查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Agriculture - Agricul tural Robots have been presented. According tonews originating from Xiangtan, P eople’s Republic of China, by NewsRx correspondents, research stated,“Replacing humans with robots for fruit harvesting is the trend of agricultural automation in the future.However, for grape harvesting robots, locating the picking point becomes a significant challenge in highlyoccluded environments due to the smal l fruit stem, which can be entirely obscured by fruit leaves whenthe observatio n angle is poor.”Financial support for this research came from Key Project of Guangdong Fundament al and ApplicationFundamental Research Joint Fund.Our news journalists obtained a quote from the research from Xiangtan University , “In the letter, aview planner based on an active vision strategy is proposed to address the occlusion problem. It aims tofind the picking point by altering the observation perspective of the harvesting robot. The view planningprocess i s achieved through multiple iterations. Each iteration consists of three key ste ps: randomlygenerating candidate views, predicting the ideal perspective using a score function, and guiding the roboticarm to change the viewpoint. To evalua te the degree of occlusion, a novel concept of Spatial CoverageRate Metric (SC) is introduced. Based on this, the score function is improved by incorporating S C andmotion cost. Finally, to validate the effectiveness of the planner, we con ducted comparative experimentswith other advanced view planners on a real grape harvesting robot.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Machine Learning is the subject o f a report. According to news originating fromXiamen, People’s Republic of Chin a, by NewsRx correspondents, research stated, “Due to the increasedconcern abou t energy and environmental issues, significant attention has been paid to the de velopmentof large-scale energy storage devices to facilitate the utilization of clean energy sources. The redox flowbattery (RFB) is one of the most promising systems.”Our news journalists obtained a quote from the research from Xiamen University, “Recently, the highcost of transition-metal complex-based RFB has promoted the development of aqueous RFBs with redoxactiveorganic molecules. To expand the w orking voltage, computational chemistry has been applied tosearch for organic m olecules with lower or higher redox potentials. However, redox potential computation based on implicit solvation models would be challenging due to difficulty i n parametrization whenconsidering the complex solvation of supporting electroly tes. Besides, although ab initio molecular dynamics(AIMD) describes the support ing electrolytes with the same level of electronic structure theory asthe redox couple, the application is impeded by the high computation costs. Recently, mac hine learningmolecular dynamics (MLMD) has been illustrated to accelerate AIMD by several orders of magnitude withoutsacrificing the accuracy. It has been est ablished that redox potentials can be computed by MLMD withtwo separated machin e learning potentials (MLPs) for reactant and product states, which is redundantand inefficient. In this work, an automated workflow is developed to construct a universal MLP for bothstates, which can compute the redox potentials or acidi ty constants of redox-active organic moleculesmore efficiently."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Liver Diseases and Con ditions - Non-Alcoholic Fatty Liver Diseaseis the subject of a report. Accordin g to news originating from Zhejiang, People’s Republic of China, byNewsRx corre spondents, research stated, “Concrete epidemiological evidence has suggested the mutuallycontributingeffect respectively between nonalcoholic fatty liver dise ase (NAFLD), type 2 diabetes mellitus(T2DM), and periodontitis (PD); however, t heir shared crosstalk mechanism remains an open issue. TheNAFLD, PD, and T2DM-r elated datasets were obtained from the NCBI GEO repository.”Our news journalists obtained a quote from the research from Zhejiang University , “Their commondifferentially expressed genes (DEGs) were identified and the fu nctional enrichment analysis performed bythe DAVID platform determined relevant biological processes and pathways. Then, the STRING databaseestablished a PPI network of such DEGs and topological analysis through Cytoscape 3.7.1 software along with the machine-learning analysis by the least absolute shrinkage and sele ction operator (LASSO)algorithm screened out hub characteristic genes. Their ef ficacy was validated by external datasets using thereceiver operating character istic (ROC) curve, and gene expression and location of the most robust one wasd etermined using single-cell sequencing and immunohistochemical staining. Finally , the promising drugswere predicted through the CTD database, and the CB-DOCK 2 and Pymol platform mimicked moleculardocking. Intersection of differentially e xpressed genes from three datasets identified 25 shared DEGs ofthe three diseas es, which were enriched in MHC II-mediated antigen presenting process. PPI netwo rkand LASSO machine-learning analysis determined 4 feature genes, of which the MS4A6A gene mainlyexpressed by macrophages was the hub gene and key immune cell type. Molecular docking simulationchosen fenretinide as the most promising med icant for MS4A6A macrophages.