An Adaptive Noise Reduction Method for High Temperature and Low Voltage Electromagnetic Detection Signals Based on SVMD Combined with ICEEMDAN.

In view of the low signal-to-noise ratio (SNR) of shear wave electromagnetic acoustic transducers (EMAT) in the detection of high-temperature equipment, the use of low excitation voltage (LEV) further deteriorates the detection results, resulting in the echo signal containing defects being drowned in noise. For the extraction of the EMAT signal, an adaptive noise reduction method is proposed. Firstly, the minimum envelope entropy is taken as the fitness function for the Harris Hawks Optimizer (HHO), and the optimal successive variational mode decomposition (SVMD) balance parameter is searched by HHO adaptive iteration to decompose LEV EMAT signals at high temperatures.

Electromagnetic Acoustic Detection of Pipe Defects Hidden above T-Type Support Structures with Circumferential Shear Horizontal Guided Wave.

When pipe defects are generated above the T-type support structure location, it is difficult to distinguish the reflection signals caused by the weld bead at the support structure from the reflection echoes of pipe defects. Therefore, in order to effectively detect pipe defects, a waveform subtraction method with a circumferential shear horizontal (CSH) guided wave is proposed, which is generated by an electromagnetic acoustic transducer (EMAT). First, a CSH guided wave mode with a center frequency of 500 kHz is selected to establish a three-dimensional model with and without pipe defects above the support structure.

Mapping specific groundwater nitrate concentrations from spatial data using machine learning: A case study of chongqing, China.

Groundwater resources is not only important essential water resources but also imperative connectors within the intricate framework of the ecological environment. High nitrate concentrations in groundwater can exerting adverse impacts on human health. It is imperative to accurately delineate the distribution characteristics of groundwater nitrate concentrations.

Enhanced performance of acridine degradation and power generation by microbial fuel cell with g-CN/PANI-DA/CF anode.

Microbial fuel cell (MFC) has attracted much attention in treating organic wastewater due to its double functions of degrading organics and generating electricity with microorganisms as biocatalysts. Unfortunately, some organics with biological toxicity such as acridine could inhibit the growth and activity of the microorganisms on the anode so that the double functions of MFC would recede. Enhancing microbial activity by using new biocompatible materials as anodes is prospective to solve problem.

Effects of Different Natural Factors on Rheological Properties of SBS Modified Asphalt.

Typical climatic environments such as UV radiation, high temperature and strong wind in cold and arid regions have a significant effect on asphalt aging. The intent of this work is to reveal the evolution law of natural aging of SBS-modified asphalt under the complex adverse climate environment in cold and arid regions. Furthermore, the contribution rate of various environmental factors of natural aging of asphalt in cold and arid regions was analyzed.

Domain Adaptive Box-Supervised Instance Segmentation Network for Mitosis Detection.

The number of mitotic cells present in histopathological slides is an important predictor of tumor proliferation in the diagnosis of breast cancer. However, the current approaches can hardly perform precise pixel-level prediction for mitosis datasets with only weak labels (i.e.

Deploying and scaling distributed parallel deep neural networks on the Tianhe-3 prototype system.

Due to the increase in computing power, it is possible to improve the feature extraction and data fitting capabilities of DNN networks by increasing their depth and model complexity. However, the big data and complex models greatly increase the training overhead of DNN, so accelerating their training process becomes a key task. The Tianhe-3 peak speed is designed to target E-class, and the huge computing power provides a potential opportunity for DNN training.

Crowd Scene Analysis Encounters High Density and Scale Variation.

Crowd scene analysis receives growing attention due to its wide applications. Grasping the accurate crowd location is important for identifying high-risk regions. In this article, we propose a Compressed Sensing based Output Encoding (CSOE) scheme, which casts detecting pixel coordinates of small objects into a task of signal regression in encoding signal space.

A Deep Learning Approach for Maximum Activity Links in D2D Communications.

Mobile cellular communications are experiencing an exponential growth in traffic load on Long Term Evolution (LTE) eNode B (eNB) components. Such load can be significantly contained by directly sharing content among nearby users through device-to-device (D2D) communications, so that repeated downloads of the same data can be avoided as much as possible. Accordingly, for the purpose of improving the efficiency of content sharing and decreasing the load on the eNB, it is important to maximize the number of simultaneous D2D transmissions.

Microscopic Properties of Hydrogen Peroxide Activated Crumb Rubber and Its Influence on the Rheological Properties of Crumb Rubber Modified Asphalt.

Crumb rubber modified (CRM) asphalt binder has been affirmed to improve resistance to rutting, moisture susceptibility, low-temperature cracking, and asphalt durability. However, CRM has poor compatibility with asphalt since crumb rubber molecules are vulcanized. The objective of this study was to develop a new method to prepare activated crumb rubber using hydrogen peroxide (HO) solution and to explore the rheological properties of HO activated CRM (ACRM) asphalt.

Catalytic micro-ozonation by FeO nanoparticles @ cow-dung ash for advanced treatment of biologically pre-treated leachate.

In this work, the biologically pre-treated leachate was subjected to catalytic micro-ozonation using cow-dung ash composites loaded with FeO nanoparticles (nano-FeO@CDA) as the catalyst. The optimal conditions used were nano-FeO@CDA dosage of 0.8 g/L, input ozone of 3.

Treatment of stabilized landfill leachate by Fenton-like process using FeO particles decorated Zr-pillared bentonite.

FeO particles decorated Zr pillared bentonite (FeO/Zr-B) were successfully synthesized, which were used to treat stabilized landfill leachate by Fenton-like process. The organics removal and biodegradability were both significantly improved owing to good catalytic stability of the magnetically recoverable catalyst. With the catalyst dosage of 1.

Fairness-Aware Resource Allocation in Multi-Hop Wireless Powered Communication Networks with User Cooperation.

In wireless powered communication networks (WPCNs), the harvested energy varies greatly among user nodes (UNs), resulting in throughput unfairness. Since the harvested energy is limited, each UN must strategically allocate the energy used for forwarding the other nodes’ information and for transmitting its own information, which further aggravates the global unfairness in terms of throughput. In this paper, we leverage user cooperation in multi-hop transmission to improve the throughput fairness.

DOMe: A deduplication optimization method for the NewSQL database backups.

Reducing duplicated data of database backups is an important application scenario for data deduplication technology. NewSQL is an emerging database system and is now being used more and more widely. NewSQL systems need to improve data reliability by periodically backing up in-memory data, resulting in a lot of duplicated data.