查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news reporting from Catania, Italy, by NewsRx journalists, research stated, “Seismic vulnerability assessment in urban areas would, in principle, require the detailed modeling of every single building and the implementation of complex numerical calculations.” Financial supporters for this research include Italian Ministry of University And Research; Prin2020. The news editors obtained a quote from the research from University of Catania: “This procedure is clearly difficult to apply at an urban scale where many buildings must be considered; therefore, it is essential to have simplified, but at the same time reliable, approaches to vulnerability assessment. Among the proposed strategies, one of the most interesting concerns is the application of machine learning algorithms, which are able to classify buildings according to their vulnerability on the basis of training procedures applied to existing datasets. In this paper, machine learning algorithms were applied to a dataset which collects and catalogs the structural characteristics of a large number of buildings and reports the damage observed in L'Aquila territory during the intense seismic activity that occurred in 2009.” According to the news editors, the research concluded: “A combination of a trained neural network and a random forest algorithm allows us to identify an opportune “a-posteriori” vulnerability score, deduced from the observed damage, which is compared to an “a-priori” vulnerability one, evaluated taking into account characteristic indexes for building's typologies. By means of this comparison, an inverse approach to seismic vulnerability assessment, which can be extended to different urban centers, is proposed.”
查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news originating from Xi'an, People's Republic of China, by NewsRx correspondents, research stated, “As an indicator of the optical characteristics of perovskite materials, the band gap is a crucial parameter that impacts the functionality of a wide range of optoelectronic devices. Obtaining the band gap of a material via a labor-intensive, time-consuming, and inefficient high-throughput calculation based on first principles is possible.” Funders for this research include Shaanxi Association For Science And Technology Youth Talent Support Program; Natural Science Foundation of Shaanxi Province. The news journalists obtained a quote from the research from Xijing University: “However, it does not yield the most accurate results. Machine learning techniques emerge as a viable and effective substitute for conventional approaches in band gap prediction. This paper collected 201 pieces of data through the literature and open-source databases. By separating the features related to bits A, B, and X, a dataset of 1208 pieces of data containing 30 feature descriptors was established. The dataset underwent preprocessing, and the Pearson correlation coefficient method was employed to eliminate non-essential features as a subset of features. The band gap was predicted using the GBR algorithm, the random forest algorithm, the LightGBM algorithm, and the XGBoost algorithm, in that order, to construct a prediction model for organic-inorganic hybrid perovskites. The outcomes demonstrate that the XGBoost algorithm yielded an MAE value of 0.0901, an MSE value of 0.0173, and an R2 value of 0.991310. These values suggest that, compared to the other two models, the XGBoost model exhibits the lowest prediction error, suggesting that the input features may better fit the prediction model.”
查看更多>>摘要：Researchers detail new data in artificial intelligence. According to news reporting originating from the University of Kufa by NewsRx correspondents, research stated, “Face recognition is a biometric technology that involves identifying and verifying individuals based on their facial features.” Our news editors obtained a quote from the research from University of Kufa: “It finds applications in security, surveillance, and user authentication systems. The extraction of facial image features and classifier selection are more challenging to identify with conventional facial recognition technologies, and the recognition rate is lower. The paper present proposed model combined between deep wavelet scattering transform network regarding the extraction of features and machine learning for classification purposes. The proposed model consists four stage: obtaining images, performing pre-processing, extracting features, and then applying classification techniques. using both SoftMax classifier (part of deep learning model) and Support Vector Machine classifier (SVM). We used property collected dataset called MULB dataset. The experimental result shows that SVM classifier provide better results than SoftMax classifier.”
查看更多>>摘要：New research on Robotics is the subject of a report. According to news originating from Jilin, People's Republic of China, by NewsRx correspondents, research stated, “Singing voice separation on robots faces the problem of interpreting ambiguous auditory signals. The acoustic signal, which the humanoid robot perceives through its onboard microphones, is a mixture of singing voice, music, and noise, with distortion, attenuation, and reverberation.” Financial support for this research came from China University Industry, University and Research Innovation Fund. Our news journalists obtained a quote from the research from Jilin Normal University, “In this paper, we used the 3D Inception-ResUNet structure in the U-shaped encoding and decoding network to improve the utilization of the spatial and spectral information of the spectrogram. Multiobjectives were used to train the model: magnitude consistency loss, phase consistency loss, and magnitude correlation consistency loss. We recorded the singing voice and accompaniment derived from the MIR-1K dataset with NAO robots and synthesized the 10-channel dataset for training the model.” According to the news editors, the research concluded: “The experimental results show that the proposed model trained by multiple objectives reaches an average NSDR of 11.55 dB on the test dataset, which outperforms the comparison model.”
查看更多>>摘要：Investigators publish new report on robotics. According to news reporting out of Moscow Aviation Institute (National Research University) by NewsRx editors, research stated, “The paper developed a method for calculating the stress-strain state of a robotic structure made of composite material under dynamic action. The bearing capacity of multilayer composite materials is affected by the location of the warp threads of the composite material.” Our news reporters obtained a quote from the research from Moscow Aviation Institute (National Research University): “By changing the orientation of the layers, it is possible to change the bearing capacity of the composite material. In the present work, such a study was carried out for a robotic system made of a composite material under the action of a dynamic operational load. An eight-layer composite material with different layer orientations was considered. Carbon fiber was used as the basis. As a robotic system stand was considered, designed to simulate flight characteristics in laboratory conditions. The simulation of the stand was carried out. The bench was approximated by finite elements. The convergence of the results of the finite element model of the stand was checked by condensing the finite element mesh and comparison the results obtained. Robotic systems are equipped with elements that move the channels: bearings, gear rims, gearboxes, motors. In the present study they were replaced in the finite element model with a system of bar elements of identical stiffness.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Madrid, Spain, by NewsRx correspondents, research stated, “Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability.” Our news journalists obtained a quote from the research, “In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability.” According to the news editors, the research concluded: “It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.”
