查看更多>>摘要：Research findings on evolutionary computation are discussed in a new report. According to news originating from the University of Adelaide by NewsRx correspondents, research stated, “In real-world optimisation, it is common to face several sub-problems interacting and forming the main problem.” The news editors obtained a quote from the research from University of Adelaide: “There is an interdependency between the sub-problems, making it impossible to solve such a problem by focusing on only one component. The travelling thief problem (TTP) belongs to this category and is formed by the integration of the travelling salesperson problem (TSP) and the knapsack problem (KP). In this paper, we investigate the inter-dependency of the TSP and the KP by means of quality diversity (QD) approaches. QD algorithms provide a powerful tool not only to obtain high-quality solutions but also to illustrate the distribution of high-performing solutions in the behavioural space. We introduce a multi-dimensional archive of phenotypic elites (MAP-Elites) based evolutionary algorithm using well-known TSP and KP search operators, taking the TSP and KP score as the behavioural descriptor. MAP-Elites algorithms are QD-based techniques to explore high-performing solutions in a behavioural space.”
查看更多>>摘要：Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Maoming, People’s Republic of China, by NewsRx correspondents, research stated, “Modern data analysis methods, including machine learning (ML), have become essential instruments for uncovering concealed patterns and deducing correlations that conventional analytical techniques may encounter limitations in handling. This study provides a detailed introduction to a three-dimensional sensor array for hypochlorite and hydroxyl radical developed using machine learning methods, based on the sensitive differentiation of spectroscopic properties using a single fluorescent probe.” Funders for this research include National Natural Science Foundation of China (NSFC), Projects of Talents Recruitment of GDUPT, Guangdong Basic and Applied Basic Research Foundation.
查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating from Sheffield, United Kingdom, by NewsRx editors, the research stated, “This paper deals with the problem of estimating notch fatigue limits via machine learning. The proposed strategy is based on those constitutive elements that were used by the pioneers like Peterson, Neuber, Heywood, and Topper to devise their well-known formulas.” Our news editors obtained a quote from the research from the University of Sheffield, “The machine learning algorithms being considered were trained and tested using a database containing 238 notch fatigue limits taken from the literature. The outcomes from this study confirm that machine learning is a promising approach for designing notched components against fatigue. In particular, the accuracy in the estimates can easily be increased by simply increasing size and quality of the calibration dataset. Further, since machine learning regression models are highly flexible and can handle highdimensional datasets with many input features, they can capture complex relationships between input features and the target variable. This means that the accuracy in estimating notch fatigue limit can be increased by including in the analyses further input features like, for instance, grain size or hardness.”
查看更多>>摘要：Research findings on robotics are discussed in a new report. According to news reporting originating from Brasov, Romania, by NewsRx correspondents, research stated, “Autonomous legged navigation in unstructured environments is still an open problem which requires the ability of an intelligent agent to detect and react to potential obstacles found in its area.” Financial supporters for this research include Romanian Executive Agency For Higher Education, Research, Development, And Innovation Funding. The news correspondents obtained a quote from the research from Transilvania University: “These obstacles may range from vehicles, pedestrians, or immovable objects in a structured environment, like in highway or city navigation, to unpredictable static and dynamic obstacles in the case of navigating in an unstructured environment, such as a forest road. The latter scenario is usually more difficult to handle, due to the higher unpredictability. In this paper, we propose a vision dynamics approach to the path planning and navigation problem for a quadruped robot, which navigates in an unstructured environment, more specifically on a forest road.”
查看更多>>摘要：New research on Oncology - Bladder Cancer is the subject of a report. According to news reporting originating from Shandong, People’s Republic of China, by NewsRx correspondents, research stated, “To establish a model for predicting lymph node metastasis in bladder cancer (BCa) patients. We retroactively enrolled 239 patients who underwent three-phase CT and resection for BCa in two centers (training set, n = 185; external test set, n = 54).” Our news editors obtained a quote from the research from the Affiliated Hospital of Qingdao University, “We reviewed the clinical characteristics and CT features to identify significant predictors to construct a clinical model. We extracted the hand-crafted radiomics features and deep learning features of the lesions. We used the Minimum Redundancy Maximum Relevance algorithm and the least absolute shrinkage and selection operator logistic regression algorithm to screen features. We used nine classifiers to establish the radiomics machine learning signatures. To compensate for the uneven distribution of the data, we used the synthetic minority over-sampling technique to retrain each machine-learning classifier. We constructed the combined model using the top-performing radiomics signature and clinical model, and finally presented as a nomogram. We evaluated the combined model’s performance using the area under the receiver operating characteristic, accuracy, calibration curves, and decision curve analysis. We used the Kaplan-Meier survival curve to analyze the prognosis of BCa patients. The combined model incorporating radiomics signature and clinical model achieved an area under the receiver operating characteristic of 0.834 (95% CI: 0.659-1.000) for the external test set. The calibration curves and decision curve analysis demonstrated exceptional calibration and promising clinical use. The combined model showed good risk stratification performance for progression-free survival. The proposed CT-based combined model is effective and reliable for predicting lymph node status of BCa patients preoperatively. Bladder cancer is a type of urogenital cancer that has a high morbidity and mortality rate. Lymph node metastasis is an independent risk factor for death in bladder cancer patients.”
