查看更多>>摘要：Investigators publish new report on robotics. According to news reporting from Chicago, Illinois, by NewsRx journalists, research stated, "Designing robotic systems that can change their physical form factor as well as their compliance to adapt to environmental constraints remains a major conceptual and technical challenge." The news reporters obtained a quote from the research from University of Chicago: "To address this, we introduce the Granulobot, a modular system that blurs the distinction between soft, modular, and swarm robotics. The system consists of gear-like units that each contain a single actuator such that units can self-assemble into larger, granular aggregates using magnetic coupling. These aggregates can reconfigure dynamically and also split into subsystems that might later recombine. Aggregates can self-organize into collective states with solid- and liquid-like properties, thus displaying widely differing compliance. These states can be perturbed locally via actuators or externally via mechanical feedback from the environment to produce adaptive shape-shifting in a decentralized manner. This, in turn, can generate locomotion strategies adapted to different conditions."
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting from Beijing, People's Republic of China, by NewsRx journalists, research stated, "Anaerobic fermentation is an effective method to harvest volatile fatty acids (VFAs) from waste activated sludge (WAS). Accurately predicting and optimizing VFAs production is crucial for anaerobic fermentation engineering." The news correspondents obtained a quote from the research from Beijing Forestry University, "In this study, we developed machine learning models using two innovative strategies to precisely predict the daily yield of VFAs in a laboratory anaerobic fermenter. Strategy-1 focuses on model interpretability to comprehend the influence of variables of interest on VFAs production, while Strategy-2 takes into account the cost of variable acquisition, making it more suitable for practical applications in prediction and optimization. The results showed that Support Vector Regression emerged as the most effective model in this study, with testing R values of 0.949 and 0.939 for the two strategies, respectively. We conducted feature importance analysis to identify the critical factors that influence VFAs production. Detailed explanations were provided using partial dependence plots and Shepley Additive Explanations analyses. To optimize VFAs production, we integrated the developed model with optimization algorithms, resulting in a maximum yield of 2997.282 mg/L. This value was 45.2 % higher than the average VFAs level in the operated fermenter."
查看更多>>摘要：Data detailed on Artificial Intelligence have been presented. According to news reporting originating from Swansea, United Kingdom, by NewsRx correspondents, research stated, "PurposeThe technology acceptance model (TAM) is a widely used framework explaining why users accept new technologies. Still, its relevance is questioned because of evolving consumer behavior, demographics and technology." The critical evaluation encompasses its historical trajectory, evolutionary growth, identified limitations and, more specifically, its relevance in the context of hospitality and tourism research. FindingsTAM's limitations within the hospitality and tourism context revolve around its individualcentric perspective, limited scope, static nature, cultural applicability and reliance on self-reported measures. Research limitations/implicationsTo optimize TAM's efficacy, the authors propose several strategic recommendations. These include embedding TAM within the specific context of the industry, delving into TAM-driven artificial intelligence adoption, integrating industry-specific factors, acknowledging cultural nuances and using comprehensive research methods, such as mixed methods approach."
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Anhui, People's Republic of China, by NewsRx correspondents, research stated, "Inferring consumers' preferences provides a better understanding of their purchase behavior, which is very important for business success, e.g., recommendation systems and targeted advertising. In this paper, we propose an explainable machine learning approach, namely Multi-view Latent Dirichlet Allocation (MVLDA), to infer and interpret consumer preferences." Financial supporters for this research include Foundation of China, Fundamental Research Funds for the Central Universities, National Engineering Laboratory for Big Data Distribution and Ex-change Technologies.
查看更多>>摘要：Fresh data on robotics are presented in a new report. According to news reporting originating from Cologne, Germany, by NewsRx correspondents, research stated, "In our society interaction with robots is becoming more and more frequent since robots are not only used in the industry, but increasingly often in assistance and in health system." The news editors obtained a quote from the research from University of Cologne: "Perception of robots and their movements is crucial for their acceptance. Here we shortly review basic mechanisms of perception of actions, and then of perception of robotic and human movements. The literature demonstrates that there are commonalities, but also differences in the perception of human and robotic movements. Especially interesting are biologic gender differences in the perception of robotic movements. The results show that males seem to be more sensitive to the differences between robotic and anthropomorphic movements, whereas females seem not to perceive such differences. However, females transfer more anthropomorphic features to robotic movements."
