查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics are disc ussed in a new report. According to news reporting out of Kaifeng, People’s Repu blic of China, by NewsRx editors, research stated, “In the domain of smart robot ics, the refinement of tactile imaging constitutes a seminal element for enhance ment of human-machine interaction (HMI) and enrichment of artificial intelligenc e (AI). This field is confronted with dual challenges of achieving high-sensitiv e pressure detection and precise localization of tactile stimuli.” Funders for this research include National Natural Science Foundation of China ( NSFC), Natural Science Foundation of Henan.
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Cervical Ca ncer is the subject of a report. According to news reporting from Binzhou, Peopl e’s Republic of China, by NewsRx journalists, research stated, “This study was d esigned to determine the diagnostic performance of fluorine-18-fluorodeoxyglucos e (F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics- based machine learning (ML) in the classification of cervical adenocarcinoma (AC ) and squamous cell carcinoma (SCC). Pretreatment F-FDG PET/CT data were retrosp ectively collected from patients who were diagnosed with locally advanced cervic al cancer at two centers.”
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in robotics. According to news originating from Guangdong, People’s Republic of Chi na, by NewsRx correspondents, research stated, “In this study, we designed a gro und-aerial robotic system for the warehouse inventory.” The news editors obtained a quote from the research from Sun Yat-sen University: “The system fully exploits the advantages of UAV and UGV, giving it a stronger competitive edge than previous solutions. The sensors and hardwares used in this system also have modest requirements for computational resources and electrical power, which allows for long-term inventory. An integrated localization framewo rk is established to achieve an accurate localization of this system. We propose d a LiDAR-Inertial Odometry and a targetbased relative localization method to p rovide accurate pose estimation for the entire system. We conducted a series of tests using motion-capture cameras to validate the accuracy and robustness of th e ground-aerial robotic 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 artific ial intelligence. According to news originating from Olsztyn, Poland, by NewsRx editors, the research stated, “Machine learning algorithms are increasingly ofte n used to predict real estate prices because they generate more accurate results than conventional statistical or geostatistical methods.” Our news journalists obtained a quote from the research from University of Warmi a and Mazury Olsztyn: “This study proposes a methodology for incorporating infor mation about the spatial distribution of residuals, estimated by kriging, into s elected machine learning algorithms. The analysis was based on apartment prices quoted in the Polish capital of Warsaw.” According to the news reporters, the research concluded: “The study demonstrated that machine learning combined with geostatistical methods significantly improv es the accuracy of housing price predictions. Local factors that influence housi ng prices can be directly incorporated into the model with the use of dedicated maps.”
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 originating from Jharkhand, India, by NewsRx correspondents, research stated, “Asteroids pose significant threats to Earth, necessitating early detection for potential deflection. Leveraging machin e learning (ML), we classify asteroids into near-Earth Asteroids (particularly A tens, Amors, Apollos, and Apoheles) and non-near-Earth asteroids, further catego rizing them based on hazard potential.” Our news journalists obtained a quote from the research from Indian Institute fo r Technology, “Training the seven models on a comprehensive data set of 4687 ast eroids, we achieve high accuracy in prediction. The predictive capability of the se models is critical for informed decision-making in planetary defense strategi es. We apply different regularization techniques to prevent overfitting and vali date the models using a large unseen data set. A rigorous long-term N-body integ ration spanning 1 Myr is executed utilizing the Mercury N-body integrator to ill uminate the evolution of asteroid properties over extended temporal scales. Foll owing this integration process, the best-performing ML model is employed to clas sify asteroids based on their orbital characteristics and hazardous status respe ctively. Our findings highlight the effectiveness of ML in asteroid classificati on and prediction, paving the way for large-scale applications. By dividing a 1 Myr integration into intervals, we uncover temporal trends in asteroid behaviour , revealing insights into hazard evolution and ejection patterns. Notably, initi ally, hazardous asteroids tend to transition to non-hazardous states over time, elucidating key dynamics in planetary defense. We illustrate these findings thro ugh plotted graphs, providing valuable insights into asteroid dynamics.”
