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    Research from University of Coimbra Reveals New Findings on Robotics (Benchmarki ng human-robot collaborative assembly tasks)

    103-104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 out of Coimbra, Portugal, by NewsRx editors, res earch stated, “Manufacturing assembly tasks can vary in complexity and level of automation. Yet, achieving full automation can be challenging and inefficient, p articularly due to the complexity of certain assembly operations.” Funders for this research include Fundacao Para A Ciencia E A Tecnologia. Our news correspondents obtained a quote from the research from University of Co imbra: “Humanrobot collaborative work, leveraging the strengths of human labor alongside the capabilities of robots, can be a solution for enhancing efficiency . This paper introduces the CT benchmark, a benchmark and model set designed to facilitate the testing and evaluation of human-robot collaborative assembly scen arios. It was designed to compare manual and automatic processes using metrics s uch as the assembly time and human workload. The components of the model set can be assembled through the most common assembly tasks, each with varying levels o f difficulty. The CT benchmark was designed with a focus on its applicability in human-robot collaborative environments, with the aim of ensuring the reproducib ility and replicability of experiments. Experiments were carried out to assess a ssembly performance in three different setups (manual, automatic and collaborati ve), measuring metrics related to the assembly time and the workload on human op erators.”

    Study Findings on Artificial Intelligence Discussed by a Researcher at Sankalcha nd Patel University (Resolving Charging Station Placement Issues for Electric Ve hicles: Hybrid Optimization-Assisted Multi-Objective Framework)

    104-105页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on artificial intelligence have bee n presented. According to news reporting out of Gujarat, India, by NewsRx editor s, research stated, “As new energy technology has advanced to a respectable leve l, Electric Vehicles (EV) have gained recognition from people all over the world and have become increasingly popular in a number of nations.” Our news journalists obtained a quote from the research from Sankalchand Patel U niversity: “Effective charging station placement is critical for the rapid growt h of electric vehicles, as it is vital to provide convenience for electric vehic les while also ensuring the effectiveness of traffic networks. The location of a n EV charging station is simply an application situation for the facility locati on problem. Traditional works often pay attention to the mileage concerns of ele ctric vehicle customers while ignoring their competitive and strategic charging tactics. This research aims to frame the allocation of charging stations issue a s a multi-faceted venture by assessing the aspects economically along with the c haracteristics of the power grid like “cost, Voltage stability, Reliability, and Power loss (VRP) index, waiting time, and accessibility index”. Further, we pro posed a hybrid artificial intelligence to resolve the allocation issue. The prop osed new Artificial Intelligence (AI) based algorithm is termed as Hybridized Sa lp and Harris Algorithm (HS-HA).”

    New Machine Learning Study Findings Have Been Reported by Investigators at Unive rsity of Illinois (Prediction of Stress-strain Behavior of Pet Frp-confined Conc rete Using Machine Learning Models)

    105-106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 Machine Learning are pre sented in a new report. According to news reporting from Urbana, Illinois, by Ne wsRx journalists, research stated, “Polyethylene terephthalate (PET) fiber-reinf orced polymer (FRR) has been recently developed, which possesses a bilinear tens ile stressstrain relationship and a large rupture strain (LRS) capacity. This s tudy presents a novel approach for accurately predicting the stress-strain behav ior of PET FRP-confined concrete using machine learning (ML) techniques.” The news correspondents obtained a quote from the research from the University o f Illinois, “A comprehensive dataset comprising 154 axial compression test speci mens, including both circular and noncircular cases, was utilized for training a nd testing ML models. Three advanced ML models, namely extreme gradient boosting (XGBoost), random forest regression (RFR), and k-nearest neighbors (KNN), were applied to predict mechanical properties for both circular and noncircular speci mens. XGBoost consistently outperformed RFR and KNN, demonstrating superior accu racy in predicting stress-strain curves for both specimen types. Performance eva luation relied on key metrics such as coefficient of determination (R2), mean sq uare error (MSE), root mean square error (RMSE), and mean absolute error (MAE). Furthermore, the predicted stress-strain curves generated by XGBoost were compar ed to experimental data and a mechanism model, highlighting the superiority of X GBoost in capturing critical curve points and emphasizing its accuracy and consi stency.”

    Researchers at Hong Kong University of Science and Technology Release New Data o n Machine Learning (Fault detection using machine learning based dynamic ICA-dis tributed CCA: Application to industrial chemical process)

    106-106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 artificial intelligen ce have been presented. According to news reporting from Hong Kong University of Science and Technology by NewsRx journalists, research stated, “Unexpected acci dents and events in industrial chemical processes have resulted in a considerabl e number of causalities and property damage.” Our news journalists obtained a quote from the research from Hong Kong Universit y of Science and Technology: “Safety process management in industrial chemical p rocesses is critical to avoid and ensure casualties and property damage. However , due to the immense scope and high complexity of current industrial chemical pr ocesses, the traditional safety process management approaches cannot address the se challenges to attain adequate fault detection accuracy. To address this issue , an innovative machine learning-based distributed canonical correlation analysi s-dynamic independent component analysis (DICADCCA) approach is needed to impro ve the fault detection effectiveness of complicated systems. The (DICA-DCCA) mod el could potentially detect anomalies and faults in industrial chemical data by utilizing three essential statistics:Id2,Ie2and squared prediction error (SPE). The practical effectiveness of the proposed frameworks is evaluated and compared using a continuous stirred tank reactor (CSTR) framework as a standard benchmar k study. The research findings present that the suggested (DICA-DCCA) approach i s more resilient and effective in detecting abnormalities and faults than the IC A and DICA approaches with FDR 100 % and FAR 0 %.”

