OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System

Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to take humans out of the loop when building artificial intelligence (AI) applications, scant literature has focused on how AutoML works well in open-environment scenarios such as the process of training and updating large models, industrial supply chains or the industrial metaverse, where people often face open-loop problems during the search process: they must continuously collect data, update data and models, satisfy the requirements of the development and deployment environment, support massive devices, modify evaluation metrics, etc. Addressing the open-environment issue with pure data-driven approaches requires considerable data, computing resources, and effort from dedicated data engineers, making current AutoML systems and platforms inefficient and computationally intractable. Human-computer interaction is a practical and feasible way to tackle the problem of open-environment AI. In this paper, we introduce OmniForce, a human-centered AutoML (HAML) system that yields both human-assisted ML and ML-assisted human techniques, to put an AutoML system into practice and build adaptive AI in open-environment scenarios. Specifically, we present OmniForce in terms of ML version management; pipeline-driven development and deployment collaborations; a flexible search strategy framework; and widely provisioned and crowdsourced application algorithms, including large models. Furthermore, the (large) models constructed by OmniForce can be automatically turned into remote services in a few minutes; this process is dubbed model as a service (MaaS). Experimental results obtained in multiple search spaces and real-world use cases demonstrate the efficacy and efficiency of OmniForce

A New Method on Calibrating PSF of Remote Sensing Space Plane Arraycamera

Point spread function (PSF) of an imaging system is an important parameter to a remote sensing imaging system, and it is the important basis for image restoration [1]. The knife-edges method has been widely used to measure PSF because it provides a relatively easy way to get the point spread function. However, the location of the edge points in edge spread function (ESF) is difficult to determine of the knife-edges method, resulting in the inaccuracy of the point spread function. In this paper, we propose a new method to solve the problem of phase influence for calibrating PSF of space plane array camera. This method include: the design of target, the process of calibration and data processing. Then this method was used on calibrating PSF of GF-4 satellite panchromatic camera. The results showed that the new method could determine the PSF correctly

Anti-icing Capacity and Service Life Research on the Controlled Released Anti-icing Asphalt Modifier

The release rate of chloride ions could be controlled by adding additives into the anti-icing modifier, for the purpose of extending the modifier’s usage life. The anti-icing capacity of the modifier with controlled released additives was researched in this paper by the “Chloride ion concentration change monitoring test” and “Dynamic water simulation test”, and the service life of the modifier has been analyzed

Rapid Determination of Cr³⁺ and Mn²⁺ in Water Using Laser-Induced Breakdown Spectroscopy Combined with Filter Paper Modified with Gold Nanoclusters

Excessive emissions of heavy metals not only cause environmental pollution but also pose a direct threat to human health. Therefore, rapid and accurate detection of heavy metals in the environment is of great significance. Herein, we propose a method based on laser-induced breakdown spectroscopy (LIBS) combined with filter paper modified with bovine serum albumin-protected gold nanoclusters (LIBS-FP-AuNCs) for the rapid and sensitive detection of Cr3+ and Mn2+. The filter paper modified with AuNCs was used to selectively enrich Cr3+ and Mn2+. Combined with the multi-element detection capability of LIBS, this method achieved the simultaneous rapid detection of Cr3+ and Mn2+. Both elements showed linear ranges for concentrations of 10–1000 μg L−1, with limits of detection of 7.5 and 9.0 μg L−1 for Cr3+ and Mn2+, respectively. This method was successfully applied to the determination of Cr3+ and Mn2+ in real water samples, with satisfactory recoveries ranging from 94.6% to 105.1%. This method has potential application in the analysis of heavy metal pollution

Anti-icing Capacity and Service Life Research on the Controlled Released Anti-icing Asphalt Modifier

The release rate of chloride ions could be controlled by adding additives into the anti-icing modifier, for the purpose of extending the modifier’s usage life. The anti-icing capacity of the modifier with controlled released additives was researched in this paper by the “Chloride ion concentration change monitoring test” and “Dynamic water simulation test”, and the service life of the modifier has been analyzed