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on are discussed in a new report. According to news reporting originating from Wuhan, People’s Repub lic of China, by NewsRx correspondents, research stated, “Fault diagnosis is vit al for improving the reliability and safety of mechanical equipment. Existing fa ult diagnosis methods require a large number of samples for model training.” Funders for this research include National Natural Science Foundation of China; Interdisciplinary Research Program of Huazhong University of Science And Technol ogy.
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Skin Diseases and Cond itions - Psoriasis is the subject of a report. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Ps oriasis, characterized by chronic inflammation, is a persistent skin condition t hat is notoriously challenging to manage and prone to relapse. Despite significa nt advancements in its treatment, many adverse reactions still occur.” The news correspondents obtained a quote from the research from the Chinese Acad emy of Medical Sciences, “Therefore, exploring the mechanisms behind the occurre nce and development of psoriasis is extremely important. The weighted correlatio n network analysis (WGCNA) algorithm was used to identify phenotype-related gene s in patients with psoriasis. We recruited clinical samples of patients with pso riasis, and used single-cell RNA sequencing (scRNA-seq) to visualize divergent g enes and metabolisms of varied cells for the psoriasis. Various machine-learning methods were used to identify core genes, and molecular docking was used to ana lyze the stability of leptomycin B targeting pituitary tumor transforming 1 (PTT G1). Immunofluorescence (IHC) analysis, multiplex immunofluorescence (mIF) analy sis, and quantitative reverse transcription polymerase chain reaction (qRT-PCR) were used to validate the results. Our results identified 1391 genes associated with the phenotype in patients with psoriasis and highlighted the significant al terations in T-cell functionality observed in the disease by WGCNA. There were n ine distinct cellular clusters in psoriasis analyzed with the aid of scRNA-seq d ata. Each subtype of cell exhibited distinct genetic profiles, functional roles, signaling mechanisms, and metabolic characteristics. Machine-learning methods f urther demonstrated the potential diagnostic value of T cell-derived PTTG1 and i ts relationship with T-cell exhaustion in psoriasis. Lastly, the leptomycin B wa s scrutinized and verified had high stability targeting PTTG1. This study elucid ates the biological basis of psoriasis. At the same time, it was discovered that PTTG1 derived from exhausted T cells serves as a diagnostic biomarker for psori asis.”
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Starkville, Mi ssissippi, by NewsRx editors, research stated, “Artificial insemination (AI) pla ys a critical role in livestock reproduction, with semen quality being essential . In swine, AI primarily uses cool-stored semen adhering to industry standards a ssessed through routine analysis, yet fertility inconsistencies highlight the ne ed for enhanced semen evaluation.” Financial supporters for this research include National Institute of Food And Ag riculture, U.S. Department of Agriculture; Usda-ars Biophotonics.
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in androids. According to news reporting originating from Seoul, South Korea, by Ne wsRx correspondents, research stated, “We envision a telepresence system that en hances remote work by facilitating both physical and immersive visual interactio ns between individuals.” Financial supporters for this research include National Research Foundation of K orea; Korea Institute of Science And Technology (Kist) Institutional Program; In stitute of Information & Communications Technology Planning & Evaluation.
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 from Sheffield, United Kingdom, by NewsRx journa lists, research stated, “Acoustic sensing system deployed on an autonomous platf orm (also referred to as robot) for accurate condition monitoring and fault dete ction in pipes requires the knowledge of wave scattering from various in-pipe fa ults or the robot itself. Existing solutions to estimate wave scattering tend to either be constrained to the plane wave regime or be computationally expensive outside this range.” Funders for this research include Engineering & Physical Sciences Research Council (EPSRC), EPSRC, Grant UKCRIC-National Distributed Water Infrast ructure Facility, European Union (EU).