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    Shandong University Reports Findings in Machine Learning (Assessing the determinants of corporate environmental investment: a machine learning approach)

    11-12页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating in Weihai, People's Republic of China, by NewsRx journalists, research stated, "In recent years, experts and academics in the environmental management field have developed an interest in the factors and evaluation techniques that influence corporate environmental investment decisions. However, there are substantial differences between studies employing the most recent evaluation methodologies and those that use indicator systems." The news reporters obtained a quote from the research from Shandong University, "To explore the mechanisms that influence corporate environmental investment, this study investigated the determinants of environmental investment through the perspectives of firm, board, chair, and chief executive officer (CEO) characteristics using a machine learning approach. Based on a large-scale data sample from Chinese-listed companies, the results indicated that the extreme gradient boosting (XGBoost) model had an accuracy of up to 97.63%, thus performing the best. Additionally, the model that used SHapley Additive exPlanations (SHAP) to interpret XGBoost showed that a company's sales performance was the most important factor that influenced environmental investment, followed by CEO tenure, board independence, board gender diversity, chair academic experience, and the company's level of internationalization. Furthermore, when examining the sample of heavily polluting enterprises, sales, board gender diversity, CEO tenure, chair academic experience, board independence, and chair-CEO duality, all were found to play crucial roles in predicting environmental investment."
      原文链接:
    • NETL
    • NSTL

    Researchers at Saveetha University Have Reported New Data on Ankylosing Spondylitis (Advanced Model Based Machine Learning Technique for Early Stage Prediction of Ankylosing Spondylitis Under Timely Analysis With Featured Textures)

    12-13页
    查看更多>>摘要：Investigators publish new report on Musculoskeletal Diseases and Conditions - Ankylosing Spondylitis. According to news originating from Chennai, India, by NewsRx correspondents, research stated, "In the medical field, ankylosing spondylitis (AS) is arthritis with symptoms that differs from person to person and takes a long time to evaluate. For predicting radiographic progression, the prediction within the prognostics employing the approach of time-series records performed reasonably well when used with clinical variables from the first visit dataset." Our news journalists obtained a quote from the research from Saveetha University, "The integration and analysis of numerous variables of different types had limitations as per prior research work under statistical analysis on the radiographic progressions. With the time-series approach propagated through the records fed via electronic means, the study has been developed utilizing machine learning models (ML) for radiographic progression estimation among patients impacted towards AS. These models' performance might be enhanced by adding more data, including radiography of the spinal column or even the lifetime data. Comparison has been made within Model A/diagnostic B's precision through the development of clinical model gaining the reach of 2.5% subjected to spondylarthritis characteristics listed in the categorization criteria attributed to Spondylarthritis Assessment under International Society. Furthermore, the abridged model with linear regression gained a reach of 2.6% for viability with a lower range Model of A/B."
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Vellore Institute of Technology Researchers Focus on Robotics (Dual Mode PID Controller for Path Planning of Encoder Less Mobile Robots in Warehouse Environment)

    13-14页
    查看更多>>摘要：Investigators discuss new findings in robotics. According to news reporting originating from Chennai, India, by NewsRx correspondents, research stated, "Mobile robots have emerged as versatile substitutes for human labor across diverse domains, offering promising applications in surveillance, healthcare, and beyond. Fundamental to their autonomy are the core capabilities of movement, perception, cognition, and navigation." Funders for this research include Vellore Institute of Technology, Chennai. Our news correspondents obtained a quote from the research from Vellore Institute of Technology: "This research introduces a novel approach known as the Dual PID based low-cost navigation system (DPLNS), designed specifically for indoor warehouse-like environments. The primary objective of this technique is to enable seamless point-to-point traversal. This is achieved through a fusion of gyroscope correction and visual PID control mechanisms. Leveraging a strategically positioned eagle-eye perspective camera, the system gained crucial insights for navigation. To ensure the uninterrupted execution of planned trajectories, the system employs the Message Queuing Telemetry Transport (MQTT) protocol. This technology ensures smooth communication and coordination of actions. The experimental validation of the proposed strategy highlights its efficacy, positioning it as a promising solution for modern warehouse automation needs."
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Investigators at University of Ottawa Report Findings in Machine Learning (Empirical Analysis of Performance Assessment for Imbalanced Classification)

