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    Studies from Taiyuan University of Technology Reveal New Findings on Machine Lea rning (Research on Annual Runoff Prediction Model Based on Adaptive Particle Swa rm Optimization-Long Short-Term Memory with Coupled Variational Mode Decompositi on ...)

    79-80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 originating from Taiyuan, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “Accurate me dium- and long-term runoff prediction models play crucial guiding roles in regio nal water resources planning and management. However, due to the significant var iation in and limited amount of annual runoff sequence samples, it is difficult for the conventional machine learning models to capture its features, resulting in inadequate prediction accuracy.” Funders for this research include National Natural Science Foundation of China; Basic Research Programs of Shanxi Province; Open Research Fund of Henan Key Labo ratory of Water Resources Conservation And Intensive Utilization in The Yellow R iver Basin.
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    New Robotics Findings Reported from Shanghai University of Electric Power (Distu rbance-rejection Position Tracking Control of Industrial Robots Via a Discrete-t ime Super-twisting Observer-based Fast Terminal Sliding Mode Approach)

    80-81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 originating in Shanghai, People’s Re public of China, by NewsRx journalists, research stated, “Facing the system unce rtainties caused by unmodeled dynamics and unpredictable external disturbances, the robot position control for meeting the high-performance control requirements on higher accuracy and faster beat is vital for many industrial applications, s uch as welding and laser cutting tasks. This work aims to cope with the problem of precise and fast position tracking for robot manipulators with an effective a nd safe control scheme.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Fundamental Research Funds for the Central Universities.
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    Radiation Oncology Department Reports Findings in Artificial Intelligence (Artif icial Intelligence-suggested Predictive Model of Survival in Patients Treated Wi th Stereotactic Radiotherapy for Early Lung Cancer)

    82-83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 Bergamo, Italy, b y NewsRx journalists, research stated, “Overall survival (OS)-predictive models to clinically stratify patients with stage I Non-Small Cell Lung Cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) are still unavailable. The aim of this work was to build a predictive model of OS in this setting.” The news correspondents obtained a quote from the research from Radiation Oncolo gy Department, “Clinical variables of patients treated in three Institutions wit h SBRT for stage I NSCLC were retrospectively collected into a reference cohort A (107 patients) and 2 comparative cohorts B1 (32 patients) and B2 (38 patients) . A predictive model was built using Cox regression (CR) and artificial neural n etworks (ANN) on reference cohort A and then tested on comparative cohorts. Coho rt B1 patients were older and with worse chronic obstructive pulmonary disease ( COPD) than cohort A. Cohort B2 patients were heavier smokers but had lower Charl son Comorbidity Index (CCI). At CR analysis for cohort A, only ECOG Performance Status 0-1 and absence of previous neoplasms correlated with better OS. The mode l was enhanced combining ANN and CR findings. The reference cohort was divided i nto prognostic Group 1 (0-2 score) and Group 2 (3-9 score) to assess model’s pre dictions on OS: grouping was close to statistical significance (p=0.081). One an d 2-year OS resulted higher for Group 1, lower for Group 2. In comparative cohor ts, the model successfully predicted two groups of patients with divergent OS tr ends: higher for Group 1 and lower for Group 2. The produced model is a relevant tool to clinically stratify SBRT candidates into prognostic groups, even when a pplied to different cohorts.”
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    New Findings from Purdue University in the Area of Machine Learning Published (F erroelectric capacitors and field-effect transistors as in-memory computing elem ents for machine learning workloads)

    84-85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 new report. According to news reporting out of Purdue Univ ersity by NewsRx editors, research stated, “This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate machine learning ( ML) workloads.” Funders for this research include Semiconductor Research Corporation.
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    University of Milano Bicocca Reports Findings in Machine Learning (Vibrational s pectroscopy coupled with machine learning sheds light on the cellular effects in duced by rationally designed TLR4 agonists)

    85-85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 Milano, Italy, by News Rx correspondents, research stated, “In this work, we present the potential of F ourier transform infrared (FTIR) microspectroscopy to compare on whole cells, in an unbiased and untargeted way, the capacity of bacterial lipopolysaccharide (L PS) and two rationally designed molecules (FP20 and FP20Rha) to activate molecul ar circuits of innate immunity. These compounds are important drug hits in the d evelopment of vaccine adjuvants and tumor immunotherapeutics.” Our news journalists obtained a quote from the research from the University of M ilano Bicocca, “The biological assays indicated that FP20Rha was more potent tha n FP20 in inducing cytokine production in cells and in stimulating IgG antibody production post-vaccination in mice. Accordingly, the overall significant IR spe ctral changes induced by the treatment with LPS and FP20Rha were similar, lipids and glycans signals being the most diagnostic, while the effect of the less pot ent molecule FP20 on cells resulted to be closer to control untreated cells.”
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    New Findings from Nanjing University of Information Science and Technology (NUIS T) Update Understanding of Robotics (Dsnet: Double Strand Robotic Grasp Detectio n Network Based On Cross Attention)

