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    Findings from Universitas Pendidikan Indonesia Advance Knowledge in Machine Lear ning (Digital audio preservation for Indonesian traditional vocal recognition ba sed on machine learning: A literature review and bibliometric analysis)

    19-20页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting originating from the Univer sitas Pendidikan Indonesia by NewsRx correspondents, research stated, “The study aims to save Indonesia’s extensive voice history by comprehensively examining e xisting literature and doing a bibliometric analysis.” The news journalists obtained a quote from the research from Universitas Pendidi kan Indonesia: “This approach provides a comprehensive understanding of this fie ld’s development, methodology, obstacles, and potential future paths. The key fo cus is machine learning approaches to identify and safeguard Indonesian traditio nal vocals using several methods, like spectrogram-based techniques, convolution al and recurrent neural networks, transfer learning, attention mechanisms, and h ybrid learning. Examining these technologies considers Indonesia’s voice variety , providing insights into their adaptability to handling distinct scales, tuning s, and stylistic variances. The study incorporates a bibliometric analysis to me asure the expansion of literature and ascertain the prominent authors, journals, and keywords in this developing topic. This study improves our comprehension of the research terrain and the conceptual paths that drive the progress of the fi eld. Indonesia’s traditional vocal music faces the imminent challenges of indust rialization and globalization.”
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    New Support Vector Machines Findings Reported from Peking University (Magnetic A nomaly Detection Method Based On Multifeatures and Support Vector Machine)

    20-21页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Support Vector Machines have been published. According to news reporting originating in Beijing, People’ s Republic of China, by NewsRx journalists, research stated, “Magnetic anomaly d etection methods for identifying concealed ferromagnetic targets have been widel y used in various fields. Enhancing detection capabilities under low signal-to-n oise ratios (SNRs) is an urgent concern.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
      原文链接:
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    University of Mons Reports Findings in Laryngeal Cancer (Surgical, Functional, a nd oncological outcomes of transoral robotic surgery for cT1-T3 supraglottic lar yngeal Cancers: A systematic review)

    21-22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 Mons, Belgi um, by NewsRx editors, the research stated, “This systematic review investigated the surgical, functional, and oncological outcomes of transoral robotic supragl ottic laryngectomy (TORS-SGL) for cT1-T3 laryngeal squamous cell carcinoma (LSCC ). Two investigators conducted an updated PubMed, Scopus, and Cochrane Library s ystematic review for studies investigating the surgical, functional, and oncolog ical outcomes of TORS-SGL using the PRISMA statements.” Our news journalists obtained a quote from the research from the University of M ons, “The bias analysis was conducted with the MINORS. Twenty-one studies were i ncluded, accounting for 896 patients. TORS-SGL was primarily performed for cT1 ( 39.1 %), cT2 (46.9 %), and some selected cT3 (7.7 % ) LSCCs. Surgical margins were positive in 10.8 % of cases. The me an hospital stay was 8.6 days. Hemorrhage (6.3 %), pneumonia (5.5 % ), and aspiration (1.7 %) are the primary complications. The surgic al margins were positive in 10.6 % of cases. Feeding tubes, tempor ary tracheotomy, and definitive percutaneous gastrostomy are found in 65.6 % , 19.7 %, and 5.2 % of patients, respectively. The or al diet is restarted after a mean of 7.2 days. The 5-year OS and DFS of TORS-SGL were estimated to be 78.3 %, and 91.7 %, with 5-year local-relapse-free survival and nodal-relapse-free survival of 90.8 % , and 86.6 %, respectively. The TORS-SGL is a safe, and effective s urgical approach for cT1-T3 SGL. The functional and surgical outcomes appear com parable with TOLM-SGL.”
      原文链接:
    • NETL
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    Reports on Robotics Findings from Singapore University of Technology and Design Provide New Insights (Door-Density-Aware Path Planning)

    22-23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 robotics are disc ussed in a new report. According to news reporting from Singapore University of Technology and Design by NewsRx journalists, research stated, “Doors are part of the building infrastructure that mobile robots have to pass through to reach zo nes on the other side.” Funders for this research include National Robotics Programme; Agency For Scienc e, Technology And Research.
      原文链接:
    • NETL
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    Studies from University of Nantes Provide New Data on Robotics (Control Analysis of an Underactuated Bio-inspired Robot)

    23-23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 Robotics are presented i n a new report. According to news originating from Nantes, France, by NewsRx cor respondents, research stated, “This article is devoted to the control of bio-ins pired robots that are underactuated. These robots are composed of tensegrity joi nts remotely actuated with cables, which mimic the musculoskeletal system of the bird neck.” Our news journalists obtained a quote from the research from the University of N antes, “A computed torque control (CTC) is applied to these robots as well as an original control called pseudo computed torque control (PCTC). This new control uses the dynamics and the pseudo-inverse of the Jacobian matrix. The stability of the two proposed controls is then analyzed through linearization of the dynam ic model and expression of the closed-loop transfer function in the Laplace doma in. We show that, depending on the desired trajectory, the CTC can be unstable w hen the controlled variables are the end effector position and orientation. For a robot with many joints and a limited number of cables, the CTC is always unsta ble. Instead, the PCTC shows a large domain of stability. The analysis is comple mented by experimental tests demonstrating that the CTC and PCTC exhibit similar performance when the CTC is stable.”
      原文链接:
    • NETL
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    New Alopecia Findings from Fudan University Outlined (A Comparative Study On the Application of Robotic Hair Restoration Technology Versus Traditional Follicula r Unit Excision In Male Androgenetic Alopecia)

