查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Turing Machines is the subject of a report. According to news reporting from Ulm, Germany, by NewsRx j ournalists, research stated, "Computability on uncountable sets has no standard formalization, unlike that on countable sets, which is given by Turing machines. Some of the approaches to define computability in these sets rely on order-theo retic structures to translate such notions from Turing machines to uncountable s paces." Financial support for this research came from European Research Council (ERC). The news correspondents obtained a quote from the research from Ulm University, "Since these machines are used as a baseline for computability in these approach es, countability restrictions on the ordered structures are fundamental. Here, w e show several relations between the usual countability restrictions in order-th eoretic theories of computability and some more common order-theoretic countabil ity constraints, like order density properties and functional characterizations of the order structure in terms of multi-utilities."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Heart Disorders and Di seases - Heart Disease is the subject of a report. According to news reporting f rom Basel, Switzerland, by NewsRx journalists, research stated, "Functionally re levant coronary artery disease (fCAD) can result in premature death or nonfatal acute myocardial infarction. Its early detection is a fundamentally important ta sk in medicine." Financial support for this research came from Alfried Krupp von Bohlen und Halba ch-Stiftung. The news correspondents obtained a quote from the research from the University H ospital of Basel, "Classical detection approaches suffer from limited diagnostic accuracy or expose patients to possibly harmful radiation. Here we show how mac hine learning (ML) can outperform cardiologists in predicting the presence of st ress-induced fCAD in terms of area under the receiver operating characteristic ( AUROC: 0.71 vs. 0.64, p = 4.0E-13). We present two ML approaches, the first usin g eight static clinical variables, whereas the second leverages electrocardiogra m signals from exercise stress testing. At a target post-test probability for fC AD of <15%, ML facilitates a potential reducti on of imaging procedures by 15-17% compared to the cardiologist's judgement. Predictive performance is validated on an internal temporal data spli t as well as externally."
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 Ar tificial Intelligence. According to news reporting out of Bronx, New York, by Ne wsRx editors, research stated, "The physical interactions between proteins are l argely determined by the structural properties at their binding interfaces. It w as found that the binding interfaces in distinctive protein complexes are highly similar." Funders for this research include National Institutes of Health (NIH) - USA, Alb ert Einstein College of Medicine. Our news journalists obtained a quote from the research from the Albert Einstein College of Medicine, "The structural properties underlying different binding in terfaces could be further captured by artificial intelligence. In order to test this hypothesis, we broke protein-protein binding interfaces into pairs of inter acting fragments. We employed a generative model to encode these interface fragm ent pairs in a lowdimensional latent space. After training, new conformations o f interface fragment pairs were generated. We found that, by only using a small number of interface fragment pairs that were generated by artificial intelligenc e, we were able to guide the assembly of protein complexes into their native con formations. These results demonstrate that the conformational space of fragment pairs at protein-protein binding interfaces is highly degenerate. Features in th is degenerate space can be well characterized by artificial intelligence."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Heidelberg, Germa ny, by NewsRx editors, the research stated, "Increasing population and healthcar e costs make changes in the healthcare system necessary. This article deals with ChatGPT's perspective on the future role of radiologists in the AI-driven hospi tal." Financial support for this research came from Universitatsklinikum Heidelberg. The news correspondents obtained a quote from the research from University Hospi tal Heidelberg, "This perspective will be augmented by further considerations by the author. AI-based imaging technologies and chatbots like ChatGPT can help im prove radiologists' performance and workflow in the future AI-driven hospital."
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 - Pa ttern Recognition and Artificial Intelligence have been presented. According to news reporting out of Salford, United Kingdom, by NewsRx editors, research state d, "Classification of multiple types of spice images is automatically challengin g due to conflict between the texture patterns of spice images. This work aims t o develop an automatic system for classifying different types of spice images so that the system can choose an appropriate spice to make herbal tea using Carall uma fimbriata." Our news journalists obtained a quote from the research from the University of S alford, "This work considers the following seven spices, namely, cinnamon, citru s peel, clove, ginger, jeera, kokum, mint, and Caralluma fimbriata as one more c lass for classification. Most of the existing systems need human intervention to choose different spices to make Caralluma fimbriata tea. It is observed that th e pattern of different spice images represents different textures. This observat ion motivated us to extract features based on multi-Sobel kernels. To reduce the number of computations, the proposed work introduces a novel idea of corner det ection based on Gaussian distribution. For each corner, the method performed is multi-Sobel kernels for extracting features. The features are fed to convolution al neural network layers for the classification of multiple spice images."