查看更多>>摘要：Current study results on artificial intelligence have been published. According to news reporting originating from Callaghan, Australia, by NewsRx correspondents, research stated, “Industrial fans are critical components in industrial production, where unexpected damage of important fans can cause serious disruptions and economic costs. One trending market segment in this area is where companies are trying to add value to their products to detect faults and prevent breakdowns, hence saving repair costs before the main product is damaged.” The news correspondents obtained a quote from the research from Newcastle University: “This research developed a methodology for early fault detection in a fan system utilizing machine learning techniques to monitor the operational states of the fan. The proposed system monitors the vibration of the fan using an accelerometer and utilizes a machine learning model to assess anomalies. Several of the most widely used algorithms for fault detection were evaluated and their results benchmarked for the vibration monitoring data. It was found that a simple Convolutional Neural Network (CNN) model demonstrated notable accuracy without the need for feature extraction, unlike conventional machine learning (ML)-based models. Additionally, the CNN model achieved optimal accuracy within 30 epochs, demonstrating its efficiency. Evaluating the CNN model performance on a validation dataset, the hyperparameters were updated until the optimal result was achieved. The trained model was then deployed on an embedded system to make real-time predictions. The deployed model demonstrated accuracy rates of 99.8%, 99.9% and 100.0% for Fan-Fault state, Fan-Off state, and Fan-On state, respectively, on the validation data set.”
查看更多>>摘要：New research on Surgery - Arthroplasty is the subject of a report. According to news reporting out of Copenhagen, Denmark, by NewsRx editors, research stated, “There is increasing evidence that genderspecific hemoglobin thresholds may not be ideal in the surgical population. Thus, preoperative anemia defined as a hemoglobin of <13.0 g/dL is a well-established risk factor in elective surgery.” Financial support for this research came from Novo Nordisk Fonden. Our news journalists obtained a quote from the research from the University of Copenhagen, “However, few studies have investigated the specific influence of preoperative hemoglobin within a machine-learning model using data from an optimized fast-track surgical setup. A secondary analysis on the specific influence of preoperative hemoglobin level on a machine-learning model developed for identifying patients at increased risk of a length of stay (LOS) of >4 day or readmissions due to medical complications in fast-track total hip and knee arthroplasty within a well-defined fast-track protocol. To evaluate the effect of hemoglobin on the model we calculated SHaply Additive Explanation (SHAP) values for the 3913 patients from our previous test-dataset and stratified by gender and total hip and knee arthroplasty, respectively. The study period ran from January 2017 to August 2017. Median LOS was 1 day and mean preoperative Hb was 15.5 g/dL (SD:1.5), lower in women (14.9 vs. 16.2 g/dL) and with 30.5% of women versus 12.0% of men having a Hb of <13.0 g/dL. There was a steep increase in SHAP value with a preoperative Hb <14.8 g/dL, and irrespective of gender age and procedure type.”
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting from Guangdong, People's Republic of China, by NewsRx journalists, research stated, “Polydrug therapy is now recognized as a crucial treatment, and the analysis of drug-drug interactions (DDIs) offers substantial theoretical support and guidance for its implementation. Predicting potential DDIs using intelligent algorithms is an emerging approach in pharmacological research.” The news correspondents obtained a quote from the research from the Guangdong University of Technology, “However, the existing supervised models and deep learning-based techniques still have several limitations. This paper proposes a novel DDI analysis and prediction framework called the Multi-View Semi-supervised Graph-based (MVSG) framework, which provides a comprehensive judgment by integrating multiple DDI features and functions without any time-consuming training process. Unlike conventional approaches, MVSG can search for the most suitable similarity (or distance) measurement among DDI data and construct graph structures for each feature. By employing a parameter self-tuning strategy, MVSG fuses multiple graphs according to the contributions of features' information. The actual anticancer drug data are extracted from the authoritative public database for evaluating the effectiveness of our framework, including 904 drugs, 7730 DDI records and 19 types of drug interactions. Validation results indicate that the prediction is more accurate when multiple features are adopted by our framework. In comparison to conventional machine learning techniques, MVSG can achieve higher performance even with less labeled data and without a training process.”
查看更多>>摘要：New research on Oncology - Rectal Cancer is the subject of a report. According to news reporting out of Yangzhou, People's Republic of China, by NewsRx editors, research stated, “Rectal cancer is one of the most prevalent cancers that arise in the digestive tract. The purpose of this retrospective study was to investigate the impact of visceral fat area (VFA) on postoperative outcomes in mid and low rectal cancer patients undergoing robotic surgery (RS).” Our news journalists obtained a quote from the research from Nanjing University, “Data were collected on patients who underwent robotic anterior rectal resection in a single center from December 2019 to October 2023. Clinical pathology information was analyzed. Statistical analysis was done on the computed tomography (CT) imaging data. A total of 277 patients were included in the study, including 121 cases with visceral obesity (VO) and 156 cases without VO. There was no statistically significant disparity in the lymph node dissection count, blood loss, duration of hospitalization, time to first liquid diet, early postoperative complications, histopathologic specimen indices (quality of TME and CRM involvement rate), and or the rate of conversion to open surgery between VO and non-VO group (P >0.05). Nevertheless, the group of individuals with VO experienced a lengthier duration of surgery (P <0.001) and a delayed time until the first passage of flatus (P <0.001) in comparison to the group without VO. The study suggests that VO does not significantly impact early complications or the quality of surgical outcomes in mid and low rectal cancer patients undergoing robotic surgery.”
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