查看更多>>摘要：Data detailed on robotics have been presented. According to news reporting out of Hubei, People’s Republic of China, by NewsRx editors, research stated, “Efficient and safe path planning for autonomous navigation is paramount in advancing the motion control capabilities of mobile robots.” Funders for this research include The National Natural Science Foundation of China; Hubei Provincial Science And Technology Plan Project. The news correspondents obtained a quote from the research from Hubei University of Technology: “To obtain the global optimal smooth path for mobile robots, a multi-strategy ensemble Harris hawks optimization algorithm (SDHHO) is proposed in this paper. The spiral search strategy is adopted to improve the early update method of the algorithm, which can improve the global exploration ability. To achieve better balance between global exploration and local exploitation, the Sine chaotic map is introduced to the escape energy, replacing random components. Furthermore, an elite differential mutation strategy combined with Gaussian mutation is designed to prevent the algorithm from falling into local optima. We compared the SDHHO algorithm with other classical and novel algorithms on 23 benchmark functions, and the results demonstrated the superiority of SDHHO.”
查看更多>>摘要：A new study on Artificial Intelligence is now available. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “As the world is increasingly infused with artificial intelligence (AI), school teachers are beginning to acquire AI literacy and to integrate AI-related content into their teaching practices. However, research on teachers’ AI competencies is still in its early stage, leaving many gaps yet to be explored.” The news correspondents obtained a quote from the research from Tsinghua University, “This study engaged 364 Chinese practicing teachers involved in teaching AI lessons after receiving training, employing a six-factor instrument. The survey assessed teachers’ efficacies in understanding AI and teaching AI, with additional considerations of promoting ethical awareness and designing socially beneficial AI applications. In addition, teachers’ continuous intention to learn AI and their attitudes toward teaching AI were measured. The survey underwent rigorous validation procedures, confirming its construct validity through confirmatory factor analysis, and demonstrating satisfactory reliabilities and convergent and discriminant validities through other statistical analyses. Structural equation modeling provided support for most of the hypotheses. Further, variance analyses indicated that high school teachers scored higher than primary and middle school teachers across all six measured factors, possibly due to the contextual demands of the university entrance examinations. Overall, the findings suggest a willingness among teachers to enhance their competencies for teaching AI, and underscore the need for increased attention on strengthening teachers’ competencies to promote ethical judgement and design AI for social good.”
查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating from Syracuse, New York, by NewsRx correspondents, research stated, “We propose a novel approach, which we call machine learning strategy identification (MLSI), to uncovering hidden decision strategies. In this approach, we first train machine learning models on choice and process data of one set of participants who are instructed to use particular strategies, and then use the trained models to identify the strategies employed by a new set of participants.” Financial support for this research came from National Natural Science Foundation of China (NSFC). Our news editors obtained a quote from the research from Syracuse University, “Unlike most modeling approaches that need many trials to identify a participant’s strategy, MLSI can distinguish strategies on a trial-by-trial basis. We examined MLSI’s performance in three experiments. In Experiment I, we taught participants three different strategies in a paired-comparison decision task. The best machine learning model identified the strategies used by participants with an accuracy rate above 90%. In Experiment Ⅱ, we compared MLSI with the multiple-measure maximum likelihood (MM-ML) method that is also capable of integrating multiple types of data in strategy identification, and found that MLSI had higher identification accuracy than MM-ML. In Experiment Ⅲ, we provided feedback to participants who made decisions freely in a task environment that favors the non-compensatory strategy take-the-best. The trial-by-trial results of MLSI show that during the course of the experiment, most participants explored a range of strategies at the beginning, but eventually learned to use take-the-best.”
