查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting originating in Hubei, People’s Republic of China, by NewsRx journalists, research stated, “The study investigates fishing gear parameters through sea trials to optimize fishing efficiency of trawlers. We utilized the self-invented ‘winch retracting device with an abnormality judgment function’ to measure the warp length, while employing ‘a wireless trawl monitoring system’ to measure the horizontal and vertical expansion of the net mouth.” Funders for this research include The “Pioneer” and “Leading Goose” R&D Program of Zhejiang, National Natural Science Foundation of China (NSFC), Natural Science Foundation of Hubei Province. The news reporters obtained a quote from the research from the Wuhan University of Technology, “Based on the sea trial data, a polynomial regression model is used to propose an empirical formula applicable to trawlers establishing a comprehensive relationship between the net mouth area, warp length, 48 and towing speed. In the simulation experiments, three machine learning algorithms are effectively tested to predict the net mouth area variations under unknown sea conditions, where the Multilayer Perception (MLP) algorithm demonstrates a robust predictive performance for trawling vessels.”
查看更多>>摘要：New research on Oncology - Endometrial Cancer is the subject of a report. According to news reporting originating in Montreal, Canada, by NewsRx journalists, research stated, “To compare surgical outcomes of patients with endometrial cancer who underwent robotic surgery across different BMI categories. A retrospective study including all consecutive patients with endometrial cancer who underwent robotic surgery at a tertiary cancer center between December 2007 and December 2022.” The news reporters obtained a quote from the research from Jewish General Hospital, “The study analyzed outcome measures, including blood loss, surgical times, length of hospitalization, perioperative complications, and conversion rates with the Kruskal-Wallis test for BMI group differences and the Chisquared test for associations between categorical variables. A total of 1329 patients with endometrial cancer were included in the study. Patients were stratified by BMI: <30.0 (n = 576; 43.3%), 30.0-39.9 (n = 449; 33.8%), and 40.0 (n = 304; 22.9%). There were no significant differences in post-anesthesia care unit (PACU) stay (p = 0.105) and hospital stay (p = 0.497) between the groups. The rate of postop complications was similar across the groups, ranging from 8.0% to 9.5% (p = 0.761). The rate of conversion to laparotomy was also similar across the groups, ranging from 0.7% to 1.0% (p = 0.885). Women with a BMI 40.0 had a non-clinically relevant but greater median estimated blood loss (30 mL vs. 20 mL; p<0.001) and longer median operating room (OR) time (288 min vs. 270 min; p<0.001). Within the OR time, the median set-up time was longer for those with a higher BMI (58 min vs. 50 min; p<0.001). However, skin-to-skin time (209 min vs. 203 min; p = 0.202) and post-op time (14 min vs. 13 min; p = 0.094) were comparable between groups.”
查看更多>>摘要：New research on Parasitic Diseases and Conditions - Schistosomiasis is the subject of a report. According to news reporting originating in Giessen, Germany, by NewsRx journalists, research stated, “Schistosomiasis, a prevalent water-borne disease second only to malaria, significantly impacts impoverished rural communities, primarily in Sub-Saharan Africa where over 90% of the severely affected population resides. The disease, majorly caused by Schistosoma mansoni and S. haematobium parasites, relies on freshwater snails, specifically Biomphalaria and Bulinus species, as crucial intermediate host (IH) snails.” Funders for this research include Deutscher Akademischer Austauschdienst, Justus-Liebig-Universitat Giessen. The news reporters obtained a quote from the research from Justus-Liebig-University Giessen, “Targeted snail control is advisable, however, there is still limited knowledge about the community structure of the two genera especially in East Africa. Utilizing a machine learning approach, we employed random forest to identify key features influencing the distribution of both IH snails in this region. Our results reveal geography and climate as primary factors for Biomphalaria, while Bulinus occurrence is additionally influenced by soil clay content and nitrogen concentration. Favorable climate conditions indicate a high prevalence of IHs in East Africa, while the intricate connection with geography might signify either dispersal limitations or environmental filtering. Predicted probabilities demonstrate non-linear patterns, with Bulinus being more likely to occur than Biomphalaria in the region.”
查看更多>>摘要：New research on Robotics is the subject of a report. According to news reporting originating from Piraeus, Greece, by NewsRx correspondents, research stated, “While gynecological malignancies are more commonly diagnosed in elderly women, a substantial proportion of women will still be diagnosed with some type of gynecologic cancer during their reproductive age. Over 10% of newly diagnosed ovarian cancers and over one third of newly diagnosed cervical cancers involve women who are under the age of 45.” Our news editors obtained a quote from the research from Metaxa Cancer Hospital, “This, coupled with the rising trend of women having their first child after the age of 35, has led to a concerning prevalence of complex fertility issues among women who have been diagnosed with cancer. Since the advent of roboticassisted surgeries in gynecology, there has been a rise in the occurrence of these procedures. Fertility preserving gynecological surgeries require precise management in order to avoid fertility disorders.” According to the news editors, the research concluded: “Therefore, we conducted a narrative review of robotic assisted fertility sparing surgery in gynecologic malignancies in order to highlight the role of this approach in preserving fertility.”
查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating from Warsaw, Poland, by NewsRx correspondents, research stated, “Infrared spectroscopy is a crucial analytical tool in organic chemistry, but interpreting IR data can be challenging. This study provides a comprehensive analysis of five machine learning models: logistic regression, KNN (k-nearest neighbors), SVM (support vector machine), random forest, and MLP (multilayer perceptron), and their effectiveness in interpreting IR spectra.” Our news editors obtained a quote from the research from the Warsaw University of Technology, “The simple KNN model outperformed the more complex SVM model in execution time and F1 score, proving the potential of simpler models in interpreting the IR data. The combination of original spectra with its corresponding derivatives improved the performance of all models with a minimal increase in execution time. Denoising of the IR data was investigated but did not significantly improve performance. Although the MLP model showed better performance than the KNN model, its longer execution time is substantial.” According to the news editors, the research concluded: “Ultimately, KNN is recommended for rapid results with minimal performance compromise, while MLP is suggested for projects prioritizing accuracy despite longer execution time. [GRAPHICS].”
