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 originating from Maribor, Slo venia, by NewsRx correspondents, research stated, “Artificial intelligence (AI) has witnessed an exponential increase in use in various applications.” Our news journalists obtained a quote from the research from University of Marib or: “Recently, the academic community started to research and inject new AI-base d approaches to provide solutions to traditional software-engineering problems. However, a comprehensive and holistic understanding of the current status needs to be included. To close the above gap, synthetic knowledge synthesis was used t o induce the research landscape of the contemporary research literature on the u se of AI in software engineering. The synthesis resulted in 15 research categori es and 5 themes-namely, natural language processing in software engineering, use of artificial intelligence in the management of the software development life c ycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code managem ent, and mining software repositories to improve software quality. The most prod uctive country was China (n = 2042), followed by the United States (n = 1193), I ndia (n = 934), Germany (n = 445), and Canada (n = 381).”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Robotics are discussed in a new report. According to news originating from Urumqi, People’s Republic of Chin a, by NewsRx correspondents, research stated, “The localization of odor sources (e.g., poisonous odor sources) is an important task for the security of the envi ronment and human society. Traditional robot localization methods are sensitive to environmental changes, leading to localization performance degradation in dyn amic environments and complex scenes.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Xinjiang Uygur Autonomous Regi on.
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 Aurora, Colorado, by N ewsRx editors, research stated, “Investigate the use of advanced natural languag e processing models to streamline the time-consuming process of writing and revi sing scholarly manuscripts.” Financial supporters for this research include National Human Genome Research In stitute. The news editors obtained a quote from the research from University of Colorado School of Medicine: “For this purpose, we integrate large language models into t he Manubot publishing ecosystem to suggest revisions for scholarly texts. Our AI -based revision workflow employs a prompt generator that incorporates manuscript metadata into templates, generating section-specific instructions for the langu age model. The model then generates revised versions of each paragraph for human authors to review. We evaluated this methodology through 5 case studies of exis ting manuscripts, including the revision of this manuscript. Our results indicat e that these models, despite some limitations, can grasp complex academic concep ts and enhance text quality. All changes to the manuscript are tracked using a v ersion control system, ensuring transparency in distinguishing between human- an d machine-generated text.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Artificial Intelligence. According to news reporting originating in Washington, District of Columbia, by NewsRx journalists, research stated, “Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and he alth care systems are even developing their own AI models, both within and outsi de of electronic health record (EHR) systems.” The news reporters obtained a quote from the research from the American College of Physicians, “These technologies have various applications throughout the prov ision of health care, such as clinical documentation, diagnostic image processin g, and clinical decision support. With the growing availability of vast amounts of patient data and unprecedented levels of clinician burnout, the proliferation of these technologies is cautiously welcomed by some physicians. Others think i t presents challenges to the patientphysician relationship and the professional integrity of physicians. These dispositions are understandable, given the ‘blac k box’ nature of some AI models, for which specifications and development method s can be closely guarded or proprietary, along with the relative lagging or abse nce of appropriate regulatory scrutiny and validation. This American College of Physicians (ACP) position paper describes the College’s foundational positions a nd recommendations regarding the use of AI- and ML-enabled tools and systems in the provision of health care. Many of the College’s positions and recommendation s, such as those related to patient-centeredness, privacy, and transparency, are founded on principles in the ACP Ethics Manual. They are also derived from cons iderations for the clinical safety and effectiveness of the tools as well as the ir potential consequences regarding health disparities.”
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 out of Amsterdam, Netherland s, by NewsRx editors, research stated, “Pleural plaques (PPs) are morphologic ma nifestations of long-term asbestos exposure. The relationship between PP and lun g function is not well understood, whereas the time-consuming nature of PP delin eation to obtain volume impedes research.” Our news journalists obtained a quote from the research from Netherlands Cancer Institute, “To automate the laborious task of delineation, we aimed to develop a utomatic artificial intelligence (AI)-driven segmentation of PP. Moreover, we ai med to explore the relationship between pleural plaque volume (PPV) and pulmonar y function tests. Radiologists manually delineated PPs retrospectively in comput ed tomography (CT) images of patients with occupational exposure to asbestos (Ma y 2014 to November 2019). We trained an AI model with a no-new-UNet architecture . The Dice Similarity Coefficient quantified the overlap between AI and radiolog ists. The Spearman correlation coefficient (r) was used for the correlation betw een PPV and pulmonary function test metrics. When recorded, these were vital cap acity (VC), forced vital capacity (FVC), and diffusing capacity for carbon monox ide (DLCO). We trained the AI system on 422 CT scans in 5 folds, each time with a different fold (n = 84 to 85) as a test set. On these independent test sets co mbined, the correlation between the predicted volumes and the ground truth was r = 0.90, and the median overlap was 0.71 Dice Similarity Coefficient. We found w eak to moderate correlations with PPV for VC (n = 80, r = -0.40) and FVC (n = 82 , r = -0.38), but no correlation for DLCO (n = 84, r = -0.09). When the cohort w as split on the median PPV, we observed statistically significantly lower VC (P = 0.001) and FVC (P = 0.04) values for the higher PPV patients, but not for DLCO (P = 0.19). We successfully developed an AI algorithm to automatically segment PP in CT images to enable fast volume extraction.”