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news reportingfrom San Antonio, Texas, by NewsRx journalists, research stated, “Modeling parameters are essential to thefidelity of nonlinear models of concrete structures subjected to earthquake ground motio ns, especially whensimulating seismic events strong enough to cause collapse. T his paper addresses two of the most significantbarriers to improving nonlinear modeling provisions in seismic evaluation standards using experimental datasets : identifying the most likely mode of failure of structural components, and impl ementing data fittingtechniques capable of recognizing interdependencies betwee n input parameters and nonlinear relationshipsbetween input parameters and mode l outputs.”The news correspondents obtained a quote from the research from the University o f Texas San Antonio,“Machine learning tools in the Scikit-learn and Pytorch lib raries were used to calibrate equations and black-box numerical models for nonl inear modeling parameters (MP) a and b of reinforced concrete columnsdefined in the ASCE 41 and ACI 369.1 standards, and to estimate their most likely mode of failure. It wasfound that machine learning regression models and machine learni ng black -boxes were more accurate thancurrent provisions in the ACI 369.1/ASCE 41 Standards. Among the regression models, Regularized LinearRegression was th e most accurate for estimating MP a, and Polynomial Regression was the most accurate for estimating MP b. The two black -box models evaluated, namely the Gaussi an Process Regressionand the Neural Network (NN), provided the most accurate es timates of MPs a and b. The NN model wasthe most accurate machine learning tool of all evaluated.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Fresh data on Robotics are presented i n a new report. According to news originatingfrom Guangdong, People’s Republic of China, by NewsRx correspondents, research stated, “The integrationof camera and LiDAR technologies has the potential to significantly enhance construction r obots’perception capabilities by providing complementary construction informati on. Structured light cameras(SLCs) are a desirable alternative as they provide comprehensive information on construction defects.”Financial supporters for this research include National Natural Science Foundati on of China (NSFC),Guangdong Natural Science Fund-General Programme, Technology and Innovation Commission of ShenzhenMunicipality.Our news journalists obtained a quote from the research from the Southern Univer sity of Science andTechnology (SUSTech), “However, fusing these two types of in formation depends largely on the sensors’relative positions, which can only be established through extrinsic calibration. This paper introduces anovel calibra tion algorithm considering a customized board for SLCs and repetitive LiDARs, wh ich aredesigned to facilitate the automation of construction robots. The calibr ation board is equipped with foursymmetrically distributed hemispheres, whose c enters are obtained by fitting the spheres and adoptionwith the geometric const raints. Subsequently, the spherical centers serve as reference features to estimate the relationship between the sensors. These distinctive features enable our proposed method to onlyrequire one calibration board pose and minimize human in tervention. We conducted both simulation andreal-world experiments to assess th e performance of our algorithm.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in Machine Learning. According to news reportingfrom Tamil Nadu, India, by NewsRx journalists, research stated, “This work introduces an innovativemethodology to enhance the efficiency of solar Parabolic Trough Collectors by integrating corr ugated tubereceivers accompanied by conical strip inserts. Conventional optimiz ation techniques involving adjustmentsin size, material composition, and insert configurations often necessitate supplementary energy input.”The news correspondents obtained a quote from the research from Annamalai Univer sity, “A conceptcentered around augmenting turbulence was introduced, employing corrugated tube receivers to addressthis challenge. The study encompassed empi rical investigations employing three corrugated copper tubereceivers, each poss essing distinct pitches (8 mm, 10 mm, and 12 mm) while maintaining uniform corrugation heights (2 mm). These experiments were conducted within a regime of lamin ar flow conditionscharacterized by Reynolds numbers spanning from 700 to 2000. The primary objective was to identify themost favorable absorber geometry, subs equently coupled with three varying pitches of conical strip inserts(20 mm, 30 mm and 50 mm) to intensify heat transference. The findings unveiled that the cor rugatedtube with an 8 mm pitch and 2 mm corrugation height, combined with a con ical strip insert possessing apitch of 20 mm, exhibited promising results. This specific amalgamation yielded remarkable enhancementsin the augmented Nusselt number (132%), friction factor (38%), and thermal effi ciency (9%) in contrastto the unadorned tube operating under analo gous conditions.