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    Swiss Federal Institute of Technology Lausanne (EPFL) Reports Findings in Machin e Learning (Solvation Free Energies from Machine Learning Molecular Dynamics)

    55-56页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting from Lausanne, Switzerland, by NewsRx jo urnalists, research stated, “The present work proposes an extension to the appro ach of [Xi, C; et al. 6878] to calculate i on solvation free energies from first-principles (FP) molecular dynamics (MD) si mulations of a hybrid solvation model. The approach is first re-expressed within the quasi-chemical theory of solvation.” The news correspondents obtained a quote from the research from the Swiss Federa l Institute of Technology Lausanne (EPFL), “Then, to allow for longer simulation times than the original first-principles molecular dynamics approach and thus i mprove the convergence of statistical averages at a fraction of the original com putational cost, a machine-learned (ML) energy function is trained on FP energie s and forces and used in the MD simulations. The ML workflow and MD simulation t imes ( 200 ps) are adjusted to converge the predicted solvation energies within a chemical accuracy of 0.04 eV.”
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    Huazhong University of Science and Technology Reports Findings in Rectal Cancer (Machine learning model for prediction of permanent stoma after anterior resecti on of rectal cancer: A multicenter study)

    56-57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 - Rectal Canc er is the subject of a report. According to news reporting from Wuhan, People’s Republic of China, by NewsRx journalists, research stated, “The conversion from a temporary to a permanent stoma (PS) following rectal cancer surgery significan tly impacts the quality of life of patients. However, there is currently a lack of practical preoperative tools to predict PS formation.” The news correspondents obtained a quote from the research from the Huazhong Uni versity of Science and Technology, “The purpose of this study is to establish a preoperative predictive model for PS using machine learning algorithms to guide clinical practice. In this retrospective study, we analyzed clinical data from a total of 655 patients who underwent anterior resection for rectal cancer, with 552 patients from one medical center and 103 from another. Through machine learn ing algorithms, five predictive models were developed, and each was thoroughly e valuated for predictive performance. The model with superior predictive accuracy underwent additional validation using both an independent testing cohort and th e external validation cohort. The Shapley Additive exPlanations (SHAP) approach was employed to elucidate the predictive factors influencing the model, providin g an in-depth visual analysis of its decisionmaking process. Eight variables we re selected for the construction of the model. The support vector machine (SVM) model exhibited superior predictive performance in the training set, evidenced b y an AUC of 0.854 (95 % CI:0.803-0.904). This performance was corr oborated in both the testing set and external validation set, where the model de monstrated an AUC of 0.851 (95%CI:0.748-0.954) and 0.815 (95% CI:0.710-0.919), respectively, indicating its efficacy in identifying the PS.”
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    Research from University of Rhode Island Has Provided New Data on Machine Learni ng (Analysis of Emerging Variants of Turkey Reovirus using Machine Learning)

    57-58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 artificial in telligence have been published. According to news originating from the Universit y of Rhode Island by NewsRx editors, the research stated, “Avian reoviruses cont inue to cause disease in turkeys with varied pathogenicity and tissue tropism. T urkey enteric reovirus has been identified as a causative agent of enteritis or inapparent infections in turkeys.” Our news editors obtained a quote from the research from University of Rhode Isl and: “The new emerging variants of turkey reovirus, tentatively named turkey art hritis reovirus (TARV) and turkey hepatitis reovirus (THRV), are linked to tenos ynovitis/arthritis and hepatitis, respectively. Turkey arthritis and hepatitis r eoviruses are causing significant economic losses to the turkey industry. These infections can lead to poor weight gain, uneven growth, poor feed conversion, in creased morbidity and mortality and reduced marketability of commercial turkeys. To combat these issues, detecting and classifying the types of reoviruses in tu rkey populations is essential. This research aims to employ clustering methods, specifically K-means and Hierarchical clustering, to differentiate three types o f turkey reoviruses and identify novel emerging variants. Additionally, it focus es on classifying variants of turkey reoviruses by leveraging various machine le arning algorithms such as Support Vector Machines, Naive Bayes, Random Forest, D ecision Tree, and deep learning algorithms, including convolutional neural netwo rks (CNNs). The experiments use real turkey reovirus sequence data, allowing for robust analysis and evaluation of the proposed methods.”
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    Findings from Catholic University Louvain (UCLouvain) Yields New Data on Artific ial Intelligence (Ai Ir: Charting International Relations In the Age of Artifici al Intelligence)

