查看更多>>摘要：Current study results on Robotics have been published. According to news reporting originating from Munich, Germany, by NewsRx correspondents, research stated, “Mobile manipulators are envisioned to serve more complex roles in people’s everyday lives. With recent breakthroughs in large language models, task planners have become better at translating human verbal instructions into a sequence of tasks.” Financial support for this research came from CGIAR. Our news editors obtained a quote from the research from Technical University Munich (TU Munich), “However, there is still a need for a decision-making algorithm that can seamlessly interface with the highlevel task planner to carry out the sequence of tasks efficiently. In this work, building on the idea of nonlinear lexicographic optimization, we propose a novel Hierarchical-Task Model Predictive Control framework that is able to complete sequential tasks with improved performance and reactivity by effectively leveraging the robot’s redundancy. Compared to the state-of-the-art task-prioritized inverse kinematic control method, our approach has improved hierarchical trajectory tracking performance by 42% on average when facing task changes, robot singularity, and reference variations. Compared to a typical single-task architecture, our proposed hierarchical task control architecture enables the robot to traverse a shorter path in task space and achieves an execution time 2.3 times faster when executing a sequence of delivery tasks.”
查看更多>>摘要：Investigators discuss new findings in artificial intelligence. According to news reporting originating from Saskatoon, Canada, by NewsRx correspondents, research stated, “Prosthetic technology has witnessed remarkable advancements, yet challenges persist in achieving autonomous grasping control while ensuring the user’s experience is not compromised.” Funders for this research include Nserc (Natural Sciences And Engineering Research Council of Canada) Create (Collaborative Research And Training Experience) Program. The news correspondents obtained a quote from the research from University of Saskatchewan: “Current electronic prosthetics often require extensive training for users to gain fine motor control over the prosthetic fingers, hindering their usability and acceptance. To address this challenge and improve the autonomy of prosthetics, this paper proposes an automated method that leverages computer vision-based techniques and machine learning algorithms. In this study, three reinforcement learning algorithms, namely Soft ActorCritic (SAC), Deep Q-Network (DQN), and Proximal Policy Optimization (PPO), are employed to train agents for automated grasping tasks. The results indicate that the SAC algorithm achieves the highest success rate of 99% among the three algorithms at just under 200,000 timesteps.”
查看更多>>摘要：New research on Nervous System Diseases and Conditions Hemiplegia is the subject of a report. According to news reporting from Jinan, People’s Republic of China, by NewsRx journalists, research stated, “No study has yet demonstrated the effect of lower limb gait rehabilitation robot treatment combined with acupuncture on stroke patients. To explore the effect of acupuncture combined with lower limb gait rehabilitation robot on walking function in patients with hemiplegia after stroke.” The news correspondents obtained a quote from the research from Shandong Provincial Third Hospital, “Fifty-six patients with hemiplegia after stroke were enrolled and randomly divided into two groups. The control group received regular rehabilitation training and acupuncture therapy; the intervention group was additionally trained by AiWalker-I lower limb gait robot. Both groups received 5 sessions a week for 4 weeks. Walking function parameters were assessed before and after the 4-week treatment. There was no significant difference in all parameters between the two groups in baseline (P >0.05). After 4 weeks of treatment, all parameters including the effectiveness of functional ambulation category (FAC), time up and go test (TUGT) time, Wisconsin gait scale (WGS) score, walking spatiotemporal parameters were all significantly improved in both groups with a significant better effect in the intervention group (P <0.05).”
查看更多>>摘要：Investigators discuss new findings in Robotics Robotics and Automation. According to news reporting originating from Hangzhou, People’s Republic of China, by NewsRx correspondents, research stated, “A novel RGB-based continuous perception garment classification approach is proposed in this letter, with the aim of identifying the correct category of the garment from a set of categories. It has been observed that treating a video of the continuous deformation of cloth as a set of disordered static figures leads to low classification precision.” Financial support for this research came from Natural Science Foundation of Zhejiang Province. Our news editors obtained a quote from the research from Zhejiang University, “On the contrary, investigating the temporal information between frames can significantly improve the quality of extracted features and increase classification performance. In this regard, we propose a hybrid temporal fusion RGBbased algorithm, including an improved image-level shallow temporal feature extraction module (STEM) and a binary-tree fusion module (BiTF) for adaptive feature fusion. STEM incorporates multi-scale optical flow and long-short-term memorised information to capture both static features in every single image and dynamic features in consecutive images. BiTF constructs a tree-shaped structure to fuse an arbitrary number of extracted features in a video.”