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Oncology - Breast Canc er is the subject of a report. According tonews reporting originating in Fujian , People’s Republic of China, by NewsRx journalists, research stated,“Breast ca ncer is a major threat to women’s health globally. Early detection of breast can cer is crucialfor saving lives.”The news reporters obtained a quote from the research, “One important early sign is the appearanceof breast calcification in mammograms. Accurate segmentation and analysis of calcification can improvediagnosis and prognosis. However, smal l size and diffuse distribution make calcification prone to oversight.This stud y aims to develop an efficient approach for segmenting and quantitatively analyz ing breastcalcification from mammograms. The goal is to assist radiologists in discerning benign versus malignantlesions to guide patient management. This stu dy develops a framework for breast calcification segmentationand analysis using mammograms. A Pro_UNeXt algorithm is proposed to accurately segmen t calcificationlesions by enhancing the UNeXt architecture with a microcalcific ation detection block, fused-MBConvmodules, multiple-loss-function training, an d data augmentation. Quantitative features are then extractedfrom the segmented calcification, including morphology, size, density, and spatial distribution. T hesefeatures are used to train machine learning classifiers to categorize lesio ns as malignant or benign. Theproposed Pro_UNeXt algorithm achieve d superior segmentation performance versus UNet and UNeXtmodels on both public and private mammogram datasets. It attained a Dice score of 0.823 for microcalcification detection on the public dataset, demonstrating its accuracy for small l esions. For quantitativeanalysis, the extracted calcification features enabled high malignant/benign classification, with AdaBoostreaching an AUC of 0.97 on t he private dataset. The consistent results across datasets validate therepresen tative and discerning capabilities of the proposed features. This study develops an efficientframework integrating customized segmentation and quantitative ana lysis of breast calcification. Pro_UNeXt offers precise localizatio n of calcification lesions. Subsequent feature quantification and machinelearni ng classification provide comprehensive malignant/benign assessment.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on robotics have been pr esented. According to news originating fromSingapore, Singapore, by NewsRx corr espondents, research stated, “Mobile service robots employ visionsystems to dis cern objects in their workspaces for navigation or object detection.”Financial supporters for this research include National Robotics Programme (Nrp) Bau, Ermine Ⅲ;A*star.The news reporters obtained a quote from the research from Singapore University of Technology andDesign: “The lighting conditions of the surroundings affect a robot’s ability to discern and navigate in itswork environment. Robot inclusivi ty principles can be used to determine the suitability of a site’s lightingcond ition for robot performance. This paper proposes a novel framework for autonomou sly auditing theRobot Inclusivity Index of indoor environments based on the lig hting condition (RII-lux). The frameworkconsiders the factors of light intensit y and the presence of glare to define the RII-Lux of a particularlocation in an environment.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Robotics is the subjec t of a report. According to news reportingout of Fujian, People’s Republic of C hina, by NewsRx editors, research stated, “Although consumers’evaluation and ad option of robotic services have been widely investigated, the effectiveness of r oboticsales promotion in the hospitality industry remains unclear. Utilizing th e benefit congruency framework,this study proposes that robotic (human) promoti on is more suitable for utilitarian (hedonic) benefits.”Funders for this research include National Natural Science Foundation of China ( NSFC), Fujian ProvincialFederation of Social Sciences, Fundamental Research Fun ds for the Central Universities.Our news journalists obtained a quote from the research from Xiamen University, “Based on an experimentwith and field data provided by a Chinese restaurant cha in, this study demonstrates that robotsperform better than humans in monetary p romotion (e.g., price discounts) that offers utilitarian benefitsbut not in non monetary promotion (e.g., extra dish) associated with hedonic benefits. Moreover , ananthropomorphic language style can reduce the performance difference betwee n robots and humans innonmonetary promotion.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Investigators publish new report on Transportatio n - Intelligent Transport Systems. According tonews reporting out of Jilin, Peo ple’s Republic of China, by NewsRx editors, research stated, “Accuratepositioni ng of intelligent connected vehicle (ICV) is a key element for the development o f cooperativeintelligent transportation system. In vehicular networks, lots of state-related measurements, especially themutual measurements between ICVs, are shared.”Financial support for this research came from National Natural Science Foundatio n of China (NSFC).Our news journalists obtained a quote from the research from Jilin University, “ It is an advisable strategyto fuse these measurements for a more robust positio ning. In this context, an innovative framework,referred to as multisource-multi target cooperative positioning (MMCP) is presented. In MMCP, ICVs arelocal info rmation source, that upload both the states of ICVs estimated by on-board sensor s and therelative vectors between surrounding objects and vehicles to a fusion centre. In the fusion centre, ICVs areselected as the global targets, and the r elative vectors are converted into global measurements. Then,the MMCP is modell ed into a multi-target tracking problem with specific targets. This paper proposes a low complexity Gaussian mixture probability hypothesis density (GM-PHD-LC) filter to match andfuse the global measurements to further improve the estimati on of ICVs. The evaluation results showthat our GM-PHD-LC can provide 10 Hz pos itioning services in urban area, and significantly improve thepositioning accur acy compared to the standalone global navigation satellite system. This paper pr oposesa low complexity Gaussian mixture probability hypothesis density (GM-PHD-LC) filter.”
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