首页期刊导航|Robotics & Machine Learning Daily News
期刊信息/Journal information
Robotics & Machine Learning Daily News
NewsRx
Robotics & Machine Learning Daily News

NewsRx

Robotics & Machine Learning Daily News/Journal Robotics & Machine Learning Daily News
正式出版
收录年代

    Studies in the Area of Machine Learning Reported from University of New South Wa les (An Integrated Mcdm Model With Enhanced Decision Support In Transport Safety Using Machine Learning Optimization)

    94-95页
    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 Ma chine Learning. According to news reporting from Sydney, Australia, by NewsRx jo urnalists, research stated, “Having the capacity to effectively manage multi-cri teria decision-making (MCDM) issues with considerable reliability is a crucial p rerequisite for any MCDM model. This study introduces an advanced MCDM model tha t integrates logarithmic percentage change-driven objective weighting (LOPCOW), multi-objective optimization on the basis of a ratio analysis plus the full mult iplicative form (MULTIMOORA), and density-based spatial clustering of applicatio ns with noise (DBSCAN).” Financial support for this research came from Harvard-China Project on Energy, E conomy and Environment at Harvard University.

    Research Division Reports Findings in Machine Learning (Late-life suicide: machi ne learning predictors from a large European longitudinal cohort)

    95-96页
    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 Padova, Italy, by News Rx editors, research stated, “People in late adulthood die by suicide at the hig hest rate worldwide. However, there are still no tools to help predict the risk of death from suicide in old age.” Our news journalists obtained a quote from the research from Research Division, “Here, we leveraged the Survey of Health, Ageing, and Retirement in Europe (SHAR E) prospective dataset to train and test a machine learning model to identify pr edictors for suicide in late life. Of more than 16,000 deaths recorded, 74 were suicides. We matched 73 individuals who died by suicide with people who died by accident, according to sex (28.8% female in the total sample), age at death (67 ? 16.4 years), suicidal ideation (measured with the EURO-D scale), and the number of chronic illnesses. A random forest algorithm was trained on d emographic data, physical health, depression, and cognitive functioning to extra ct essential variables for predicting death from suicide and then tested on the test set. The random forest algorithm had an accuracy of 79% (95% CI 0.60-0.92, p = 0.002), a sensitivity of.80, and a specificity of.78. Among th e variables contributing to the model performance, the three most important fact ors were how long the participant was ill before death, the frequency of contact with the next of kin and the number of offspring still alive. Prospective clini cal and social information can predict death from suicide with good accuracy in late adulthood.”

    Affiliated Hospital of Nanjing Medical University Reports Findings in Hemihepate ctomy [Robot-assisted hemihepatectomy is superior to laparosc opic hemihepatectomy through dorsal approach: A propensity score-matched study ( with videos)]

    96-97页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Surgery - Hemihepatect omy is the subject of a report. According to news reporting out of Nanjing, Peop le’s Republic of China, by NewsRx editors, research stated, “Dorsal approach is the potentially effective strategy for minimally invasive liver resection. This study aimed to compare the outcomes between robot-assisted and laparoscopic hemi hepatectomy through dorsal approach.” Our news journalists obtained a quote from the research from the Affiliated Hosp ital of Nanjing Medical University, “We compared the patients who underwent robo t-assisted hemihepatectomy (Rob-HH) and who had laparoscopic hemihepatectomy (La p-HH) through dorsal approach between January 2020 and December 2022. A 1:1 prop ensity score-matching (PSM) analysis was performed to minimize bias and confound ing factors. Ninety-six patients were included, 41 with Rob-HH and 55 with Lap-H H. Among them, 58 underwent left hemihepatectomy (LHH) and 38 underwent right he mihepatectomy (RHH). Compared with Lap-HH group, patients with Rob-HH had less e stimated blood loss (median: 100.0 vs. 300.0 mL, P = 0.016), lower blood transfu sion rates (4.9% vs. 29.1%, P= 0.003) and postoperati ve complication rates (26.8% vs. 54.5%, P = 0.016). T hese significant differences consistently existed after PSM and in the LHH subgr oups. Furthermore, robot-assisted LHH was associated with decreased Pringle dura tion (45 vs. 60 min, P = 0.047). RHH subgroup analysis showed that compared with Lap-RHH, Rob-RHH was associated with less estimated blood loss (200 vs. 400 mL, P = 0.013). No significant differences were found in other perioperative outcom es among pre- and post-PSM cohorts, such as Pringle duration, operative time, an d hospital stay.”

    Recent Research from Northeast Forestry University Highlight Findings in Machine Learning (A Review On Recent Applications of Machine Learning In Mechanical Pro perties of Composites)

    97-98页
    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 Harbin, People’s Republ ic of China, by NewsRx journalists, research stated, “Composites are undergoing extensive research and utilization due to theirexcellent mechanical properties, driven by human needs. Traditionally, theresearch methods in materials science p redominantly rely on empirical theoryor experimental trial and error approaches. ” Financial support for this research came from Science and Technology Innovation Platform Construction Project in Heilongjiang Province.

    Study Results from Gachon University in the Area of Artificial Intelligence Publ ished (The Functional Mechanisms through Which Artificial Intelligence Influence s the Innovation of Green Processes of Enterprises)

    98-99页
    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 originating from Seongnam, South K orea, by NewsRx correspondents, research stated, “Green process innovation is an important strategy in the high-quality development of enterprises. Digital tech nology is becoming a key factor in helping businesses address environmental issu es and contributes to their green process innovation and sustainable growth.” Our news journalists obtained a quote from the research from Gachon University: “Nevertheless, there is a lack of studies on how particular digital technology c ategories affect corporate green process innovation. Artificial intelligence (AI ) is an important part of digitalization as it can provide new technical means a nd guidance for enterprise’s innovation of green processes. This study aims to f ills this research gap by revealing the logical relationship between digital tec hnology and the green development of enterprises. Using China’s A-share-listed c ompanies as the research object from 2013 to 2022, this study employed a two-way fixed-effects model and investigated the impact of artificial intelligence (AI) on corporate green process innovation and the moderating effect of multidimensi onal intellectual capital. The results revealed that AI positively impacts corpo rate green process innovation. Human capital, structural capital, employed capit al, and relational capital strengthen this positive effect.”

