Estimation of Blast-Induced Air Overpressure in Quarry Mines Using Cubist-Based Genetic Algorithm

In the present work, blast-induced air overpressure is estimated by an innovative intelligence system based on the cubist algorithm (CA) and genetic algorithm (GA) with high accuracy, called GA–CA model. Herein, CA initialization model was developed first and the hyper-parameters of the CA model were selected randomly. Subsequently, the GA procedure was applied to perform a global search for the optimized values of the hyper-factors of the CA model. Root-mean-square error (RMSE) is utilized as a compatibility function to determine the optimal CA model with the lowest RMSE. Gaussian process (GP), conditional inference tree (CIT), principal component analysis (PCA), hybrid neural fuzzy inference system (HYFIS) and k-nearest neighbor (k-NN) models are also developed as the benchmark models in order to compare and analyze the quality of the proposed GA–CA algorithm; 164 blasting works were investigated at a quarry mine of Vietnam for this aim. The results revealed that GA significantly improved the performance of the CA model. Based on the statistical indices used for model assessment, the proposed GA–CA model was confirmed as the most superior model as compared to the other models (i.e., GP, CIT, HYFIS, PCA, k-NN). It can be applied as a robust soft computing tool for estimating blast-induced air overpressure.

     

A novel fuzzy <Emphasis Type="Italic">K</Emphasis>-nearest neighbor inference model with differential evolution for spatial prediction of rainfall-induced shallow landslides in a tropical hilly area using GIS

This research represents a novel soft computing approach that combines the fuzzy k-nearest neighbor algorithm (fuzzy k-NN) and the differential evolution (DE) optimization for spatial prediction of rainfall-induced shallow landslides at a tropical hilly area of Quy Hop, Vietnam. According to current literature, the fuzzy k-NN and the DE optimization are current state-of-the-art techniques in data mining that have not been used for prediction of landslide. First, a spatial database was constructed, including 129 landslide locations and 12 influencing factors, i.e., slope, slope length, aspect, curvature, valley depth, stream power index (SPI), sediment transport index (STI), topographic ruggedness index (TRI), topographic wetness index (TWI), Normalized Difference Vegetation Index (NDVI), lithology, and soil type. Second, 70 % landslide locations were randomly generated for building the landslide model whereas the remaining 30 % landslide locations was for validating the model. Third, to construct the landslide model, the DE optimization was used to search the optimal values for fuzzy strength (fs) and number of nearest neighbors (k) that are the two required parameters for the fuzzy k-NN. Then, the training process was performed to obtain the fuzzy k-NN model. Value of membership degree of the landslide class for each pixel was extracted to be used as landslide susceptibility index. Finally, the performance and prediction capability of the landslide model were assessed using classification accuracy, the area under the ROC curve (AUC), kappa statistics, and other evaluation metrics. The result shows that the fuzzy k-NN model has high performance in the training dataset (AUC?=?0.944) and validation dataset (AUC?=?0.841). The result was compared with those obtained from benchmark methods, support vector machines and J48 decision trees. Overall, the fuzzy k-NN model performs better than the support vector machines and the J48 decision trees models. Therefore, we conclude that the fuzzy k-NN model is a promising prediction tool that should be used for susceptibility mapping in landslide-prone areas.     

Apatite Reference Materials for SIMS Microanalysis of Isotopes and Trace Elements

Twelve apatite samples have been tested as secondary ion mass spectrometry (SIMS) reference materials. Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) analysis shows that the SLAP, NUAN and GR40 apatite gems are internally homogeneous, with most trace element mass fractions having 2 standard deviations (2s) ≤ 2.0%. BR2, BR5, OL2, AFG2 and AFB1, which have U > 63 μg g^-1, ²⁰⁶Pb/²⁰⁴Pb > 283, and homogeneous SIMS U-Pb data, have respective isotope dilution thermal ionisation mass spectrometry (ID-TIMS) ages of 2053.83 ± 0.21 Ma, 2040.34 ± 0.09 Ma, 868.87 ± 0.25 Ma, 478.71 ± 0.22 Ma and 473.25 ± 0.09 Ma. Minor U-Pb heterogeneity exists and accurate SIMS results require correction with the 3D Concordia-constrained common Pb composition. Among the studied samples, AFG2 and BR5 are the most homogeneous U-Pb reference materials. The SIMS sulfur isotopic compositions of eight of the apatites shows they are homogeneous, with 2s for both 10³δ³⁴S and 10³δ³³S < 0.55‰. One apatite, BR96, has Δ³³S = -0.36 ± 0.2‰. The apatite samples have ID-TIMS ⁸⁷Sr/⁸⁶Sr between 0.704214 ± 0.000030 and 0.723134 ± 0.000035.     