查看更多>>摘要：Investigators discuss new findings in Bioengineering - Combinatorial Materials. According to news originating from Albuquerque, New Mexico, by NewsRx correspondents, research stated, "Advancements in high-throughput data generation and physics-informed artificial intelligence and machine-learning algorithms are rapidly challenging the status quo for how materials data is collected, analyzed, and communicated with the world." Funders for this research include United States Department of Energy (DOE), United States Department of Energy (DOE).
查看更多>>摘要：Investigators publish new report on Machine Learning. According to news originating from Nijmegen, Netherlands, by NewsRx correspondents, research stated, "In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement." Financial supporters for this research include Netherlands Organization for Scientific Research (NWO), Slovenian Research Agency - Slovenia, Spanish Government, ICSC - Centro Nazionale di Ricerca in High Performance Computing, NRF SARChI, Big Data and Quantum Computing - European Union, Netherlands Organization for Scientific Research (NWO), NRF Funding agencies.
查看更多>>摘要：Current study results on artificial intelligence have been published. According to news originating from Beijing, People's Republic of China, by NewsRx editors, the research stated, "Sandstonehosted uranium deposits are indeed significant sources of uranium resources globally." Financial supporters for this research include Ministry of Science And Technology of The People's Republic of China. The news journalists obtained a quote from the research from China University of Geosciences: "They are typically found in sedimentary basins and have been extensively explored and exploited in various countries. They play a significant role in meeting global uranium demand and are considered important resources for nuclear energy production. Erlian Basin, as one of the sedimentary basins in northern China, is known for its uranium mineralization hosted within sandstone formations. In this research, machine learning (ML) methodology was applied to mineral prospectivity mapping (MPM) of the metallogenic zone in the Manite depression of the Erlian Basin. An ML model of 92% accuracy was implemented with the random forest algorithm. Additionally, the confusion matrix and receiver operating characteristic curve were used as model evaluation indicators."
查看更多>>摘要：Investigators publish new report on robotics. According to news reporting from Guangzhou, People's Republic of China, by NewsRx journalists, research stated, "Insects exhibit remarkable abilities in navigating complex natural environments, whether it be evading predators, capturing prey, or seeking out con-specifics, all of which rely on their compact yet reliable neural systems." Our news correspondents obtained a quote from the research from Guangzhou University: "We explore the field of bio-inspired robotic vision systems, focusing on the locust inspired Lobula Giant Movement Detector (LGMD) models. The existing LGMD models are thoroughly evaluated, identifying their common meta-properties that are essential for their functionality. This article reveals a common framework, characterized by layered structures and computational strategies, which is crucial for enhancing the capability of bio-inspired models for diverse applications. The result of this analysis is the Strategic Prototype, which embodies the identified meta-properties. It represents a modular and more flexible method for developing more responsive and adaptable robotic visual systems. The perspective highlights the potential of the Strategic Prototype: LGMD-Universally Prototype (LGMD-UP), the key to re-framing LGMD models and advancing our understanding and implementation of bio-inspired visual systems in robotics."
查看更多>>摘要：A new study on Robotics - Field Robotics is now available. According to news reporting originating in Hangzhou, People's Republic of China, by NewsRx journalists, research stated, "Multisensor fusion-based localization technology has achieved high accuracy in autonomous systems. How to improve the robustness is the main challenge at present." Financial support for this research came from National Natural Science Foundation of China (NSFC). The news reporters obtained a quote from the research from Zhejiang University, "The most commonly used LiDAR and camera are weather-sensitive, while the frequency-modulated continuous wave Radar has strong adaptability but suffers from noise and ghost effects. In this paper, we propose a heterogeneous localization method called Radar on LiDAR Map, which aims to enhance localization accuracy without relying on loop closures by mitigating the accumulated error in Radar odometry in real time. To accomplish this, we utilize LiDAR scans and ground truth paths as Teach paths and Radar scans as the trajectories to be estimated, referred to as Repeat paths. By establishing a correlation between the Radar and LiDAR scan data, we can enhance the accuracy of Radar odometry estimation. Our approach involves embedding the data from both Radar and LiDAR sensors into a density map. We calculate the spatial vector similarity with an offset to determine the corresponding place index within the candidate map and estimate the rotation and translation. To refine the alignment, we utilize the Iterative Closest Point algorithm to achieve optimal matching on the LiDAR submap. The estimated bias is subsequently incorporated into the Radar SLAM for optimizing the position map. We conducted extensive experiments on the Mulran Radar Data set, Oxford Radar RobotCar Dataset, and our data set to demonstrate the feasibility and effectiveness of our proposed approach. Our proposed scan projection descriptors achieves homogeneous and heterogeneous place recognition and works much better than existing methods. Its application to the Radar SLAM system also substantially improves the positioning accuracy."
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