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 Kyiv, Ukraine, by NewsRx correspondents, research stated, "The paper studies the attitude to cr itical thinking, academic integrity and the Artificial Intelligence use of the U krainian medical PhD students. In 2023, 56 medical PhD students from the Bogomol ets National Medical University, Kyiv, Ukraine, underwent the survey." Our news journalists obtained a quote from the research from Bogomolets National Medical University, "The participation was voluntary, upon the oral consent. Th e data included in the survey questions include various aspects related to criti cal thinking, analysis skills, and attitudes towards plagiarism. A significant m ajority of the medical PhD students (75%) place high importance on critical thinking. While a majority (89.29%) apply analysis and cri tical thinking skills in their English studies, there's a notable percentage (7. 14%) that is uncertain. Although most are aware of the unacceptabil ity of cheating and plagiarism (75%), a small proportion admit to h aving plagiarized (12.5%). Only 30.4% of the responde nts reported using GPT Chat for study. Responses to witnessing peers plagiarize or using Artificial Intelligence show a varied attitude, with many expressing un willingness to report such incidents (30.36%). The survey highlight s the recognized importance of critical thinking in academic study among medical PhD students, while also points to areas where attitudes and practices regardin g these skills could be improved. The study shows a vast area for improvement re garding academic integrity, as almost one-third of respondents need more defined standards."
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 originating from La Jolla, Cal ifornia, by NewsRx correspondents, research stated, "This study evaluates and co mpares the accuracy of responses from 2 artificial intelligence platforms to pat ients' oculoplasticsrelated questions. Questions directed toward oculoplastic s urgeons were collected, rephrased, and input independently into ChatGPT-3.5 and BARD chatbots, using the prompt: "As an oculoplastic surgeon, how can I respond to my patient's question?." Responses were independently evaluated by 4 experien ced oculoplastic specialists as comprehensive, correct but inadequate, mixed cor rect and incorrect/outdated data, and completely incorrect."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in London, United Kingdom, by NewsRx journalists, research stated, "Demonstrating and assessing s elf-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer. We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that est imates parameter maps without training data." Financial supporters for this research include Prostate Cancer UK, Engineering a nd Physical Sciences Research Council, University College London Hospitals NHS F oundation Trust.
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 out of Shanghai, People's Republic of China, by NewsRx editors, research stated, "This article studies a metamodule motion design approach for homogenous modular robotic systems in self-configuration." Funders for this research include National Natural Science Foundation of China. Our news reporters obtained a quote from the research from Shanghai Maritime Uni versity: "By utilizing configuration diversity, scalability and unit-substitutab ility, homogenous modular robotic systems can be a promising approach to life de tection and space exploration in the future. Based on the requirements of the po tential applications, self-configuration can be considered as the precondition. As similar to swarm robotic systems, the distributed control strategy in which t he modular robots are operated in a sequence of motion circles consist of ‘detec tion'- ‘decision'- ‘execution' is of great significance. However, there is a lim itation to the applicability of previously proposed work on the self-configurati on topic, due to the fact that the self-configuration strategy execution suffers from the motion constraints of modular robots. In order to solve the problem, w e propose a grid partition method that removes the gap between the locomotion of a single modular robot and the reconfiguration of the whole system."
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 from Hangzhou, People's Republic of China, by NewsRx correspondents, research stated, "Traditional underwater ri gid robots have some shortcomings that limit their applications in the ocean." Funders for this research include National Natural Science Foundation of China. Our news reporters obtained a quote from the research from Zhejiang University: "In contrast, because of their inherent flexibility, soft robots, which have gai ned popularity recently, offer greater adaptability, efficiency, and safety than rigid robots. Among them, the soft actuator is the core component to power the soft robot. Here, we propose a class of soft electrohydraulic bending actuators suitable for underwater robots, which realize the bending motion of the actuator by squeezing the working liquid with an electric field. The actuator consists o f a silicone rubber film, polydimethylsiloxane (PDMS) films, soft electrodes, si licone oils, an acrylic frame, and a soft flipper. When a square wave voltage is applied, the actuator can generate continuous flapping motions. By mimicking Ha liclystus auricula, we designed an underwater robot based on six soft electrohyd raulic bending actuators and constructed a mechanical model of the robot."
