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    School of Mathematics Researchers Update Knowledge of Intelligence Technology (Feature extraction and learning approaches for cancellable biometrics: A survey)

    20-21页
    查看更多>>摘要：Investigators discuss new findings in intelligence technology. According to news re-porting from the School of Mathematics by NewsRx journalists, research stated, "Biometric recognition is a widely used technology for user authentication." Funders for this research include Australian Research Council. Our news correspondents obtained a quote from the research from School of Mathematics: "In the application of this technology, biometric security and recognition accuracy are two important issues that should be considered. In terms of biometric security, cancellable biometrics is an effective technique for protecting biometric data. Regarding recognition accuracy, feature representation plays a significant role in the performance and reliability of cancellable biometric systems. How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community, especially from researchers of cancellable biometrics. Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance, while the privacy of biometric data is protected."
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Data from Curtin University Advance Knowledge in Artificial Intelligence (Professionalism In Artificial Intelligence: the Link Between Technology and Ethics)

    21-22页
    查看更多>>摘要：Research findings on Artificial Intelligence are discussed in a new report. According to news reporting originating from Bentley, Australia, by NewsRx correspondents, research stated, "Ethical conduct of artificial intelligence (AI) is undoubtedly becoming an ever more pressing issue considering the inevitable integration of these technologies into our lives." Our news editors obtained a quote from the research from Curtin University, "The literature so far discussed the responsibility domains of AI; this study asks the question of how to instil ethicality into AI technologies. Through a three-step review of the AI ethics literature, we find that (i) the literature is weak in identifying solutions in ensuring ethical conduct of AI, (ⅱ) the role of professional conduct is underexplored, and (ⅲ) based on the values extracted from studies about AI ethical breaches, we thus propose a conceptual framework that offers professionalism as a solution in ensuring ethical AI."
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Study Findings from University of North Dakota Broaden Understanding of Machine Learning [Quantifying the Effects of Pressure Management for the Williston Basin Brine Extraction and Storage Test (Best) Site Using Machine Learning]

    22-23页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting out of Grand Forks, North Dakota, by NewsRx editors, research stated, "Active reservoir management (ARM) through brine extraction can reduce pressure buildup during large-scale implementation of carbon capture and storage (CCS) projects. This study used machine learning (ML)-assisted approaches to analyze bottomhole pressure (BHP) responses to various brine injection and extraction scenarios." Financial support for this research came from DOE's Office of Fossil Energy's Carbon Storage Research Program through the National Energy Technology Laboratory (NETL). Our news journalists obtained a quote from the research from the University of North Dakota, "Field monitoring data were collected over a 2-year operation period at two injection wells and one extraction well (about 400 m away) as part of a Brine Extraction and Storage Test (BEST) in the North Dakota portion of the Williston Basin. Injection activities increased the BHPs at the injection wells by around 0.70 MPa (similar to 100 psi) during the operation period. Extraction activities demonstrated the capability to decrease the BHPs at the injection wells by approximately 0.21-0.34 MPa (30-50 psi) depending on the ratio of the extraction and injection well flow rates (the " extraction ratio " - a normalization procedure used in the analysis). The pressure reduction provided by the extraction well equated to 30-50 % of the pressure buildup at the injection well."
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    New Findings on Robotics Described by Investigators at Maulana Azad National Institute of Technology (A Physics-based Failure Study of Smart Artificial Tissues In Human-like Soft Robots)

    23-24页
    查看更多>>摘要：A new study on Robotics is now available. According to news originating from Madhya Pradesh, India, by NewsRx correspondents, research stated, "Artificial tissues made of fiber-reinforced elastomers typically have mechanical properties similar to biological tissues. Such a similarity motivates artificial tissue usage in building human-like soft robots aiming primarily to perform a wide range of humanlike motions and effectively interact with the human environment." Our news journalists obtained a quote from the research from the Maulana Azad National Institute of Technology, "Soft robots can be ripped or damaged for unknown reasons in a variety of applications. The literature has no unified stress-based criterion for predicting the critical zones of artificial tissues undergoing deformations. Such a unified stress-based criterion typically entails detecting internal damage and establishing the stress limit criterion based on the maximum stretching threshold. The current study establishes an experimentally validated rupture criterion for a novel class of smart artificial tissues made of electro-active polymers motivated by biological tissue damages in several robust conditions. A thermodynamically consistent mechanoelectrical deformation model is formulated, demonstrating that such tissues have inherent anisotropy that must be taken into account when modeling such materials. Later, a continuum physics-based rupture model is derived as a unified stress-based criterion to investigate the effect of physical parameters associated with artificial tissue failure."
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Research from University of Lausanne Yields New Findings on Machine Learning (Climate-invariant machine learning)

