查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Cerebrovascular Diseas es and Conditions - Stroke is the subject of a report. According to news reporti ng originating in Daqing, People’s Republic of China, by NewsRx journalists, res earch stated, “This study proposed an outcome prediction method to improve the a ccuracy and efficacy of ischemic stroke outcome prediction based on the diversit y of whole brain features, without using basic information about patients and im age features in lesions. In this study, we directly extracted dynamic radiomics features (DRFs) from dynamic susceptibility contrast perfusion-weighted imaging (DSCPWI) and further extracted static radiomics features (SRFs) and static enco ding features (SEFs) from the minimum intensity projection (MinIP) map, which wa s generated from the time dimension of DSC-PWI images.” The news reporters obtained a quote from the research from Northeast Petroleum U niversity, “After selecting whole brain features F from the combinations of DRFs , SRFs, and SEFs by the Lasso algorithm, various machine and deep learning model s were used to evaluate the role of F in predicting stroke outcomes. The experim ental results show that the feature F generated from DRFs, SRFs, and SEFs (Resne t 18) outperformed other single and combination features and achieved the best m ean score of 0.971 both on machine learning models and deep learning models and the 95% CI were (0.703, 0.877) and (0.92, 0.983), respectively. Be sides, the deep learning models generally performed better than the machine lear ning models.”
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 Ar tificial Intelligence. According to news reporting originating from Suzhou, Peop le’s Republic of China, by NewsRx correspondents, research stated, “Traffic meas urement is the bedrock of the next-generation network systems. While it plays a crucial role in bringing fundamental data and support to core network functions, it also confronts the challenge of meeting the diverse demands of new network t raffic characteristics and emerging applications.” Our news editors obtained a quote from the research from Soochow University, “Th e network-wide measurement has received more and more attention. Given that big network data is distributed in nature, it is essential to aggregate the views of multiple measurement points to build a network-wide perception of traffic. Anot her latest trend involves artificial intelligence technologies that allow seamle ss aggregation of multifaceted network traffic data to advance traffic data anal ysis and support related applications.” According to the news editors, the research concluded: “Nonetheless, a gap remai ns in existing methodologies, which often fail to fully address the diverse dema nds of network traffic measurement in this evolving landscape.”
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 out of the Technische Univer sitat Dortmund by NewsRx editors, research stated, “Synergies between MAchine le arning, Real-Time analysis and Hybrid architectures for efficient Event Processi ng and decision-making (SMARTHEP) is a European Training Network, training a new generation of Early Stage Researchers (ESRs) to advance real-time decision-maki ng, driving data-collection and analysis towards synonymity.” Our news journalists obtained a quote from the research from Technische Universi tat Dortmund: “SMARTHEP brings together scientists from major LHC collaborations at the frontiers of real-time analysis (RTA) and key specialists from computer science and industry. By solving concrete problems as a community, SMARTHEP will further the adoption of RTA techniques, enabling future High Energy Physics (HE P) discoveries and generating impact in industry. ESRs will contribute to Europe an growth, leveraging their hands-on experience in machine learning and accelera tors towards commercial deliverables in fields that can profit most from RTA, e. g., transport, manufacturing, and finance.”
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 - Androids are presented in a new report. According to news reporting originating from Nanjing, People’s Republic of China, by NewsRx correspondents, research stated, “In the process of robot research and development, due to the vulnerability of hardware, simulation environment is often used to verify and test algorithms first. RoboC up3D simulation environment is developed based on open dynamic engine, and the h umanoid robot NAO is modeled as the main robot, which provides a simulation plat form for humanoid robot researchers to study robot movements.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from Nanjing University, “At the same time, it is also the official platform of RoboCup 3D events. Under the rules of soccer robot competition, it is helpful for the research of multi-robo ts, especially multi-humanoid robots’ cooperation strategy. This paper summarize s the related research in RoboCup3D simulation environment, and first introduces the basic problems existing in this simulation environment. Secondly, the resea rch of robot motion generation and optimization based on model and non-model in simulation environment is introduced respectively. Then, it introduces the relat ed research of cooperation strategy design of multi-humanoid robots under RoboCu p3D rules, including positioning, dynamic role assignment, etc.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Drugs and Therapies - Personalized Medicine is the subject of a report. According to news reporting fr om Strassen, Luxembourg, by NewsRx journalists, research stated, “Tools for pred icting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital morta lity post-SARS-CoV-2 infection.” Funders for this research include European Commission, Fonds National de la Rech erche Luxembourg, Italian Ministry of Health Projects.
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 computa tional intelligence. According to news reporting from Kanagawa, Japan, by NewsRx journalists, research stated, “The direct optimization of ship hull designs usi ng deep learning algorithms is increasingly expected, as it proposes optimizatio n directions for designers almost instantaneously, without relying on complex, t ime-consuming, and expensive hydrodynamic simulations.” Funders for this research include Japan Marine United Corporation. The news journalists obtained a quote from the research from Yokohama National U niversity: “In this study, we proposed a GAN-based 3D ship hull design optimizat ion method. We eliminated the dependence on hydrodynamic simulations by training a separate model to predict ship performance indicators. Instead of a standard discriminator, we applied a relativistic average discriminator to obtain better feedback regarding the anomalous designs. We add two new loss functions for the generator: one restricts design variability, and the other sets improvement targ ets using feedback from the performance estimation model.”
