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    Civil Aviation Flight University of China Details Findings in Machine Learning ( Airspace Situation Analysis of Terminal Area Traffic Flow Prediction Based On Bi g Data and Machine Learning Methods)

    99-99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 Ma chine Learning. According to news reporting originating in Guanghan, People's Re public of China, by NewsRx journalists, research stated, "Realtime and accurate prediction of terminal area arrival traffic flow is a key issue for terminal ar ea traffic management. In this paper, we study the advantages and disadvantages of traditional dynamics -based prediction methods and time -series based predict ion methods in the first step." Financial supporters for this research include Civil Aviation Flight University of China Fund Project, Civil Aviation Education Fund Project, Sichuan Province F und Project. The news reporters obtained a quote from the research from the Civil Aviation Fl ight University of China, "Taking the advantages of the two type of methods, a t erminal area arrival flow prediction framework based on airspace situation is pr oposed. In our method, the airspace situation is used as the machine learning fe ature to estimate the number of arrival aircraft. In addition, also based on mac hine learning approach, a correction stage is added to the algorithm to improve the accuracy of the prediction. ADS -B data collected from the terminal area of Chengdu is used to study the prediction accuracy based on different machine lear ning algorithms in the proposed framework. Experimental results show that the pr oposed method can predict the air traffic flow accurately. The average absolute error is only 0.35 aircraft/15 min, the root mean square error is 0.67 aircraft/ 15 min, and the maximum absolute error is 2 aircraft/15 min."
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    Study Data from China University of Petroleum Provide New Insights into Machine Learning (Application of Heterogeneous Ensemble Learning for Co2-brine Interfaci al Tension Prediction: Implications for Co2 Storage)

    100-100页
    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 out of Beijing, People's Re public of China, by NewsRx editors, research stated, "Carbon capture, utilizatio n, and storage (CCUS) is a green engineering technology to reduce CO2 emissions and mitigate climate warming. It is crucial to accurately predict the CO2-brine interfacial tension (IFT) in order to evaluate the carbon storage capacity of sa line aquifers." Our news journalists obtained a quote from the research from the China Universit y of Petroleum, "Traditional experimental methods are time-consuming and costly. The existing empirical correlation methods of IFT have been found to be inaccur ate. Instead, machine learning (ML) methods have a superior ability to predict I FT. However, the existing machine learning methods lack an in-depth examination of the main factors influencing IFT, as well as the simultaneous improvement str ategy of accuracy and time cost and further reliability verification. In this pa per, we first propose a heterogeneous ensemble learning IFT prediction model bas ed on XGBoost and LightGBM. The new model is simultaneously optimized in terms o f both accuracy and time cost. Our proposed model has been proven to be the most accurate and time-efficient through several comparative studies. The variable t rend analysis, the leverage method, and Shapley values (SV) are also used to inv estigate the effectiveness and interpretability of the model. The density differ ences parameter is used for the first time as an input parameter in the model wh ich is found to be an appropriate parameter. A potential law between temperature and IFT can also be derived from the new model."
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    Data on Artificial Intelligence Reported by Ilaria Baiardini and Colleagues (Exp lainable artificial intelligence for cough-related quality of life impairment pr ediction in asthmatic patients)

    101-101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 Genoa, Italy, b y NewsRx editors, research stated, "Explainable Artificial Intelligence (XAI) is becoming a disruptive trend in healthcare, allowing for transparency and interp retability of autonomous decision-making. In this study, we present an innovativ e application of a rule-based classification model to identify the main causes o f chronic cough-related quality of life (QoL) impairment in a cohort of asthmati c patients." Funders for this research include Universita degli Studi di Genova, Ministero de ll'Istruzione, dell'Universita e della Ricerca. Our news journalists obtained a quote from the research, "The proposed approach first involves the design of a suitable symptoms questionnaire and the subsequen t analyses via XAI. Specifically, feature ranking, derived from statistically va lidated decision rules, helped in automatically identifying the main factors inf luencing an impaired QoL: pharynx/larynx and upper airways when asthma is under control, and asthma itself and digestive trait when asthma is not controlled. Mo reover, the obtained if-then rules identified specific thresholds on the symptom s associated to the impaired QoL."
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    New Findings in Robotics Described from Tongji University (An Iterative Path Com pensation Method for Double-sided Robotic Roller Forming of Compact Thin-walled Profiles)

