants (MPs) fro m water. The overarching aim of this research was to develop machine learning (M L) models to predict GAC performance from adsorbent, adsorbate, and background w ater matrix properties.” The news correspondents obtained a quote from the research from North Carolina S tate University, “For model calibration, MP breakthrough curves were compiled an d analyzed to determine the bed volumes of water that can be treated until MP br eakthrough reaches ten percent of the influent MP concentration (BV10). Over 400 data points were split into training, validation, and testing sets. Seventeen v ariables describing MP, background water matrix, and GAC properties were explore d in ML models to predict log-transformed BV10 values. Using the ML models on th e testing set, predicted BV10 values exhibited mean absolute errors of 0.12 log units and were highly correlated with experimentally determined values ( 0.88). The top three drivers influencing BV10 predictions were the air-hexadecane parti tion coefficient and hydrogen bond acidity (Abraham parameters and ) of the MPs and the dissolved organic carbon concentration of the GAC influent water.”
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 out of Moscow, Russia, by New sRx editors, research stated, “Pupil dilation is controlled both by sympathetic and parasympathetic nervous system branches. We hypothesized that the dynamic of pupil size changes under cognitive load with additional false feedback can pred ict individual behavior along with heart rate variability (HRV) patterns and eye movements reflecting specific adaptability to cognitive stress.”
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 from Seattle, Washingt on, by NewsRx journalists, research stated, “Despite the emerging application of clinical decision support systems (CDSS) in pregnancy care and the proliferatio n of artificial intelligence (AI) over the last decade, it remains understudied regarding the role of AI in CDSS specialized for pregnancy care. To identify and synthesize AI-augmented CDSS in pregnancy care, CDSS functionality, AI methodol ogies, and clinical implementation, we reported a systematic review based on emp irical studies that examined AI-augmented CDSS in pregnancy care.”
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