查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Nanotechnology - Nanocomposi tes are discussed in a new report. According to news originating from San Antoni o, Texas, by NewsRx correspondents, research stated, “The bioinspired nacre or b one structure represents a remarkable example of tough, strong, lightweight, and multifunctional structures in biological materials that can be an inspiration t o design bioinspired high-performance materials. The bioinspired structure consi sts of hard grains and soft material interfaces.” Our news journalists obtained a quote from the research from the University of T exas San Antonio, “While the material interface has a very low volume percentage , its property has the ability to determine the bulk material response. Machine learning technology nowadays is widely used in material science. A machine learn ing model was utilized to predict the material response based on the material in terface properties in a bioinspired nanocomposite. This model was trained on a c omprehensive dataset of material response and interface properties, allowing it to make accurate predictions. The results of this study demonstrate the efficien cy and high accuracy of the machine learning 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 Ro botics. According to news originating from Jilin, People’s Republic of China, by NewsRx correspondents, research stated, “This study is concerned with an observ er-based independent joint control scheme for a coupled two-link rigid-flexible robotic manipulator considering the effects of actuator saturation and external disturbances. A distributed parameter model of the robotic manipulator system de scribed by ordinary and partial differential equation (ODE-PDE) is derived by us ing Hamilton’s Principle.” Funders for this research include National Natural Science Foundation of China ( NSFC), Department of Science and Technology of Jilin Province.
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 artificial in telligence have been published. According to news reporting originating from the University of Glasgow by NewsRx correspondents, research stated, “Fast, efficie nt and accurate triggers are a critical requirement for modern high energy physi cs experiments given the increasingly large quantities of data that they produce .” The news correspondents obtained a quote from the research from University of Gl asgow: “The CEBAF Large Acceptance Spectrometer (CLAS12) employs a highly effici ent electron trigger to filter the amount of data recorded by requiring at least one electron candidate in each event, at the cost of a low purity in electron i dentification. However, machine learning algorithms are increasingly employed fo r classification tasks such as particle identification due to their high accurac y and fast processing times. In this proceeding we present recently published wo rk that showed how a convolutional neural network could be deployed as a Level 3 electron trigger at CLAS12.”
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 Machine Translation. According to news originating from Xiamen, People’s Republi c of China, by NewsRx correspondents, research stated, “Despite the increasing p opularity of machine translation in second language (L2) writing, the theoretica l perspectives and complex factors shaping its use remain under synthesized. Thi s article reviews research on machine translation use in L2 writing to identify major models and factors that shape teachers’ and students’ employment of machin e translation.” Our news journalists obtained a quote from the research from JiMei University, “ Theoretical perspectives underpinning machine translation research are first syn thesized to categorize machine translation into three models: a linguistic proce ssor, a mediational artifact, and a translanguaging process. What then reviewed are empirical studies, revealing a predominant focus on linguistic factors in te rms of how machine translation shapes L2 writing. More recent research has also examined person-related factors and taken the effectiveness of machine translati on as conditioning upon individual differences of teachers and students. Context ual factors in interpersonal, instructional, and institutional settings and ideo logical factors are also identified. A conceptual framework is then developed to illuminate the interrelatedness of the identified factors during the process of using machine translation. The study argues for a need to avoid taking machine translation as a politically neutral participant in L2 writing.”
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting out of London, United Kingdom, by New sRx editors, research stated, “In robotic-assisted minimally invasive surgery, s urgeons often use intra-operative ultrasound to visualise endophytic structures and localise resection margins. This must be performed by a highly skilled surge on.” Financial supporters for this research include Wellcome / EPSRC Centre for Inter ventional and Surgical Sciences, Engineering and Physical Sciences Research Coun cil, Royal Academy of Engineering Chair in Emerging Technologies Scheme.
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 Ro botics. According to news reporting originating in Champaign, Illinois, by NewsR x journalists, research stated, “Successful deployment of mobile robots in unstr uctured domains requires an understanding of the environment and terrain to avoi d hazardous areas, getting stuck, and colliding with obstacles. Traversability e stimation-which predicts where in the environment a robot can travel-is one prom inent approach that tackles this problem.” Financial support for this research came from National Robotics Initiative 2.0. The news reporters obtained a quote from the research from the University of Ill inois, “Existing geometric methods may ignore important semantic considerations, while semantic segmentation approaches involve a tedious labeling process. Rece nt self-supervised methods reduce labeling tedium, but require additional data o r models and tend to struggle to explicitly label untraversable areas. To addres s these limitations, we introduce a weakly-supervised method for relative traver sability estimation. Our method involves manually annotating the relative traver sability of a small number of point pairs, which significantly reduces labeling effort compared to traditional segmentation-based methods and avoids the limitat ions of self-supervised methods. We further improve the performance of our metho d through a novel cross-image labeling strategy and loss function.”