    58-59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 originating from Leuven, Belgium, by NewsRx correspondents, research stated, “Over the past decade, rapid progress in artificial intelligence (AI) has transformed a range of areas, from medicine to strategic games and communication technologies, from art and culture to everyda y office work. It would be na & iuml;ve to assume that this evolut ion does not permeate and alter international affairs.” Our news journalists obtained a quote from the research from Catholic University Louvain (UCLouvain), “Building on, and solidifying, a thriving yet still fragme nted emerging literature on ‘AI IR,’ this forum gathers several critical diagnos es of the way AI technologies impact on various areas of international relations . Introducing new concepts and charting emerging empirical realities, contributo rs explore how AI advances, such as autonomous lethal systems, synthetic imagery and text, or intelligent systems, are already creating new landscapes of violen t and nonviolent international interactions. Yet, behind their distinct takes, c ontributions together stress the need to correctly locate and evaluate specific sites of AI impact, thus offering a nuanced appraisal scrutinizing grand declara tions of an ‘AI revolution’ in global politics. En la & uacute;lti ma d & eacute;cada, el r & aacute;pido progreso que ha tenido lugar con respecto a la Inteligencia Artificial (IA) ha transformado u na serie de & aacute;reas: desde la medicina hasta los juegos estr at & eacute;gicos y las tecnolog & iacute;as de la c omunicaci & oacute;n y desde el arte y la cultura hasta el trabajo cotidiano de la oficina. Ser & iacute;a ingenuo suponer que esta evoluci & oacute;n no afecta ni altera los asuntos internacionales . Este foro re & uacute;ne, partiendo de la base de una literatura emergente pr & oacute;spera pero a & uacute;n fragm entada, en materia de ‘IA, RRII,’ varios diagn & oacute;sticos cr & iacute;ticos de la forma en que las tecnolog & iac ute;as de la IA impactan en las diversas & aacute;reas de las rela ciones internacionales. Nuestros colaboradores estudian, mediante la introducci & oacute;n de nuevos conceptos y el trazado de las realidades emp & iacute;ricas emergentes, la manera a trav & eacute ;s de la cual los avances en el campo de la IA, tales como los sistemas letales aut & oacute;nomos, las im & aacute;genes y los text os sint & eacute;ticos, y los sistemas inteligentes, ya est & aacute;n creando nuevos paisajes de interacciones internacionales, tanto violent as como no violentas. Sin embargo, y al margen de las distintas opiniones expres adas, todas las contribuciones, de manera conjunta, enfatizan la necesidad de ub icar y de evaluar correctamente los sitios espec & iacute;ficos de l impacto de la IA, de manera que se pueda ofrecer una evaluaci & oacute;n matizada que estudie las impactantes declaraciones con relaci & oacute;n a una ‘revoluci & oacute;n de la IA’ dentro de la pol & iacute;tica global. Ces dix derni & egrave;res ann & eacute;es, la progression rapide de l’intelligence artificielle (IA) a transform & eacute; un & eacute;ventail de secteurs, de la m & eacute;decine aux jeux strat & eacute;giques et te chnologies de communications, et de l’art et de la culture au quotidien du trava il de bureau. Il serait bien na & iuml;f de pr & eac ute;tendre que cette & eacute;volution ne touche ni ne modifie les affaires internationales. En se fondant et en renfor & ccedil;ant une litt & eacute;rature & eacute;mergente et flori ssante mais fragment & eacute;e sur les <<RI IA > >, ce forum rassemble pl usieurs diagnostics critiques des cons & eacute;quences des techno logies d’IA sur plusieurs domaines des relations internationales. En introduisan t de nouveaux concepts et en suivant la progression des r & eacute ;alit & eacute;s empiriques & eacute;mergentes, les contributeurs s’int & eacute;ressent aux avanc & eac ute;es de l’IA, telles que les syst & egrave;mes l & eacute;taux autonomes, l’imagerie et le texte synth & eacute;tique s, ou encore les syst & egrave;mes intelligents, ainsi qu’aux nouv eaux paysages d’interactions internationales violentes et pacifiques qu’elles cr & eacute;ent d & eacute;j & agrave;. Pourtant, derri & egrave;re leurs points de vue distincts, les con tributions soulignent toutes la n & eacute;cessit & eacute; de rep & eacute;rer et d’& eacute;valuer cor rectement les sites pr & eacute;cis touch & eacute;s par l’IA.”
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    Researchers from Dr. B.R. Ambedkar National Institute of Technology Report New S tudies and Findings in the Area of Robotics (Reduction In Trajectory Error By Ge nerating Smoother Trajectory for the Time-efficient Navigation of Mobile Robot)

    59-60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 Jalandhar, India, by New sRx journalists, research stated, “Robotics is intertwined with metrology, inclu ding aircraft component inspection, automotive processes, and part geometry opti mization. Optimized trajectory planning is essential for reliable robotic arm op eration and maintaining quality in inspections and geometric enhancements, as we ll as autonomous mobile robot navigation.” The news correspondents obtained a quote from the research from the Dr. B.R. Amb edkar National Institute of Technology, “Technically, a path planning is associa ted as an optimization problem that relies on various parameters such as length minimization problem, smooth trajectory planning, low time/space complexity, and computational load. While considering all these stated parameters, choosing an optimal path to reach the destination is the primary function of path planning t echniques. This research paper is focused on the implementation of adaptive bidi rectional A* (ABA*) algorithm along with new strategy of flexible controlling po ints technique (FCP) to reduce the trajectory error by generating smoother traje ctory. With the increased number of sharp turns, the wheel skidding error is gen erated that reduce the reliability of the path planning techniques by increasing the pose estimation error. By conducting multiple trials, the proposed techniqu e has been implemented, resulting in a 100% reduction in the numbe r of collisions. Furthermore, the application of the new FCP technique eliminate s all sharp turns, leading to a 38% decrease in time lag uncertain ty compared to conventional approaches.”
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    Shandong University Researchers Update Current Data on Machine Learning (BESIII track reconstruction algorithm based on machine learning)

