期刊,Robotics & Machine Learning Daily News 2024年卷Sep.30期_国家学术搜索

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Reports on Machine Learning Findings from Universidad Panamericana Provide New I nsights (Damage Importance Analysis for Pavement Condition Index Using Machine-L earning Sensitivity Analysis)

76-77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 Aguascalientes, Mexico, by NewsRx correspondents, research stated, "The Pavem ent Condition Index (PCI) is a prevalent metric for assessing the condition of r igid pavements. The PCI calculation involves evaluating 19 types of damage." Funders for this research include Chairs Program of The National Council of Huma nities, Science And Technology (Conahcyt) Project. The news journalists obtained a quote from the research from Universidad Panamer icana: "This study aims to analyze how different types of damage impact the PCI calculation and the impact of the performance of prediction models of PCI by red ucing the number of evaluated damages. The Municipality of Leon, Gto., Mexico, p rovided a dataset of 5271 records. We evaluated five different decision-tree mod els to predict the PCI value. The Extra Trees model, which exhibited the best pe rformance, was used to assess the feature importance of each type of damage, rev ealing their relative impacts on PCI predictions. To explore the potential for r educing the complexity of the PCI evaluation, we applied Sequential Forward Sear ch and Brute Force Search techniques to analyze the performance of models with v arious feature combinations. Our findings indicate no significant statistical di fference in terms of Mean Absolute Error (MAE) and the coefficient of determinat ion (R2) between models trained with 13 features compared to those trained with All 17 features."

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Louisiana State University Health Shreveport Reports Findings in Prostatectomy ( Could trainees' finger placement at the surgeon's console affect overAll outcome s of robotic surgery in radical prostatectomy? A prospective, blinded, robotic . ..)

77-78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 Surgery - Prostatectom y is the subject of a report. According to news reporting out of Shreveport, Lou isiana, by NewsRx editors, research stated, "Robotic surgery for localized prost ate cancer offers a greater range of motion attributed to the EndoWrist instrume nts. Postoperative outcomes are linked to the quality of vesico-urethral anastom osis." Our news journalists obtained a quote from the research from Louisiana State Uni versity Health Shreveport, "Trainees frequently complain of suturing difficulty in a back-handed fashion. We aimed to analyze wrist motion using the DaVinci sim ulator. We hypothesized that using the thumb and index finger would Allow superi or surgical proficiency when compared to the middle finger. After institutional review board approval, we recruited 42 medical students in one academic medical center. Students were randomly assigned to start with their thumb and index fing er (1&2) or thumb and middle finger (1&3). Three stand ardized modules were used with nine metrics calculated, including: score, total time, economy of motion, efficiency score, collisions, inaccurate puncture, woun d approximation, out of view, and penalty subtotal. Statistical analysis of the metrics was calculated using SPSS. Three metrics were found to have differences between the finger placement of 1&3 compared to 1&2. the number of collisions, wound approximation, and penalty score where 1& 3 were used had a lower score in each. The number of collisions was 5.7 less in the 1&3 finger placement (p=0.046). This metric was found to have s tatisticAlly significant differences between finger placement where 1& 3 had a lower score compared to 1&2. The wound approximation score was 0.2 points lower when using the 1&3 placement (p=0.075). Lastly , the penalty assigned was 6.5 points lower when using 1&3 (p=0.069 ). Although finger placement did not affect the overAll score of the completed s imulation, instrument collisions and unnecessary wound complications may lead to adverse outcomes when using 1&2 despite offering a wider range of motion. This may be due to decreased comfort in hand position."

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Investigators at National University of Science & Technology MISiS Discuss Findings in Machine Learning (Machine Learning Potential To Model the D iamond Phase Nucleation In Misoriented Bilayer Graphene)

78-79页

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 have been presented. According to news reporting originating from Moscow, Russia, by NewsRx correspondents, research stated, "The machine learning potential (MLP) i s proposed based on the representation of the environment through moment tensors to model the diamond phase nucleation in misoriented bilayer graphene. MLP is t rained on a set of graphene structures, 2D diamond, and their hydrogenated modif ications obtained by density functional theory computations." Financial support for this research came from Russian Science Foundation (RSF). Our news editors obtained a quote from the research from the National University of Science & Technology MISiS, "Learned MLP accurately reproduces energies and strengths of these structures and correctly describes hydrogenatio n of bilayer graphene and the formation of interlayer bonds. Growth of the diamo nd phase in bigraphene with a 5 degrees misorientation of layers is studied usin g MLP. It is found that the formation energy increases with an increase in the n umber of hydrogen atoms, which indicates hydrogen cluster nucleation on the surf ace of bilayer graphene. Hydrogenation of the system leads to the growth of the cubic diamond region up to the AA ‘ stacking promoting the formation of lonsdale ite with the (10 (1) over bar0) surface."

