期刊,Robotics & Machine Learning Daily News 2024年卷Jun.24期_国家学术搜索

期刊信息/Journal information

Robotics & Machine Learning Daily News

NewsRx

主办单位：NewsRx

Robotics & Machine Learning Daily News/Journal Robotics & Machine Learning Daily News

正式出版

收录年代

University of Sharjah Researcher Describes Advances in Artificial Intelligence ( Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review)

28-28页

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 from the University of Sharja h by NewsRx journalists, research stated, "A vast amount of research has been co nducted on path planning over recent decades, driven by the complexity of achiev ing optimal solutions." Our news editors obtained a quote from the research from University of Sharjah: "This paper reviews multi-robot path planning approaches and presents the path p lanning algorithms for various types of robots. Multi-robot path planning approa ches have been classified as deterministic approaches, artificial intelligence ( AI)-based approaches, and hybrid approaches. Bio-inspired techniques are the mos t employed approaches, and artificial intelligence approaches have gained more a ttention recently. However, multirobot systems suffer from well-known problems such as the number of robots in the system, energy efficiency, fault tolerance a nd robustness, and dynamic targets. Deploying systems with multiple interacting robots offers numerous advantages."

原文链接:

NETL
NSTL

Tianjin University Reports Findings in Machine Learning (Comprehending Flame Dev elopment and Misfire At Advanced Engine Conditions: Detailed Experimental Charac terizations and Machine Learning-assisted Kinetic Analyses)

30-31页

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 from Tianjin, People's Repu blic of China, by NewsRx journalists, research stated, "Through comprehensive ex perimental and modeling efforts, this work unravels the underlying mechanisms go verning flame development and misfire at advanced engine conditions that are rep resentative of low-load and lean blow-out operations. Toward this, preliminary h eat release, autoignition, and flame developing patterns are characterized, via a case study of n-heptane, at ultra-lean conditions in a well-controlled optical engine under various combustion modes including homogeneous charge compression ignition (HCCI), partially premixed combustion (PPC), and reactivity-controlled compression ignition (RCCI)." Funders for this research include National Natural Science Foundation of China ( NSFC), Hong Kong Special Administrative Region of China.

原文链接:

NETL
NSTL

Selcuk University Reports Findings in Artificial Intelligence (Comparative Analy sis of Artificial Intelligence Chatbot Recommendations for Urolithiasis Manageme nt: A Study of EAU Guideline Compliance)

31-31页

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 originating in Konya, Turkey, by NewsRx journalists, research stated, "Artificial intelligence (AI) ap plications are increasingly being utilized by both patients and physicians for a ccessing medical information. This study focused on the urolithiasis section (pe rtaining to kidney and ureteral stones) of the European Association of Urology ( EAU) guideline, a key reference for urologists." The news reporters obtained a quote from the research from Selcuk University, "W e directed inquiries to four distinct AI chatbots to assess their responses in r elation to guideline adherence. A total of 115 recommendations were transformed into questions, and responses were evaluated by two urologists with a minimum of 5 years of experience using a 5-point Likert scale (1-False, 2-Inadequate, 3-Su fficient, 4- Correct, and 5-Very Correct). The mean scores for Perplexity and Cha tGPT 4.0 were 4.68 (SD: 0.80) and 4.80 (SD: 0.47), respectively, both significan tly differed the scores of Bing and Bard (Bing vs. Perplexity, p<.001; Bard vs. Perplexity, p<.001; Bing vs. ChatGPT, p<.001; Bard vs. ChatGPT, p<.001). Bing had a mean score of 4 .21 (SD: 0.96), while Bard scored 3.56 (SD: 1.14), with a significant difference (Bing vs. Bard, p<.001). Bard exhibited the lowest score a mong all chatbots. Analysis of references revealed that Perplexity and Bing cite d the guideline most frequently (47.3% and 30%, respe ctively). Our findings demonstrate that ChatGPT 4.0 and, notably, Perplexity ali gn well with EAU guideline recommendations."