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting out of A’Sharq iyah University (ASU) by NewsRx editors, research stated, “The present study aim s to explore the factors influencing the utilization of Information audit in the context of Egypt and Jordan, with specific attention given to the role of artif icial intelligence (AI). A sample of 443 respondents participated in the study, and data collection was carried out through a non-probability convenience and sn owball sampling approach.” The news journalists obtained a quote from the research from A’Sharqiyah Univers ity (ASU): “The findings reveal that internal determinants are positively associ ated with the intention to adopt Information audit technologies, exhibiting a si gnificant impact with a beta coefficient of +0.45 (P-value <0.01), and the perceived benefits associated with their implementation. Moreove r, the study underscores the critical influence of artificial intelligence, with dimensions such as cloud computing, data mining, and e-commerce enhancing the p erceived advantages (b = 0.35, P-value <0.01) and fosterin g the intent to use Information audit technologies (b = 0.22, P-value <0.01). Additionally, there is a robust positive correlation between the intenti on to use Information audit technologies and their actual usage, where the prese nce of AI amplifies this association, indicated by a beta value of 0.48 (P-value <0.01). This study significantly enriches the existing bo dy of knowledge by delineating the determinants of Information audit usage, part icularly within the Middle Eastern context, and highlights the pivotal role of a rtificial intelligence in shaping these dynamics. The study provides empirical e vidence on the factors influencing the intention to use Information audit techno logies, the perceived benefits associated with their usage, and the actual utili zation of Information audit. Its originality lies in its focus on the underexplo red Middle East region within the Information audit literature and its investiga tion of the influence of artificial intelligence on Information audit. The impli cations of this study are significant for practitioners, auditors, and policymak ers operating within the Middle East region. The findings suggest that firms sho uld allocate sufficient support and resources to encourage the adoption of Infor mation audit technologies.”
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on Machine Learn ing. According to news reporting originating from Changchun, People’s Republic o f China, by NewsRx correspondents, research stated, “Accurate source characteriz ation and transport parameter estimation is important when seeking to predict th e spatiotemporal distribution of dense non-aqueous phase liquid (DNAPL) contamin ants in groundwater. However, this is a complex multimodal search problem prone to equifinality and premature convergence, which leads to considerable error.” Funders for this research include National Natural Science Foundation of China ( NSFC), Science and Technology Research Project of Jilin Provincial Education Dep artment.
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting from Newcastle, Australia, by NewsR x journalists, research stated, “Integrating machine learning (ML) methods in ed ucational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment a nd providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML approaches used for educati onal data analysis in the last decade and provided recommendations for further r esearch.” Financial support for this research came from The University of Newcastle (Austr alia). The news correspondents obtained a quote from the research from the University o f Newcastle, “Using a systematic literature review (SLR), we examined 77 publica tions from two large and high-impact databases for educational research using bi bliometric mapping and evaluative review analysis. Our results suggest that the top five most frequently used keywords were similar in both databases. The major ity of the publications (88%) utilised supervised ML approaches for predicting students’ performances and finding learning patterns. These methods include decision trees, support vector machines, random forests, and logistic re gression. Semi-supervised learning methods were less frequently used, but also d emonstrated promising results in predicting students’ performance.”
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 originating in Minneapolis, M innesota, by NewsRx journalists, research stated, “We address a motion planning and control problem for mobile robots to satisfy rich, time -varying tasks expre ssed as Signal Temporal Logic (STL) specifications. The specifications may inclu de tasks with nested temporal operators or time -conflicting requirements (e.g., achieving periodic tasks or tasks defined within the same time interval).” The news reporters obtained a quote from the research from the University of Min nesota, “Moreover, the tasks can be defined in locations changing with time (i.e ., dynamic targets), and their future motions are not known a priori. This unpre dictability requires an online control approach which motivates us to investigat e the use of control barrier functions (CBFs). The proposed CBFs take into accou nt the actuation limits of the robots and a feasible sequence of STL tasks. They define time -varying feasible sets of states the system must always stay inside . We show the feasible sequence generation process that even includes the decomp osition of periodic tasks and alternative scenarios due to disjunction operators . The sequence is used to define CBFs, ensuring STL satisfaction. We also show s ome theoretical results on the correctness of the proposed method.”