    24-25页
    查看更多>>摘要：New research on artificial intelligence is the subject of a new report. According to news reporting out of Lausanne, Switzerland, by NewsRx editors, research stated, "Projecting climate change is a generalization problem: We extrapolate the recent past using physical models across past, present, and future climates." Our news correspondents obtained a quote from the research from University of Lausanne: "Current climate models require representations of processes that occur at scales smaller than model grid size, which have been the main source of model projection uncertainty. Recent machine learning (ML) algorithms hold promise to improve such process representations but tend to extrapolate poorly to climate regimes that they were not trained on." According to the news reporters, the research concluded: "To get the best of the physical and statistical worlds, we propose a framework, termed "climate-invariant" ML, incorporating knowledge of climate processes into ML algorithms, and show that it can maintain high offline accuracy across a wide range of climate conditions and configurations in three distinct atmospheric models. Our results suggest that explicitly incorporating physical knowledge into data-driven models of Earth system processes can improve their consistency, data efficiency, and generalizability across climate regimes."
      原文链接:
    • NETL
    • NSTL

    Investigators from Indian Institute of Science Zero in on Robotics and Automation (Funnel-based Reward Shaping for Signal Temporal Logic Tasks In Reinforcement Learning)

    25-25页
    查看更多>>摘要：Research findings on Robotics - Robotics and Automation are discussed in a new report. According to news reporting from Bangalore, India, by NewsRx journalists, research stated, "Signal Temporal Logic (STL) is a powerful framework for describing the complex temporal and logical behaviour of the dynamical system." Financial support for this research came from Google and SERB Research Grants. The news correspondents obtained a quote from the research from the Indian Institute of Science, "Numerous studies have attempted to employ reinforcement learning to learn a controller that enforces STL specifications; however, they have been unable to effectively tackle the challenges of ensuring robust satisfaction in continuous state space and maintaining tractability. In this letter, leveraging the concept of funnel functions, we propose a tractable reinforcement learning algorithm to learn a time-dependent policy for robust satisfaction of STL specification in continuous state space." According to the news reporters, the research concluded: "We demonstrate the utility of our approach on several STL tasks using different environments." This research has been peer-reviewed.
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Shanghai Jiao Tong University Reports Findings in Dementia (Identifying Leukoaraiosis with Mild Cognitive Impairment by Fusing Multiple MRI Morphological Metrics and Ensemble Machine Learning)

    26-26页
    查看更多>>摘要：New research on Neurodegenerative Diseases and Conditions - Dementia is the subject of a report. According to news reporting out of Shanghai, People's Republic of China, by NewsRx editors, research stated, "Leukoaraiosis (LA) is strongly associated with impaired cognition and increased dementia risk. Determining effective and robust methods of identifying LA patients with mild cognitive impairment (LA-MCI) is important for clinical intervention and disease monitoring." Our news journalists obtained a quote from the research from Shanghai Jiao Tong University, "In this study, an ensemble learning method that combines multiple magnetic resonance imaging (MRI) morphological features is proposed to distinguish LA-MCI patients from LA patients lacking cognitive impairment (LA-nCI). Multiple comprehensive morphological measures (including gray matter volume (GMV), cortical thickness (CT), surface area (SA), cortical volume (CV), sulcus depth (SD), fractal dimension (FD), and gyrification index (GI)) are extracted from MRI to enrich model training on disease characterization information. Then, based on the general extreme gradient boosting (XGBoost) classifier, we leverage a weighted soft-voting ensemble framework to ensemble a data-level resampling method (Fusion + XGBoost) and an algorithm-level focal loss (FL)-improved XGBoost model (FL-XGBoost) to overcome class-imbalance learning problems and provide superior classification performance and stability. The baseline XGBoost model trained on an original imbalanced dataset had a balanced accuracy (Bacc) of 78.20%. The separate Fusion + XGBoost and FL-XGBoost models achieved Bacc scores of 80.53 and 81.25%, respectively, which are clear improvements (i.e., 2.33% and 3.05%, respectively). The fused model distinguishes LA-MCI from LA-nCI with an overall accuracy of 84.82%. Sensitivity and specificity were also well improved (85.50 and 84.14%, respectively)."
      原文链接:
    • NETL
    • NSTL

    Investigators from Sichuan University Zero in on Helicobacter pylori (Handling Noisy Labels Via One-step Abductive Multi-target Learning and Its Application To Helicobacter Pylori Segmentation)