    24-25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 Skin Diseases and Condit ions - Alopecia are presented in a new report.According to news reporting from Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “T he robotic hair transplant technology, ARTAS, has a series of fine mechanical st ructure and an intelligent recognition system that allows it to independently se lect hair follicular units (FUs) and effectively harvest hair. After entering Ch ina in 2016, ARTAS has attracted the attention of hair transplant surgeons and h air loss patients given its advantages in a short learning curve and simple oper ation.” Financial support for this research came from Shanghai Shenkang Hospital Develop ment Center Clinical Three Year Action Plan.
      原文链接:
    • NETL
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    Researchers’ Work from Kyushu Institute of Technology Focuses on Robotics (Tethe rbot: Experimental Demonstration and Path Planning of Cable-Driven Climbing in M icrogravity)

    24-24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 reporting originating from Kitakyushu, Japa n, by NewsRx correspondents, research stated, “In this paper, we introduce Tethe rbot, a cable-driven climbing robot designed for microgravity environments with sparse holding points, such as space stations or asteroids.” Financial supporters for this research include Japan Society For The Promotion o f Science (Jsps) Kakenhi. The news journalists obtained a quote from the research from Kyushu Institute of Technology: “Tetherbot consists of a platform with a robotic arm that is suspen ded via cables from multiple grippers. It achieves climbing locomotion by altern ately positioning the platform with the cables and relocating the grippers with the robotic arm from one holding point to the next. The main contribution of thi s work is the first experimental demonstration of autonomous cable-driven climbi ng in an environment with sparse holding points. To this end, we outline the des ign, kinematics, and statics of the Tetherbot and present a path planning algori thm to relocate the grippers. We demonstrate autonomous cable-driven climbing th rough an experiment conducted in a simulated microgravity environment using the path planning algorithm and a prototype of the robot.”
      原文链接:
    • NETL
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    Studies from Jiangsu University Update Current Data on Robotics (Underwater Robo t Target Detection Algorithm Based On Yolov8)

    25-26页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on Robotics. Acc ording to news reporting originating in Zhenjiang, People’s Republic of China, b y NewsRx journalists, research stated, “Although the ocean is rich in energy and covers a vast portion of the planet, the present results of underwater target i dentification are not sufficient because of the complexity of the underwater env ironment. An enhanced technique based on YOLOv8 is proposed to solve the problem s of low identification accuracy and low picture quality in the target detection of current underwater robots.” Funders for this research include Jiangsu Province Industrial Prospect and Key C ore Technology Project, Postgraduate Research and Practice Innovation Program of Jiangsu Province.
      原文链接:
    • NETL
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    New Findings on Machine Learning from Chinese Academy of Sciences Summarized (Au to-machine Learning-based w-band Highefficiency Oscillator Design)

    26-27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 originating from Beijing, P eople’s Republic of China, by NewsRx correspondents, research stated, “In this a rticle, automatic machine learning (ML) technology and global optimization algor ithms have been combined to achieve a fast and high-performance extended interac tion oscillator (EIO) design. An EIO model is manually designed to give a compar ison.” Funders for this research include National Magnetic Confinement Fusion (MCF) Ene rgy Research and Development Program, Scientific Instrument Developing Project o f Chinese Academy of Sciences.
      原文链接:
    • NETL
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    Research on Machine Learning Published by a Researcher at Baekdudaegan National Arboretum (Non-Destructive Seed Viability Assessment via Multispectral Imaging a nd Stacking Ensemble Learning)

    27-28页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting from the Baekdudaegan Natio nal Arboretum by NewsRx journalists, research stated, “The tetrazolium (TZ) test is a reliable but destructive method for identifying viable seeds.” Funders for this research include R&D Program For Forest Science Te chnology. Our news journalists obtained a quote from the research from Baekdudaegan Nation al Arboretum: “In this study, a non-destructive seed viability analysis method f or Allium ulleungense was developed using multispectral imaging and stacking ens emble learning. Using the Videometerlab 4, multispectral imaging data were colle cted from 390 A. ulleungense seeds subjected to NaCl-accelerated aging treatment s with three repetitions per treatment. Spectral values were obtained at 19 wave lengths (365-970 nm), and seed viability was determined using the TZ test. Next, 80% of spectral values were used to train Decision Tree, Random F orest, LightGBM, and XGBoost machine learning models, and 20% were used for testing. The models classified viable and non-viable seeds with an acc uracy of 95-91% on the K-Fold value (n = 5) and 85-81% on the test data. A stacking ensemble model was developed using a Decision Tree as the meta-model, achieving an AUC of 0.93 and a test accuracy of 90% .”
      原文链接:
    • NETL
    • NSTL