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Investigators at University of Mannheim Discuss Findings in Artificial Intellige nce (Evidence-based Development of an Instrument for the Assessment of Teachers' Self-perceptions of Their Artificial Intelligence Competence)

79-80页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Artificial Intelligen ce have been presented. According to news reporting from Mannheim, Germany, by N ewsRx journalists, research stated, "Artificial intelligence (AI) competence in education is a set of skills that enable teachers to ethicAlly and responsibly d evelop, apply, and evaluate AI for learning and teaching processes. While AI com petence becomes a key competence for teachers, current research on the acceptanc e and use of AI in classroom practice with a specific focus on the required comp etencies of teachers related to AI is scarce." Financial support for this research came from Universitt Mannheim (3157). The news correspondents obtained a quote from the research from the University o f Mannheim, "This study builds on an AI competence model and investigates predis positions of AI competence among N = 480 teachers in vocational schools. AI comp etence can be modeled as combining six competence dimensions. Findings suggest t hat the different competence dimensions are currently unequAlly developed."

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University of Belgrade Reports Findings in Artificial Intelligence (Influence of next-generation artificial intelligence on headache research, diagnosis and tre atment: the junior editorial board members'vision - part 1)

80-81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 from Belgrade, Serbia, by NewsRx journalists, research stated, "Artificial intelligence (AI) is revolu tionizing the field of biomedical research and treatment, leveraging machine lea rning (ML) and advanced algorithms to analyze extensive health and medical data more efficiently. In headache disorders, particularly migraine, AI has shown pro mising potential in various applications, such as understanding disease mechanis ms and predicting patient responses to therapies." The news correspondents obtained a quote from the research from the University o f Belgrade, "Implementing next-generation AI in headache research and treatment could transform the field by providing precision treatments and augmenting clini cal practice, thereby improving patient and public health outcomes and reducing clinician workload. AI-powered tools, such as large language models, could facil itate automated clinical notes and faster identification of effective drug combi nations in headache patients, reducing cognitive burdens and physician burnout. AI diagnostic models also could enhance diagnostic accuracy for non-headache spe cialists, making headache management more accessible in general medical practice . Furthermore, virtual health assistants, digital applications, and wearable dev ices are pivotal in migraine management, enabling symptom tracking, trigger iden tification, and preventive measures. AI tools also could offer stress management and pain relief solutions to headache patients through digital applications. Ho wever, considerations such as technology literacy, compatibility, privacy, and r egulatory standards must be adequately addressed."

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New Machine Learning Study Results from School of Computer Science and Engineeri ng Described (Pavement Distress Detection, Classification, and Analysis Using Ma chine Learning Algorithms: A Survey)

81-81页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on artificial intelligence have been published. According to news reporting originating from Tamil Nadu, In dia, by NewsRx correspondents, research stated, "Distress is any observable dete rioration or damage that negatively impacts the road's performance and safety." Funders for this research include Manipal Academy of Higher Education (Mahe), Ma nipal, Karnataka, India. The news journalists obtained a quote from the research from School of Computer Science and Engineering: "Potholes cracks, rutting, and bleeding are a few examp les of distress. Maintaining the roads and detecting distress on the surface of the road is critical to avoid impending accidents, consequently saving lives. Th e article primarily explains the systematic approach of autonomous techniques fo r detecting distress such as potholes and cracks. Among the array of methods emp loyed for finding distress, the current study reviews the features of three diff erent artificial intelligence (AI) techniques, which include machine and deep le arning approaches. Applications of these techniques help in finding pavement dis tress apart from the vibration, 2D, and 3D methods. This systematic approach exp lains the autonomous techniques for detecting surface distress, the scope of com bining those approaches, and their limitations."

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Johns Hopkins University Reports Findings in Nanoplastics (Integrating Metal-Phe nolic Networks-Mediated Separation and Machine Learning-Aided Surface-Enhanced R aman Spectroscopy for Accurate Nanoplastics Quantification and Classification)

