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 Groningen, Neth erlands, by NewsRx editors, research stated, “The processes of nutrient uptake a nd signal sensing are crucial for microbial survival and adaptation. Membrane-em bedded proteins involved in these functions (transporters and receptors) are com monly regarded as unrelated in terms of sequence, structure, mechanism of action and evolutionary history.” Our news journalists obtained a quote from the research from the University of G roningen, “Here, we analyze the protein structural universe using recently devel oped artificial intelligence-based structure prediction tools, and find an unexp ected link between prominent groups of microbial transporters and receptors. The so-called S-components of Energy-Coupling Factor (ECF) transporters, and the me mbrane domains of sensor histidine kinases of the 5TMR cluster share a structura l fold.”
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. According to news reporting out of Harbin, People’s Republic of China , by NewsRx editors, research stated, “Daylight has a positive impact on the hea lth, pleasure, and productivity of office workers. Analyzing how environmental p arameters affect daylight’s visual effects can help effectively evaluate dayligh t sensation and assist architects in creating more appropriate daylight environm ents.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Fundamental Research Funds for the Central Universities, Ass istant Professor Research Initiation Project at Harbin Institute of Technology, China Scholarship Council.
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 Mumbai, India, by NewsRx journalists, research stated, “The machining learning-based predictive model of double disc chemo-magnetorheological finishing process of silicon was proposed in the present manuscript. Six different methods such as CatBoost Regressor, XGB oost, Random Forest Regressor, Gradient Boosting Regressor, Linear Regression, a nd AdaBoost Regressor were used to predict the surface roughness.” The news correspondents obtained a quote from the research from Indian Institute for Technology, “The models were trained by the experimental data of surface ro ughness of silicon wafer polished at combination of different set of parameters. The gradient boosting algorithm was introduced to train the dataset of the mode ls for the surface roughness of the silicon wafer. The robustness of the models was verified with K-fold cross method. The models were verified with the conditi on monitoring data collected by experimental results. The models were also devel oped for ultrasonic assistance during the double disc chemo-magnetorheological f inishing process. The CatBoost approach outperformed the other models. The accur acy of the CatBoost model was 99.92% and 98.35% for the experimental data without and with ultrasonic vibration assistance. The opti mised values from the predicted model were 4.21 nm and 3.4 nm without and with t he assistance of vibration for the chemo-magnetorheological finishing process an d have good agreement with the experimental results.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Artificial Intelligen ce have been presented. According to news reporting originating in Jiangxi, Peop le’s Republic of China, by NewsRx journalists, research stated, “Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner ene rgy system is highly significant for ensuring the sustainable development of the economy. China’s energy structure urgently needs to be transitioned.” Financial support for this research came from National Social Science Foundation Key Project of China.
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. According to news reporting out of Tampere, Finland, by NewsRx editors, research stated, “This study grounded on computational social sciences and socia l psychology investigated sentiment and life domains, motivational, and temporal themes in social media discussions about robotic technologies. We retrieved tex t comments from the Reddit social media platform in March 2019 based on the foll owing six robotic technology concepts: robot (N = 3,433,554), AI (N = 2,821,614) , automation (N = 879,092), bot (N = 21,559,939), intelligent agent (N = 15,119) , and software agent (N = 18,324).” Financial supporters for this research include Pirkanmaa Regional Fond of the Fi nnish Cultural Foundation, Vienna Science and Technology Fund, Kone Foundation.
