查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news originating from Stockholm, Sweden, by NewsRx correspondents, research stated, "Emergency department (ED) overcrowding is a complex problem that is intricately linked with the operations of other hos pital departments. Leveraging ED real-world production data provides a unique op portunity to comprehend this multifaceted problem holistically." Our news journalists obtained a quote from the research, "This paper introduces a novel approach to analyse healthcare production data, treating the length of s tay of patients, and the follow up decision regarding discharge or admission to the hospital as atime-to-event analysis problem. Our methodology employs tradit ional survival estimators and machine learning models, and Shapley additive expl anations values to interpret the model outcomes. The most relevant features infl uencing length of stay were whether the patient received a scan at the ED, emerg ency room urgent visit, age, triage level, and the medical alarm unit category. The clinical insights derived from the explanation of the models holds promise f or increase understanding of the overcrowding from the data."
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 the Department of Civil Engineering by NewsRx correspondents, research stated, "As a critical com ponent of sustainable water management, groundwater level prediction plays a vit al role in mitigating droughts and ensuring adequate water supply. For decades, groundwater level dynamics have been primarily studied through physics-based mod els, solving partial differential equations." Funders for this research include Herff College of Engineering, University of Me mphis.
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 Machine Learning is now available. According to news reporting originating from Baton Rouge, Louisiana, by NewsRx correspondents, research stated, "Highway state agencies incur signif icant budget savings through optimal allocation of pavement Maintenance, Rehabil itation, and Reconstruction (MR&R) &R) activities. The se activities require robust prediction models that can handle large-scale, real -world data and can forecast pavement performance in the long run." Our news editors obtained a quote from the research from Louisiana State Univers ity, "Unfortunately, the traditional performance prediction models have been que stionable in terms of efficiency and accuracy, are based on a limited number of explanatory variables, and are designated to predict short-term (up to five year s) pavement conditions. Therefore, the goal of this study was to propose a machi ne learningbased technology that can predict the field performance by up to 11 years of Asphalt Concrete (AC) overlays placed on asphalt pavements in Southern states in the US based on key project conditions. The proposed technology result ed from assessing the prediction accuracy of machine learning algorithms, includ ing Decision-Tree (DT), eXtreme Gradient Boosting (XGBoost), Artificial Neural N etwork (ANN), and ensemble-learning method, in forecasting the Pavement Conditio n Index (PCI) as the pavement performance indicator. For each algorithm, six mod els were developed sequentially based on historical pavement condition data coll ected from the Louisiana Department of Transportation and Development (LaDOTD) P avement Management System (PMS) database. The six models learned from 892 log mi les of randomly placed AC overlay sections in Louisiana. The output of these mod els was the future PCI of AC overlays at a biannual rate from one to 11 years. T he findings showed that XGBoost and ensemble learning showed similar performance during model training and were further evaluated using the testing dataset. Dur ing model testing, the ensemble learning method yielded higher prediction accura cy than other algorithms, with R2 2 values decreasing from 0.77 at age 1 to 0.67 at age 11, Root Mean Square Error (RMSE) values increasing from +1.65 to +4.74, and Mean Absolute Error (MAE) increasing from 1.24 to 4.59."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on robotics and mech atronics are discussed in a new report. According to news reporting out of Saita ma, Japan, by NewsRx editors, research stated, "In this study, we propose an aut omated excavation system for pneumatic caisson construction using either a singl e excavator or multiple excavators." The news reporters obtained a quote from the research from Nippon Institute of T echnology: "The system divides the work area among the excavators and manages th e transition of occupied states in shared areas to reduce the risk of collisions . Additionally, the Laplace potential method is employed for path planning to av oid collisions with equipment inside the caisson. The system also includes a mec hanism for disposing of soil outside the caisson by dumping it into an earth buc ket." According to the news editors, the research concluded: "To confirm the effective ness of the proposed method, verification tests were conducted: one using a sing le excavator in a narrower-than-usual caisson, and another using two excavators in atest field. These tests demonstrated the method's effectiveness."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting from Federal University by NewsRx journalists, research stated, "Artificial insemination (AI) success in bovine re production is vital for the cattle industry's economic sustainability and for ad vancing the understanding of reproductive physiology. Identify high-fertile anim als' fertility is a complex task due to multifactorial traits, including hormona l, age-related, and body condition factors." Financial supporters for this research include Coordenacao De Aperfeicoamento De Pessoal De Nivel Superior; Conselho Nacional De Desenvolvimento Cientifico E Te cnologico; Fundacao De Apoio Ao Desenvolvimento Do Ensino, Ciencia E Tecnologia Do Estado De Mato Grosso Do Sul.
