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    New Findings in Robotics and Automation Described from Zhejiang University (Mbrv o: a Blur Robust Visual Odometry Based On Motion Blurred Artifact Prior)

    57-57页
    查看更多>>摘要：Investigators publish new report on Ro botics - Robotics and Automation. According to news reporting from Hangzhou, Peo ple's Republic of China, by NewsRx journalists, research stated, "How to estimat e camera pose from motion-blurred images remains a challenge for visual odometry . The blurring artifacts are inevitably caused by the exposure during camera mot ion." Financial support for this research came from Leading Goose R&D Pro gram of Zhejiang Province, China. The news correspondents obtained a quote from the research from Zhejiang Univers ity, "While current visual odometry regards them as noise, we argue that it is n ecessary to extract potential information from blur artifacts, as they contain p rior knowledge of camera motion. Base on this, we propose a blur-robust visual o dometry that improves the accuracy of camera pose estimation through exposure tr ajectory. Specifically, we first use the exposure trajectory to guide pixel matc hing between neighboring frames. The blur mask is then generated based on the ma gnitude of the exposure trajectory. The mask makes the pose module pay less atte ntion to the feature information in the severely blurred regions."
      原文链接:
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    China Agricultural University Reports Findings in Machine Learning (Abnormal phe notypic defects detection of jujube using explainable machine learning enhanced computer vision)

    57-58页
    查看更多>>摘要：New research on Machine Learning is th e subject of a report. According to news reporting from Beijing, People's Republ ic of China, by NewsRx journalists, research stated, "Jujube is susceptible to b iotic and abiotic adversity stresses resulting in abnormal phenotypic defects. T herefore, abnormal phenotype fruits should be removed during postharvest sorting to increase added value." The news correspondents obtained a quote from the research from China Agricultur al University, "An improved maximum horizontal diameter linear regression (MHD-L R) method for size grading of jujube prior to detection of abnormal phenotypic d efects was developed. The accuracy of the MHD-LR model is 95%, with an error of only 0.95 mm. In addition, a method for detecting abnormal phenotyp ic defects in jujube was established. It can effectively and accurately classify seven kinds of jujube phenotypes (regular, irregular, wrinkled, moldy, hole-bro ken, skin-broken, and scarred). The data augmentation method based on linear int erpolation can effectively expand the dataset with a variance of only 0.0006. Su pport vector machine-decision tree (SVMDT), logistic regression, back propagatio n neural network, and long shortterm memory network models were established to classify jujube samples with different phenotypes, with accuracies of 99.57% , 99.00%, 99.14%, and 99.29%, respectivel y. The results showed that the SVMDT model had higher accuracy and explainabilit y."
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    Study Findings on Machine Learning Are Outlined in Reports from Shenzhen Univers ity (Lcz-based City-wide Solar Radiation Potential Analysis By Coupling Physical Modeling, Machine Learning, and 3d Buildings)

    58-59页
    查看更多>>摘要：Current study results on Machine Learn ing have been published. According to news reporting originating from Shenzhen, People's Republic of China, by NewsRx correspondents, research stated, "Addressi ng climate change and urban energy problems is a great challenge. Building Integ rated Photovoltaics (BIPV) plays a pivotal role in energy conservation and carbo n emission reduction." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Key Project of Shenzhen Commission of Science and Technology.
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    Shandong Provincial Hospital Affiliated to Shandong First Medical University Rep orts Findings in Machine Learning (An ensemble machine learning model assists in the diagnosis of gastric ectopic pancreas and gastric stromal tumors)