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 Guangzhou, People ’s Republic of China, by NewsRx journalists, research stated, “This study aimed to develop artificial intelligence models for predicting postoperative functiona l outcomes in patients with rhegmatogenous retinal detachment (RRD). A retrospec tive review and data extraction were conducted on 184 patients diagnosed with RR D who underwent pars plana vitrectomy (PPV) and gas tamponade.” The news correspondents obtained a quote from the research from Southern Medical University, “The primary outcome was the best-corrected visual acuity (BCVA) at three months after the surgery. Those with a BCVA of less than 6/18 Snellen acu ity were classified into a vision impairment group. A deep learning model was de veloped using presurgical predictors, including ultra-widefield fundus images, s tructural optical coherence tomography (OCT) images of the macular region, age, gender, and preoperative BCVA. A fusion method was used to capture the interacti on between different modalities during model construction. Among the participant s, 74 (40%) still had vision impairment after the treatment. There were significant differences in age, gender, presurgical BCVA, intraocular press ure, macular detachment, and extension of retinal detachment between the vision impairment and vision non-impairment groups. The multimodal fusion model achieve d a mean area under the curve (AUC) of 0.91, with a mean accuracy of 0.86, sensi tivity of 0.94, and specificity of 0.80. Heatmaps revealed that the macular invo lvement was the most active area, as observed in both the OCT and ultra-widefiel d images. This pilot study demonstrates that artificial intelligence techniques can achieve a high AUC for predicting functional outcomes after RRD surgery, eve n with a small sample size. Machine learning methods identified The macular regi on as the most active region.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligen ce have been presented. According to news originating from Hamad Bin Khalifa Uni versity by NewsRx editors, the research stated, “Stress recognition, particularl y using machine learning (ML) with physiological data such as heart rate variabi lity (HRV), holds promise for mental health interventions.” Funders for this research include Qatar National Research Fund. The news reporters obtained a quote from the research from Hamad Bin Khalifa Uni versity: “However, limited datasets in affective computing and healthcare resear ch can lead to inaccurate conclusions regarding the ML model performance. This s tudy employed supervised learning algorithms to classify stress and relaxation s tates using HRV measures. To account for limitations associated with small datas ets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, a nd model evaluation. Our findings highlight that the random forest model achieve d the best performance in distinguishing stress from non-stress states. Notably, it showed higher performance in identifying stress from relaxation (F1-score: 8 6.3%) compared to neutral states (F1-score: 65.8%).”
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 originating from Yongzhou, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Marble cement (MC) i s a new binding material for concrete, and the strength assessment of the result ing materials is the subject of this investigation.” Our news journalists obtained a quote from the research from Hunan University of Science and Engineering: “MC was tested in combination with rice husk ash (RHA) and fly ash (FA) to uncover its full potential. Machine learning (ML) algorithm s can help with the formulation of better MC-based concrete. ML models that coul d predict the compressive strength (CS) of MC-based concrete that contained FA a nd RHA were built. Gene expression programming (GEP) and multi-expression progra mming (MEP) were used to build these models. Additionally, models were evaluated by calculating R ~2 values, carrying out statistical tests, creating Taylor’s diagram, and comparin g theoretical and experimental readings. When comparing the MEP and GEP models, MEP yielded a slightly better-fitted model and better prediction performance (R ~2 = 0.96, mean absolute error = 0.646, root mean square error = 0.900, and Nash-S utcliffe efficiency = 0.960).”
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 food safety h ave been published. According to news reporting from Ogbomosho, Nigeria, by News Rx journalists, research stated, “Predictive microbiology is a rapidly evolving field that has gained significant interest over the years due to its diverse app lication in food safety. Predictive models are widely used in food microbiology to estimate the growth of microorganisms in food products.” The news editors obtained a quote from the research from Helix Biogen Institute: “These models represent the dynamic interactions between intrinsic and extrinsi c food factors as mathematical equations and then apply these data to predict sh elf life, spoilage, and microbial risk assessment. Due to their ability to predi ct the microbial risk, these tools are also integrated into hazard analysis crit ical control point (HACCP) protocols. However, like most new technologies, sever al limitations have been linked to their use. Predictive models have been found incapable of modeling the intricate microbial interactions in food colonized by different bacteria populations under dynamic environmental conditions. To addres s this issue, researchers are integrating several new technologies into predicti ve models to improve efficiency and accuracy. Increasingly, newer technologies s uch as whole genome sequencing (WGS), metagenomics, artificial intelligence, and machine learning are being rapidly adopted into newer-generation models.”
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. According to news originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “PurposeThe paper focuses on the iss ue of manual rebar-binding tasks in the construction industry, which are marked by high labor intensity, high costs and inefficient operations. The rebar-bindin g robots that are currently available are not fully mature.”
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