    27-28页
    查看更多>>摘要：Data detailed on Gram-Negative Bacteria - Helicobacter pylori have been presented. According to news reporting from Chengdu, People's Republic of China, by NewsRx journalists, research stated, "Learning from noisy labels is an important concern in plenty of real-world scenarios. Various approaches for this concern first make corrections corresponding to potentially noisy-labeled instances, and then update predictive model with information of the made corrections." Financial supporters for this research include Sichuan Science and Technology Program, The 1<middle dot>3<middle dot>5 project for disciplines of excellence Clinical Research Incubation Project, West China Hospital, Sichuan University, China, The 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University, China, Technological Innovation Project of Chengdu New Industrial Technology Research Institute.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Ohio State University Wexner Medical Center Reports Findings in Artificial Intelligence (Online artificial intelligence platforms and their applicability to gastrointestinal surgical operations)

    28-29页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating from Columbus, Ohio, by NewsRx correspondents, research stated, "The internet is a common source of health information for patients. Interactive online artificial intelligence (AI) may be a more reliable source of health-related information than traditional search engines." Our news editors obtained a quote from the research from Ohio State University Wexner Medical Center, "This study aimed to assess the quality and perceived utility of chat-based AI responses related to 3 common gastrointestinal (GI) surgical procedures. A survey of 24 questions covering general perioperative information on cholecystectomy, pancreaticoduodenectomy (PD), and colectomy was created. Each question was posed to Chat Generative Pre-trained Transformer (ChatGPT) in June 2023, and the generated responses were recorded. The quality and perceived utility of responses were independently and subjectively graded by expert respondents specific to each surgical field. Grades were classified as 'poor,' 'fair,' 'good,' 'very good,' or 'excellent.' Among the 45 respondents (general surgeon [n = 13], surgical oncologist [n = 18], colorectal surgeon [n = 13], and transplant surgeon [n = 1]), most practiced at an academic facility (95.6%). Respondents had been in practice for a mean of 12.3 years (general surgeon, 14.5 ± 7.2; surgical oncologist, 12.1 ± 8.2; colorectal surgeon, 10.2 ± 8.0) and performed a mean 53 index operations annually (cholecystectomy, 47 ± 28; PD, 28 ± 27; colectomy, 81 ± 44). Overall, the most commonly assigned quality grade was 'fair' or 'good' for most responses (n = 622/1080, 57.6%). Most of the 1080 total utility grades were 'fair' (n = 279, 25.8%) or 'good' (n = 344, 31.9%), whereas only 129 utility grades (11.9%) were 'poor.' Of note, ChatGPT responses related to cholecystectomy (45.3% ['very good'/'excellent'] vs 18.1% ['poor'/'fair']) were deemed to be better quality than AI responses about PD (18.9% ['very good'/'excellent'] vs 46.9% ['poor'/'fair']) or colectomy (31.4% ['very good'/'excellent'] vs 38.3% ['poor'/'fair']). Overall, only 20.0% of the experts deemed ChatGPT to be an accurate source of information, whereas 15.6% of the experts found it unreliable. Moreover, 1 in 3 surgeons deemed ChatGPT responses as not likely to reduce patient-physician correspondence (31.1%) or not comparable to in-person surgeon responses (35.6%). Although a potential resource for patient education, ChatGPT responses to common GI perioperative questions were deemed to be of only modest quality and utility to patients."
      原文链接:
    • NETL
    • NSTL

    Studies from Tulane University Yield New Information about Artificial Intelligence (Artificial Intelligence for the Practical Assessment of Nutritional Status In Emergencies)

    29-30页
    查看更多>>摘要：Investigators publish new report on Artificial Intelligence. According to news reporting originating from New Orleans, Louisiana, by NewsRx correspondents, research stated, "This paper describes a novel method for detecting child malnutrition based on artificial intelligence and facial photography. Estimates of severe and moderate acute malnutrition in children are critical for rapid emergency responses." Financial support for this research came from UNICEF. Our news editors obtained a quote from the research from Tulane University, "However, the two traditional measurement methods, mid-upper arm circumference (MUAC) and weight-for-height (WFH), are impractical in conflict and catastrophic disaster situations. They require well-trained enumerators, cumbersome equipment, and close supervision. The Method for Extremely Rapid Observation of Nutritional Status (MERON) addresses the problem, using simple facial photographs. Facial features are extracted to predict Body Mass Index (BMI) in adults and Weight for Height Z Score (WFHZ) in children under five. MERON correctly predicts adult BMI classification with 78% accuracy. A variant of the model, trained on a sample of 3167 children in Kenya, successfully classified 60% of cases. On most measures, MERON was easier and more culturally acceptable to use than the traditional measurement methods."
      原文链接:
    • NETL
    • NSTL
    • Wiley