    59-60页
    查看更多>>摘要：New research on Machine Learning is th e subject of a report. According to news reporting from Jinan, People's Republic of China, by NewsRx journalists, research stated, "To develop an ensemble machi ne learning (eML) model using multiphase computed tomography (MPCT) for distingu ishing between gastric ectopic pancreas (GEP) and gastric stromal tumors (GIST) in lesions <3 cm. In this study, we retrospectively collec ted MPCT images from 138 patients between April 2017 and June 2023 across two ce nters." Financial support for this research came from National Natural Science Foundatio n of China. The news correspondents obtained a quote from the research from Shandong Provinc ial Hospital Affiliated to Shandong First Medical University, "Cohort 1 comprise d 94 patients divided into a training cohort and an internal validation cohort, while the 44 patients from Cohort 2 constituted the external validation cohort. Deep learning (DL) models were constructed based on the lesion region, and radio mics features were extracted to develop radiomics models, which were later integ rated into the fusion model. Model performance was assessed through the analysis of the area under the receiver operating characteristic curve (AUROC). The diag nostic efficacy of the optimal model was compared with that of a radiologist. Ad ditionally, the radiologist with the assistance of the eML model provides a seco ndary diagnosis, to assess the potential clinical value of the model. After eval uation using an external validation cohort, the radiomics model demonstrated the highest performance in the venous phase, achieving AUROC of 0.87. The DL model showed optimal performance in the non-contrast phase, with AUROC of 0.81. The eM L achieved the best performance across all models, with AUROC of 0.90. The use o f eML-assisted analysis resulted in a significant improvement in the junior radi ologist's accuracy, rising from 0.77 to 0.93 (p <0.05). Ho wever, the senior radiologist's accuracy, while improving from 0.86 to 0.95, did not exhibit a statistically significant difference. eML model based on MPCT can effectively distinguish between GEPs and GISTs <3 cm. The multiphase CT-based fusion model, incorporating radiomics and DL technology, pr oves effective in distinguishing between GEP and gastric stromal tumors, serving as a valuable tool to enhance diagnoses and offering references for clinical de cision-making. No studies yet differentiated these tumors via radiomics or DL. R adiomics and DL methodologies unveil potentially distinct phenotypes within lesi ons. Quantitative analysis on CT for GIST and ectopic pancreas."
      原文链接:
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    Centre Hospitalier Regional Reports Findings in Robotics (Pain outcomes of outsi de-the-cage robotic thoracic surgery: a prospective matched-cohort study)

    61-61页
    查看更多>>摘要：New research on Robotics is the subjec t of a report. According to news reporting out of Nancy, France, by NewsRx edito rs, research stated, "Management of acute and chronic pain after thoracic surger y for pulmonary resection or thymectomy remains a challenge for both thoracic su rgeons and anesthesiologists. Advances in minimally invasive robotic procedures have made subcostal outside-the-cage (OTC) resections possible, but the procedur e's pain benefits have not been previously measured." Our news journalists obtained a quote from the research from Centre Hospitalier Regional, "A singlecenter cohort was consented to undergo robotic-assisted thor acoscopic surgery (RATS) with an OTC or transthoracic (TT) approach. On every po st-operative day (POD), patients were asked to complete the visual analog scale (VAS) of pain, assigning a score of 0-10 with higher scores equaling higher pain intensity. Additionally, patients' opioid consumption was recorded and classifi ed using morphine equivalent dose (MED). Descriptive statistics of demographics, Mann-Whitney, and Chi-squared tests were performed in a matched analysis. Altog ether, 50 OTC patients and 50 TT patients were included. For each group, 1 pneum onectomy, 19 lobectomies, 10 segmentectomies, and 20 thymectomies were performed . Between groups, most were male (n = 54; p = 0.42) and there were no difference s in American Society of Anesthesiologists scores (p = 0.51), or tobacco consump tion (p = 0.45). Patients who received an OTC approach experienced significantly lower pain scores on POD-0 (p = 0.001), POD-1 (p <0.001), and POD-2 (p <0.001). POD-3 OTC VAS scores were not diffe rent from those of the TT group (p = 0.09). Similarly, MED was lower for the OTC group on POD-0 (p <0.001), POD-1 (p = 0.03), and POD-3 (p = 0.03)."
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    Reports from Anhui University Describe Recent Advances in Computational Intellig ence (Smem: a Subspace Merging Based Evolutionary Method for High-dimensional Fe ature Selection)

    62-62页
    查看更多>>摘要：Fresh data on Machine Learning - Compu tational Intelligence are presented in a new report. According to news reporting originating from Hefei, People's Republic of China, by NewsRx correspondents, r esearch stated, "In the past decade, evolutionary algorithms (EAs) have shown th eir promising performance in solving the problem of feature selection. Despite t hat, it is still quite challenging to design the EAs for high-dimensional featur e selection (HDFS), since the increasing number of features causes the search sp ace of EAs grows exponentially, which is known as the ‘curse of dimensionality." Funders for this research include National Natural Science Foundation of China ( NSFC), Key Projects of University Excellent Talents Support Plan of Anhui Provin cial Department of Education, Key Program of Natural Science Project of Educatio nal Commission of Anhui Province, University Synergy Innovation Program of Anhui Province.
      原文链接:
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    University of Derby Reports Findings in Machine Learning (A statistical evaluati on of the sexual dimorphism of the acetabulum in an Iberian population)

