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    Reports Outline Machine Learning Study Findings from Beijing Forestry University (Discrimination of New and Aged Seeds Based on On-Line Near-Infrared Spectrosco py Technology Combined with Machine Learning)

    38-39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 originating from Beijing, People's Repu blic of China, by NewsRx correspondents, research stated, "The harvest year of m aize seeds has a significant impact on seed vitality and maize yield." Financial supporters for this research include Natural Science Foundation of Jia ngsu Province; National Natural Science Foundation of China; Open Project of Chi na Food Flavor And Nutrition Health Innovation Center. The news reporters obtained a quote from the research from Beijing Forestry Univ ersity: "Therefore, it is vital to identify new seeds. In this study, an on-line near-infrared (NIR) spectra collection device (899- 1715 nm) was designed and em ployed for distinguishing maize seeds harvested in different years. Compared wit h least squares support vector machine (LS-SVM), k-nearest neighbor (KNN), and e xtreme learning machine (ELM), the partial least squares discriminant analysis ( PLS-DA) model has the optimal recognition performance for maize seed harvest yea rs. Six different preprocessing methods, including Savitzky-Golay smoothing (SGS ), standard normal variate transformation (SNV), multiplicative scatter correcti on (MSC), Savitzky-Golay 1 derivative (SG-D1), Savitzky-Golay 2 derivative (SG-D 2), and normalization (Norm), were used to improve the quality of the spectra. T he Monte Carlo cross-validation uninformative variable elimination (MC-UVE), com petitive adaptive reweighted sampling (CARS), bootstrapping soft shrinkage (BOSS ), successive projections algorithm (SPA), and their combinations were used to o btain effective wavelengths and decrease spectral dimensionality."
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    Cancer Hospital Reports Findings in Post-Operative Complications (Personalized P rediction of Postoperative Complication and Survival Among Colorectal Liver Meta stases Patients Receiving Simultaneous Resection Using Machine Learning Approach es: ...)

    39-40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 Post-Operative Complic ations is the subject of a report. According to news reporting out of Beijing, P eople's Republic of China, by NewsRx editors, research stated, "To predict clini cal important outcomes for colorectal liver metastases (CRLM) patients receiving colorectal resection with simultaneous liver resection by integrating demograph ic, clinical, laboratory, and genetic data. Random forest (RF) models were devel oped to predict postoperative complications and major complications (binary outc omes), as well as progression-free survival (PFS) and overall survival (OS) (tim e-to-event outcomes) of the CRLM patients based on data from two hospitals."
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    University of Sao Paulo Reports Findings in Machine Learning (Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers an d machine learning applications in dairy cattle)

    40-41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 Sao Paulo, Brazil, by NewsRx correspondents, research stated, "This study aimed to compare the accurac y of IFN-t stimulated gene abundance (ISGs) in peripheral blood mononuclear cell s (PBMCs), CL blood perfusion by Doppler ultrasound (Doppler-US), plasma concent ration of P4 on Day 21 and pregnancy-associated glycoproteins (PAGs) test on Day 25 after timed-artificial insemination (TAI) for early pregnancy diagnosis in d airy cows and heifers. Holstein cows (n = 140) and heifers (n = 32) were subject ed to a hormonal synchronization protocol and TAI on Day 0."
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    Researchers from University of Nis Publish Findings in Machine Learning (Applyin g eXplainable AI Techniques to Interpret Machine Learning Predictive Models for the Analysis of Problematic Internet Use among Adolescents)

    41-42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 the University of Nis by NewsRx correspondents, research stated, "This resear ch focusses on the potential application of artificial intelligence (AI) techniq ues in the analysis of behavioural addictions, specifically addressing problemat ic Internet use among adolescents." The news reporters obtained a quote from the research from University of Nis: "U sing tabular data from a representative sample from Serbian high schools, the au thors investigated the feasibility of employing eXplainable AI (XAI) techniques, placing special emphasis on feature selection and feature importance methods. T he results indicate a successful application to tabular data, with global interp retations that effectively describe predictive models. These findings align with previous research, which confirms both relevance and accuracy. Interpretations of individual predictions reveal the impact of features, especially in cases of misclassified instances, underscoring the significance of XAI techniques in erro r analysis and resolution. Although AI's influence on the medical domain is subs tantial, the current state of XAI techniques, although useful, is not yet advanc ed enough for the reliable interpretation of predictions."
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    Studies from School of Computing Describe New Findings in Artificial Intelligenc e (Velocious: a Resilient Iot Architecture for 6g Based Intelligent Transportati on System With Expeditious Movement Mechanism)