查看更多>>摘要：New research on Oncology - Pancreatic Cancer is the subject of a report. According to news reporting from Hebei, People’s Republic of China, by NewsRx journalists, research stated, “MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. However, the prognostic value of MYC-related genes in pancreatic adenocarcinoma (PAAD) remains unclarified.” The news correspondents obtained a quote from the research from the Fourth Hospital of Hebei Medical University, “Gene expression data and clinical information of PAAD patients were obtained from The Cancer Genome Atlas (TCGA) database (training set). Validation sets included GSE57495, GSE62452, and ICGC-PACA databases. LASSO regression analysis was used to develop a risk signature for survival prediction. Single-cell sequencing data from GSE154778 and CRA001160 datasets were analyzed. Functional studies were conducted using siRNA targeting RHOF and ITGB6 in PANC-1 cells. High MYC expression was found to be significantly associated with a poor prognosis in patients with PAAD. Additionally, we identified seven genes (ADGRG6, LINC00941, RHOF, SERPINB5, INSYN2B, ITGB6, and DEPDC1) that exhibited a strong correlation with both MYC expression and patient survival. They were then utilized to establish a risk model (MYCsig), which showed robust predictive ability. Furthermore, MYCsig demonstrated a positive correlation with the expression of HLA genes and immune checkpoints, as well as the chemotherapy response of PAAD. RHOF and ITGB6, expressed mainly in malignant cells, were identified as key oncogenes regulating chemosensitivity through EMT. Downregulation of RHOF and ITGB6 reduced cell proliferation and invasion in PANC-1 cells. The developed MYCsig demonstrates its potential in enhancing the management of patients with PAAD by facilitating risk assessment and predicting response to adjuvant chemotherapy.”
查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news reporting from Karnataka, India, by NewsRx journalists, research stated, “Ensemble learning combines multiple base models to enhance predictive performance and generalize better on unseen data.” The news editors obtained a quote from the research from Affiliated to Visvesvaraya Technological University: “In the context of Computed Tomography (CT) image processing, ensemble techniques often leverage diverse machine learning or deep learning architectures to achieve the best results. Ensemble machine learning and deep learning techniques have revolutionized the field of CT image processing by significantly improving accuracy, robustness, and efficiency in various medical imaging tasks. These methods have been instrumental in tasks such as image reconstruction, segmentation, classification, and disease diagnosis. The ensemble models can be divided into those based on decision fusion strategies, bagging, boosting, stacking, negative correlation, explicit/implicit ensembles, homogeneous/heterogeneous ensembles, and explicit/implicit ensembles. In comparison to shallow or traditional, machine learning models and deep learning architectures are currently performing better.”
查看更多>>摘要：Researchers detail new data in artificial intelligence. According to news originating from Changsha, People’s Republic of China, by NewsRx editors, the research stated, “Due to excellent comprehensive properties such as high strength, high hardness, and excellent high-temperature oxidation resistance, the refractory high-entropy alloys have broad application prospects and research value in the fields of aerospace and nuclear energy.” The news correspondents obtained a quote from the research from Central South University: “However, the refractory high-entropy alloys have very complex composition features, making it difficult to perform alloy design. It seriously restricts the development of high-performance refractory high-entropy alloys. In recent years, the machine learning technique has been gradually applied to various high-performance alloys with efficient and accurate modeling and prediction capability. In this review, there was a comprehensive summary of research achievements on machine learning-driven design of refractory high-entropy alloys. A detailed review on the applications and progress of machine learning technique in different aspects was given, including alloy phase structure design, mechanical property prediction, strengthening mechanism analysis and acceleration of atomic simulations. Finally, the currently existing problems in this direction were summarized.”
查看更多>>摘要：Investigators publish new report on robotics. According to news reporting from Tokyo, Japan, by NewsRx journalists, research stated, “This paper presents a model for generating expressive robot motions based on human expressive movements.” Financial supporters for this research include Jsps Kakenhi; Nedo. The news reporters obtained a quote from the research from Tokyo University of Agriculture and Technology: “The proposed data-driven approach combines variational autoencoders and a generative adversarial network framework to extract the essential features of human expressive motion and generate expressive robot motion accordingly. The primary objective was to transfer the underlying expressive features from human to robot motion. The input to the model consists of the robot task defined by the robot’s linear velocities and angular velocities and the expressive data defined by the movement of a human body part, represented by the acceleration and angular velocity.” According to the news editors, the research concluded: “The experimental results show that the model can effectively recognize and transfer expressive cues to the robot, producing new movements that incorporate the expressive qualities derived from the human input. Furthermore, the generated motions exhibited variability with different human inputs, highlighting the ability of the model to produce diverse outputs.”