    102-102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 Robotics is the subjec t of a report. According to news originating from Shanghai, People's Republic of China, by NewsRx correspondents, research stated, "High-precision robotic formi ng of ultrahigh strength materials is challenging due to the significant stiffne ss deformation of industrial robots. In this work, a double-sided robotic roller forming process was developed to form ultrahigh strength steels to thin-walled profiles." Financial supporters for this research include Science & Technolog y Commission of Shanghai Municipality (STCSM), China Scholarship Council. Our news journalists obtained a quote from the research from Tongji University, "Synchronized laser heating prior to plastic deformation was initially introduce d as a means of reducing the required forming forces. Considering the varying fo rming forces during the compensation of stiffness-deformation-induced path devia tion, an iterative path compensation method was proposed and implemented to enab le continuous adjustments of path compensation values, utilizing a robot stiffne ss model and the correlation between compensation values and forming forces. Res ults show that laser heating has a significant positive effect on reducing sprin gback angle due to the decrease of forming forces, while the path compensation f acilitates the forming of compact thin-walled profiles with sharp bending radii. " According to the news editors, the research concluded: "It is validated that the proposed method for iterative path compensation is conducive to the determinati on of the optimized path compensation values with limited iterations."
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    Research from University of Texas Tyler Yields New Study Findings on Machine Lea rning (Machine Learning Application of Generalized Gaussian Radial Basis Functio n and Its Reproducing Kernel Theory)

    103-104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 out of Tyler, Texas, by NewsR x editors, research stated, "Gaussian Radial Basis Function Kernels are the most -often-employed kernel function in artificial intelligence for providing the opt imal results in contrast to their respective counterparts." Funders for this research include Office of Dean; Office of Research, Scholarshi p, And Sponsored Programs; Robert R. Muntz Library At The University of Texas.The news reporters obtained a quote from the research from University of Texas T yler: "However, our understanding surrounding the utilization of the Generalized Gaussian Radial Basis Function across different machine learning algorithms, su ch as kernel regression, support vector machines, and pattern recognition via ne ural networks is incomplete. The results delivered by the Generalized Gaussian R adial Basis Function Kernel in the previously mentioned applications remarkably outperforms those of the Gaussian Radial Basis Function Kernel, the Sigmoid func tion, and the ReLU function in terms of accuracy and misclassification. This art icle provides a concrete illustration of the utilization of the Generalized Gaus sian Radial Basis Function Kernel as mentioned earlier."
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    Researcher from University of Technology-Iraq Describes Findings in Intelligent Systems (Improved rapidly exploring random tree using salp swarm algorithm)

    103-103页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Data detailed on intelligent systems have been pr esented. According to news reporting from Baghdad, Iraq, by NewsRx journalists, research stated, "Due to the limitations of the initial rapidly exploring random tree (RRT) algorithm, robotics faces challenges in path planning." The news journalists obtained a quote from the research from University of Techn ology-Iraq: "This study proposes the integration of the metaheuristic salp swarm algorithm (SSA) to enhance the RRT algorithm, resulting in a new algorithm term ed IRRT-SSA. The IRRT-SSA addresses issues inherent in the original RRT, enhanci ng efficiency and path-finding capabilities. A detailed explanation of IRRT-SSA is provided, emphasizing its distinctions from the core RRT. Comprehensive insig hts into parameterization and algorithmic processes contribute to a thorough und erstanding of its implementation. Comparative analysis demonstrates the superior performance of IRRT-SSA over the basic RRT, showing improvements of approximate ly 49, 54, and 54% in average path length, number of nodes, and nu mber of iterations, respectively."
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    New Robotics Study Findings Have Been Reported from SETI Institute (in Situ Real -time Monitoring for Aseptic Drilling: Lessons Learned From the Atacama Rover As trobiology Drilling Studies Contamination Control Strategy and Implementation .. .)

    104-105页
    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 Robotics have been published. According to news originating from Mountain View, California, b y NewsRx correspondents, research stated, "In 2019, the Atacama Rover Astrobiolo gy Drilling Studies (ARADS) project field-tested an autonomous rover-mounted rob otic drill prototype for a 6-Sol life detection mission to Mars (Icebreaker). AR ADS drilled Mars-like materials in the Atacama Desert (Chile), one of the most l ife-diminished regions on Earth, where mitigating contamination transfer into li fe-detection instruments becomes critical." Financial supporters for this research include National Aeronautics and Space Ad ministration PSTAR, Unidad de Excelencia "Maria de Maeztu" Centrode Astrobiologi a (CSIC-INTA) program by the Spanish Ministry of Science and Innovation/State Ag ency of Research (MCIN/AEI/), ERDF: A way of making Europe.
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    Studies from Massachusetts Institute of Technology Have Provided New Information about Robotics (Spectral Sparsification for Communication-efficient Collaborati ve Rotation and Translation Estimation)