    63-63页
    查看更多>>摘要：New research on Machine Learning is th e subject of a report. According to news originating from Derby, United Kingdom, by NewsRx correspondents, research stated, "Sex estimation is essential for hum an identification within bioarchaeological and medico-legal contexts. Amongst th e sexually dimorphic skeletal elements commonly utilised for this purpose, the p elvis is usually preferred because of its direct relationship with reproduction. " Financial support for this research came from Universitat de Girona. Our news journalists obtained a quote from the research from the University of D erby, "Furthermore, the posterior part of the innominate bone has proven to have better preservation within degraded contexts. With the aim of investigating the potential of the vertical acetabular diameter as a sex marker, 668 documented i ndividuals from three different Iberian skeletal collections were randomly divid ed into training and test samples and eventually analysed using different statis tical approaches. Two traditional (Discriminant Function Analysis and Logistic R egression Analysis) and four Machine learning methodologies (Support Vector Clas sification, Decision Tree Classification, k Nearest Neighbour Classification, an d Neural Networks) were performed and compared. Amongst these statistical modali ties, Machine Learning methodologies yielded better accuracy outcomes, with DTC garnering highest accuracy percentages of 83.59% and 89.85% with the sex-pooled and female samples, respectively. With males, ANN yielded hi ghest accuracy percentage of 87.70%, when compared to other statist ical approaches. Higher accuracy obtained with ML, along with its minimal statis tical assumptions, warrant these approaches to be increasingly utilised for furt her investigations involving sex estimation and human identification. In this li ne, the creation of a statistical platform with easier user interface can render such robust statistical modalities accessible to researchers and practitioners, effectively maximising its practical use."
      原文链接:
    • NETL
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    Recent Findings from Tianjin University Has Provided New Information about Robot ics (An Adaptive Lumped-mass Dynamic Model and Its Control Application for Conti nuum Robots)

    64-64页
    查看更多>>摘要：Current study results on Robotics have been published. According to news reporting originating in Tianjin, People's Re public of China, by NewsRx journalists, research stated, "Dynamic modeling for c ontinuum robots remains challenging due to their large nonlinear deformation and the variation of dynamic parameters during movement. In this paper, a lumpedmas s dynamic model (LMD) for a continuum robot is constructed including elastic and viscous parameters in the robotic joints." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from Tianjin University, " Then the appropriate dynamic parameters (e.g. spring and damping coefficients of the LMD) with respect to the motion status (e.g. position and velocity of the r obot) are estimated using a Genetic Algorithm (GA). Based on the obtained data s et, a MultiLayer Perception (MLP) is trained to establish a direct mapping from the motion status to the dynamic parameters, so the LMD can tune its parameters in real-time when moving within the workspace, resulting an adaptive lumped-mass dynamic model (ALMD)."
      原文链接:
    • NETL
    • NSTL

    Yunnan Agricultural University Reports Findings in Machine Learning (Rapid and a ccurate identification of Gastrodia elata Blume species based on FTIR and NIR sp ectroscopy combined with chemometric methods)

    65-66页
    查看更多>>摘要：New research on Machine Learning is th e subject of a report. According to news reporting originating in Kunming, Peopl e's Republic of China, by NewsRx journalists, research stated, "Different variet ies of Gastrodia elata Blume (G. elata Bl.) have different qualities and differe nt contents of active ingredients, such as polysaccharide and gastrodin, and it is generally believed that the higher the active ingredients, the better the qua lity of G. elata Bl. and the stronger the medicinal effects. Therefore, effectiv e identification of G. elata Bl. species is crucial and has important theoretica l and practical significance." The news reporters obtained a quote from the research from Yunnan Agricultural U niversity, "In this study, first unsupervised PCA and t-SNE are established for data visualisation, follow by traditional machine learning (PLS-DA, OPLS-DA and SVM) models and deep learning (ResNet) models were established based on the four ier transform infrared (FTIR) and near infrared (NIR) spectra data of three G. e lata Bl. species. The results show that PLS-DA, OPLS-DA and SVM models require c omplex preprocessing of spectral data to build stable and reliable models."
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    New Machine Learning Data Has Been Reported by a Researcher at Liverpool John Mo ores University (Automated Machine Learning and Asset Pricing)

    65-65页
    查看更多>>摘要：Investigators publish new report on ar tificial intelligence. According to news reporting from Liverpool, United Kingdo m, by NewsRx journalists, research stated, "We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regr ession-based strategies generally used in the finance and econometric literature ." Our news journalists obtained a quote from the research from Liverpool John Moor es University: "We examine 17 benchmark factor model specifications based on Exp ected Utility Theory and theory drawn from behavioural finance. We assess whethe r machine learning can identify features of the data-generating process undetect ed by standard methods and rank the best-performing algorithms. Our tests use 95 years of CRSP data, from 1926 to 2021, encompassing the price history of the br oad US stock market."
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