|
|
|
Muhammad Tayyab, Rana Ammar Aslam, Umar Farooq, Sikandar Ali, Shahbaz Nasir Khan, Mazhar Iqbal, Muhammad Imran Khan and Naeem Saddique
Groundwater Arsenic (As) data are often sparse and location-specific, making them insufficient to represent the heterogeneity in groundwater quality status at unsampled locations. Interpolation techniques have been used to map groundwater As data at unsa...
ver más
|
|
|
|
|
|
Xiaoyun Song, Heping Zheng, Lei Xu, Tingting Xu and Qiuyu Li
An investigation was carried out to study the influence of two types of anti-washout admixtures (AWAs) on the performance of underwater concrete, specifically, workability and washout resistance. The tested AWAs were hydroxypropyl methylcellulose (HPMC) ...
ver más
|
|
|
|
|
|
Enrique González-Núñez, Luis A. Trejo and Michael Kampouridis
This research aims at applying the Artificial Organic Network (AON), a nature-inspired, supervised, metaheuristic machine learning framework, to develop a new algorithm based on this machine learning class. The focus of the new algorithm is to model and ...
ver más
|
|
|
|
|
|
Thanda Shwe and Masayoshi Aritsugi
Intelligent applications in several areas increasingly rely on big data solutions to improve their efficiency, but the processing and management of big data incur high costs. Although cloud-computing-based big data management and processing offer a promi...
ver más
|
|
|
|
|
|
Max Käding and Steffen Marx
Acoustic emission monitoring (AEM) has emerged as an effective technique for detecting wire breaks resulting from, e.g., stress corrosion cracking, and its application on prestressed concrete bridges is increasing. The success of this monitoring measure ...
ver más
|
|
|