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    Studies from Guizhou Normal University in the Area of Machine Learning Reported (More Is Better? the Impact of Predictor Choice On the Ine Oil Futures Volatilit y Forecasting)

    77-77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 originating in Guizhou, Peop le's Republic of China, by NewsRx journalists, research stated, "This paper aims to address the predictor choice issue in forecasting volatility of INE oil futu res by a comprehensive comparative study with a large number of predictive varia bles and applying machine learning models along with their interpretability tool s. The main finding is that the selection of predictors is crucial for improving volatility forecasting accuracy, but it is not always the case that including m ore predictive variables leads to better forecasting results, even for machine l earning models." The news reporters obtained a quote from the research from Guizhou Normal Univer sity, "Specifically, this paper has five major findings: (1) A few variables can significantly improve forecasting accuracy independently, but their contributio n is limited. (2) Increasing the number of predictors from specific categories ( market sentiment indicators, crude oil futures prices from other exchanges, and energy market indicators) helps to enhance forecasting accuracy. (3) Lowfrequenc y variables have a weak effect on improving the daily volatility. (4) Ensemble t ree models perform better than traditional machine learning models based on vari able selection with dynamic parameter optimization, even without much parameter tuning. The above findings still hold true under a series of robustness tests an d economic value assessments."
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    Investigators at State University Londrina Describe Findings in Artificial Intel ligence (Datafication, Artificial Intelligence and Images: the Dominant Paradigm In the Representation of Knowledge In Images)

    78-78页
    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 from Londrina, Brazil, by N ewsRx journalists, research stated, "This paper aims to verify whether Generativ e Artificial Intelligence tools for image generation replicate biases and social stereotypes present in the dominant paradigm. A case study was carried out usin g the Leonardo.Ai tool, which generated images using simple combined terms, name ly: ‘Scientist, person'; ‘Cook, person'; ‘Doctor, person'; ‘CEO, person'; ‘House keeper, person'; and ‘Nurse, person." Financial support for this research came from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES). The news correspondents obtained a quote from the research from State University Londrina, "The images were analyzed using Rodrigues' (2007) image documentary a nalysis methodology and Gemma Penn's (2008) contributions. The analysis criteria included gender, age group, ethnicity, body type, clothes, and circumscribed el ements. The images generated by the Leonardo.Ai tool were found to have a series of characteristics that perpetuate bias and social stereotypes."
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    Researchers at State Key Laboratory Release New Data on Artificial Intelligence (Machine learning advancements in organic synthesis: A focused exploration of ar tificial intelligence applications in chemistry)

    79-79页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news reporting out of the State Key Laboratory b y NewsRx editors, research stated, "Artificial intelligence (AI) is driving a re volution in chemistry, reshaping the landscape of molecular design." Funders for this research include Science And Technology Commission of Shanghai Municipality; National Natural Science Foundation of China. Our news editors obtained a quote from the research from State Key Laboratory: " This review explores AI's pivotal roles in the field of organic synthesis applic ations. AI accurately predicts reaction outcomes, controls chemical selectivity, simplifies synthesis planning, accelerates catalyst discovery, and fuels materi al innovation and so on. It seamlessly integrates data-driven algorithms with ch emical intuition to redefine molecular design. As AI chemistry advances, it prom ises accelerated research, sustainability, and innovative solutions to chemistry 's pressing challenges. The fusion of AI and chemistry is poised to shape the fi eld's future profoundly, offering new horizons in precision and efficiency."
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    New Robotics Study Findings Recently Were Reported by Researchers at South China University of Technology (Tactile-sensingbased Robotic Grasping Stability Anal ysis)

    79-80页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news reporting from Guangzhou, People's Republic of China, by N ewsRx journalists, research stated, "Tactile signals play a crucial role in enab ling robots to successfully manipulate unfamiliar objects. For robots to grasp u nknown objects securely and without causing damage, it is essential that they ca n analyze grasping stability in real time through tactile signals and respond pr omptly." Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
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    Data from New Delhi Update Knowledge in Machine Learning (Development of machine learning models for estimation of daily evaporation and mean temperature: a cas e study in New Delhi, India)