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 out of University Park, Pennsylvania , by NewsRx editors, research stated, “Gamma-ray spectroscopy is an essential to ol in nuclear science, nuclear security, and environmental monitoring. However, challenges arise in interpreting spectral data due to the presence of low counts , multiple sources, and dynamic backgrounds.” Financial supporters for this research include Defense Threat Reduction Agency ( DTRA) as part of the Interaction of Ionizing Radiation, Matter University Resear ch Alliance (IIRM-URA). Our news journalists obtained a quote from the research from Pennsylvania State University (Penn State), “To address these issues, a novel feature-driven analyt ical approach for gamma-ray spectral analysis using machine-learning techniques is developed. The method utilizes a series of random forest models for in-distri bution (ID) multi-label classification, and the model-derived feature importance values to guide the out-of-distribution (OOD) detection task. The performance o f this approach is quantitatively evaluated across various spectral parameters, including acquisition time, number of sources, energy of an OOD source, and back ground composition. Increasing the acquisition time from 1 s to 100 s leads to i mproved performance for multi-label classification, with 22 sources achieving F1 -scores >= 0.9 after 50 s acquisitions for a CLLBC handh eld detector and a standoff distance of 30 cm. The feature-driven analytical app roach also demonstrates robustness when handling complex source mixtures. Furthe rmore, it provides contextual energetic information for OOD detection. The resul ts presented here highlight the interpretability of the approach, establishing c lear links between the spectral features and underlying physics. Moreover, the a pproach effectively distinguishes overlapping spectral signatures of different I D gamma-ray sources, enhancing human reliability in machine learning-based gamma -ray spectral analysis.”
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 Chiba, Japan, by NewsRx correspondents, research stated, “Indoor position fingerprintbased locat ion estimation methods have been widely used by applications on smartphones.” Our news journalists obtained a quote from the research from Chiba University: “ In these localization estimation methods, it is very popular to use the RSSI (Re ceived Signal Strength Indication) of signals to represent the position fingerpr int. This paper proposes the design of a particle filter for reducing the estima tion error of the machine learning-based indoor BLE location fingerprinting meth od. Unlike the general particle filter, taking into account the distance, the pr oposed system designs improved likelihood functions, considering the coordinates based on fingerprint points using mean and variance of RSSI values, combining t he particle filter with the k-NN (k-Nearest Neighbor) algorithm to realize the r eduction in indoor positioning error.”
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 robotics have bee n published. According to news reporting from Shanghai, People’s Republic of Chi na, by NewsRx journalists, research stated, “This paper presents a hybrid adapti ve control strategy for upper limb rehabilitation robots using impedance learnin g.” Funders for this research include National Natural Science Foundation of China. Our news correspondents obtained a quote from the research from Donghua Universi ty: “The hybrid adaptation consists of a differential updating mechanism for the estimation of robotic modeling uncertainties and periodic adaptations for the o nline learning of time-varying impedance. The proposed hybrid adaptive controlle r guarantees asymptotical control stability and achieves variable impedance regu lation for robots without interaction force measurements. According to Lyapunov’ s theory, we proved that the proposed impedance learning controller guarantees t he convergence of tracking errors and ensures the boundedness of the estimation errors of robotic uncertainties and impedance profiles.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on artificial intelligence is the su bject of a new report. According to news reporting from Urumqi, People’s Republi c of China, by NewsRx journalists, research stated, “Accurate estimation of surf ace evapotranspiration (ET) in the Heihe River Basin using remote sensing data i s crucial for understanding water dynamics in arid regions. In this paper, by co upling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization.”Financial supporters for this research include National Natural Science Foundati on of China; China Postdoctoral Science Foundation; Technology Innovation Team ( Tianshan Innovation Team), Innovative Team For Efficient Utilization of Water Re sources in Arid Regions.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on robotics is now available. Accordi ng to news originating from Yiyang, People’s Republic of China, by NewsRx corres pondents, research stated, “The development of intelligent robot has always been an important research direction in the field of artificial intelligence, and th e object detection of robot is the basis of intelligent perception and autonomou s action.” Financial supporters for this research include Social Contribution of Hunan Scie nce And Technology Innovation Plan, Engineering Research And Application of Auto matic Knotting Equipment For Bamboo Mat Based on Biomimetic Dexterous Hands.
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