82-82页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Nanotechnology - Nanoplastics is the subject of a report. According to news reporting from Baltimore, Maryland, b y NewsRx journalists, research stated, "Increasing accumulation of nanoplastics across ecosystems poses a significant threat to both terrestrial and aquatic lif e. Surfaceenhanced Raman scattering (SERS) is an emerging technique used for na noplastics detection." The news correspondents obtained a quote from the research from Johns Hopkins Un iversity, "However, the identification and classification of nanoplastics using SERS faces chAllenges regarding sensitivity and accuracy as nanoplastics are spa rsely dispersed in the environment. Metal-phenolic networks (MPNs) have the pote ntial to rapidly concentrate and separate various types and sizes of nanoplastic s. SERS combined with machine learning may improve prediction accuracy. Herein, we report the integration of MPNs-mediated separation with machine learning-aide d SERS methods for the accurate classification and high-precision quantification of nanoplastics, which is tailored to include the complete region of characteri stic peaks across diverse nanoplastics in contrast to the traditional manual ana lysis of SERS spectra on a singular characteristic peak. Our customized machine learning system (e.g., outlier detection, classification, quantification) Allows for the identification of detectable nanoplastics (accuracy 81.84% ), accurate classification (accuracy > 97%) , and sensitive quantification of various types of nanoplastics (polystyrene (PS ), poly(methyl methacrylate) (PMMA), polyethylene (PE), and poly(lactic acid) (P LA)) down to ultralow concentrations (0.1 ppm) as well as accurate classificatio n (accuracy > 92%) of nanoplastic mixtures at a subppm level."

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Findings on Artificial Intelligence Reported by Investigators at University of E lectronic Science and Technology of China (Bc4llm: a Perspective of Trusted Arti ficial Intelligence When Blockchain Meets Large Language Models)

83-84页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Artificial Intelligence are presented in a new report. According to news reporting originating in Chengd u, People's Republic of China, by NewsRx journalists, research stated, "In recen t years, artificial intelligence (AI) and machine learning (ML) are reshaping so ciety's production methods and productivity, and also changing the paradigm of s cientific research. Among them, the AI language model represented by ChatGPT has made great progress." Financial supporters for this research include National Key Research & Development Program of China, National Natural Science Foundation of China (NSFC ), Natural Science Foundation of Sichuan Province, Open Research Projects of Zhe jiang Lab, PCL Future Greater-Bay Area Network Facilities for Large-Scale Experi ments and Applications. The news reporters obtained a quote from the research from the University of Ele ctronic Science and Technology of China, "Such large language models (LLMs) serv e people in the form of AI-generated content (AIGC) and are widely used in consu lting, healthcare, and education. However, it is difficult to guarantee the auth enticity and reliability of AIGC learning data. In addition, there are also hidd en dangers of privacy disclosure in distributed AI training. Moreover, the conte nt generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition. The above information security issues in the coming era of AI powered by LLMs will be infinitely amplified and affect everyon e's life. Therefore, we consider empowering LLMs using blockchain technology wit h superior security features to propose a vision for trusted AI. This survey mai nly introduces the motivation and technical route of blockchain for LLM (BC4LLM) , including reliable learning corpus, secure training process, and identifiable generated content. Meanwhile, this survey also reviews the potential application s and future chAllenges, especiAlly in the frontier communication networks field , including network resource Allocation, dynamic spectrum sharing, and semantic communication."

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First Affiliated Hospital of Wenzhou Medical University Reports Findings in Lary ngeal Cancer (Molecular characterization, immunocorrelation analysis, WGCNA anal ysis and machine learning modeling of genes associated with copper death subtype s of ...)

84-84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 Oncology - Laryngeal C ancer is the subject of a report. According to news reporting out of Wenzhou, Pe ople's Republic of China, by NewsRx editors, research stated, "Laryngeal cancer is a malignant tumor that originates from the mucous membrane of the larynx. Cur rently, the specific involvement mechanism of copper death in laryngeal cancer p atients has not been deeply studied." Our news journalists obtained a quote from the research from the First Affiliate d Hospital of Wenzhou Medical University, "This study aims to explore the molecu lar characteristics and clinical survival significance of copper death-related g enes in laryngeal cancer. Relevant transcriptomes and clinical data were retriev ed and downloaded from the GEO database. Differential expression genes related t o laryngeal cancer and copper death were selected, and the immune function, clin ical risk correlation, and survival prognosis were analyzed. The differential an alysis results showed that the differential expression genes related to laryngea l cancer and Cu-proptosis included SLC31A1 and ATP7B, and there was interaction between the immune cell groups in the differential genes of copper death in lary ngeal cancer. Decreasing the expression of the gene ANXA5 or increasing the expr ession of the gene SERPINH1 can increase the susceptibility to laryngeal cancer. Copper death-related genes can affect the survival prognosis of laryngeal cance r patients."

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Second Affiliated Hospital of Chongqing Medical University Reports Findings in A rtificial Intelligence (Quality control of elbow joint radiography using a YOLOv 8-based artificial intelligence technology)

85-86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 out of Chongqing, Peop le's Republic of China, by NewsRx editors, research stated, "To explore an artif icial intelligence (AI) technology employing YOLOv8 for quality control (QC) on elbow joint radiographs. From January 2022 to August 2023, 2643 consecutive elbo w radiographs were collected and randomly assigned to the training, validation, and test sets in a 6:2:2 ratio."

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