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 Machine Learn ing have been published. According to news reporting out of Dayton, Ohio, by New sRx editors, research stated, "Recent modern computing and trends in digital tra nsformation provide a smart healthcare system for predicting diseases at an earl y stage. In healthcare services, Internet of Things (IoT) based models play a vi tal role in enhancing data processing and detection." Our news journalists obtained a quote from the research from Wright State Univer sity, "As IoT grows, processing data requires more space. Transferring the patie nt reports takes too much time and energy, which causes high latency and energy. To overcome this, Edge computing is the solution. The data is analysed in the e dge layer to improve the utilization. This paper proposed effective prediction o f resource allocation and prediction models using IoT and Edge, which are suitab le for healthcare applications. The proposed system consists of three modules: d ata preprocessing using filtering approaches, Resource allocation using the Deep Q network, and prediction phase using an optimised DL model called DBN-LSTM wit h frog leap optimization. The DL model is trained using the training health data set, and the target field is predicted. It has been tested using the sensed data from the IoT layer, and the patient health status is expected to take appropria te actions. With timely prediction using edge devices, doctors and patients conv eniently take necessary actions. The primary objective of this system is to secu re low latency by improving the quality of service (QoS) metrics such as makespa n, ARU, LBL, TAT, and accuracy. The deep reinforcement learning approach is empl oyed due to its considerable acceptance for resource allocation."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news originating from London, United Kingdom, by NewsRx correspondents, research stated, "Measuring pilot mental workload (MWL) is crucial for enhancing aviation safety." The news correspondents obtained a quote from the research from Imperial College London: "However, MWL is a multi-dimensional construct that could be affected b y multiple factors. Particularly, in the context of a more automated cockpit set ting, the traditional methods of assessing pilot MWL may face challenges. Heart rate variability (HRV) has emerged as a potential tool for detecting pilot MWL d uring real-flight operations. This review aims to investigate the relationship b etween HRV and pilot MWL and to assess the performance of machine-learning-based MWL detection systems using HRV parameters. A total of 29 relevant papers were extracted from three databases for review based on rigorous eligibility criteria We observed significant variability across the reviewed studies, including stu dy designs and measurement methods, as well as machine-learning techniques."
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 - Intelligent Systems are discussed in a new report. According to news reporting out of Zhanjiang, People's Republic of China, by NewsRx editors, research state d, "Dynamic Tensor Inversion (DTI) is an emerging issue in recent research, prev alent in artificial intelligence development frameworks such as TensorFlow and P yTorch. Traditional numerical methods suffer significant lagging error when addr essing this issue." Financial supporters for this research include Stable Supporting Fund of Acousti c Science and Technology Laboratory, Characteristic Innovation Program of the Ed ucation Department of Guangdong Province.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news originating from Da Nang, Vietnam, by NewsRx corre spondents, research stated, "Reinforced concrete (RC) flat slabs, a popular choi ce in construction due to their flexibility, are susceptible to sudden and britt le punching shear failure. Existing design methods often exhibit significant bia s and variability." Financial support for this research came from Seoul National University of Scien ce and Technology (SeoulTech) - Seoul National University of Science and Technol ogy (SeoulTech). Our news journalists obtained a quote from the research from Dong-A University, "Accurate estimation of punching shear strength in RC flat slabs is crucial for effective concrete structure design and management. This study introduces a nove l computation method, the jellyfish-least square support vector machine (JSLSSV R) hybrid model, to predict punching shear strength. By combining machine learni ng (LSSVR) with jellyfish swarm (JS) intelligence, this hybrid model ensures pre cise and reliable predictions. The model's development utilizes a real-world exp erimental data set. Comparison with seven established optimizers, including arti ficial bee colony (ABC), differential evolution (DE), genetic algorithm (GA), an d others, as well as existing machine learning (ML)-based models and design code s, validates the superiority of the JS-LSSVR hybrid model."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Oxford, United Kingdom , by NewsRx editors, research stated, "Collaborative efforts in artificial intel ligence (AI) are increasingly common between high-income countries (HICs) and lo w- to middle-income countries (LMICs). Given the resource limitations often enco untered by LMICs, collaboration becomes crucial for pooling resources, expertise , and knowledge." Financial supporters for this research include Horizon 2020 Framework Programme, Wellcome Trust, National Institute for Health and Care Research. Our news journalists obtained a quote from the research from the University of O xford, "Despite the apparent advantages, ensuring the fairness and equity of the se collaborative models is essential, especially considering the distinct differ ences between LMIC and HIC hospitals. In this study, we show that collaborative AI approaches can lead to divergent performance outcomes across HIC and LMIC set tings, particularly in the presence of data imbalances. Through a real-world COV ID-19 screening case study, we demonstrate that implementing algorithmic-level b ias mitigation methods significantly improves outcome fairness between HIC and L MIC sites while maintaining high diagnostic sensitivity."
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