    14-15页
    查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting out of Ottawa, Canada, by NewsRx editors, research stated, "There are multiple scenarios in machine learning where the data used presents a heavy bias towards one of the classes. Evaluating the performance of machine learning models in such imbalanced scenarios proves to be difficult and challenging, as one of the classes is poorly represented in the data, and this class is often more relevant to the end-user." Financial support for this research came from CGIAR. Our news journalists obtained a quote from the research from the University of Ottawa, "An abundance of performance metrics have been devised and commonly used in order to solve these specific problems, however, there is often a lack of common agreement on which metric is best and which to use in specific imbalanced scenarios. In this study, we experimentally study the impact of choosing one metric over another in the evaluation of a classifier for binary classification, as well as the effect of data characteristics such as class imbalance and noise on those metrics. Based on our extensive empirical analysis, we provide a set of easy-to-follow guidelines for which performance metric is best to use depending on the context of the problem."
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    New Robotics Study Results from Shanghai Jiao Tong University Described (Task Scheduling for Heterogeneous Agents Pickup and Delivery Using Recurrent Open Shop Scheduling Models)

    15-15页
    查看更多>>摘要：Research findings on Robotics are discussed in a new report. According to newsreporting originating from Shanghai, People’s Republic of China, by NewsRx editors, the research stated,“We study the transport-pick agents task scheduling (TPTS) problem in heterogeneous agents pickupand delivery (HAPD). Two functionally heterogeneous agent types, transport agents and pick agents,collaborate to execute multi-goal tasks subjecting to complex-schedule dependency.”Funders for this research include National Key R&D Program of China, National Natural ScienceFoundation of China (NSFC), Science & Technology Commission of Shanghai Municipality (STCSM).Our news editors obtained a quote from the research from Shanghai Jiao Tong University, “The objectiveis to plan a collective time-extended task schedule with the minimization of total completion time. To bridgethe gap between robot task scheduling and general scheduling theory, a novel recurrent open shop scheduling(ROSS) problem variant with unique sequence structure is defined. New sequence and schedule modelsare extended to accommodate for it. Afterwards, the problem-specific append-beam-Christofides (ABC)constructive heuristic, greedy local search (GLS) and simulated annealing (SA) metaheuristic algorithms aredesigned accordingly. Theoretically, we rigorously analyze sequence and schedule structures, and algorithmicproperties; empirically, we study the influence of different algorithm settings on a comprehensive dataset.Design guidelines and parameter settings of these algorithms are provided. The application conditions ofthe proposed methodology is discussed along with a baseline algorithm TEAMWISE.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Findings from University of Pavol Jozef Safarik in the Area of Machine Learning Reported (A Parsimonious, Computationally Efficient Machine Learning Method for Spatial Regression)

    16-16页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting originating in Kosice, Slovakia, by NewsRx journalists, research stated, "We introduce the modified planar rotator method (MPRS), a physically inspired machine learning method for spatial/temporal regression. MPRS is a non-parametric model which incorporates spatial or temporal correlations via shortrange, distance-dependent 'interactions' without assuming a specific form for the underlying probability distribution." Financial support for this research came from Vedeck Grantov Agentra MScaron;VVaScaron; SR a SAV. The news reporters obtained a quote from the research from the University of Pavol Jozef Safarik, "Predictions are obtained by means of a fully autonomous learning algorithm which employs equilibrium conditional Monte Carlo simulations. MPRS is able to handle scattered data and arbitrary spatial dimensions. We report tests on various synthetic and real-word data in one, two and three dimensions which demonstrate that the MPRS prediction performance (without hyperparameter tuning) is competitive with standard interpolation methods such as ordinary kriging and inverse distance weighting. MPRS is a particularly effective gap-filling method for rough and non-Gaussian data (e.g., daily precipitation time series). MPRS shows superior computational efficiency and scalability for large samples. Massive datasets involving millions of nodes can be processed in a few seconds on a standard personal computer."
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Second Affiliated Hospital of Guilin Medical University Reports Findings in Bladder Cancer (A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer)

    17-17页
    查看更多>>摘要：New research on Oncology - Bladder Cancer is the subject of a report. According to news reporting out of Guangxi, People's Republic of China, by NewsRx editors, research stated, "Comprehensive action patterns of programmed cell death (PCD) in bladder cancer (BLCA) have not yet been thoroughly investigated. Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed a multiple programmed cell death index (MPCDI) based on a machine learning computational framework." Our news journalists obtained a quote from the research from the Second Affiliated Hospital of Guilin Medical University, "We found that in the TCGA-BLCA training cohort and the independently validated GSE13507 cohort, the patients with high-MPCDI had a worse prognosis, whereas patients with low-MPCDI had a better prognosis. By combining clinical characteristics with the MPCDI, we constructed a nomogram. The C-index demonstrated that the nomogram was significantly more accurate compared to other variables, including MPCDI, age, gender, and clinical stage. The results of the decision curve analysis demonstrated that the nomogram had a better net clinical benefit compared to other clinical variables. Subsequently, we revealed the heterogeneity of BLCA patients, with significant differences in terms of overall immune infiltration abundance, immunotherapeutic response, and drug sensitivity in the two MPCDI groups. Encouragingly, the high-MPCDI patients showed better efficacy for commonly used chemotherapeutic drugs than the low-MPCDI patients, which suggests that MPCDI scores have a guiding role in chemotherapy for BLCA patients."
      原文链接:
    • NETL
    • NSTL

