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 Cerebro vascular Diseases and Conditions - Stroke. According to news originating from He idelberg, Germany, by NewsRx correspondents, research stated, “Quantitative and automated volumetric evaluation of early ischemic changes on non-contrast CT (NC CT) has recently been proposed as a new tool to improve prognostic performance i n patients undergoing endovascular therapy (EVT) for acute ischemic stroke (AIS) . We aimed to test its clinical value compared with the Alberta Stroke Program E arly CT Score (ASPECTS) in a large single-institutional patient cohort.” Financial support for this research came from Physician-Scientist Program of the Medical Faculty of the University of Heidelberg.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Boltzmann machines are p resented in a new report. According to news reporting out of the Universitas Muh ammadiyah Malang by NewsRx editors, research stated, “Choosing a specialization was not an easy task for some students, especially for those who lacked confiden ce in their skill and ability.” Our news journalists obtained a quote from the research from Universitas Muhamma diyah Malang: “Specialization in tertiary education became the benchmark and key to success for students’ future careers. This study was conducted to provide th e learning outcomes record, which showed the specialization classification for t he Informatics students by using the data from the students of 2013-2015 who had graduated. The total data was 319 students. The classification method used for this study was the Restricted Boltzmann Machine (RBM). However, the data showed imbalanced class distribution because the number of each field differed greatly. Therefore, SMOTE was added to classify the imbalanced class.” According to the news reporters, the research concluded: “The accuracy obtained from the combination of RBM and SMOTE was 70% with a 0.4 mean squa red error.”
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 Robotic s. According to news reporting originating from Chennai, India, by NewsRx corres pondents, research stated, “Frequency reconfigurable antennas play a prominent r ole in telecommunication technologies. This paper presents a reconfigurable ante nna that could define the stretch properties in association with the intrinsic s train sensing capabilities.” Our news editors obtained a quote from the research from the Department of ECE, “The stretchable resin is synthesized using Magnesium Nitrate Hexahydrate, Alumi nium Nitrate Nanohydrate, the mixture was reduced and polymerized and finally ma de conductive stretchable resin with the help of CNT’s (Carbon Nano Tubes). The solution is characterized by the help of SEM and EDAX measurements. The conducti ng stretchable polymer resin could elongate upto 100% along with t he fabric dielectric, Lycra. The electrical conductivity of the resin is 8 S/m. The precise dimension of the antenna was done with the help of a micro-cutter. T he inverted S shape of the antenna helps to achieve bandwidth. The fabricated an tenna operates within 4GHz and 8GHz with a gain of up to 3.3dB, Front to the Bac k ratio of 7.42. It is experimented by varying the strain to achieve frequency r econfiguration ranging from 0% to 75%. The fabricatio n and characterization of extremely efficient stretchable and reconfigurable ant enna for C band frequency applications are described.”
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 Storrs, Connecticut, by NewsRx editors, research stated, “Monitoring the health of lithium-ion batte ries’ internal components as they age is crucial for optimizing cell design and usage control strategies. However, quantifying component-level degradation typic ally involves aging many cells and destructively analyzing them throughout the a ging test, limiting the scope of quantifiable degradation to the test conditions and duration.” Our news journalists obtained a quote from the research from the University of C onnecticut, “Fortunately, recent advances in physics-informed machine learning ( PIML) for modeling and predicting the battery state of health demonstrate the fe asibility of building models to predict the long-term degradation of a lithium-i on battery cell’s major components using only shortterm aging test data by lever aging physics. In this paper, we present four approaches for building physicsinf ormed machine learning models and comprehensively compare them, considering accu racy, complexity, ease-of-implementation, and their ability to extrapolate to un tested conditions. We delve into the details of each physics-informed machine le arning method, providing insights specific to implementing them on small battery aging datasets. Our study utilizes long-term cycle aging data from 24 implantab le-grade lithium-ion cells subjected to varying temperatures and C-rates over fo ur years.”