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-Robotics and Automation is now available. According to news reporting out of Hanoi, Vietnam, by NewsRx editors, the research stated, "The absence of tactile sensing signifi cantly impacts the quality of life for individuals with limb loss. While prosthe tic legs are invaluable tools for lower-limb amputees, the lack of tactile feedb ack presents a substantial limitation." Financial support for this research came from Hanoi University of Science and Te chnology (HUST). Our news journalists obtained a quote from the research from the Hanoi Universit y of Science and Technology, "This letter introduces a novel design and technica l implementation for a sensory below-knee prosthetic leg, named TacLeg, specific ally targeting leg prostheses for lower-limb amputees. Through simulation and ex perimental investigation, the proposed system demonstrates robust tactile sensin g capabilities upon contact with the environment. These preliminary results high light the functionality of the TacLeg device, showcasing its integration of soft elastomers and vision-based sensing to provide efficiently tactile feedback, wh ile also ensuring safety and durability."
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 and mechatronic s are presented in a new report. According to news reporting out of Aomori, Japa n, by NewsRx editors, research stated, "In off-pump coronary artery bypass graft ing (OPCAB), the coronary arteries are joined as the heart beats." Funders for this research include Japan Science And Technology Agency; Japan Soc iety For The Promotion of Science. Our news editors obtained a quote from the research from Hirosaki University: "T his procedure requires high skill and experience to be performed reliably and qu ickly. Although training kits are commonly used for technical training, the inab ility of trainees to always be with experienced surgeons for guidance and to rec eive immediate evaluation remains problematic. To address this problem, a system that allows a single trainee to observe and quantitatively evaluate the procedu res performed by an experienced surgeon is being developed. In this study, to an alyze the differences between the motions of experienced and novice surgeons, Le ap Motion was used to measure the hand motion of the vascular anastomosis perfor med by both surgeons using atraining kit. Using the measured data, the features of the vascular anastomosis surgical techniques performed by experienced and no vices were tested using the Mann-Whitney U test."
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 Machine Learning is now available. According to news reporting originating from Guiyang, People's Repub lic of China, by NewsRx correspondents, research stated, "Machine learning (ML) sees an increasing prevalence of being used in the Internet of Things (IoT)-base d smart grid. However, the trustworthiness of ML is a severe issue that must be addressed to accommodate the trend of ML-based smart grid applications (MLsgAPPs )." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Zhejiang Province, Fundamental Research Funds for the Central Universities, National Research Foundation Singa pore and MOE Tier 1, Key Laboratory of CS&AUS of Zhejiang Province, Guizhou Provincial Science and Technology Projects, Guizhou Provincial Research Project (Youth) for Universities.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news reporting out of Gujarat, India , by NewsRx editors, research stated, "Pavement subgrade design relies on the re silient modulus (Mr) r ) to analyze structural response to vehicle-like loading. Adding stabilizers to the soil subgrade makes estimating Mr r difficult and res ource-intensive." Our news journalists obtained a quote from the research from the School of Techn ology, "This study uses an automated machine learning (ML) strategy to predict t he Mr r of stabilized clayey soil using recycled plastic waste. The proposed met hod automates model selection and hyperparameter tuning, making it a feasible al ternative to tedious ML modeling and costly laboratory testing. From extensive l aboratory investigation involving 3285 experimental data points, the automated M L model using Bayesian optimization evaluates ensembles, support vector machine (SVM), neural network (NET), decision trees, (TREE), and Gaussian process (GP) r egression models, identifying the best model based on cross-validation mean squa red error (MSE). Bayesian optimization explores hyperparameter spaces to find op timal configurations, enhancing the accuracy, scalability, and reliability of th e prediction model. The optimization process yielded the best results for the en semble least square boost (LSBoost) model with a cross-validation mean squared e rror (MSE) value of 6.723x10–29. The optimized ML model's performance is measur ed using R2 2 and adjusted R2. 2. The LSboost model's R2 2 and adjusted R2 2 val ues of 0.9999 suggested overfitting, prompting further investigations using perf ormance metrics like root mean squared error (RMSE), mean absolute error (MSE), and probability density function (PDF) for normalized absolute error (NAE) for t raining and testing datasets for the predictive ML model. The small RMSE and MAE (0.0049 and 0.0005) values and symmetrical NAE distribution of the proposed ML model demonstrate its high accuracy and generalization capabilities. The propose d model was subsequently tested on the new, unseen data and achieved predictions with an error rate of 0.24%."
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 from Vancouver, Canada , by NewsRx journalists, research stated, "As healthcare embraces the transformative potential of Artificial Intelligence (AI), it is imperative to safeguard patient and provider safety, equity, and trust in the healthcare system. This arti cle outlines the approach taken by the British Columbia (BC) Provincial Health S ervices Authority (PHSA) to establish clinical governance for the responsible de ployment of AI tools in healthcare." The news correspondents obtained a quote from the research, "Leveraging its prov ince-wide mandate and expertise, PHSA establishes the infrastructure and process es to proactively and systematically intake, assess, prioritize, and evaluate AI tools. PHSA proposes a coordinated approach in AI tool deployment in collaborat ion with regional health authorities to prevent duplication of efforts and ensur e equitable access to existing and emerging AI tools across the province of BC, incorporating principles of anti-Indigenous racism, cultural safety, and humilit y."
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