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    Findings in the Area of Machine Learning Reported from Beijing University of Che mical Technology (Physics-informed Machine Learning Approach for Molten Pool Mor phology Prediction and Process Evaluation In Directed Energy Deposition of 12crn i2 ...)

    115-116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 Machine Learning. According to news reporting originating in Beijing, People's R epublic of China, by NewsRx journalists, research stated, "The advancement of ma chine learning (ML) provides possibilities for in-situ monitoring and feedback c ontrol during directed energy deposition (DED) additive manufacturing (AM) proce ss. However, obtaining sufficient and high-quality training samples experimental ly is expensive and infeasible." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Key Research and Development Program of Sichuan Province, Na tional Key Research and Development Program of China.
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    University of Aberdeen Researcher Adds New Findings in the Area of Machine Learn ing (A Multi-Farm Global-to-Local Expert-Informed Machine Learning System for St rawberry Yield Forecasting)

    116-116页
    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 Aberdeen, United Kingdom, by NewsRx editors, the research stated, "The importance of forecasting crop yields in agriculture cannot be overstated." Funders for this research include The Data Lab. The news reporters obtained a quote from the research from University of Aberdee n: "The effects of yield forecasting are observed in all the aspects of the supp ly chain from staffing to supplier demand, food waste, and other business decisi ons. However, the process is often inaccurate and far from perfect. This paper e xplores the potential of using expert forecasts to enhance the crop yield predic tions of our global-to-local XGBoost machine learning system. Additionally, it i nvestigates the ERA5 climate model's viability as an alternative data source for crop yield forecasting in the absence of on-farm weather data."
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    Studies from Fujian Normal University Yield New Data on Machine Learning (A Nove l Student Achievement Prediction Model Based On Bagging-cart Machine Learning Al gorithm)

    117-117页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Machine Learning have be en published. According to news reporting originating from Fujian, People's Repu blic of China, by NewsRx editors, the research stated, "The learning effect of s tudents is crucial for assessing teaching quality, thus playing a significant ro le in teaching management. Predicting student achievement is a major challenge i n understanding the learning effect of students." Our news editors obtained a quote from the research from Fujian Normal Universit y, "Currently, many studies have utilized machine learning methods such as the d ecision tree algorithms C4.5, ID3, CART, J48, random forest, and others. However , few studies have explored the use of the Bagging algorithm in this field. Ther efore, this study proposes a classification prediction method for student achiev ement based on the Bagging-CART algorithm. Initially, the student achievement da ta is preprocessed, and the Apriori method is applied to mine the strongly assoc iated dataset. The optimal hyper-parameters are determined through grid search t o train and predict the Bagging-CART algorithm. Furthermore, the CART, J48, and Bagging-CART algorithms are trained, and their evaluation indicators are compare d using a confusion matrix. The results indicate that the Bagging-CART model ach ieves an accuracy of 98.16%, a recall rate of 91.80%, a precision of 90.83%, and an F1 score of 94.87%. In c omparison, the accuracy, precision, and F1 scores are higher than those obtained with CART and J48. Although the recall rate is slightly lower than that of CART by 0.26%, it is 0.52% higher than that of J48."
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    Hohai University Reports Findings in Robotics (Tumro: a Tunable Multimodal Wheel ed Jumping Robot Based On the Bionic Mechanism of Jumping Beetles)

    118-118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 Changzhou, People's Republi c of China, by NewsRx correspondents, research stated, "The implementation of mu ltimodal motion ensures the stable operation in complex terrain environments, th us providing an effective guarantee for system performance. The crawling-jumping robot has the ability to navigate in various road conditions utilizing differen t modes of movement." Financial supporters for this research include National Key Research and Develop ment Program of China, Postgraduate Research & Practice Innovation Program of Jiangsu Province, Fundamental Research Funds for the Central Univers ities.
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    Data on Neuroendocrine Cancer Reported by Ash Kieran Clift and Colleagues (Ident ifying patients with undiagnosed small intestinal neuroendocrine tumours in prim ary care using statistical and machine learning: model development and validatio n ...)