查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news originating from Tamil Nadu, India, by NewsRx correspondents, research stated, “There are numerous challenges with existing domestic energy meter reading systems, in constructions, narrow bandwidths, low rates, poor real-time, and slow two-way communications. This paper used an Automatic Meter Reading device with wireless technology to solve the problems.” The news reporters obtained a quote from the research from M. Kumarasamy College of Engineering: “The proposed approach uses the Internet of Things (IoT) to communicate between the Electricity Board and the user section, allowing the customer’s electricity usage and bill information to be transmitted. The customer receives information on bill amounts and payments through IoT. In the past decade, the Indian power sector accomplished a great deal in policy reforms, private sector participation in generation and transmission, and the development of new manufacturing technology and capabilities, still more to accomplish and obstacles to overcome for capitalization. Therefore, the private sectors are very active in investing in various parts of the value chain. Nevertheless, the majority engagement of private investors is taking place in the generation. This trend is driven by de-licensing of generation, fiscal incentives for large-scale capacity increases, and competitive buying of electricity.”
查看更多>>摘要：New research on Surgical Procedures Bronchoscopy is the subject of a report. According to news reporting out of Shanghai, People’s Republic of China, by NewsRx editors, research stated, “Robotic-assisted bronchoscopy (RAB) is a newly developed bronchoscopic technique for the diagnosis of peripheral pulmonary lesions (PPLs). The objective of this meta-analysis was to analyze the diagnostic yield and safety of RAB in patients with PPLs.” Financial support for this research came from Science and Technology Commission of Shanghai Municipality. Our news journalists obtained a quote from the research from the Shanghai Jiao Tong University School of Medicine, “Five databases (PubMed, Embase, Web of Science, CENTRAL, and ClinicalTrials.gov) were searched from inception to April 2023. Two independent investigators screened retrieved articles, extracted data, and assessed the study quality. The pooled diagnostic yield and complication rate were estimated. Subgroup analysis was used to explore potential sources of heterogeneity. Publication bias was assessed using funnel plots and the Egger test. Sensitivity analysis was also conducted to assess the robustness of the synthesized results. A total of 725 lesions from 10 studies were included in this meta-analysis. No publication bias was found. Overall, RAB had a pooled diagnostic yield of 80.4% (95% CI: 75.7%-85.1%). Lesion size of >30 mm, presence of a bronchus sign, and a concentric radial endobronchial ultrasound view were associated with a statistically significantly higher diagnostic yield. Heterogeneity exploration showed that studies using cryoprobes reported better yields than those without cryoprobes (90.0%, 95% CI: 83.2%-94.7% vs. 79.0%, 95% CI: 75.8%-82.2%, p<0.01). The pooled complication rate was 3.0% (95% CI: 1.6%-4.4%).”
查看更多>>摘要：Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Singapore, Singapore, by NewsRx correspondents, research stated, “Hydrogels are soft polymeric materials with promising applications in biomedical fields. Understanding their fracture behavior is crucial for optimizing device design and performance.” Our news editors obtained a quote from the research from Nanyang Technological University, “However, predicting hydrogel fracture is challenging due to the complex interplay between material properties and environmental factors. In this study, a machine learning (ML) approach to predict hydrogel fracture behavior is presented. A multiscale hydrogel fracture model is developed to generate simulation data, which is used to train a predictive neural network model. The ML model utilizes a hierarchical architecture of convolution long short-term memory units to capture spatial and temporal dependencies in the data. Model predictions are found to closely match simulation results with high accuracy, demonstrating the ability to learn complex fracture processes. Comparison of crack lengths shows the model can generalize across different material parameters. This work highlights the potential of ML for advancing the understanding of hydrogel fracture and soft matter failure. The presented approach provides an efficient framework for predicting fracture in complex materials and systems. This study introduces a machine learning (ML) approach to predict hydrogel fracture behavior crucial for biomedical applications. Utilizing a multiscale hydrogel fracture model and a hierarchical architecture of convolutional long short-term memory units, the ML model accurately captures complex fracture processes.”