查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news reporting originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Shield tunnel segment uplift is a common phenomenon in construction.” Our news editors obtained a quote from the research from Shanghai University: “Excessive and unstable uplift will affect tunnel quality and safety seriously, shorten the tunnel life, and is not conducive to the sustainable management of the tunnel’s entire life cycle. However, segment uplift is affected by many factors, and it is challenging to predict the uplift amount and determine its cause accurately. Existing research mainly focuses on analyzing uplift factors and the uplift trend features for specific projects, which is difficult to apply to actual projects directly. This paper sorts out the influencing factors of segment uplift and designs a spatial-temporal data fusion mechanism for prediction.”
查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting from Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “Amidst the critical role that high-quality labeled data plays in advancing machine learning, the persistence of noise within widelyused datasets remains a challenge. While noise learning has gained traction within machine learning, particularly in computer vision, its exploration in text and multimodal classification domains has lagged.” Financial supporters for this research include National Key Research and Development Project, National Natural Science Foundation of China (NSFC).
查看更多>>摘要：Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Chengdu, People’s Republic of China, by NewsRx correspondents, research stated, “Accurate State of Health (SOH) estimation of battery systems is critical to vehicle operation safety. However, it’s difficult to guarantee the performance of a single model due to the unstable quality of raw data obtained from lithium-ion battery aging and the complexity of operating conditions in actual vehicle operation.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), National Natural Science Foundation of China (NSFC).
查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting out of Cookeville, Tennessee, by NewsRx editors, research stated, “Deep learning (DL) has proven to be effective in detecting sophisticated malware that is constantly evolving. Even though deep learning has alleviated the feature engineering problem, finding the most optimal DL model’s architecture and set of hyper-parameters, remains a challenge that requires domain expertise.” Financial support for this research came from National Science Foundation (NSF). Our news journalists obtained a quote from the research from Tennessee Technological University, “In addition, many of the proposed state-of-the-art models are very complex and may not be the best fit for different datasets. A promising approach, known as Automated Machine Learning (AutoML), can reduce the domain expertise required to develop custom DL models by automating the ML pipeline key components, namely hyperparameter optimization and neural architecture search (NAS). AutoML reduces the amount of human trial-and-error involved in designing DL models, and in more recent implementations can find new model architectures with relatively low computational overhead.Research on the feasibility of using AutoML for malware detection is very limited. This work provides a comprehensive analysis and insights on using AutoML for both static and online malware detection. For static, our analysis is performed on two widely used malware datasets: SOREL-20M to demonstrate efficacy on large datasets; and EMBER-2018, a smaller dataset specifically curated to hinder the performance of machine learning models. In addition, we show the effects of tuning the NAS process parameters on finding a more optimal malware detection model on these static analysis datasets. Further, we also demonstrate that AutoML is performant in online malware detection scenarios using Convolutional Neural Networks (CNNs) for cloud IaaS. We compare an AutoML technique to six existing state-of-the-art CNNs using a newly generated online malware dataset with and without other applications running in the background during malware execution. We show that the AutoML technique is more performant than the state-of-the-art CNNs with little overhead in finding the architecture.”
查看更多>>摘要：Fresh data on Robotics are presented in a new report. According to news originating from Wuhan, People’s Republic of China, by NewsRx correspondents, research stated, “PurposeBecause of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this paper is to propose a deep learning torque prediction method based on long short-term memory (LSTM) recurrent neural networks optimized by particle swarm optimization (PSO), which can accurately predict the the joint The proposed model optimized the LSTM with PSO algorithm to accurately predict the Irs joint torque. The authors design an excitation trajectory for ABB 1600-10/145 experimental robot and collect its relative dynamic data.”
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