查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Lahore, Pakist an, by NewsRx editors, research stated, "ABSTRACT: Water is one of the most crit ical resources for maintaining life. Although it makes upto 70% of the earth's surface but only a small amount of it is usable." The news editors obtained a quote from the research from University of Engineeri ng and Technology: "Since water is used for a variety of functions, its quality must be determined before usage. The rapid increase of the world's population ha s also had a significant influence on the environment, particularly on water qua lity. The quality of water has been deteriorating in recent years due to various pollutants. To control the water pollution, modeling and predicting the water q uality has become a crucial need. In this work, we propose a machine learning (M L)-based model to predict and classify the water quality. The results from six d ifferent ML models are analyzed for accuracy, precision, recall, and F1 score as performance measures."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology-Colon Cance r is the subject of a report. According to news reporting out of Changchun, Peop le's Republic of China, by NewsRx editors, research stated, "The metabolic signa ture identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and imp rove patient survival. Here, we combined an untargeted metabolic analysis strate gy based on internal extractive electrospray ionization mass spectrometry and th e machine learning approach to analyze metabolites in 173 pairs of cancer sample s and matched normal tissue samples to build robust metabolic signature models f or diagnostic purposes." Our news journalists obtained a quote from the research from Jilin University, " Screening and independent validation of metabolic signatures from colorectal can cers via machine learning methods (Logistic Regression_L1 for featu re selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accur acy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabol ic molecule PC (30:0) showing good diagnostic performance. In addition, genes as sociated with PC (30:0) were identified by multiomics analysis (combining metabo lic data with transcriptomic data analysis) and our results showed that PC (30:0 ) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on robotics have been published. According to news reporting from Guangzhou, People's Republic o f China, by NewsRx journalists, research stated, "With the development of the na vigation technology, the outdoor navigation has made great progress, whereas the indoor navigation has some areas which is underdeveloped, insufficient to meet the rapidly increasing demands of people as well as the robotics." The news editors obtained a quote from the research from South China University of Technology: "Even though, the advance in indoor navigation technology still h as really brought a wide range of applications and a broad market, for instance, the flourishing intelligent warehouse system utilizes multi-robot operation whi ch have the certain requirement for an accurate indoor navigation system. As for the indoor navigation, the OGC standard IndoorGML has been released and undergo ing revision constantly. While the document really provides more advantageous su pport for the applications of Indoor Location-Based Services (LBS), in some aspe cts, especially the door-to-door navigation and the warehouse environment, it is not sufficiently adaptable, with still some room for improvement. IndoorGML is powerful for the common indoor scenarios like malls and offices, while as for ca refully-arranged warehouse environment and other large-scale operation scenarios with multi-robots that is more similar to an ordered system, it is obviously in sufficient. In this paper, we discuss about the potential to combination of Indo orGML and ITS standard ISO 20524 (GDF5.1), and extend the OGC standard indoorGML . We analyze the definition as well as function of related concepts, making some comparisons between these two standards."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Sheff ield, United Kingdom, by NewsRx correspondents, research stated, "The convergenc e of digital pathology and artificial intelligence could assist histopathology i mage analysis by providing tools for rapid, automated morphological analysis. Th is systematic review explores the use of artificial intelligence for histopathol ogical image analysis of digitised central nervous system (CNS) tumour slides." Financial supporters for this research include National Institute for Health and Care Research, Wellcome / EPSRC Centre for Interventional and Surgical Sciences.