查看更多>>摘要：Current study results on Robotics have been published. According to news reporting originating in Zhejiang, People’s Republic of China, by NewsRx journalists, research stated, “The rapid expansion and integration of robots in the service industry have transformed the way services are delivered. With service robots increasingly replacing frontline human staff, the dynamics of service encounters have shifted from human-to-human to human-to-robot interactions, thereby significantly impacting the process of value co-creation.” Funders for this research include Natural Science Foundation of Zhejiang Province, Philosophy and Social Science Foundation of Zhejiang Province. The news reporters obtained a quote from the research from Zhejiang Gongshang University, “The active involvement of customers in co-creating value with these robots becomes crucial for the successful implementation of robotic services. Drawing upon social perception theory, we investigate the influence of service robots’ proactivity on customers’ willingness to engage in value co-creation and delve into the underlying mechanisms. Three studies were conducted across diverse service settings, each involving different service robots. Consistently, the findings demonstrate that customers display a greater inclination to cocreate value with proactive service robots. The proactive behavior exhibited by these robots substantially enhances customers’ perceptions of warmth and competence. Importantly, these effects are observed across various service scenarios and customer segments, including both premium and regular customers, thus affirming the robustness and generalizability of our findings. Our research provides practical guidance for practitioners involved in the implementation of service robots.”
查看更多>>摘要：Data detailed on Artificial Intelligence have been presented. According to news reporting originating from Braunschweig, Germany, by NewsRx correspondents, research stated, “Additive Manufacturing (AM) and in particular has gained significant attention due to its capability to produce complex geometries using various materials, resulting in cost and mass reduction per part. However, metal AM parts often contain internal defects inherent to the manufacturing process.” Financial support for this research came from Deutsches Zentrum fr Luftund Raumfahrt e. V. (DLR) (4202). Our news editors obtained a quote from the research from Technical University Braunschweig (TU Braunschweig), “Non-Destructive Testing (NDT), particularly Computed Tomography (CT), is commonly employed for defect analysis. Today adopted standard inspection techniques are costly and time-consuming, therefore an automatic approach is needed. This paper presents a novel eXplainable Artificial Intelligence (XAI) methodology for defect detection and characterization. To classify pixel data from CT images as pores or inclusions, the proposed method utilizes Support Vector Machine (SVM), a supervised machine learning algorithm, trained with an Area Under the Curve (AUC) of 0.94. Density-Based Spatial Clustering with the Application of Noise (DBSCAN) is subsequently applied to cluster the identified pixels into separate defects, and finally, a convex hull is employed to characterize the identified clusters based on their size and shape. The effectiveness of the methodology is evaluated on Ti6Al4V specimens, comparing the results obtained from manual inspection and the ML-based approach with the guidance of a domain expert.”
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news originating from New Orleans, Louisiana, by NewsRx correspondents, research stated, “Machine learning has been successfully applied in recent years to screen materials for a variety of applications. However, despite recent advances, most screening-based machine learning approaches are limited in generality and transferability, requiring new models to be created from scratch for each new application.” Funders for this research include Division of Chemistry, BIRD Foundation. Our news journalists obtained a quote from the research from Tulane University, “This is particularly apparent in catalysis, where there are many possible intermediates and transition states of interest in addition to a large number of potential catalytic materials. In this work, we developed a new machine learning framework that is built on chemical principles and allows the creation of general, interpretable, reusable models. Our new architecture uses latent variables to create a set of submodels that each take on a relatively simple learning task, leading to higher data efficiency and promoting transfer learning. This architecture infuses fundamental chemical principles, such as the existence of elements as discrete entities. We show that this architecture allows for the creation of models that can be reused for many different applications, providing significant improvements in efficiency and convenience. For example, our architecture allows simultaneous prediction of adsorption energies for many adsorbates on a broad array of alloy surfaces with mean absolute errors (MAEs) around 0.20-0.25 eV. The integration of latent variables provides physical interpretability, as predictions can be explained in terms of the learned chemical environment as represented by the latent space. Further, these latent variables also serve as new feature representations, allowing efficient transfer learning. For example, new models with useful levels of accuracy can be created with less than 10 data points, including transfer learning to an experimental data set with an MAE less than 0.15 eV.”
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