查看更多>>摘要：Research findings on Robotics are disc ussed in a new report. According to news reporting out of Shaanxi, People's Repu blic of China, by NewsRx editors, research stated, "Industrial robots are promis ing and competitive alternatives for performing machining operations due to thei r advantages of good mobility, high flexibility and low cost. However, the appli cation of industrial robots in the field of high-precision machining such as gri nding is hugely limited by the characteristic of weak stiffness." Funders for this research include National Natural Science Foundation of China ( NSFC), Natural Science Foundation of Shaanxi Province, Key Research and Developm ent Program of Shaanxi, Open Fund of Hubei Provincial Key Laboratory of Modern M anufacturing Quality Engineering.
查看更多>>摘要：New study results on robotics have bee n published. According to news reporting out of Bremen, Germany, by NewsRx edito rs, research stated, "Mechanical Scanning Sonars (MSS) are popular underwater se nsors for Unmanned Underwater Vehicles (UUV) due to their low cost, small size, and low power consumption." Financial supporters for this research include Deutsche Forschung Gemeinschaft ( Dfg) in The Project ‘‘unconstrained Synthetic Aperture Sonar (U-sas),''; Federal Ministry For Economic Affairs And Climate Action (Bmwk) in The Project ‘‘triple -gnc.''.
查看更多>>摘要：Research findings on artificial intell igence are discussed in a new report. According to news originating from Florenc e, Italy, by NewsRx editors, the research stated, "Model-driven development (MDD ) in the Artificial Intelligence of Things (AIoT) domain faces significant chall enges in ensuring the consistency and preservation of model properties during tr ansformations, often leading to system inconsistencies." Financial supporters for this research include Tecnologico De Monterrey, Mexico; King Saud University, Riyadh, Saudi Arabia.
查看更多>>摘要：New research on Machine Learning is th e subject of a report. According to news reporting originating in Guangxi, Peopl e's Republic of China, by NewsRx journalists, research stated, "Lung adenocarcin oma (LUAD) is a malignancy affecting the respiratory system. Most patients are d iagnosed with advanced or metastatic lung cancer due to the fact that most of th eir clinical symptoms are insidious, resulting in a bleak prognosis." The news reporters obtained a quote from the research from the Second Affiliated Hospital of Guilin Medical University, "Given that abnormal reprogramming of as paragine metabolism (AM) has emerged as an emerging therapeutic target for anti- tumor therapy. However, the clinical significance of abnormal reprogramming of A M in LUAD patients is unclear. In this study, we collected 864 asparagine metabo lism-related genes (AMGs) and used a machine-learning computational framework to develop an asparagine metabolism immunity index (AMII) for LUAD patients. Throu gh the utilization of median AMII scores, LUAD patients were segregated into eit her a low-AMII group or a high-AMII group. We observed outstanding performance o f AMII in predicting survival prognosis in LUAD patients in the TCGA-LUAD cohort and in three externally independently validated GEO cohorts (GSE72094, GSE37745 , and GSE30219), and poorer prognosis for LUAD patients in the high-AMII group. The results of univariate and multivariate analyses showed that AMII can be used as an independent risk factor for LUAD patients. In addition, the results of C- index analysis and decision analysis showed that AMII-based nomograms had a robu st performance in terms of accuracy of prognostic prediction and net clinical be nefit in patients with LUAD. Excitingly, LUAD patients in the low-AMII group wer e more sensitive to commonly used chemotherapeutic drugs."
查看更多>>摘要：Research findings on machine translati on are discussed in a new report. According to news reporting originating from S handong, People's Republic of China, by NewsRx correspondents, research stated, "With the acceleration of globalization, machine translation (MT) plays an incre asingly prominent role in cross-language communication." The news journalists obtained a quote from the research from Qilu Medical Univer sity: "However, how to evaluate the quality of machine translation, especially c onsidering the nuances in different semantic contexts, remains a challenge. This paper proposes an automatic scoring model for machine translation quality based on deep transfer learning, which aims to accurately perceive and evaluate the q uality of translated texts in different semantic contexts. Firstly, a pre-traine d deep neural network model is used to extract the semantic feature representati on of the sentences in the source language and the target language, so as to cap ture the semantic information of the sentences. Then, deep transfer learning is used to map the semantic features of source language and target language into th e shared feature space. By sharing feature space, an effective relationship is e stablished between the semantic representations of two languages, so as to achie ve cross-language quality evaluation. The experimental results show that the mod el has made significant progress in evaluating the quality of machine translatio n."