    42-43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 from Chenn ai, India, by NewsRx correspondents, research stated, "The Internet of Things [IoT] has provided fascinating solutions in various fields. As the significant usages of IoT in smart cities incorporate almost all the domain s such as healthcare, Vehicle to Vehicle (V2V), Energy sector, home automation, pollution monitoring, garbage collection, gardening, environment, road and rail transportation, education, public and private sector organization, etc., the nee d for developing an intelligent IoT architecture for every domain is a paramount criterion." Our news editors obtained a quote from the research from the School of Computing , "In this research, we are interested in designing and developing, an IoT archi tecture, Velocious, which will provide a fast and speedy transportation system w ithout delay and with a greater obstacle avoidance mechanism. The integration of sensors and actuators with a cognitive level of thinking based on circumstances leads to decisions with reasoning using the explainable Artificial Intelligence (AI) concept. The procedure of data acquisition, data transferring, and data in terpretation requires a federated learning concept with context awareness where the location, time, and situation act as the prime context in decision-making. I t can be purported that the development of a smart city relies on different sect ors, and consequently the development of an Intelligent Transport System (ITS), highly relies on expansion. Development, penetration, and growth of IoT technolo gies with seamless integration with other domain architectures too. To lead smar t and safe travel with fuel consumption, obstacle avoidance, and traffic managem ent decisions are mandated with explainable Artificial Intelligence (AI) which c ould be built in Velocious. This research provides Velocious to be applicable to incorporate integrating all the necessary information required for setting up d ecisions and making rules. These types of rules can also be viewed as a rule set with proper explanations in decision-making in critical circumstances."
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    Report Summarizes Machine Learning Study Findings from Xi'an University of Techn ology (Urban Inundation Rapid Prediction Method Based On Multi-machine Learning Algorithm and Rain Pattern Analysis)

    43-44页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Machine Learning have be en published. According to news reporting originating in Shaanxi, People's Repub lic of China, by NewsRx journalists, research stated, "Urban inundation disaster s caused by extreme rainfall events are becoming increasingly severe. However, t he numerical inundation model based on physical process has relatively slow comp utational speed and struggle to meet the demands of current forecasting and earl y warning systems." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Chinesisch-Deutsches Mobilitatsprogramm, Key R& D Program of Shaanxi of China, Natural Science Foundations of Shaanxi Province, Key Science and Technology Projects of Power China, Major company -level science and technology projects of Northwest Engineering Corporation Limited, Power Chi na.
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    Fudan University Reports Findings in Bladder Cancer (Machine learning identifies the role of SMAD6 in the prognosis and drug susceptibility in bladder cancer)

    44-45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 - Bladder Can cer is the subject of a report. According to news reporting out of Shanghai, Peo ple's Republic of China, by NewsRx editors, research stated, "Bladder cancer (BC a) is among the most prevalent malignant tumors affecting the urinary system. Du e to its highly recurrent nature, standard treatments such as surgery often fail to significantly improve patient prognosis." Funders for this research include National Natural Science Foundation of China, Leading Talent Program by Shanghai Municipal Health Commission, Medical Innovati on Research Special Project by Science and Technology Commission of Shanghai Mun icipality, Clinical Scientific and Technological Innovation Project by Shanghai Hospital Development Center.
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    Researchers from Tarim University Discuss Findings in Intelligent Systems (Point cloud completion network for 3D shapes with morphologically diverse structures)

    45-46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 in telligent systems. According to news originating from Tarim University by NewsRx editors, the research stated, "Point cloud completion is a challenging task tha t involves predicting missing parts in incomplete 3D shapes. While existing stra tegies have shown effectiveness on point cloud datasets with regular shapes and continuous surfaces, they struggled to manage the morphologically diverse struct ures commonly encountered in real-world scenarios." Funders for this research include The National Natural Science Foundation of Chi na; The First-class Undergraduate Programmes Foundation in Computer Graphics At Tarim University; The First-class Major in The Internet of Things Engineering At Tarim University.
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    Chinese Academy of Sciences Reports Findings in Robotics (A Suspended, 3D Morphi ng Sensory System for Robots to Feel and Protect)

    46-47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 from Ningbo, People's Republic of Chi na, by NewsRx journalists, research stated, "Artificial sensory systems with syn ergistic touch and pain perception hold substantial promise for environment inte raction and human-robot communication. However, the realization of biological sk in-like functional integration of sensors with sensitive touch and pain percepti on still remains a challenge." Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China. The news correspondents obtained a quote from the research from the Chinese Acad emy of Sciences, "Here, a concept is proposed of suspended electronic skins enab ling 3D deformation-mechanical contact interactions for achieving synergetic ult rasensitive touch and adjustable pain perception. The suspended sensory system c an sensitively capture tiny touch stimuli as low as 0.02 Pa and actively perceiv e pain response with reliable 5200 cycles via 3D deformation and mechanical cont act mechanism, respectively. Based on the touch-pain effect, a visualized feedba ck demo with miniaturized sensor arrays on artificial fingers is rationally desi gned to give a pain perception mapping on sharp surfaces."
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    Study Findings from Hunan Normal University Provide New Insights into Artificial Intelligence (Innovative application of artificial intelligence in a multi-dime nsional communication research analysis: a critical review)

    47-48页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting from Hunan Normal Univer sity by NewsRx journalists, research stated, "Artificial intelligence (AI) imita tes the human brain's capacity for problem-solving and making decisions by using computers and other devices." Our news editors obtained a quote from the research from Hunan Normal University : "People engage with artificial intelligence-enabled products like virtual agen ts, social bots, and language-generation software, to name a few. The paradigms of communication theory, which have historically put a significant focus on huma n-to-human communication, do not easily match these gadgets. AI in multidimensio nal touch is the subject of this review article, which provides a comprehensive analysis of the most recent research published in the field of AI, specifically related to communication. Additionally, we considered several theories and model s (communication theory, AI-based persuasion theory, social exchange theory, Fra mes of mind, Neural network model, L-LDA model, and Routine model) to explain a complex phenomenon and to create a conceptual framework that is appropriate for this goal and a voluntary relationship between two or more people that lasts for an extended period. Communication and media studies focus on human-machine comm unication (HMC), a rapidly developing research area."
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