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 Gothenburg, Sweden, by NewsRx editors, research stated, “Structural details of oligosaccharides, or gl ycans, often carry biological relevance, which is why they are typically elucida ted using tandem mass spectrometry. Common approaches to distinguish isomers rel y on diagnostic glycan fragments for annotating topologies or linkages.” Financial supporters for this research include Branco Weiss Fellowship - Society in Science, Knut och Alice Wallenbergs Stiftelse, Vetenskapsradet, University o f Gothenburg.
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, “Real-time detection of t he mechanical state of ballast bed during the tamping operation in railway maint enance is of great significance for improving the effectiveness of operations. I n this study, a novel test method named the track shifting test was proposed bas ed on the track realigning operation of the tamping vehicle.” Financial support for this research came from Science and Technology Research an d Development Project of China State Railway Group Co., Ltd.. The news correspondents obtained a quote from the research from Beijing Jiaotong University, “The track panel was pushed by the shifting device. Moreover, the l ateral resistance of ballast bed was reflected through easily measured indexes. An accurate coupling model of the shifting device and the ballasted track was co nstructed. Based on the model, the mechanical response of ballast and the track panel induced by the shifting load was analyzed. Results indicated that at an ef fective loading displacement of 2 mm, the lateral resistance of ballast bed with in a detectable range of up to five sleepers can be inverted by the shifting for ce and the displacement of sleepers. A machine learning model was established to obtain the mapping relationship between the shifting force, the displacement of sleepers, and the lateral resistance of ballast bed. Therefore, real-time detec tion of the lateral resistance was achieved by combining the proposed test metho d and the machine learning algorithm.”
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 trans lation have been published. According to news reporting originating from the Uni versity of Geneva by NewsRx correspondents, research stated, “In a rapidly evolv ing language services landscape where the boundaries between translation, revisi on, and post-editing are becoming increasingly blurred, this article provides a state-of-the-art review on the intricate relationship between human translators and Neural Machine Translation (NMT).” The news journalists obtained a quote from the research from University of Genev a: “While acknowledging the significant advancements made in the field of Artifi cial Intelligence (AI) applied to automatic language processing, we want to emph asize the pressing need to reassert the value of human translators over unconsci ous algorithms that automatically generate translations. This paper also highlig hts the synergy between human skills and technology, positioning NMT as a key ad ditional tool in a translator’s toolkit that enhances both speed and efficiency to meet the exponentially growing demand for translation services and to cope wi th the ever-tightening deadlines. Nevertheless, considering the ambivalent effec ts of NMT on the quality of the final product, we advocate for the informed and responsible use of machine translation (MT) tools by both professionals and tran slation students.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Cancer is the subject of a report. According to news reporting out of Montreal, Canada, by NewsRx edit ors, research stated, “To characterize robotic surgery publications in gynecolog ic oncology, and to identify factors associated with high citation metrics. A cr oss-sectional study SETTING: Original articles on robotic surgery in gynecologic oncology. No patients involved.” Our news journalists obtained a quote from the research from McGill University, “Robotic surgeries in gynecologic oncology. We performed PubMed Medical Subject Headings search for original articles on robotic surgery in gynecologic oncology . We analyzed citation scores and income level of country of publication, as wel l as factors associated with high citation metrics. Overall, 566 studies during 2005 to 2023 were included. Of those 292, 51.6% were from North Am erica, and 182 32.2% from Europe.The leading tumor site studied w as endometrial cancer (57.4%). The majority (87.6%) of studies were retrospective and 13 (2.3%) were randomized controlle d trials. Most studies (94.2%) originated in highincome countries. Articles from middle-income countries had lower citations per year as compared to high-income countries (median 1.6 vs 2.5, p =.002) and were published in lowe r-impact factor journals (median 2.6 vs 4.3, p<.001) when compared with high-income countries. Cervical cancer studies had higher represen tation in middle-income countries than in high-income countries (48.5% vs 18.4%, p<.001). In a multivariable regress ion analysis, journal’s impact factor [aOR 95% CI 1.26 (1.12-1.40)], cervical cancer topic [aOR 95% CI 3.0 (1.58-5.91)], and North American publications [aOR 95% CI 2.07 (1.08-3.97)] were independently associated with higher number of citations per year. The majo rity of robotic surgery research in gynecologic oncology is retrospective and fr om high-income countries.”