    80-81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 originating from New Delhi, I ndia, by NewsRx correspondents, research stated, "ABSTRACT: Accurate prediction of pan evaporation and mean temperature is crucial for effective water resources management, influencing the hydrological cycle and impacting water availability ." The news reporters obtained a quote from the research from Division of Agricultu ral Engineering: "This study focused on New Delhi's semi-arid climate, data span ning 31 years (1990-2020) were used to predict these variables using advanced al gorithms such as Bagging, Random Subspace (RSS), M5P, and REPTree. The models we re rigorously evaluated using 10 performance metrics, including correlation coef ficient, mean absolute error (MAE), and Nash-Sutcliffe Efficiency (NSE) model co efficient. The Bagging model emerged as the best model with performance indices values as r, MAE, RMSE, RAE, RRSE, MBE NSE, d, KGE, and MAPE as 0.86, 0.76, 1.43 , 32.70, 49.44, 0.03, 0.85, 0.96, 0.90, and 22.0, respectively, during model tes ting phase for pan evaporation prediction. In predicting mean temperature, the B agging model reported the best results with performance indices values as r, MAE , RMSE, RAE, RRSE, MBE NSE, d, KGE, and MAPE as 0.86, 0.76, 1.43, 32.70, 49.44, 0.03, 0.85, 0.96, 0.90 and 22.0, respectively, during the model testing phase."
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    Department of Radiology Reports Findings in Artificial Intelligence (Automatic d etection of cognitive impairment in patients with white matter hyperintensity an d causal analysis of related factors using artificial intelligence of MRI)

    81-82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 Artificial Intelligenc e is the subject of a report. According to news reporting out of Chongqing, Peop le's Republic of China, by NewsRx editors, research stated, "White matter hyperi ntensity (WMH) is a common feature of brain aging, often linked with cognitive d ecline and dementia. This study aimed to employ deep learning and radiomics to d evelop models for detecting cognitive impairment in WMH patients and to analyze the causal relationships among cognitive impairment and related factors." Our news journalists obtained a quote from the research from the Department of R adiology, "A total of 79 WMH patients from hospital 1 were randomly divided into a training set (62 patients) and a testing set (17 patients). Additionally, 29 patients from hospital 2 were included as an independent testing set. All partic ipants underwent formal neuropsychological assessments to determine cognitive st atus. Automated identification and segmentation of WMH were conducted using VB-n et, with extraction of radiomics features from cortex, white matter, and nuclei. Four machine learning classifiers were trained on the training set and validate d on the testing set to detect cognitive impairment. Model performances were eva luated and compared. Causal analyses were conducted among cortex, white matter, nuclei alterations, and cognitive impairment. Among the models, the logistic reg ression (LR) model based on white matter features demonstrated the highest perfo rmance, achieving an AUC of 0.819 in the external test dataset. Causal analyses indicated that age, education level, alterations in cortex, white matter, and nu clei were causal factors of cognitive impairment. The LR model based on white ma tter features exhibited high accuracy in detecting cognitive impairment in WMH p atients."
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    New Robotics Study Findings Recently Were Reported by Researchers at Southeast U niversity (A Multi-directional Magneticdriven Multifunctional Soft Crawling Rob ot)

    82-83页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Robotics have been pr esented. According to news reporting originating from Nanjing, People's Republic of China, by NewsRx correspondents, research stated, "Multifunctional and multi -freedom integrated magnetic-driven soft robots have received widespread attenti on in the past decade. However, the current magnetic-driven soft crawling robots with multiple functional modules focus on the development of new materials or i nnovation of driving component." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from Southeast University, " Herein, we propose a soft crawling robot that materializes multi-directional mot ion driven only through a unidirectional magnetic field (MF) while possessing th e ability to communication, loading, and positioning. The locomotion of robot re lies on ingenious leg design to generate differences in friction between each le g and the ground by controlling the MF intensity. The integrated wireless commun ication modules on the robot ‘ s legs serve as a medium for interacting with the external world, enabling the robot to effectively perceive the environment via electromagnetic coupling. In addition, the magnetic-driven soft crawling robot c arries loads (3.37 g) larger than twice its own weight for motion."
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    Studies from Huazhong University of Science and Technology Reveal New Findings o n Robotics [Online Whole-stage Gait Planning Method for Biped Robots Based On Improved Variable Springloaded Inverted Pendulum With Finite-s ized Foot (Vslip-ff) ...]