查看更多>>摘要：Researchers detail new data in Support Vector Machines. According to news reporting out of Tangshan, People’s Republic of China, by NewsRx editors, research stated, “A digital twin model based on superpixel features is established to solve the problem of noise and similar gray values between foreground and background of pellet images. With superpixel as the basic unit of segmentation, the influence of single pixel on segmentation results is reduced, and allows for higher segmentation accuracy.” Funders for this research include Natural Science Foundation of Hebei Province, Basic Research Funds for Universities. Our news journalists obtained a quote from the research from the North China University of Science and Technology, “The gray-level co-occurrence matrix is used to represent the superpixel characteristic information, and the color moment and gray level distribution are combined to comprehensively characterize the superpixel. Through principal component analysis and correlation analysis, The feature compression of superpixel is realized, and the computational efficiency is improved. The superpixel binary classification data set is built, and the multidimensional feature information of superpixel is extracted as input vector to train the binary classification model of SVM, and the image segmentation problem is transformed into foreground and background classification problem. A multi-scale superpixel segmentation boundary optimization method is proposed to further refine the boundary region of foreground and background. A four-neighborhood search algorithm is proposed to reduce the missegmentation rate of edge superpixels. Experimental results show that the accuracy of the proposed method can reach 95.87%, the precision of image edge segmentation is high, and the foreground and background of granular image are accurately segmented.”
查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating in Minneapolis, Minnesota, by NewsRx journalists, research stated, “This ‘white paper’is a concise perspective of the potential of machine learning in the process systems engineering (PSE) domain, based on a session during FIPSE 5, held in Crete, Greece, June 27-29, 2022.” Financial support for this research came from National Science Foundation (NSF). The news reporters obtained a quote from the research from the University of Minnesota, “The session included two invited talks and three short contributed presentations followed by extensive discussions. This paper does not intend to provide a comprehensive review on the subject or a detailed exposition of the discussions; instead its aim is to distill the main points of the discussions and talks, and in doing so, highlight open problems and directions for future research.” According to the news reporters, the research concluded: “The general conclusion from the session was that machine learning can have a transformational impact on the PSE domain enabling new discoveries and innovations, but research is needed to develop domain-specific techniques for problems in molecular/material design, data analytics, optimization, and control.” This research has been peer-reviewed.
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Warsaw, Poland, by NewsRx correspondents, research stated, “This paper aims to thoroughly discuss the impact of artificial intelligence (AI) on clinical practice in interventional cardiology (IC) with special recognition of its most recent advancements. Thus, recent years have been exceptionally abundant in advancements in computational tools, including the development of AI.” Our news journalists obtained a quote from the research from the Polish Academy of Sciences, “The application of AI development is currently in its early stages, nevertheless new technologies have proven to be a promising concept, particularly considering IC showing great impact on patient safety, risk stratification and outcomes during the whole therapeutic process. The primary goal is to achieve the integration of multiple cardiac imaging modalities, establish online decision support systems and platforms based on augmented and/or virtual realities, and finally to create automatic medical systems, providing electronic health data on patients. In a simplified way, two main areas of AI utilization in IC may be distinguished, namely, virtual and physical. Consequently, numerous studies have provided data regarding AI utilization in terms of automated interpretation and analysis from various cardiac modalities, including electrocardiogram, echocardiography, angiography, cardiac magnetic resonance imaging, and computed tomography as well as data collected during robotic-assisted percutaneous coronary intervention procedures.”
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