原文链接:

NETL
NSTL

University of Sydney Reports Findings in Artificial Intelligence [Frequency and characteristics of errors by artificial intelligence (AI) in readi ng screening mammography: a systematic review]

32-33页

原文链接:

NETL
NSTL

Reports Outline Artificial Intelligence Study Findings from Institute of Journal ism (A Rapid Investigation of Artificial Intelligence Generated Content Footprin ts in Scholarly Publications)

32-32页

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 reporting originating fr om Chengdu, People's Republic of China, by NewsRx correspondents, research state d, "This study reports on a novel phenomenon observed in scholarly publications. " Our news correspondents obtained a quote from the research from Institute of Jou rnalism: "Some research articles unrelated to the field of artificial intelligen ce (AI)-generated content (AIGC) contain phrases such as 'As an AI language mode l ...' The authors conceptualize this phenomenon as 'AIGC footprints.' To provid e early evidence, they conducted a small-scale sample investigation by collectin g twenty-five articles. These articles were published by authors from countries in Central Asia, South Asia, and Africa. Among these authors, there were assista nt professors, doctoral and master's students. Single authors and single affilia tions were more common. Analysis of the article content revealed that some autho rs utilized ChatGPT for literature reviews or idea generation. The twenty-five a rticles with AIGC footprints were published in eighteen different academic journ als." According to the news reporters, the research concluded: "The emergence of AIGC footprints reflects the potential challenges faced by scholarly publishing and h igher education. The authors also provide several recommendations."

原文链接:

NETL
NSTL

Study Data from Chinese Academy of Sciences Update Knowledge of Machine Learning (An Experimental Application of Machine Learning Algorithms To Optimize the Fel Lasing Via Beam Trajectory Tuning At Dalian Coherent Light Source)

34-34页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Dalian, People's Repub lic of China, by NewsRx correspondents, research stated, "The lasing optimizatio n of Free -Electron Laser (FEL) facilities is a time-consuming and challenging t ask. Instead of operating manually by experienced operators, implementation of m achine learning algorithms offers a rapid and adaptable approach for FEL lasing optimization." Funders for this research include National Key R & D Program of Ch ina, National Natural Science Foundation of China (NSFC), Scientific Instrument Developing Project of Chinese Academy of Science, DICP, China Postdoctoral Scien ce Foundation, Specific Research Assistant Funding Program from Chinese Academy of Sciences, Pre-study Project of Dalian Advanced Light Source from city of Dali an. Our news editors obtained a quote from the research from the Chinese Academy of Sciences, "Recently, such an experiment has been conducted at the vacuum ultravi olet FEL facility - Dalian Coherent Light Source (DCLS). Four algorithms, namely the standard and the neural network -based genetic algorithms, the deep determi nistic policy gradient and the soft actor critic reinforcement learning algorith ms, have been employed to enhance the FEL intensity by optimizing the electron b eam trajectory. These algorithms have shown notable efficacy in enhancing the FE L lasing, especially the reinforcement learning ones which achieved convergence within only approximately 400 iterations."

原文链接:

NETL
NSTL

Reports from University of Auckland Describe Recent Advances in Machine Learning (Integrating Image Analysis and Machine Learning for Moisture Prediction and Ap pearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment)

35-35页

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 Aucklan d, New Zealand, by NewsRx editors, the research stated, "The appearance of dried fruit clearly influences the consumer's perception of the quality of the produc t but is a subtle and nuanced characteristic that is difficult to quantitatively measure, especially online." The news editors obtained a quote from the research from University of Auckland: "This paper describes a method that combines several simple strategies to asses s a suitable surrogate for the elusive quality using imaging, combined with mult ivariate statistics and machine learning. With such a convenient tool, this stud y also shows how one can vary the pretreatments and drying conditions to optimiz e the resultant product quality. Specifically, an image batch processing method was developed to extract color (hue, saturation, and value) and morphological (a rea, perimeter, and compactness) features. The accuracy of this method was verif ied using data from a case study experiment on the pretreatment of hot-air-dried kiwifruit slices. Based on the extracted image features, partial least squares and random forest models were developed to satisfactorily predict the moisture r atio (MR) during drying process. The MR of kiwifruit slices during drying could be accurately predicted from changes in appearance without using any weighing de vice."