    83-84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 Ro botics. According to news reporting originating from Wuhan, People's Republic of China, by NewsRx correspondents, research stated, "Environmental adaptability a nd real-time control are significant to the actual application of biped robots. The current Spring-Loaded Inverted Pendulum (SLIP) walking exhibits the complian t interaction with environments." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from the Huazhong University of Science and Technology, "However, the movability and controllability of this model is limited owing to the lack of ankles. Moreover, complicated nonlinear o ptimization problems in gait generation bring difficulties to real-time control. To overcome these problems, this study proposes an online wholestage gait plann ing method to enhance the bipedal walking performance. Firstly, considering the role of ankles, this study applies the proposed template model called Variable S pring-Loaded Inverted Pendulum with Finite-sized Foot (VSLIP-FF) model. Then a F inite State Machine (FSM)-based gait pattern including the corresponding bio-ins pired gait strategies is established, which extends the single cyclic gait to th e whole-stage gait. Secondly, to realize real-time gait planning, an online gait generator based on a neural network is applied to reduce the calculational burd en. Finally, the method is applied on the simulation prototype and real robot pl atform for verification."
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    Studies from School of Management Update Current Data on Artificial Intelligence (The Buffering Role of Workplace Mindfulness: How Job Insecurity of Human-artif icial Intelligence Collaboration Impacts Employees' Work-life-related Outcomes)

    84-85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 Artificial Intelligence are presented in a new report. According to news reporting from Heilongjiang, Pe ople's Republic of China, by NewsRx journalists, research stated, "Currently, em ployees are not being replaced by artificial intelligence (AI), but they are fac ing increasing pressure to adapt and master new AI-related skills-regardless of their attitude to AI collaboration. Drawing on the job demands-resources model ( JD-R) and Probst's (2002) framework, we explain how and when job insecurity rela ted to human-AI collaboration (HAI-C) influences employees' tech-learning anxiet y and subsequent work-life-related outcomes." Financial support for this research came from Natural Science Foundation of Heil ongjiang Province. The news correspondents obtained a quote from the research from the School of Ma nagement, "Additionally, we examine whether workplace mindfulness can mitigate t he negative effect of HAI-C job insecurity. We conducted an online experiment (s tudy 1: N = 226) and a three-wave lagged survey (study 2: N = 350) with Chinese employees who daily work with AI. Our results show that HAI-C job insecurity pos itively relates to HAI-C tech-learning anxiety and subsequently affects employee s' creative performance, informal field-based learning, well-being, and psycholo gical health. Workplace mindfulness played a crucial role in mitigating the nega tive effect of HAI-C job insecurity on tech-learning anxiety. Specifically, for employees with higher workplace mindfulness, the indirect effects of HAI-C job i nsecurity on work-life outcomes through tech-learning anxiety were weaker."
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    Patent Issued for Machine learning based automated pairing of individual custome rs and small businesses (USPTO 12001970)

    85-88页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting originatin g from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Al len, Morgan S. (Waxhaw, NC, US), Carroll, Matthew E. (Charlotte, NC, US), Kingst on, Tamara S. (Peoria, AZ, US), Sanghvi, Siten (Westfield, NJ, US), Shannon, Ste phen T. (Charlotte, NC, US), filed on September 27, 2023, was published online o n June 4, 2024. The assignee for this patent, patent number 12001970, is Bank of America Corpora tion (Charlotte, North Carolina, United States). Reporters obtained the following quote from the background information supplied by the inventors: "Aspects of the disclosure relate to deploying machine learnin g systems to predict customer needs. In particular, one or more aspects of the d isclosure relate to machine learning based automated pairing of customers and bu sinesses. "Enterprise organizations may utilize various computing infrastructure to provid e services to their customers. Customers of the enterprise organization may incl ude individuals and businesses. In some instances, a customer may make a purchas e, and there may be business customers that have offerings that may be beneficia l to a customer. Detecting a pattern of purchase activity for customers, and mat ching them to appropriate business customers, may be of high significance to an enterprise organization. In many instances, however, it may be difficult to ensu re detection of such need, and connecting customers and businesses, while also a ttempting to optimize the resource utilization, bandwidth utilization, and effic ient operations of the computing infrastructure involved in maintaining, accessi ng, and executing such purchase activities."
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