A New Method on Calibrating PSF of Remote Sensing Space Plane Arraycamera

Point spread function (PSF) of an imaging system is an important parameter to a remote sensing imaging system, and it is the important basis for image restoration [1]. The knife-edges method has been widely used to measure PSF because it provides a relatively easy way to get the point spread function. However, the location of the edge points in edge spread function (ESF) is difficult to determine of the knife-edges method, resulting in the inaccuracy of the point spread function. In this paper, we propose a new method to solve the problem of phase influence for calibrating PSF of space plane array camera. This method include: the design of target, the process of calibration and data processing. Then this method was used on calibrating PSF of GF-4 satellite panchromatic camera. The results showed that the new method could determine the PSF correctly

A New Method on Calibrating PSF of Remote Sensing Space Plane Arraycamera

Point spread function (PSF) of an imaging system is an important parameter to a remote sensing imaging system, and it is the important basis for image restoration [1]. The knife-edges method has been widely used to measure PSF because it provides a relatively easy way to get the point spread function. However, the location of the edge points in edge spread function (ESF) is difficult to determine of the knife-edges method, resulting in the inaccuracy of the point spread function. In this paper, we propose a new method to solve the problem of phase influence for calibrating PSF of space plane array camera. This method include: the design of target, the process of calibration and data processing. Then this method was used on calibrating PSF of GF-4 satellite panchromatic camera. The results showed that the new method could determine the PSF correctly

Investigation of Time-Varying Cable Tension of Bridges Using Time-Frequency Reassignment Techniques Based on Structural Health Monitoring Data

Cables have been increasingly utilized in modern long-span or tied-arch bridges as the main bearing structures. Real-time identification of time-varying cable tension is essential for assessing the service performance of bridges. Vibration-based methods have been an increasing research focus in recent decades. However, a long time interval is needed to estimate structural frequency using vibration-based methods, increasing the calculating time of cable tension. The time-varying cable tension is thus difficult to extract. This study proposes a time-frequency reassignment-based algorithm to reduce the detection time to address this issue. Combined with a time-frequency analysis tool and vibration theory of cables, the algorithm can identify the time-varying frequency and further quickly calculate the time-varying cable tension within 12.8 s. The features of the proposed algorithm are mainly threefold: identifying the time-varying frequencies with high precision; without some prior knowledge of vibration; having no other requirements for sensor modes. Moreover, the experimental validation is conducted using a quasi-static loading in a workshop and a dynamic field test on Sutong Bridge, respectively. The results show that the proposed algorithm can be used to identify time-varying tension and assess the service performance of cables, providing a new path for real-time condition monitoring of bridges in service

Investigation of Time-Varying Cable Tension of Bridges Using Time-Frequency Reassignment Techniques Based on Structural Health Monitoring Data

Cables have been increasingly utilized in modern long-span or tied-arch bridges as the main bearing structures. Real-time identification of time-varying cable tension is essential for assessing the service performance of bridges. Vibration-based methods have been an increasing research focus in recent decades. However, a long time interval is needed to estimate structural frequency using vibration-based methods, increasing the calculating time of cable tension. The time-varying cable tension is thus difficult to extract. This study proposes a time-frequency reassignment-based algorithm to reduce the detection time to address this issue. Combined with a time-frequency analysis tool and vibration theory of cables, the algorithm can identify the time-varying frequency and further quickly calculate the time-varying cable tension within 12.8 s. The features of the proposed algorithm are mainly threefold: identifying the time-varying frequencies with high precision; without some prior knowledge of vibration; having no other requirements for sensor modes. Moreover, the experimental validation is conducted using a quasi-static loading in a workshop and a dynamic field test on Sutong Bridge, respectively. The results show that the proposed algorithm can be used to identify time-varying tension and assess the service performance of cables, providing a new path for real-time condition monitoring of bridges in service