    Reports from Southern University of Science and Technology (SUSTech) Add New Dat a to Research in Machine Learning (Machine Learning Prediction of Co-Seismic Lan dslide with Distance and Azimuth Instead of Peak Ground Acceleration)

    99-99页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting originating fr om Shenzhen, People’s Republic of China, by NewsRx correspondents, research stat ed, “Most machine learning (ML) studies on predicting co-seismic landslides have relied on Peak Ground Acceleration (PGA).” Funders for this research include National Natural Science Foundation of China; Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Techn ology; Shenzhen Science And Technology Program; High Level Special Funds.

    Department of Pulmonary and Critical Care Medicine Reports Findings in Asthma (G enetic biomarker prediction based on gender disparity in asthma throughout machi ne learning)

    100-101页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Lung Diseases and Cond itions - Asthma is the subject of a report. According to news originating from Y antai, People’s Republic of China, by NewsRx correspondents, research stated, “A sthma is a chronic respiratory condition affecting populations worldwide, with p revalence ranging from 1-18% across different nations. Gender diff erences in asthma prevalence have attracted much attention.” Financial support for this research came from Key Research and Development Plan of Shandong Province. Our news journalists obtained a quote from the research from the Department of P ulmonary and Critical Care Medicine, “The aim of this study was to investigate b iomarkers of gender differences in asthma prevalence based on machine learning. The data came from the gene expression omnibus database (GSE69683, GSE76262, and GSE41863), which involved in a number of 575 individuals, including 240 males a nd 335 females. Theses samples were divided into male group and female group, re spectively. Grid search and cross-validation were employed to adjust model param eters for support vector machine, random forest, decision tree and logistic regr ession model. Accuracy, precision, recall, and F score were used to evaluate the performance of the models during the training process. After model optimization , four machine learning models were utilized to predict biomarkers of sex differ ences in asthma. In order to validate the accuracy of our results, we performed Wilcoxon tests on the genes expression. In datasets GSE76262 and GSE69683, suppo rt vector machine, random forest, logistic regression, and decision tree all ach ieve 100% accuracy, precision, recall, and F score. Our findings r eveal that XIST serves as a common biomarker among the three samples, comprising a total of 575 individuals, with higher expression levels in females compared t o males (<0.01).”

    New Findings from University of Technology-Iraq Describe Advances in Androids (A pplication of Particle Swarm Optimization to a Hybrid H /Sliding Mode Controller Design for the Triple Inverted Pendulum System)

    101-101页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on androids are presented i n a new report. According to news reporting out of Baghdad, Iraq, by NewsRx edit ors, research stated, “The robotics field of engineering has been witnessing rap id advancements and becoming widely engaged in our lives recently. Its applicati on has pervaded various areas that range from household services to agriculture, industry, military, and health care.” Our news reporters obtained a quote from the research from University of Technol ogy-Iraq: “The humanoid robots are electro-mechanical devices that are construct ed in the semblance of humans and have the ability to sense their environment an d take actions accordingly. The control of humanoids is broken down to the follo wing: sensing and perception, path planning, decision making, joint driving, sta bility and balance. In order to establish and develop control strategies for joi nt driving, stability and balance, the triple inverted pendulum is used as a ben chmark. As the presence of uncertainty is inevitable in this system, the need to develop a robust controller arises. The robustness is often achieved at the exp ense of performance. Hence, the controller design has to be optimized based on t he resultant control system’s performance and the required torque. Particle Swar m Optimization (PSO) is an excellent algorithm in finding global optima, and it can be of great help in automatic tuning of the controller design. This paper pr esents a hybrid H /sliding mode controller optimized by the PSO algorithm to con trol the triple inverted pendulum system.”

    Findings from Vrije Universiteit Brussel (VUB) in the Area of Androids Described (Human-in-the-loop Optimization of Wearable Robotic Devices To Improve Human-ro bot Interaction: a Systematic Review)

    102-102页
    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 - Androids. According to news reporting originating from Brussels, Belgium, by NewsRx correspondents, research stated, “This article presents a systematic rev iew on wearable robotic devices that use human-in-the-loop optimization (HILO) s trategies to improve human-robot interaction. A total of 46 HILO studies were id entified and divided into upper and lower limb robotic devices.” Funders for this research include Strategic Research Program Exercise, Brain in Health and Disease: Added Value of Human-Centered Robotics, Vrije Universiteit B russel, Belgium, German Research Foundation (DFG).

    Study Findings from Tsinghua University Broaden Understanding of Machine Learnin g (The Cost-Optimal Control of Building Air Conditioner Loads Based on Machine L earning: A Case Study of an Office Building in Nanjing)

    103-103页
    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 Beijing, People’s Repu blic of China, by NewsRx editors, research stated, “Building envelopes and indoo r environments exhibit thermal inertia, forming a virtual energy storage system in conjunction with the building air conditioner (AC) system.” Funders for this research include Opening Funds of State Key Laboratory of Build ing Safety And Built Environment & National Engineering Research C enter of Building Technology; Young Elite Scientists Sponsorship Program By Cast .