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in artificial intelligence. According to news reporting originating from Knoxville, Tennessee, by NewsRx correspondents, research stated, "Identifying stress in ol der adults is a crucial field of research in health and well-being. This allows us to take timely preventive measures that can help save lives." Funders for this research include University of Tennessee At Knoxville. Our news journalists obtained a quote from the research from University of Tenne ssee: "That is why a nonobtrusive way of accurate and precise stress detection i s necessary. Researchers have proposed many statistical measurements to associat e stress with sensor readings from digital biomarkers. With the recent progress of Artificial Intelligence in the healthcare domain, the application of machine learning is showing promising results in stress detection. Still, the viability of machine learning for digital biomarkers of stress is under-explored. In this work, we first investigate the performance of a supervised machine learning algo rithm (Random Forest) with manual feature engineering for stress detection with contextual information. The concentration of salivary cortisol was used as the g olden standard here. Our framework categorizes stress into No Stress, Low Stress , and High Stress by analyzing digital biomarkers gathered from wearable sensors . We also provide a thorough knowledge of stress in older adults by combining ph ysiological data obtained from wearable sensors with contextual clues from a str ess protocol. Our context-aware machine learning model, using sensor fusion, ach ieved a macroaverage F-1 score of 0.937 and an accuracy of 92.48% in identifying three stress levels. We further extend our work to get rid of the burden of manual feature engineering. We explore Convolutional Neural Network ( CNN)-based feature encoder and cortisol biomarkers to detect stress using contex tual information."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news reporting from the University of Miskol c by NewsRx journalists, research stated, "In artificial intelligence, combating overfitting and enhancing model generalization is crucial." The news journalists obtained a quote from the research from University of Misko lc: "This research explores innovative noise-induced regularization techniques, focusing on natural language processing tasks. Inspired by gradient noise and Dr opout, this study investigates the interplay between controlled noise, model com plexity, and overfitting prevention. Utilizing long short-term memory and bidire ctional long short term memory architectures, this study examines the impact of noise-induced regularization on robustness to noisy input data."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on artificial intelligenc e is the subject of a new report. According to news reporting from Saarbrucken, Germany, by NewsRx journalists, research stated, "The foundation of materials sc ience and engineering is the establishment of process-microstructure-property li nks, which in turn form the basis for materials and process development and opti mization." The news reporters obtained a quote from the research from Saarland University: "At the heart of this is the characterization and quantification of the material 's microstructure. To date, microstructure quantification has traditionally invo lved a human deciding what to measure and included labor-intensive manual evalua tion. Recent advancements in artificial intelligence (AI) and machine learning ( ML) offer exciting new approaches to microstructural quantification, especially classification and semantic segmentation. This promises many benefits, most nota bly objective, reproducible, and automated analysis, but also quantification of complex microstructures that has not been possible with prior approaches. This r eview provides an overview of ML applications for microstructure analysis, using complex steel microstructures as examples."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Beijing, People's Repu blic of China, by NewsRx editors, research stated, "As the turbine load increase s, both the blade profile losses and secondary flow losses in the endwall region cannot be ignored for turbines operating at low Reynolds numbers. To fully expl ore the flow control effects of the blade and endwall shapes, a viable integrate d parameterization method and optimization method are formulated for turbine sta ges." Funders for this research include National Natural Science Foundation of China ( NSFC), National Major Science and Technology Project of China.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting out of Campeche, Mexico, by NewsRx editors, research stated, "This work aimed to describe the adsorption behavior of Congo red (CR) onto activated biochar material prepared from * * Haematoxylum campechi-anum* * waste (* * ABHC* * ). The carbon precursor was soaked with phos phoric acid, followed by pyrolysis to convert the precursor into activated bioch ar." Funders for this research include Tecnologico De Monterrey.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in artificial intelligence. According to news originating from Moscow, Russia, by N ewsRx correspondents, research stated, "Nafion, a versatile polymer used in elec trochemistry and membrane technologies, exhibits complex behaviors in saline env ironments." The news editors obtained a quote from the research from Bauman Moscow State Tec hnical University: "This study explores Nafion membrane's IR spectra during soak ing and subsequent drying processes in salt solutions at various concentrations. Utilizing the principles of Fick's second law, diffusion coefficients for these processes are derived via exponential approximation. By harnessing machine lear ning (ML) techniques, including the optimization of neural network hyperparamete rs via a genetic algorithm (GA) and leveraging various regressors, we effectivel y pinpointed the optimal model for predicting diffusion coefficients. Notably, f or the prediction of soaking coefficients, our model is composed of layers with 64, 64, 32, and 16 neurons, employing ReLU, ELU, sigmoid, and ELU activation fun ctions, respectively."
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