查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on robotics are disc ussed in a new report. According to news reporting from Obuda University by News Rx journalists, research stated, “Recent advancements in mechatronics and roboti cs have led to the emergence of a wide range of technologies with potential appl ications across various industries.” The news reporters obtained a quote from the research from Obuda University: “Th is progress has been observed in recent years and is expected to continue as the integration of robots into daily life becomes more widespread. Despite these de velopments, deploying robots in industrial environments, particularly in assembl y operations, still presents several challenges, including effectively distribut ing skills-based tasks between human and robotic workers. This paper proposes an approach to improve the performance of mobile robot systems for optimal path pl anning. The technique utilizes motion capture technology to collect real-time da ta on the robot’s movements, generate optimal path planning strategies, and enab le remote control and monitoring of the robot’s activities. The proposed approac h can significantly enhance mobile robot systems’ capabilities in various indust rial settings. The results of our study demonstrate that the integration of moti on capture technology can substantially improve the accuracy and efficiency of p ath planning in mobile robot systems and enhance their overall performance.”
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 originating from Shanghai, People’s Rep ublic of China, by NewsRx correspondents, research stated, “A machine learning-b ased alloy rapid design system (ARDS) was proposed to customize the preparation strategies for the desired properties or predict the alloy properties following the preparation strategies. For achieving this, three regression algorithms: lin ear regression (LR), support vector regression (SVR), and back propagation neura l network (BPNN), were employed separately to train the multi-property predictio n model, in which the machine learning (ML) model built using SVR was proved to be the best.” Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC).
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 originating in Helsinki, Finl and, by NewsRx journalists, research stated, “Block copolymers, composed of poly (2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they fo rm micelles that carry poorly water-soluble drugs. Many recent studies have inve stigated the effects of structural changes of the polymer and the hydrophobic ca rgo on drug loading.” The news reporters obtained a quote from the research from the University of Hel sinki, “In this work, we combine these data to establish an extended formulation database. Different molecular properties and fingerprints are tested for their applicability to serve as formulation-specific mixture descriptors. A variety of classification and regression models are built for different descriptor subsets and thresholds of loading efficiency and loading capacity, with the best models achieving overall good statistics for both cross- and external validation (bala nced accuracies of 0.8). Subsequently, important features are dissected for inte rpretation, and the DrugBank is screened for potential therapeutic use cases whe re these polymers could be used to develop novel formulations of hydrophobic dru gs.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from Montclair State University by N ewsRx editors, the research stated, “The American healthcare system allocates co nsiderable resources compared to peer-developed nations.” The news correspondents obtained a quote from the research from Montclair State University: “However, outcomes significantly trail behind, particularly in life expectancy. This study addresses questions about the enduring trends in healthca re spending as a percentage of Gross Domestic Product (GDP), notable factors con tributing to this concerning trend, and the timing to apply an emergency brake t o curb this accelerating trajectory. Advanced machine learning algorithms, such as Random Forest and Support Vector Regression (SVR), in conjunction with tradit ional statistical forecasting methods, are used to forecast future patterns. The research underscores the importance of healthcare analytics in unraveling the i ntricacies of the healthcare system.”
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 Lincoln, Nebraska , by NewsRx editors, the research stated, “Advancements in imaging, computer vis ion, and automation have revolutionized various fields, including field-based hi gh-throughput plant phenotyping (FHTPP).” Financial supporters for this research include United States Department of Agric ulture. Our news correspondents obtained a quote from the research from University of Ne braska-Lincoln: “This integration allows for the rapid and accurate measurement of plant traits. Deep Convolutional Neural Networks (DCNNs) have emerged as a po werful tool in FHTPP, particularly in crop segmentationidentifying crops from t he background-crucial for trait analysis. However, the effectiveness of DCNNs of ten hinges on the availability of large, labeled datasets, which poses a challen ge due to the high cost of labeling. In this study, a deep learning with bagging approach is introduced to enhance crop segmentation using high-resolution RGB i mages, tested on the NU-Spidercam dataset from maize plots. The proposed method outperforms traditional machine learning and deep learning models in prediction accuracy and speed. Remarkably, it achieves up to 40% higher Inter section-over-Union (IoU) than the threshold method and 11% over co nventional machine learning, with significantly faster prediction times and mana geable training duration.”