    60-61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 artificial in telligence. According to news reporting out of Shandong University by NewsRx edi tors, research stated, “Track reconstruction is one of the most important and ch allenging tasks in the offline data processing of collider experiments.” The news journalists obtained a quote from the research from Shandong University : “For the BESIII detector working in the tau-charm energy region, plenty of eff orts were made previously to improve the tracking performance with traditional m ethods, such as template matching and Hough transform etc. However, for difficul t tracking tasks, such as the tracking of low momentum tracks, tracks from secon dary vertices and tracks with high noise level, there is still large room for im provement. In this contribution, we demonstrate a novel tracking algorithm based on machine learning method. In this method, a hit pattern map representing the connectivity between drift cells is established using an enormous MC sample, bas ed on which we design an optimal method of graph construction, then an edgeclass ifying Graph Neural Network is trained to distinguish the hit-on-track from nois e hits. Finally, a clustering method based on DBSCAN and RANSAC is developed to cluster hits from multiple tracks. Track fitting algorithm based on GENFIT2 is a lso studied to obtain the track parameters, where deterministic annealing filter are implemented to deal with ambiguities and potential noises.”
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    New Findings on Machine Learning Described by Investigators at University of Sus sex (A High-performance Conical-neck Helmholtz Resonator-based Piezoelectric Sel f-powered System for Urban Transportation)

    61-62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 originating from Brighton, United Kingd om, by NewsRx correspondents, research stated, “As urbanization accelerates, the issue of traffic noise escalates. Efficiently harnessing this prevalent acousti c energy and facilitating its collection and conversion has emerged as a notable challenge in contemporary research.” Our news journalists obtained a quote from the research from the University of S ussex, “This paper introduces a piezoelectric self -powered system anchored on a Conical -Neck Helmholtz Resonator -Based Piezoelectric Self -Powered System (CN HR-PSS) which places the piezoelectric device inside a Conical -Neck Helmholtz r esonator. This system amalgamates acoustic energy harvesting, traffic noise abat ement, and traffic condition discernment. It combines by two parts, including a Piezoelectric Self -Powered Node (PSN) and a machine learning algorithm. The PSN , employing the Conical Neck Helmholtz Resonator and piezoelectric module, seize s noise and transmutes it into electrical energy, showcasing robust scalability. Multiple PSNs coalesce to form a sound barrier for traffic noise mitigation. Co ncurrently, the voltage signals emanated by the PSN also encapsulate traffic sta tus information. The algorithm extracts feature from the output signal and emplo ys machine learning to decipher traffic conditions.”
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    Huaqiao University Reports Findings in Machine Learning (A Generalized Detection Framework for Covert Timing Channels Based On Perceptual Hashing)

    62-63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 Machine Learning are pre sented in a new report. According to news originating from Xiamen, People’s Repu blic of China, by NewsRx correspondents, research stated, “Network covert channe ls use network resources to transmit data covertly, and their existence will ser iously threaten network security. Therefore, an effective method is needed to pr event and detect them.” Financial support for this research came from The Subsidized Project for Postgra duates Innovative Fund in Scientifific Research of Huaqiao University.
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    New Findings from Jiangsu University in Robotics Provides New Insights (Design a nd Development of Dual-extruder Food 3d Printer Based On Selective Compliance As sembly Robot Arm and Printing of Various Inks)

    63-64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 reporting from Zhenjiang, People’s Republic of China, by NewsRx journalists, research stated, “Recent research in food 3D prin ting mainly focuses on ink materials, with relatively limited research on printe r equipment development. Furthermore, the development of traditional food three -axis 3D printer is high cost and low productivity.” Financial supporters for this research include State Key Laboratory of Utilizati on of Woody Oil Resource, National Key Research and Development Program of China , National Natural Science Foundation of China (NSFC), Natural Science Foundatio n of Jiangsu Province, Jiangsu Province Research Fund.
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    Deraya University Researchers Update Current Study Findings on Machine Learning (Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment)

    64-65页
    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 artific ial intelligence. According to news originating from Deraya University by NewsRx correspondents, research stated, “This study investigates the application of ca vitation in non-invasive abdominal fat reduction and body contouring, a topic of considerable interest in the medical and aesthetic fields. We explore the poten tial of cavitation to alter abdominal fat composition and delve into the optimiz ation of fat prediction models using advanced hyperparameter optimization techni ques, Hyperopt and Optuna.” Financial supporters for this research include Deraya University.
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