    Amsterdam University Medical Center Reports Findings in Robotics (Training in ro botic-assisted surgery: a systematic review of training modalities and objective and subjective assessment methods)

    107-107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 reporting from Amsterdam, Netherlands, by NewsR x journalists, research stated, “The variety of robotic surgery systems, trainin g modalities, and assessment tools within robotic surgery training is extensive. This systematic review aimed to comprehensively overview different training mod alities and assessment methods for teaching and assessing surgical skills in rob otic surgery, with a specific focus on comparing objective and subjective assess ment methods.” The news correspondents obtained a quote from the research from Amsterdam Univer sity Medical Center, “A systematic review was conducted following the PRISMA gui delines. The electronic databases Pubmed, EMBASE, and Cochrane were searched fro m inception until February 1, 2022. Included studies consisted of robotic-assist ed surgery training (e.g., box training, virtual reality training, cadaver train ing and animal tissue training) with an assessment method (objective or subjecti ve), such as assessment forms, virtual reality scores, peer-to-peer feedback or time recording. The search identified 1591 studies. After abstract screening and full-texts examination, 209 studies were identified that focused on robotic sur gery training and included an assessment tool. The majority of the studies utili zed the da Vinci Surgical System, with dry lab training being the most common ap proach, followed by the da Vinci Surgical Skills Simulator. The most frequently used assessment methods included simulator scoring system (e.g., dVSS score), an d assessment forms (e.g., GEARS and OSATS). This systematic review provides an o verview of training modalities and assessment methods in robotic-assisted surger y. Dry lab training on the da Vinci Surgical System and training on the da Vinci Skills Simulator are the predominant approaches. However, focused training on t issue handling, manipulation, and force interaction is lacking, despite the abse nce of haptic feedback.”

    Recent Findings in Machine Learning Described by a Researcher from Beijing Jiaot ong University (House Price Prediction Based on Machine Learning Algorithms - Ta king Ames as an Example)

    108-108页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on artificial in telligence. According to news reporting from Beijing, People’s Republic of China , by NewsRx journalists, research stated, “This study delves into the significan ce and methods of predicting housing prices.” Our news reporters obtained a quote from the research from Beijing Jiaotong Univ ersity: “Utilizing a dataset from Kaggle, the author selected 10 variables highl y correlated with housing prices, including OverallQual, GrLivArea, and GarageCa rs. Various models such as random forest and multiple linear regression were emp loyed for prediction and comparison. Results indicate that for data with strong linear relationships, the predictive performance of the multiple linear regressi on model surpasses that of the random forest model.”

    Research from University of Tunis Provides New Study Findings on Artificial Inte lligence (Artificial Intelligence and Digital Technology in Their Relation to Hu man Existence and Artistic Creativity)

    108-109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 artificial in telligence have been published. According to news originating from the Universit y of Tunis by NewsRx correspondents, research stated, “This research explores th e impact of artificial intelligence and digital technologies on human existence and artistic creativity in our contemporary reality.” Our news correspondents obtained a quote from the research from University of Tu nis: “The paper sheds light on the transformations of the relationship between h umans and technology, where the study responded to questions about whether these technologies are just tools or have a deeper impact on the human experience. Th e paper also focused on the impact of these technologies on artistic creativity, where it was shown that artificial intelligence can be a source of inspiration for creativity, and that digital technologies provide new platforms for artistic expression. However, challenges were observed related to the importance of pres erving authenticity and balance between technical and human factors in a rapidly changing society. The paper highlighted the importance of developing policies a nd ethical frameworks that guide the use of technologies towards enhancing human values and encouraging creativity. With a focus on developing technology that r espects human identity and promotes diversity of creativity. This makes us face an approach of benefiting from technology without giving up the essential aspect s of humanity and art.”

    Investigators at University of California Los Angeles (UCLA) Discuss Findings in Intelligent Vehicles (Cooperative Localization In Transportation 5.0)

    109-110页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Transportation - Intelligent Vehicles are discussed in a new report. According to news originating from Los Angeles, California, by NewsRx correspondents, research stated, “In the era of f uture mobility within Transportation 5.0, autonomy and cooperation across all ro ad users and smart infrastructure stand as the key features to enhance transport ation safety, efficiency, and sustainability, supported by cooperative perceptio n, decision-making and planning, and control.” Financial support for this research came from FHWA Center for Excellence on New Mobility and Automated Vehicles Program.

    Findings in Machine Learning Reported from Banaras Hindu University (Appraisal o f Visible/ir and Microwave Datasets for Land Surface Fluxes Estimation Using Mac hine Learning Techniques)

    110-111页
    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 Varanasi, Indi a, by NewsRx editors, research stated, “Land surface fluxes such as Soil Moistur e (SM) and Soil Temperature (ST) are very important variables for many applicati ons that includes agriculture water management, weather and climate prediction, natural disasters etc. Further, they are important for understanding soil proces ses, hydrological balances as well as changes in microbial population.” Funders for this research include Institute of Eminence, Banaras Hindu Universit y, RESPOND.

    Study Data from Delhi Technological University Update Understanding of Robotics (Track Consensus-based Labeled Multi-target Tracking In Mobile Distributed Senso r Network)

    111-112页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on Robotics. Acc ording to news originating from Delhi, India, by NewsRx correspondents, research stated, “This paper proposes an efficient algorithm for tracking multiple targe ts using a network of static and mobile sensors (robots). Multi-target tracking has a broad array of applications, including crowd monitoring, vehicle tracking, warehouse automation, and pedestrian safety, among others.” Financial support for this research came from University Grants Commission, Indi a.