查看更多>>摘要：2024 OCT 08 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on artificial intelligence is the su bject of a new report. According to news reporting out of the University of Tech nology by NewsRx editors, research stated, "This research aims to explore more e fficient machine learning (ML) algorithms with better performance for short-term forecasting. Upto- date literature shows a lack of research on selecting practi cal ML algorithms for short-term forecasting in real-time industrial application s." Financial supporters for this research include Shanxi Coking Coal Project; Shanx i Social Science Federation.
查看更多>>摘要：New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Paris , France, by NewsRx correspondents, research stated, "This study explores the ap plication of Line-field Confocal Optical Coherence Tomography (LC-OCT) imaging c oupled with artificial intelligence (AI)-based algorithms to investigate atopic dermatitis (AD), a common inflammatory dermatosis. AD acute and chronic lesions (ADL) were compared to clinically healthy-looking skin (ADNL)." Our news editors obtained a quote from the research from Saint-Louis Hospital, " LC-OCT was used noninvasively and in real-time to image the skin of AD patients during flare-ups and monitor remissions under topical steroid treatment for 2 we eks. Quantitative parameters were extracted from the images, including morpholog ical and cellular-level markers of epidermal architecture. A novel cellular-leve l parameter, nuclei ‘atypia,' which quantifies the orderliness of epidermal rene wal, was used to highlight abnormal maturation processes. Compared to healthy sk in, AD lesions exhibited significant increases in both epidermal and stratum cor neum (SC) thickness, along with a more undulated dermo-epidermal junction (DEJ). Additionally, keratinocyte nuclei (KN) were larger, less compact, and less orga nized in lesional areas, as indicated by the atypia parameter. A higher degree o f atypia was observed in chronic lesions compared to acute ones. Following treat ment, all the parameters normalized to levels observed in healthy skin within 2 weeks, mirroring clinical improvements. This study provides insights into the qu antification of epidermal renewal using a noninvasive imaging technique, highlig hting differences between ADL/ADNL and acute/chronic lesions."
查看更多>>摘要：Research findings on Robotics are disc ussed in a new report. According to news reporting from Hangzhou, People's Repub lic of China, by NewsRx journalists, research stated, "The dynamics of hydraulic robots are complicated due to the closed-chain joints formed by cylinder articu lation. This article is focused on presenting a model-based control framework fo r rapid locomotion, integrating closed-chain dynamics without a substantial incr ease in computational costs." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Key Research and Development Program of Zhejiang Province. The news correspondents obtained a quote from the research from Zhejiang Univers ity, "The virtual decomposition control (VDC) approach has been adapted and inno vatively extended to a leg system for the first time, featuring a floating base and variable contact constraints. In this article, a position control framework is proposed, consisting of three VDC-based controllers designed specifically for the stance phase and the swing phase, respectively. During the stance phase, a constrained estimation model is developed to recursively compute the previously incalculable dynamic equations. Furthermore, the control laws are designed to en sure that the virtual power flows caused by contact constraints do not affect th e stability. In the swing phase, a noninertial frame is established to transform the underactuated system into a fully actuated fixed-base system. Despite being position controlled, our framework enables the leg system to generate complianc e by setting a separate low-gain VDC-based controller during the landing stage. Experiments reveal that the proposed framework exhibits better position trajecto ry tracking performance and jumping ability in highly dynamic motion compared wi th the state-of-the-art position controller."
查看更多>>摘要：Investigators publish new report on Ma chine Learning. According to news reporting originating from Beijing, People's R epublic of China, by NewsRx correspondents, research stated, "In the process of replacing coal seam CH4 with CO2, the CH4 diffusion rate, production, and CO2 st orage determine the effectiveness of the replacement. Predicting the changes in CH4 diffusion rates, production, and CO2 sequestration during the CO(2 )injectio n process in coal beds, based on historical data, presents a highly nonlinear ch allenge influenced by various gas injection parameters." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Key RD Program.
查看更多>>摘要：Investigators publish new report on ar tificial intelligence. According to news reporting from Egaila, Kuwait, by NewsR x journalists, research stated, "The widespread dissemination of fake news on so cial media has necessitated the development of more sophisticated detection meth ods to maintain information integrity." The news correspondents obtained a quote from the research from American Univers ity of the Middle East: "This research systematically investigates the effective ness of different word embedding techniques- TF-IDF, Word2Vec, and FastText-when applied to a variety of machine learning (ML) and deep learning (DL) models for fake news detection. Leveraging the TruthSeeker dataset, which includes a divers e set of labeled news articles and social media posts spanning over a decade, we evaluated the performance of classifiers such as Support Vector Machines (SVMs) , Multilayer Perceptrons (MLPs), and Convolutional Neural Networks (CNNs). Our a nalysis demonstrates that SVMs using TF-IDF embeddings and CNNs employing TF-IDF embeddings achieve the highest overall performance in terms of accuracy, precis ion, recall, and F1 score. These results suggest that TF-IDF, with its capacity to highlight discriminative features in text, enhances the performance of models like SVMs, which are adept at handling sparse data representations. Additionall y, CNNs benefit from TF-IDF by effectively capturing localized features and patt erns within the textual data. In contrast, while Word2Vec and FastText embedding s capture semantic and syntactic nuances, they introduce complexities that may n ot always benefit traditional ML models like MLPs or SVMs, which could explain t heir relatively lower performance in some cases."