    86-86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 Robotics is the subjec t of a report. According to news reporting out of Nanjing, People’s Republic of China, by NewsRx editors, research stated, “In this letter, we propose a Double Strand robotic grasp detection Network (DSNet), that combines a transformer bran ch and a U-Net branch within an encoder-decoder structure. The DSNet is designed to reconcile differences between these two approaches and provide access to bot h local and global resources.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
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    'Methods And Apparatus For Machine Learning System For Edge Computer Vision And Active Reality' in Patent Application Approval Process (USPTO 20240135319)

    87-90页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A patent application by the inventors FRIEDL, Jonah (Kirkland, WA, US); GRESCHLER, David (Kirkland, WA, US); VOGEL, Jo n (Kirkland, WA, US), filed on January 4, 2024, was made available online on Apr il 25, 2024, according to news reporting originating from Washington, D.C., by N ewsRx correspondents. This patent application is assigned to NOMAD Go Inc. (Kirkland, Washington, Unit ed States). The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “The management of an inventory relies heavily o n human-based calculations and actions. Some known systems allow humans to effic iently manage their inventory of items at massive scales using cameras placed in warehouses or retail spaces. Furthermore, some known systems require strict org anization and single appearances per item without distinguishing the packaging o f items sharing the same stock keeping unit (SKU) or the various ways items are stored. Moreover, some known systems use fixed cameras with computer vision and can require multiple cameras that are limited to specific areas and views with m ultiple blind spots. Additionally, such known technologies often rely on manual data input, which can be tedious, time consuming, and lead to inaccuracies.
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    Researchers Submit Patent Application, 'System And Method For Estimating The Pos e Of A Localizing Apparatus Using Reflective Landmarks And Other Features', for Approval (USPTO 20240135703)

    90-95页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – From Washington, D.C., NewsRx journali sts report that a patent application by the inventors HEHN, Markus (Zurich, CH); WIDMER, Lino (Zurich, CH), filed on December 13, 2021, was made available onlin e on April 25, 2024. No assignee for this patent application has been made.News editors obtained the following quote from the background information suppli ed by the inventors: “Indoor navigation of robots, for example drones, is an imp ortant problem, e.g., in the field of automatic warehousing. Such robots are loc alizing agents. To facilitate indoor navigation, the robot, e.g., the drone, nee ds to know its current position with respect to its environment. Contrary to out door environments in which GNSS (Global Navigation Satellite Systems) can be emp loyed, providing a high localization accuracy, GNSS in indoor environments is of ten not reliable due to signal attenuation and multi-path effects. Existing RF l ocalization technologies for indoor and outdoor spaces also struggle with signal attenuation and multi-path effects limiting the usability in complex environmen ts, for instance, in the presence of a significant amount of metal.
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    Patent Issued for Obstacle recognition method for autonomous robots (USPTO 11966 229)

    96-99页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – According to news reporting originatin g from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Eb rahimi Afrouzi, Ali (Henderson, NV, US), Mehrnia, Soroush (Helsingborg, SE), fil ed on May 22, 2023, was published online on April 23, 2024. The assignee for this patent, patent number 11966229, is AI Incorporated (Toront o, Canada). Reporters obtained the following quote from the background information supplied by the inventors: “Autonomous robots are being used with increasing frequency to carry out routine tasks such as vacuuming, mopping, cutting grass, polishing fl oors, etc. During operation, a robot may encounter objects that may act as an ob struction to the operation of the robot. For example, objects such as cords, wir es, clothing, and toys may become stuck in the wheels or other moving parts of t he robot as it drives close to or over the objects. Interaction with such object s may cause the robot to malfunction or prevent the robot from completing a task . A method for avoiding entanglement with objects may be useful.”
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    Researchers Submit Patent Application, 'Interactive Concept Editing In Computer- Human Interactive Learning', for Approval (USPTO 20240135098)

    107-110页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – From Washington, D.C., NewsRx journali sts report that a patent application by the inventors AMERSHI, Saleema A. (Seatt le, WA, US); BOTTOU, Leon (Kirkland, WA, US); GRANGIER, David G. (Kirkland, WA, US); SIMARD, Patrice Y. (Bellevue, WA, US), filed on December 1, 2023, was made available online on April 25, 2024. No assignee for this patent application has been made. News editors obtained the following quote from the background information suppli ed by the inventors: “A collection of data that is extremely large can be diffic ult to search and/or analyze. For example, in the case of the Web, a large fract ion of the data is unstructured and value is locked in the data itself. It is no t enough to store the web page of a service provider. For this information to be useful, it needs to be understood. A string of digits could be a model number, a bank account, or a phone number depending on context. For instance, in the con text of a ski product, the string “Length: 170,175,180 cm” refers to 3 different ski lengths, not a ski length of 1700 kilometers. An incorrect interpretation o f the data may result in useless information.
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