原文链接:

NETL
NSTL

Hanoi University of Science and Technology Reports Findings in Machine Learning (Comparing the accuracy of two machine learning models in detection and classifi cation of periapical lesions using periapical radiographs)

36-36页

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 from Hanoi, Vietnam, by NewsR x journalists, research stated, "Previous deep learning-based studies were mainl y conducted on detecting periapical lesions; limited information in classificati on, such as the periapical index (PAI) scoring system, is available. The study a imed to apply two deep learning models, Faster R-CNN and YOLOv4, in detecting an d classifying periapical lesions using the PAI score from periapical radiographs (PR) in three different regions of the dental arch: anterior teeth, premolars, and molars." The news correspondents obtained a quote from the research from the Hanoi Univer sity of Science and Technology, "Out of 2658 PR selected for the study, 2122 PR were used for training, 268 PR were used for validation and 268 PR were used for testing. The diagnosis made by experienced dentists was used as the reference d iagnosis. The Faster R-CNN and YOLOv4 models obtained great sensitivity, specifi city, accuracy, and precision for detecting periapical lesions. No clear differe nce in the performance of both models among these three regions was found. The t rue prediction of Faster R-CNN was 89%, 83.01% and 91 .84% for PAI 3, PAI 4 and PAI 5 lesions, respectively. The corresp onding values of YOLOv4 were 68.06%, 50.94%, and 65.31 %."

原文链接:

NETL
NSTL

Researcher from North China University of Technology Publishes New Studies and F indings in the Area of Robotics (Research on Six- Degree-of-Freedom Refueling Rob otic Arm Positioning and Docking Based on RGB-D Visual Guidance)

37-37页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in robotics. A ccording to news originating from Beijing, People's Republic of China, by NewsRx editors, the research stated, "The main contribution of this paper is the propo sal of a six-degree-of-freedom (6-DoF) refueling robotic arm positioning and doc king technology guided by RGB-D camera visual guidance, as well as conducting in -depth research and experimental validation on the technology." Financial supporters for this research include National Natural Science Foundati on of China. Our news reporters obtained a quote from the research from North China Universit y of Technology: "We have integrated the YOLOv8 algorithm with the Perspective-n -Point (PnP) algorithm to achieve precise detection and pose estimation of the t arget refueling interface. The focus is on resolving the recognition and positio ning challenges of a specialized refueling interface by the 6-DoF robotic arm du ring the automated refueling process. To capture the unique characteristics of t he refueling interface, we developed a dedicated dataset for the specialized ref ueling connectors, ensuring the YOLO algorithm's accurate identification of the target interfaces. Subsequently, the detected interface information is converted into precise 6-DoF pose data using the PnP algorithm. These data are used to de termine the desired end-effector pose of the robotic arm. The robotic arm's move ments are controlled through a trajectory planning algorithm to complete the ref ueling gun docking process."

原文链接:

NETL
NSTL

New Findings Reported from Medical University of Vienna Describe Advances in Rob otics (A navigated, robot-driven laser craniotomy tool for frameless depth elect rode implantation. An in-vivo recovery animal study)

38-38页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on robotics is the subjec t of a new report. According to news originating from Vienna, Austria, by NewsRx editors, the research stated, "We recently introduced a frameless, navigated, r obot-driven laser tool for depth electrode implantation as an alternative to fra me-based procedures. This method has only been used in cadaver and non-recovery studies. This is the first study to test the robot-driven laser tool in an in vi vo recovery animal study." Our news correspondents obtained a quote from the research from Medical Universi ty of Vienna: "A preoperative computed tomography (CT) scan was conducted to pla n trajectories in sheep specimens. Burr hole craniotomies were performed using a frameless, navigated, robot-driven laser tool. Depth electrodes were implanted after cut-through detection was confirmed. The electrodes were cut at the skin l evel postoperatively. Postoperative imaging was performed to verify accuracy. Hi stopathological analysis was performed on the bone, dura, and cortex samples. Fo urteen depth electrodes were implanted in two sheep specimens. Anesthetic protoc ols did not show any intraoperative irregularities. One sheep was euthanized on the same day of the procedure while the other sheep remained alive for 1 week wi thout neurological deficits. Postoperative MRI and CT showed no intracerebral bl eeding, infarction, or unintended damage. The average bone thickness was 6.2 mm (range 4.1-8.0 mm). The angulation of the planned trajectories varied from 65.5° to 87.4°. The deviation of the entry point performed by the frameless laser bea m ranged from 0.27 mm to 2.24 mm. The histopathological analysis did not reveal any damage associated with the laser beam."

原文链接:

NETL
NSTL

首页
1
2
3
4
5
6
7