查看更多>>摘要：Data detailed on Robotics have been pr esented. According to news reporting out of Boston, Massachusetts, by NewsRx edi tors, research stated, "Despite the current surge of interest in autonomous robo tic systems, robot activity recognition within restricted indoor environments re mains a formidable challenge. Conventional methods for detecting and recognizing robotic arms' activities often rely on vision-based or light detection and rang ing (LiDAR) sensors, which require line-of-sight (LoS) access and may raise priv acy concerns, for example, in nursing facilities." Funders for this research include Office of Naval Research, National Science Fou ndation (NSF), United States Department of Homeland Security (DHS), US Army Rese arch Laboratory (ARL).
查看更多>>摘要：Current study results on Machine Learn ing have been published. According to news reporting from Birmingham, United Kin gdom, by NewsRx journalists, research stated, "An onboard facility shows promise in efficiently converting floating plastics into valuable products, such as met hanol, negating the need for regional transport and land-based treatment. Gasifi cation presents an effective means of processing plastics, requiring their trans formation into gasification-compatible feedstock, such as hydrochar." Financial support for this research came from Marie Sklstrok;odowska Curie Actio ns Fellowships by The European Research Executive Agency, Belguim. The news correspondents obtained a quote from the research from Aston University , "This study explores hydrochar composition modeling, utilizing advanced algori thms and rigorous analyses to unravel the intricacies of elemental composition r atios, identify influential factors, and optimize hydrochar production processes . The investigation begins with decision tree modeling, which successfully captu res relationships but encounters overfitting challenges. Nevertheless, the decis ion tree vote analysis, particularly for the H/C ratio, yielding an impressive R 2 of 0.9376. Moreover, the research delves into the economic feasibility of the marine plastics-to-methanol process. Varying payback periods, driven by fluctuat ing methanol prices observed over a decade (ranging from 3.3 to 7 yr for hydroch ar production plants), are revealed. Onboard factories emerge as resilient solut ions, capitalizing on marine natural gas resources while striving for near-net-z ero emissions."
查看更多>>摘要：A new study on Machine Learning-Comp utational Intelligence is now available. According to news reporting from Shenzh en, People's Republic of China, by NewsRx journalists, research stated, "Tensor- oriented multi-view subspace clustering has achieved significant strides in asse ssing highorder correlations of multi-view data. Nevertheless, most of existing investigations are typically hampered by the two flaws: (1) Self-representation based tensor subspace learning usually induces high time and space complexity, and is limited in perceiving nonlinear local structure in the embedding space. ( 2) The tensor singular value decomposition model redistributes each singular val ue equally without considering the diverse importance among them." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of Guangdong Province, N ational Natural Science Foundation of China Joint Fund Project Key Support Proje ct, Guangdong Provincial Key Laboratory of Novel Security Intelligence Technolog ies.
查看更多>>摘要：Research findings on artificial intell igence are discussed in a new report. According to news reporting out of the Uni versity of Ha'il by NewsRx editors, research stated, "The utilization of various tools by researchers to enhance heat transfer (HT) in fluid flow is steadily on the rise. These tools encompass both active and passive methods." Our news journalists obtained a quote from the research from University of Ha'il : "This study involved an experimental examination of HT and fluid flow within a micro-fin tube. The strategies were implemented to improve Nu: ferrofluid, micr o-fins, and a rotating magnetic field. Before implementation, the magnetic ferro fluid was evaluated for particle size and stability. The results were validated, demonstrating a good correlation with the anticipated outcomes. The use of a mi crofin tube and ferrofluid can enhance HT about 7-14 % and 7-22 % , respectively. Additionally, a rotating magnetic field can improve HT by approx imately 10%-37 %."
查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news originating from Beijing, People's Republic o f China, by NewsRx correspondents, research stated, "Precision glass molding (PG M) is an effective approach to manufacturing infrared chalcogenide glass (ChG) a spherical lens with complex shapes. However, infrared ChG aspherical lens often experiences form error in the designed profile and the final profile obtained by PGM." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Science and Technology Major Project of Jiangxi Province.
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