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 originating from the Faculty of Economics an d Management by NewsRx correspondents, research stated, “This paper investigated the factors in the technology-organization-environment (TOE) framework that aff ect the decision of whether to adopt electronic commerce (EC) or not within smal l- and medium-sized enterprises (SMEs).” Our news editors obtained a quote from the research from Faculty of Economics an d Management: “To this end, a questionnaire-based survey was conducted to collec t data from 60 managers or owners of manufacturing SMEs in Tunisia. Unlike the t raditional regression approaches, we referred to novel machine learning (ML) tec hniques and reveal that ML techniques reach a higher level of performance in for ecasting driving factors to EC adoption compared to the traditional logistic reg ression approach.”
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 Madrid, Spain, by NewsRx journalists, resear ch stated, “Decision-making systems allow artificial agents to adapt their behav iours, depending on the information they perceive from the environment and inter nal processes.” Financial supporters for this research include Agencia Estatal De Investigacion (Aei), Spanish Ministerio De Ciencia E Innovacion; European Union Nextgeneration eu/prtr. Our news correspondents obtained a quote from the research from University Carlo s III of Madrid: “Human beings possess unique decision-making capabilities, adap ting to current situations and anticipating future challenges. Autonomous robots with adaptive and anticipatory decision-making emulating humans can bring robot s with skills that users can understand more easily. Human decisions highly depe nd on dopamine, a brain substance that regulates motivation and reward, acknowle dging positive and negative situations. Considering recent neuroscience studies about the dopamine role in the human brain and its influence on decision-making and motivated behaviour, this paper proposes a model based on how dopamine drive s human motivation and decision-making. The model allows robots to behave autono mously in dynamic environments, learning the best action selection strategy and anticipating future rewards.”
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 Berlin, Germany, by News Rx journalists, research stated, “Non-targeted screenings (NTS) are essential to ols in different fields, such as forensics, health and environmental sciences. N TSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance-based met hods.” The news correspondents obtained a quote from the research, “As the identificati on of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, b oth the diversity of mass spectral signals and the sheer quantity of different M L tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field. In this work, we illustrate which ML-based methods are available for compound annotation in non-targeted MS experiments and provide a nuanced comparison of the ML models used in MS data an alysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research.”
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 originating from Doornfontein, Sou th Africa, by NewsRx editors, the research stated, “Terrestrial diesel spills si gnificantly threaten the natural environment and human health, necessitating eff ective bioremediation strategies for diesel-contaminated soil. This study aims t o evaluate the impact of diesel spills on soil water retention capacity and the effectiveness of different bioremediation methods.” Financial supporters for this research include University of Johannesburg. Our news editors obtained a quote from the research from University of Johannesb urg: “Four tanks (A-D) were used to compare natural attenuation, bioaugmentation , biostimulation, and a combination of bioaugmentation and biostimulation in enh ancing diesel degradation. The findings demonstrated that soil water retention d ecreases with higher diesel concentrations and increases with more compost. Afte r 21 days, the Diesel Range Organics (DRO) removal efficiencies for Tanks A, B, C, and D were 15.70 %, 23.31 %, 29.65 %, and 49.78 %, respectively. The degradation kinetics primarily follo wed first-order reaction models, with combined bioaugmentation and biostimulatio n showing the fastest reaction rate. The projected timelines for complete biorem ediation were 44 days for the combined method, 88 days for biostimulation, 116 d ays for bioaugmentation, and 178 days for natural attenuation. Machine Learning models further supported these findings, with the bilateral Artificial Neural Ne twork outperforming the Linear Regression model (R2 of 0.9990 vs.”
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 out of the University of Stra thclyde by NewsRx editors, research stated, “Femtosecond laser nanomachining rep resents a frontier in precision manufacturing, excelling in micro-and nanopatter ning across diverse materials.” Our news reporters obtained a quote from the research from University of Strathc lyde: “However, its wider adoption is hindered by unintended surface damage or m odifications stemming from complex nonlinear laser-material interactions. Moreo ver, traditional effective process optimisation effort to mitigate these issues typically necessitate extensive and time-consuming trial-and-error testing. In t his scenario, machine learning (ML) has emerged as a powerful solution to addres s these challenges. This paper provides an overview of ML’s contributions to mak ing femtosecond laser machining a more deterministic and efficient technique. Le veraging data from laser parameters and both in-situ and ex-situ imaging of proc essing outcomes, ML techniques-spanning supervised learning, unsupervised learni ng, and reinforcement learning-can significantly enhance process monitoring, pro cess modeling and prediction, parameter optimisation, and autonomous beam path p lanning.”
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 Machine Learning - Intelligent Systems. According to news originating from Hunan, Peopl e’s Republic of China, by NewsRx correspondents, research stated, “Most previous few-shot action recognition works tend to process video temporal and spatial fe atures separately, resulting in insufficient extraction of comprehensive feature s. In this paper, a novel hybrid attentive prototypical network (HAPN) framework for few-shot action recognition is proposed.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of China (NSFC).
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