    106-106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 Robotics are presented i n a new report. According to news reporting from Cambridge, Massachusetts, by Ne wsRx journalists, research stated, "We propose fast and communicationefficient optimization algorithms for multirobot rotation averaging and translation estima tion problems that arise from collaborative simultaneous localization and mappin g (SLAM), structure-from-motion (SfM), and camera network localization applicati ons. Our methods are based on theoretical relations between the Hessians of the underlying Riemannian optimization problems and the Laplacians of suitably weigh ted graphs." Financial support for this research came from ARL DCIST. The news correspondents obtained a quote from the research from the Massachusett s Institute of Technology, "We leverage these results to design a collaborative solver in which robots coordinate with a central server to perform approximate s econd-order optimization, by solving a Laplacian system at each iteration. Cruci ally, our algorithms permit robots to employ spectral sparsification to sparsify intermediate dense matrices before communication, and hence provide a mechanism to tradeoff accuracy with communication efficiency with provable guarantees. We perform rigorous theoretical analysis of our methods and prove that they enjoy (local) linear rate of convergence. Furthermore, we show that our methods can be combined with graduated nonconvexity to achieve outlier-robust estimation."
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    Fujian Normal University Reports Findings in Nanoparticles (Deciphering silver n anoparticles perturbation effects and risks for soil enzymes worldwide: Insights from machine learning and soil property integration)

    107-107页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Nanotechnology - Nanoparticles is the subject of a report. According to news reporting from Fuzhou, People's Repu blic of China, by NewsRx journalists, research stated, "Globally extensive resea rch into how silver nanoparticles (AgNPs) affect enzyme activity in soils with d iffering properties has been limited by cost-prohibitive sampling. In this study , customized machine learning (ML) was used to extract data patterns from comple x research, with a hit rate of Random Forest > Multiple Imputation by Chained Equations > Decision Tree > K-Nearest Neighbors." The news correspondents obtained a quote from the research from Fujian Normal Un iversity, "Results showed that soil properties played a pivotal role in determin ing AgNPs' effect on soil enzymes, with the order being pH > organic matter (OM) > soil texture cation exchange capa city (CEC). Notably, soil enzyme activity was more sensitive to AgNPs in acidic soil (pH <5.5), while elevated OM content (> 1.9 %) attenuated AgNPs toxicity. Compared to soil acidification, r educing soil OM content is more detrimental in exacerbating AgNPs' toxicity and it emerged that clay particles were deemed effective in curbing their toxicity. Meanwhile sand particles played a very different role, and a sandy soil sample a t > 40 % of the water holding capacity (WH C), amplified the toxicity of AgNPs. Perturbation mapping of how soil texture al ters enzyme activity under AgNPs exposure was generated, where soils with sand ( 45-65 %), silt (<22 %), and clay (35-55 %) exhibited even higher probability of positive effects of AgNPs. The average calculation results indicate the sandy clay loam (75.6 % ), clay (74.8 %), silt clay (65.8 %), and sandy clay ( 55.9 %) texture soil demonstrate less AgNPs inhibition effect."
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    Researchers Submit Patent Application, "Leaf Collector Robot Device", for Approv al (USPTO 20240081201)

    108-112页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-From Washington, D.C., NewsRx journali sts report that a patent application by the inventors Abdelsalam, Ahmed (Fairfax , VA, US); Amer, Hala (Fairfax, VA, US); Lindstrom, Dina (Leesburg, VA, US), fil ed on March 28, 2023, was made available online on March 14, 2024. No assignee for this patent application has been made. News editors obtained the following quote from the background information suppli ed by the inventors: "By way of background, this invention relates to improvemen ts in automatic leaf collector devices. Generally, cleaning up leaves, twigs, an d other yard debris during fall months can be exceptionally time consuming and e xhausting. Further, raking leaves and then shoveling them into trash bags can al so be frustrating. Additionally, constantly moving around environmental debris c an trigger severe allergies in some people. "During autumn in many communities, homeowners must haul fallen leaves to the st reet curb in order that the local municipality may collect the leaves. For homeo wners with large property and/or a great number of deciduous trees on the proper ty (and correspondingly a great number of fallen leaves), this can be a time-con suming and burdensome task. Further, using garbage bags to haul fallen leaves ca n be frustrating, as the garbage bags are susceptible to tears. Thus, torn garba ge bags may allow leaves, previously placed in the bag, to escape the confines o f the bag, thereby causing the person performing the raking to have to redo some work.
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