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 originating in Sesto Fiorenti no, Italy, by NewsRx journalists, research stated, “Understanding the fine struc tural details of inhibitor binding at the active site of metalloenzymes can have a profound impact on the rational drug design targeted to this broad class of b iomolecules. Structural techniques such as NMR, cryo-EM, and X-ray crystallograp hy can provide bond lengths and angles, but the uncertainties in these measureme nts can be as large as the range of values that have been observed for these qua ntities in all the published structures.” The news reporters obtained a quote from the research from the University of Flo rence, “This uncertainty is far too large to allow for reliable calculations at the quantum chemical (QC) levels for developing precise structure-activity relat ionships or for improving the energetic considerations in protein-inhibitor stud ies. Therefore, the need arises to rely upon computational methods to refine the active site structures well beyond the resolution obtained with routine applica tion of structural methods. In a recent paper, we have shown that it is possible to refine the active site of cobalt(II)-substituted MMP12, a metalloprotein tha t is a relevant drug target, by matching to the experimental pseudocontact shift s (PCS) those calculated using multireference ab initio QC methods. The computat ional cost of this methodology becomes a significant bottleneck when the startin g structure is not sufficiently close to the final one, which is often the case with biomolecular structures. To tackle this problem, we have developed an appro ach based on a neural network (NN) and a support vector regression (SVR) and app lied it to the refinement of the active site structure of oxalate-inhibited huma n carbonic anhydrase 2 (hCAII), another prototypical metalloprotein target. The refined structure gives a remarkably good agreement between the QC-calculated an d the experimental PCS.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Neoplasms. According to news reporting originating from New York City, New York, by NewsRx correspondents, research stated, “Multiparameter flow cytometry data is visually inspected by expert personnel as part of standard clinical disease diagnosis pr actice. This is a demanding and costly process, and recent research has demonstr ated that it is possible to utilize artificial intelligence (AI) algorithms to a ssist in the interpretive process.” Funders for this research include Department of Pathology and Laboratory Medicin e at Weill Cornell Medicine, Cornell University, National Institutes of Health ( NIH) - USA.
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 originating from Amsterdam, Netherla nds, by NewsRx correspondents, research stated, “Fluidic circuits are a promisin g recent development in embodied control of soft robots. These circuits typicall y make use of highly non-linear soft components to enable complex behaviors give n simple inputs, such as constant flow or pressure.” Financial support for this research came from European Union (EU).
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 originating from Skikda, Alge ria, by NewsRx correspondents, research stated, “Epilepsy is a brain disorder th at causes patients to suffer from convulsions, which affects their behavior and way of life. Epilepsy can be detected with electroencephalograms (EEGs), which r ecord brain neural activity.” Our news editors obtained a quote from the research, “Traditional approaches for detecting epileptic seizures from an EEG signal are time-consuming and annoying . To supersede these traditional methods, a myriad of automated seizure detectio n frameworks based on machine learning techniques have recently been developed. Feature extraction and classification are the two essential phases for seizure d etection. The classifier assigns the proper class label after feature extraction lowers the input pattern space while maintaining useful features. This paper pr oposes a new feature extraction method based on calculating nonlinear features f rom the most relevant EEG frequency bands. The EEG signal is first decomposed in to smaller time segments from which a vector of nonlinear features is computed a nd supplied to machine learning (ML) and deep learning (DL) classifiers. Experim ents on the Bonn dataset reveals an accuracy of 99.7% reached in c lassifying normal and ictal EEG signals; and an accuracy of 98.8% in the discrimination of ictal and interictal EEG signals. Furthermore, a perfor mance of 100% is achieved on the Hauz Khas dataset. The classifica tion results of the proposed approach were compared to those from published stat e of the art techniques.”
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 originating from Anhui, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “The number of bits required in phase shifters (PS) in hybrid precoding (HP) has a significa nt impact on sum-rate, spectral efficiency (SE), and energy efficiency (EE). The space and cost constraints of a realistic massive multiple-input multiple-outpu t (MIMO) system limit the number of antennas at the base station (BS), limiting the throughput gain promised by theoretical analysis.” Funders for this research include Fundamental Research Funds for the Central Uni versities, National Natural Science Foundation of China (NSFC).
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