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 new report. According to news reporting originating from N ajran, Saudi Arabia, by NewsRx correspondents, research stated, “Over the years, building appliances have become the major energy consumers to improve indoor ai r quality and occupants’ lifestyles.” Funders for this research include Deanship of Scientific Research At Najran Univ ersity For Funding This Work Under The Distinguished Research Funding Program.The news journalists obtained a quote from the research from Najran University: “The primary energy usage in building sectors, particularly lighting, Heating, V entilation, and Air conditioning (HVAC) equipment, is expected to double in the upcoming years due to inappropriate control operation activities. Recently, seve ral researchers have provided an automated solution to turn HVAC and lighting on when the space is being occupied and off when the space becomes vacant. Previou s studies indicate a lack of publicly accessible datasets for environmental sens ing and suggest developing holistic models that detect buildings’ occupancy. Add itionally, the reliability of their solutions tends to decrease as the occupancy grows in a building. Therefore, this study proposed a machine learning-based fr amework for smart building occupancy detection that considered the lighting para meter in addition to the HVAC parameter used in the existing studies. We employe d a parametric classifier to ensure a strong correlation between the predicting parameters and the occupancy prediction model.”
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 ar tificial intelligence. According to news reporting out of Shanxi, People’s Repub lic of China, by NewsRx editors, research stated, “In order to solve the problem s of business English translation teaching, a corpus-based teaching model is pro posed.” Our news reporters obtained a quote from the research from Shanxi Normal Univers ity: “The API and web crawler are used to collect data from the business English corpus, and the overall corpus structure design is completed according to the a cquired data. The corpus is pre-processed with lexical processing, theme extract ion, category labeling, and other operations to ensure the feasibility of the co rpus. The limitations of traditional business English translation teaching are h ighlighted, and the structure and implementation process of the corpus-based bus iness English translation teaching model are thoroughly examined. The research s ubjects are selected, and experimental comparisons are applied empirically to an alyze the corpus-based business English translation teaching. The data show that the mean translation score of the experimental group increased by 8.1247.”
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 reporting out of Wuhan, People’s Republic of China, by NewsRx edi tors, research stated, “Robotic manipulators play a pivotal role in modern intel ligent manufacturing and unmanned production systems, often tasked with executin g specific paths accurately. However, the input of the robotic manipulators is t rajectory which is a path with time information.” Financial supporters for this research include The Key R&D Program of Hubei Province. The news reporters obtained a quote from the research from Huazhong University o f Science and Technology: “The resulting core technology is trajectory planning methods which are broadly classified into two categories: maximum velocity curve (MVC) methods and multiphase direct collocation (MPDC)methods. This paper conc entrates on addressing challenges associated with the latter methods. In MPDC me thods, the solving efficiency and accuracy are greatly influenced by the number of discretization nodes. When dealing with systems with complex dynamics, such a s robotic manipulators, striking a balance between solving time and path discret ization errors becomes crucial. We use a mesh refinement (MR) algorithm to find a suitable number of nodes under the premise of ensuring the path discretization error. So, the actual device can effectively implement the planned solutions. N onetheless, the conventional application of the MR algorithm requires solving th e original problem in each iteration; these processes are extremely time-consumi ng and may fail to solve when dealing with a complex dynamic system. As a result , we propose a sequential optimal trajectory planning scheme to solve the proble m efficiently by dividing the original optimal control (OC) problem into two sta ges: path planning (PP) and trajectory planning (TP). In the PP stage, we employ a DC method based on arc length and an MR algorithm to identify key nodes along the specified path. This aims to minimize the approximation error introduced du ring discretization.”
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 - Robotics and Automation. According to news reporting from College Station, T exas, by NewsRx journalists, research stated, “Iterative learning control (ILC) is a method for reducing system tracking or estimation errors over multiple iter ations by using information from past iterations. The disturbance observer (DOB) is used to estimate and mitigate disturbances within the system, while the syst em is being affected by them.” Financial support for this research came from National Science Foundation (NSF). The news correspondents obtained a quote from the research from Texas A& M University, “ILC enhances system performance by introducing a feedforward sign al in each iteration. However, its effectiveness may diminish if the conditions change during the iterations. On the other hand, although DOB effectively mitiga tes the effects of new disturbances, it cannot entirely eliminate them as it ope rates reactively. Therefore, neither ILC nor DOB alone can ensure sufficient rob ustness in challenging scenarios. This study focuses on the simultaneous utiliza tion of ILC and DOB to enhance system robustness. The proposed methodology speci fically targets dynamically different linearized systems performing repetitive t asks. The systems share similar forms but differ in dynamics (e.g. sizes, masses , and controllers). Consequently, the design of learning filters must account fo r these differences in dynamics. To validate the approach, the study establishes a theoretical framework for designing learning filters in conjunction with DOB. The validity of the framework is then confirmed through numerical studies and e xperimental tests conducted on unmanned aerial vehicles (UAVs). Although UAVs ar e nonlinear systems, the study employs a linearized controller as they operate i n proximity to the hover condition.”
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