查看更多>>摘要：New study results on robotics have bee n published. According to news originating from Penang, Malaysia, by NewsRx corr espondents, research stated, "This review paper provides a detailed overview of the advancements and identifies pivotal challenges in the realm of autonomous lo ad-carrying mobile robots, with a particular focus on indoor applications for bo th ground and aerial platforms." Funders for this research include Universiti Sains Malaysia Through The Usm-indu stry Matching Grant Scheme; Western Digital (Sandisk Storage Malaysia Sdn. Bhd.) Through The Industrial Grant Scheme. The news correspondents obtained a quote from the research from University Sains Malaysia: "It critically examines the past decade's innovations in load-carryin g designs and sensor technologies, scrutinizing their impact on the enhancement of robotic autonomy and load management. The paper also presents an in-depth ana lysis of the latest trends in navigation and control algorithms essential for re fining these robots' operational efficacy in diverse indoor scenarios. By evalua ting current research outputs, this work identifies critical areas for future ex ploration, such as improving indoor navigation complexity, optimizing load handl ing for varying conditions, and pioneering precise load-sensing techniques. The paper proposes innovative research paths designed to address the identified gaps , underscoring the necessity for breakthroughs in robot design, enhanced integra tion of systems, and increased operational efficiency."
查看更多>>摘要：New research on Robotics is the subjec t of a report. According to news reporting originating from Leicester, United Ki ngdom, by NewsRx correspondents, research stated, "Wearable robots have promisin g characteristics for human augmentation; however, the the design and specificat ion stage needs to consider biomechanical impact. In this work, musculoskeletal software is used to assess the biomechanical implications of having a two-degree s-of-freedom supernumerary robotic tail mounted posterior to the human trunk." Financial support for this research came from Engineering and Physical Sciences Research Council. Our news editors obtained a quote from the research, "Forward and backward tilti ng motions were assessed to determine the optimal design specification. Specific ally; the key criteria utilised included the centre of pressure, the dynamic wre nch exerted by the tail onto the human body and a global muscle activation index . Overall, it was found that use of a supernumerary tail reduced lower limb musc le activation in quiet stance."
查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting originating in Lima, Peru, by NewsR x journalists, research stated, "Andean highland soils contain significant quant ities of soil organic carbon (SOC); however, more efforts still need to be made to understand the processes behind the accumulation and persistence of SOC and i ts fractions. This study modeled SOC variables-SOC, refractory SOC (RSOC), and t he C-13 isotope composition of SOC (delta(CSOC)-C-13)- using machine learning (ML ) algorithms in the Central Andean Highlands of Peru, where grasslands and wetla nds (‘bofedales') dominate the landscape surrounded by Junin National Reserve." Funders for this research include Consortium of International Agricultural Resea rch Centers, USDA Foreign Agricultural Service, Borlaug Fellowship Program.
查看更多>>摘要：Data detailed on Robotics have been pr esented. According to news reporting originating in Nanjing, People's Republic o f China, by NewsRx editors, the research stated, "Pick-and-place manipulation is a pivotal component in many robotic tasks. In unstructured, dynamic and uncerta in environments, controllers are required to learn and generalize pick-and-place manipulation from multitype demonstrations, which are often represented in Euc lidean (e.g., position), and non-Euclidean (e.g., quaternion, symmetric positive definite (SPD) matrix) data." Funders for this research include Natural Science Foundation of Jiangsu Province , National Natural Science Foundation of China (NSFC), Zhejiang Lab. The news reporters obtained a quote from the research from Southeast University, "While many learning from demonstration (LfD) methods excel in manipulation tas ks with single-type data, the adaptation of motion skills across different data types remains largely open. In this paper, we propose a two-stream Sequence-to-S equence Network (S2SNet) that utilizes multiple tangent spaces to learn motion s kills from multi-type demonstrations. The S2SNet is capable of adapting the lear ned motion skills to different types of waypoints, such as position waypoints, S PD-based waypoints, and quaternion waypoints. Additionally, we introduce a demon stration segmentation operation within S2SNet to enhance its generalization abil ity across different types of waypoints and to reduce the dependency on a large volume of real demonstrations. Experimental evaluations show that S2SNet outperf orms state-of-the-art methods in passing through different types of waypoints."
查看更多>>摘要：New research on artificial intelligenc e is the subject of a new report. According to news reporting from Florida, Sout h Africa, by NewsRx journalists, research stated, "Energy utilisation in residen tial dwellings is stochastic and can worsen the issue of operational planning fo r energy provisioning." Financial supporters for this research include National Research Foundation of S outh Africa. Our news correspondents obtained a quote from the research from University of So uth Africa: "Additionally, planning with intermittent energy sources exacerbates the challenges posed by the uncertainties in energy utilisation. In this work, machine learning regression schemes (random forest and decision tree) are used t o train a forecasting model. The model is based on a yearly dataset and its subs et seasonal partitions. The dataset is first preprocessed to remove inconsistenc ies and outliers. The performance measures of mean absolute error (MAE), mean sq uare error (MSE) and root mean square error (RMSE) are used to evaluate the accu racy of the model. The results show that the performance of the model can be enh anced with hyperparameter tuning."
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