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 originating from Beijing , People's Republic of China, by NewsRx editors, the research stated, "Time seri es is a typical data type in numerous domains; however, labeling large amounts o f time series data can be costly and time-consuming. Learning effective represen tation from unlabeled time series data is a challenging task." The news journalists obtained a quote from the research from Beijing University of Posts and Telecommunications: "Contrastive learning stands out as a promising method to acquire representations of unlabeled time series data. Therefore, we propose a self-supervised time-series representation learning framework via Time -Frequency Fusion Contrasting (TF-FC) to learn time-series representation from u nlabeled data. Specifically, TF-FC combines time-domain augmentation with freque ncy-domain augmentation to generate the diverse samples. For time-domain augment ation, the raw time series data pass through the time-domain augmentation bank ( such as jitter, scaling, permutation, and masking) and get time-domain augmentat ion data. For frequency-domain augmentation, first, the raw time series undergoe s conversion into frequency domain data following Fast Fourier Transform (FFT) a nalysis. Then, the frequency data passes through the frequency-domain augmentati on bank (such as low pass filter, remove frequency, add frequency, and phase shi ft) and gets frequency-domain augmentation data. The fusion method of time-domai n augmentation data and frequency-domain augmentation data is kernel PCA, which is useful for extracting nonlinear features in high-dimensional spaces. By captu ring both the time and frequency domains of the time series, the proposed approa ch is able to extract more informative features from the data, enhancing the mod el's capacity to distinguish between different time series."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news originating from Jacksonville, F lorida, by NewsRx correspondents, research stated, "To evaluate variability in a neurysm detection and the potential of artificial intelligence (AI) software as a screening tool by comparing conventional computed tomography angiography (CTA) images (standard care) with AI software. Neuroradiologists reviewed 770 CTA ima ges and reported the presence or absence of saccular aneurysms." Our news journalists obtained a quote from the research from Baptist Neurologica l Institute, "Subsequently, the images were analyzed by AI software. If the soft ware suspected an aneurysm, it flagged the corresponding image. In cases where t here was a mismatch between the radiologist's report and the AI findings, an exp ert neurosurgeon evaluated CTA images providing a definitive conclusion on the p resence or absence of an aneurysm. AI software flagged 33 cases as potential ane urysms; 16 cases were positively identified as aneurysms by radiologists, and 17 were dismissed. A total of 737 cases were considered negative by AI software, w hile in the same group, radiologists identified aneurysms in 28 CTA images. Comp ared with the radiologist's report, AI performance had a sensitivity of 36% , specificity of 97.6%, and negative predictive value of 96.2% . There were 45 mismatch cases between AI and radiologists. AI flagged 17 images as showing an aneurysm that was unreported by radiologists; the expert neurosur geon confirmed that 7 of the 17 images showed an aneurysm. In 28 images consider ed negative by AI, radiologists indicated aneurysms; 17 of those confirmed by th e neurosurgeon. AI has the potential to increase the diagnosis of unruptured int racranial aneurysms."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating from Shenyang, P eople's Republic of China, by NewsRx correspondents, research stated, "It is now adays a hot topic to apply machine learning (ML) algorithms to illustrate water temperature dynamics in lentic waters. Due to the limited amount of in-situ temp erature measurements from traditional sampling programmes, most of the related s tudies, however, restricted their analysis within the surface and rarely checked the results for whole depth profiles." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Liaoning Provincial Doctoral Research Startup Fund Project.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news reporting out of Nanjing, Peopl e's Republic of China, by NewsRx editors, research stated, "Smart data gloves ca pable of monitoring finger activities and inferring hand gestures are of signifi cance to humanmachine interfaces, robotics, healthcare, and Metaverse. Yet, mos t current smart data gloves present unstable mechanical contacts, limited sensit ivity, as well as offline training and updating of machine learning models, lead ing to uncomfortable wear and suboptimal performance during practical applicatio ns." Funders for this research include National Key R&D Program of China , National Natural Science Foundation of China (NSFC), Start-up Research Fund of Southeast University.
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 robotic s. According to news reporting out of Kangar, Malaysia, by NewsRx editors, resea rch stated, "Sprained ankles are the most commonly diagnosed injury seen by heal thcare providers and are projected to account for up to 30% of spo rts medicine injuries, with lateral ankle sprain being the most common type." The news journalists obtained a quote from the research from Universiti Malaysia Perlis: "Ankle injuries necessarily involve motion assistance to regain mobilit y, but physiotherapists are typically able to provide rehabilitation only for on e patient at each session. Numerous robotic rehabilitation strategies have been proposed in recent years; however, most of the designs have some limitations suc h as requiring the patient to sit or stand still. Hence, this study aims to deve lop a conceptual design and simulation of a compact wearable robot in aiding ank le motion for rehabilitation and training purposes. The cable-driven parallel ar chitecture used in the construction of the cable-driven ankle rehabilitation rob ot allows for the exercise of the human ankle's range of motion (ROM) to be maxi mized. The morphological chart analysis was created to explore the possible solu tions to the design development for the ankle rehabilitation device, and the fin al design was decided using the Pugh method. A three-dimensional model of the pr oposed design was visualized in SolidWorks to analyze the inverse kinematics, tr ajectory simulation and cable length analysis."
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