查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting from Blacksburg, Virginia, by NewsRx journalists, research stated, “Even with the utilization of software tools like Navisworks to automate clash detection, clash resolution in construction projects remains a slow and manual process. The reason is the meticulous nature of the process where coordinators need to ensure that resolving one clash does not lead to new clashes.” 53 The news correspondents obtained a quote from the research from Virginia Polytechnic Institute and State University (Virginia Tech), “The use of machine learning to automate clash resolution as a potential option to improve the clash resolution process has been suggested with research showing positive results to support the implementation. While the research shows high accuracy in predicting clash resolution options to support automation, the scope limits the discussion on the complex and often lengthy process of developing a machine-learning model. Based on this research gap, the authors in this paper discuss the development of a prediction model to identify clash resolution options for given clashes. The discussion is focused on individual steps involved in creating machine-learning models like data collection, data preprocessing, and machine-learning algorithm development and selection. The authors also address common challenges in the development of machine-learning models including class imbalance and availability of limited data. The authors utilize a multilabel synthetic oversampling method to generate different percentages of synthetic data to account for class imbalance and limited data sets. Using this data set, the authors trained five machine-learning algorithms and reported on their accuracy.”
查看更多>>摘要：Researchers detail new data in Machine Learning. According to news reporting out of Malvern, Pennsylvania, by NewsRx editors, research stated, “Equity factor investing has gained traction due to its ability to systematically capture premia for risk or behavioral reasons. However, developing a robust factor timing investment framework remains challenging.” Our news journalists obtained a quote from the research from Vanguard Group Inc., “In this article, the authors propose a two-stage machine model for dynamic factor rotation, which adapts to varying market conditions. In the first stage, the authors employ both supervised and unsupervised machine learning techniques to identify dynamic market risk regimes, which reflect the prevailing economic environment. Subsequently, the second stage utilizes additional ensemble supervised machine learning methods, incorporating the features identified in the first stage, to predict factor performance within each regime. The authors’ findings demonstrate that the proposed model delivers robust results across all regimes.”
查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news originating from the Massachusetts Institute of Technology by NewsRx correspondents, research stated, “Innovative machine learning techniques have facilitated the inverse design of photonic structures for numerous practical applications. Nevertheless, the quantity of data and the initial data distribution are paramount for the discovery of highly efficient photonic devices.” Financial supporters for this research include National Research Foundation of Korea; Institute For Infor- 54 mation Communication Technology Planning And Evaluation; Korea Semiconductor Research Consortium; Korea Ministry of Trade Industry And Energy. The news reporters obtained a quote from the research from Massachusetts Institute of Technology: “These devices often require simulated data ranging from thousands to several hundred thousand data points. This issue has consistently posed a major hurdle in machine learning-based photonic design problems. Therefore, we propose a new data augmentation algorithm grounded in the adjoint method, capable of generating more than 300 times the amount of original data while enhancing device efficiency. The adjoint method forecasts changes in the figure of merit (FoM) resulting from structural perturbations, requiring only two full-wave Maxwell simulations for this prediction. By leveraging the adjoint gradient values, we can augment and label several thousand new data points without any additional computations. Furthermore, the augmented data generated by the proposed algorithm displays significantly improved FoMs.”
查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news originating from Taibah University by NewsRx correspondents, research stated, “Arabic hateful speech recognition has long been a major area of focus in Natural Language Processing (NLP) research. In light of recent advancements in transformer models and deep learning, researchers are now turning to transfer learning techniques based on existing models such as BERT for Arabic hateful speech recognition.” Our news journalists obtained a quote from the research from Taibah University: “To detect Arabic hateful contexts, using advanced machine learning algorithms and NLP techniques is essential. These techniques can help to detect different forms of hateful contexts in Arabic by analyzing the text for lexical, semantic, and syntactic features. In this research, we proposed a new hybrid approach that combines deep and machine learning models to detect hateful and abusive content in Arabic. The proposed model consists of a combination of convolutional neural networks and attention layers that are trained to differentiate between normal, abusive, and hateful contexts in Arabic. In the first step, we used a pre-trained model to extract features from the hateful Arabic context. After that, we used an optimized random forest combined with particle swarm optimization and grey wolf optimizer to classify the extracted features. Finally, we evaluated the performance of the model to detect hateful Arabic contexts. To evaluate the proposed method we used 5846 and 6023 tweets with 3 categories of hateful, abusive, and normal Arabic contexts.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting out of Wuhan, People’s Republic of China, by NewsRx editors, research stated, “Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning can significantly improve fetal survival rates.” Our news journalists obtained a quote from the research from the Huazhong University of Science and Technology, “Echocardiography is one of the most accessible and widely used diagnostic tools in the diagnosis of fetal congenital heart disease. However, traditional fetal echocardiography has limitations due to fetal, maternal, and ultrasound equipment factors and is highly dependent on the skill level of the operator. Artificial intelligence (AI) technology, with its rapid development utilizing advanced computer algorithms, has great potential to empower sonographers in time-saving and accurate diagnosis and to bridge the skill gap in different regions. In recent years, AI-assisted fetal echocardiography has been successfully applied to a wide range of ultrasound diagnoses.”
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