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 Machine Learning. According to news reporting originating in London, United Kingdom, by NewsRx journalists, research stated, “Correct pressure broadening is essential for modelling radiative transfer in atmospheres, however data are lacking for th e many exotic molecules expected in exoplanetary atmospheres. Here we explore mo dern machine learning methods to mass produce pressure broadening parameters for a large number of molecules in the ExoMol data base.” Financial supporters for this research include European Research Council (ERC), STFC training grant.
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 reporting originating from Waterloo, Ca nada, by NewsRx correspondents, research stated, “The adoption of Electric Vehic les (EVs) and solar Photovoltaic (PV) generation by households is rapidly and si gnificantly increasing. Utilities are facing the challenge of efficiently managi ng EV and PV resources to help mitigate the undesirable effects on grid operatio n.” Financial support for this research came from NSERC-Alliance/OCE-VIP. Our news editors obtained a quote from the research from the University of Water loo, “Existing approaches to solve these issues depend on accurate but hard to p redict behavior of EVs and PVs, detailed knowledge of customers, and grid infras tructure, all of which complicate the effective deployment of these resources. M otivated by these practical challenges and in collaboration with industry partne rs working on addressing these issues, this paper proposes a two-level data-driv en smart controller for EV charging in distribution systems. The controller is m odeled as a Deep Reinforcement Learning (DRL) agent, which coordinates the charg ing rates of multiple EVs connected to a realistic residential feeder with high penetration of PV generation. The first level coordinates the aggregated EV load at distribution Medium Voltage (MV) level to provide Demand Response (DR) servi ces; at the Low Voltage (LV) level it aims to maximize the EVs’ state of charge at departure while avoiding the overloading of the MV/LV distribution transforme rs.”
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 intelligent syste ms have been published. According to news reporting out of Queensland University of Technology by NewsRx editors, research stated, “Adversarial attacks pose a s ignificant threat to deep learning models, specifically medical images, as they can mislead models into making inaccurate predictions by introducing subtle dist ortions to the input data that are often imperceptible to humans. Although adver sarial training is a common technique used to mitigate these attacks on medical images, it lacks the flexibility to address new attack methods and effectively i mprove feature representation.” Funders for this research include Queensland University of Technology; Australia n Research Council.
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 Machine Learning. According to news reporting from Hubei, People’s Republic of China, b y NewsRx journalists, research stated, “The shear strengthening of reinforced co ncrete (RC) beams using near -surface mounted (NSM) fibre -reinforced polymer (F RP) bars/strips has gained substantial research attention worldwide. However, ow ing to the complex failure mechanisms and many influencing parameters, the shear capacities of NSM FRP shear -strengthened beams are difficult to predict.” Funders for this research include National Natural Science Foundation of China ( NSFC), Key Research and Development Program of Hubei Province of China.
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 reporting originating from Benha University b y NewsRx correspondents, research stated, “The main topic of this paper is how t o develop pick and place delta robot with high efficiency mechanical parts and p rosaically assemble it, additionally built electrical wiring diagram all of this supported by vision computer system.” Our news editors obtained a quote from the research from Benha University: “The system has a lowcost part and solves many problems to build this robot. Electri cal section has two main components master and slave the master is raspberry pi and slave is Arduino, master is used to vision detect object and Arduino is used to invers kinematics equation, move motors to target position, control in hydra ulic system to pull the object with suction cup. The process of vison system is passing through some steps, detect the object by color range, contouring box the n send the real position to an Arduino. The experimental process proved the effe ctiveness and accuracy of the delta robot vision system in the sorting process f rom conveyor system.”
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 Robotic s. According to news reporting originating from Beijing, People’s Republic of Ch ina, by NewsRx correspondents, research stated, “This article investigates the f ormation switching problem of a group of autonomous tracked mobile robots (ATMRs ) traveling in unknown obstacle environments. Firstly, a novel formation structu re model of virtual leader-leader-follower is designed, where the leader tracks the virtual leader determined by a reference trajectory, while the followers tra ck their desired positions dictated by the virtual leader.” Funders for this research include Science and Technology Project of Fire and Res cue Bureau of Emergency Management Department, Beijing Chaoyang District Collabo rative Innovation Project.
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