    119-119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 Oncology - Neuroendocr ine Cancer is the subject of a report. According to news originating from London , United Kingdom, by NewsRx correspondents, research stated, "Neuroendocrine tum ours (NETs) are increasing in incidence, often diagnosed at advanced stages, and individuals may experience years of diagnostic delay, particularly when arising from the small intestine (SI). Clinical prediction models could present novel o pportunities for case finding in primary care." Our news journalists obtained a quote from the research, "An open cohort of adul ts (18+ years) contributing data to the Optimum Patient Care Research Database b etween 1st Jan 2000 and 30th March 2023 was identified. This database collects d e-identified data from general practices in the UK. Model development approaches comprised logistic regression, penalised regression, and XGBoost. Performance ( discrimination and calibration) was assessed using internal-external cross-valid ation. Decision analysis curves compared clinical utility. Of 11.7 million indiv iduals, 382 had recorded SI NET diagnoses (0.003 %). The XGBoost mod el had the highest AUC (0.869, 95% confidence interval [CI]: 0.841-0.898) but was mildly miscalibrated (slope 1.165, 95% CI: 1.088-1.243; calibration-in-the-large 0.010, 95% CI: -0.164 to 0.185). Clinical utility was similar across all models. Multivaria ble prediction models may have clinical utility in identifying individuals with undiagnosed SI NETs using information in their primary care records."
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    New Machine Learning Findings from Shanghai University Described (A Multi-object ive Optimization Based On Machine Learning for Dimension Precision of Wax Patter n In Turbine Blade Manufacturing)

    120-121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 originating in Shanghai, Pe ople's Republic of China, by NewsRx journalists, research stated, "Wax pattern f abrication in the investment casting of hollow turbine blades directly determine s the dimension accuracy of subsequent casting, and therefore significantly affe cts the quality of final product. In this work, we develop a machine learning-ba sed multi-objective optimization framework for improving dimension accuracy of w ax pattern by optimizing its process parameters." Financial supporters for this research include National Key Research and Develop ment Program of China, National Science and Technology Major Project "Aeroengine and Gas Turbine" of China.
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    'Artificial Intelligence For Meeting Management' in Patent Application Approval Process (USPTO 20240177118)

    121-124页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent application by the inventors Agarwal, Sweta (Birpara, IN); Chakraborty, Aditi (Plano, TX, US); Perumalla, Sar aswathi Sailaja (Visakhapatnam, IN); Vishwanathula, Rachana (Hyderabad, IN), fil ed on November 30, 2022, was made available online on May 30, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents. This patent application has not been assigned to a company or institution. The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "The present invention relates generally to usin g artificial intelligence and computing programs to facilitate management of mee tings, e.g., virtual meetings that occur with one or more parties joining via te chnology such as video conferencing.
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    Patent Application Titled 'Method For Establishing A Map Of A Parameter In An Ar ea Based On A Sensor Mounted On An Autonomous Robot' Published Online (USPTO 202 40176356)

    124-128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 Washington, D.C., by NewsRx journalists, a patent application by the inve ntors AVENEL, Loic (CHATILLON CEDEX, FR); ESNAULT, Regis (CHATILLON CEDEX, FR), filed on November 14, 2023, was made available online on May 30, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: " "Technical Field "This disclosure falls within the field of parameter mapping. "More particularly, this disclosure relates to a method for establishing a map o f a parameter in an area, based on a sensor mounted on an autonomous robot. "Prior Art "Mapping the strength of a wifi signal propagated in a defined area can be usefu l, for example for improving the strength of the wifi signal or in order to find the best place to install a wifi repeater.
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    Patent Issued for Adaptive safety systems for autonomous mobile robots (USPTO 11 994874)

    129-132页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-From Alexandria, Virginia, NewsRx jour nalists report that a patent by the inventors Croyle, Justin (Hampstead, NH, US) , Paschall, Stephen Charles (Cambridge, MA, US), filed on March 24, 2021, was pu blished online on May 28, 2024. The patent's assignee for patent number 11994874 is Amazon Technologies Inc. (Se attle, Washington, United States). News editors obtained the following quote from the background information suppli ed by the inventors: "Many companies may store, package, and ship items and/or g roups of items from material handling facilities. For example, many companies ma y store items in a material handling facility and ship items to various destinat ions (e.g., customers, stores) from the material handling facility. Various mate rial handling systems and processes, including receipt, sorting, storage, packin g, shipping, or other processing of items within a material handling facility, o ften incur significant cost and time. Accordingly, there is a need for flexible and automated systems and methods to facilitate the various material handling pr ocesses within a material handling facility, thereby improving the speed and eff iciency of such processes."
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    'Artificial Intelligence For Communication Mode Suggestion' in Patent Applicatio n Approval Process (USPTO 20240179538)

    132-135页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent application by the inventors Agarwal, Sweta (Birpara, IN); Chakraborty, Aditi (Plano, TX, US); Perumalla, Sar aswathi Sailaja (Visakhapatnam, IN); Vishwanathula, Rachana (Hyderabad, IN), fil ed on November 30, 2022, was made available online on May 30, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents. This patent application has not been assigned to a company or institution. The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "The present invention relates generally to usin g artificial intelligence and computing programs to facilitate communication mod e suggestions for a party trying to communicate with another party. "Communication platforms and modes abound implementing modern technology such as the Internet but can add complexity regarding a typical decision. A person ofte n decides what is best way to communicate with another party and cause the other party to respond. Such decision complexity may abound for inter-organizational communications."
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