    University Hospital of Clermont-Ferrand Reports Findings in Rectal Cancer (Meta-analysis of randomized clinical trials comparing robotic versus laparoscopic surgery for mid-low rectal cancers)

    18-18页
    查看更多>>摘要：New research on Oncology - Rectal Cancer is the subject of a report. According to news reporting from Clermont-Ferrand, France, by NewsRx journalists, research stated, "Robotic surgery (RS) is experiencing major development, particularly in the context of rectal cancer. The aim of this meta-analysis was to summarize data from the literature, focusing specifically on the safety and effectiveness of robotic surgery in mid-low rectal cancers, based on the hypothesis that that robotic surgery can find its most rational indication in this anatomical location." The news correspondents obtained a quote from the research from the University Hospital of Clermont- Ferrand, "The meta-analysis was conducted according to the PRISMA 2000 recommendations, including all randomized trials that compared robotic surgery versus laparoscopic surgery (LS) that were found in the Medline-PICO, Cochrane Database, Scopus and Google databases. Data were extracted independently by two reviewers. The risk of bias was analyzed according to the Cochrane Handbook method and the certainty of the evidence according to the GRADE method. The analysis was carried out with R software Version 4.2-3 using the Package for Meta-Analysis 'meta' version 6.5-0. Eight randomized trials were included (with a total of 2342 patients), including four that focused specifically on mid-low rectal cancer (n=1,734 patients). No statistically significant difference was found for overall morbidity, intra-operative morbidity, anastomotic leakage, post-operative mortality, quality of mesorectal specimen, and resection margins. The main differences identified were a lower conversion rate for RS (RR=0.48 [0.24-0.95], p=0.04, I=0%), and a longer operative time for RS (mean difference=39.11min [9.39-68.83], p＜0.01, I=96%). The other differences had no real clinical relevance, i.e., resumption of flatus passage (5hours earlier after RS), and lymph node dissection (one more lymph node for LS)."
      原文链接:
    • NETL
    • NSTL

    New Findings from Indian Institute of Technology Describe Advances in Robotics (Bicurnet: Premovement Eeg-based Neural Decoder for Biceps Curl Trajectory Estimation)

    19-19页
    查看更多>>摘要：Current study results on Robotics have been published. According to news reporting originating from New Delhi, India, by NewsRx correspondents, research stated, "Kinematic parameter (KP) estimation from early electroencephalogram (EEG) signals is essential for positive augmentation using wearable robots. However, surface EEG-based early KP estimation studies are sparse in the literature." Financial support for this research came from DRDO-JATC Project. Our news editors obtained a quote from the research from the Indian Institute of Technology, "In this study, simultaneous surface EEG and kinematics data of five participants is collected during the biceps-curl motor task. The feasibility of early estimation of KPs is demonstrated using brain source imaging (BSI). Discrete wavelet transform (DWT) is utilized for subband extraction from preprocessed EEG signals. Further, spherical and head harmonics domain features are extracted from subbands of the EEG signals. A deep-learning-based decoding model, BiCurNet, is proposed for early KP estimation using spatial and harmonics domain EEG features during the biceps-curl task. The proposed model utilizes lightweight architecture with depthwise separable convolution layers and a customized attention module (CAM). The best Pearson correlation coefficient (PCC) between the estimated and actual trajectory of 0.7 is achieved when combined EEG features (spatial and harmonics domain) in the delta band are utilized. Intra- and intersubject performance analyses are performed to evaluate the subject-adaptability of the proposed decoding model. The performance of the proposed BiCurNet is compared with the existing multilinear regression (mLR) counterpart. The robustness of the proposed model is additionally illustrated using an ablation study."
      原文链接:
    • NETL
    • NSTL
    • IEEE

    School of Mathematics Researchers Update Knowledge of Intelligence Technology (Feature extraction and learning approaches for cancellable biometrics: A survey)

    20-21页
    查看更多>>摘要：Investigators discuss new findings in intelligence technology. According to news re-porting from the School of Mathematics by NewsRx journalists, research stated, "Biometric recognition is a widely used technology for user authentication." Funders for this research include Australian Research Council. Our news correspondents obtained a quote from the research from School of Mathematics: "In the application of this technology, biometric security and recognition accuracy are two important issues that should be considered. In terms of biometric security, cancellable biometrics is an effective technique for protecting biometric data. Regarding recognition accuracy, feature representation plays a significant role in the performance and reliability of cancellable biometric systems. How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community, especially from researchers of cancellable biometrics. Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance, while the privacy of biometric data is protected."
      原文链接:
    • NETL
    • NSTL
    • Wiley