Simulation of mixed-mode fracture using SPH particles with an embedded fracture process zone

This paper focuses on the modelling of mixed-mode fracture using the conventional smoothed particle hydrodynamics (SPH) method and a mixed-mode cohesive fracture law embedded in the particles. The combination of conventional SPH and a mixed-mode cohesive model allows capturing fracture and separation under various loading conditions efficiently. The key advantage of this framework is its capability to represent complex fracture geometries by a set of cracked SPH particles, each of which can possess its own mixed-mode cohesive fracture with arbitrary orientations. Therefore, this can naturally capture complex fracture patterns without any predefined fracture topologies. Because a characteristic length scale related to the size of the fracture process zone is incorporated in the constitutive formulation, the proposed approach is independent from the spatial discretisation of the computational domain (or mesh independent). Furthermore, the anisotropic fracture responses of materials can be naturally captured thanks to the orientation of the fracture process zone embedded at the particle level. The performance of the proposed approach demonstrates its potentials in modelling mixed-mode fracture of rocks and similar quasi-brittle materials.     

Land cover and land use change related to shrimp farming in coastal areas of Quang Ninh,Vietnam using remotely sensed data

Rapid development of shrimp farming may lead to unrecognized and undesirable changes of land cover/land use patterns in coastal areas. Of special concern is the loss of mangrove forest in coastal areas such as Quang Ninh, Vietnam, which is adjacent to the World Heritage-listed Ha Long Bay. Understanding the status and changes of land cover/land use for coastal shrimp farms and mangrove forests can support environmental protection and decision-making for sustainable development in coastal areas. Within this context, this paper uses the 1999/2001 Landsat ETM+ and the 2008 ALOS AVNIR-2 imagery to investigate the contraction and expansion of shrimp farms and mangrove forests in coastal areas of Ha Long and Mong Cai, which now have a high concentration of intensive and semi-intensive shrimp farms. Images were separately analyzed and classified before using post-classification comparisons to detect land cover/land use changes in the study area. The results of this study found that the area of mangrove forest has been reduced by an estimated 927.5 ha in Ha Long and 1,144.4 ha in Mong Cai, while shrimp farming areas increased by an estimated 1,195.9 and 1,702.5 ha, respectively, over the same period. The majority of shrimp farms in Mong Cai were established at the expense of mangrove forest (49.4 %) while shrimp farms in Ha Long were mainly constructed on areas previously occupied by bare ground (46.5 %) and a significant proportion also replaced mangroves (23.9 %). The remarkable rate of mangrove loss and shrimp farming expansion detected in this study, over a relatively short time scale indicate that greater awareness of environmental impacts of shrimp farm expansion is required if this industry is to be sustainable, the important estuarine and coastal marine ecosystems are to be protected over the long term, and the capturing and storing of carbon in mangrove systems are to be enhanced for global climate change mitigation and for use as carbon offsets.     

Introduction to the China-Vietnam Cooperation Project: A Comparative Study of the Holocene Sedimentary Evolution of the Yangtze and Red River Deltas

Both China and Vietnam confront the challenges of natural geohazards and environmental changes in their deltas and coastal zones due to rapid urbanization, economic development, and the impacts of global climate change. China and Vietnam initiated a comparative study of the Holocene sedimentary evolution of the Yangtze River Delta(YRD) and Red River Delta(RRD) for the period 2015–2018 in order to improve the understanding of the two delta evolution histories in the Holocene. Previous investigative data of the two rivers, onshore delta plains, and offshore subaqueous deltas have been explored and reinterpreted. New data gleaned from boreholes, piston cores, shallow seismic and hydrodynamic sources have been collected from the offshore YRD and the East China Sea inner shelf, and surface sediments and short cores have been collected from the RRD near-shore areas. Six focal areas of the joint project have been defined for comparative studies of the two deltas, including morphological development, sequential stratigraphy, coastline shifting, sedimentary characteristics, sedimentary dynamics, and correlation with anthropogenic global climate change. The results of these study areas are presented herein. The joint project also includes cooperative capacity building; exchanges of young scientists have been organized during the project period, and hands-on training in laboratory geochemical analysis, numerical modeling, and seismic data processing and interpretation have been provided by China and its Vietnamese geoscientist partners. Joint field excursions were organized to the upstream of the Yangtze and Red Rivers in Yunan Province, China, all the way downstream along the Vietnamese portion of the Red River. These joint studies have, over the past three years, improved understanding of the evolutionary history of these two major rivers and their mechanisms of source to sink. Joint project results of these two major deltas are not limited to the geosciences; the cooperative mechanical and operational experiences have been helpful for future cooperation in the field of marine geoscience between China and Vietnam, as well for cooperative activities with other ASEAN member countries.     

Regional variations in trace element concentrations in tissues of black tiger shrimp Penaeus monodon (Decapoda: Penaeidae) from South Vietnam

The goal of the present study was to examine the specific bioaccumulation of 22 trace elements in muscle, exoskeleton and hepatopancreas of black tiger shrimp Penaeus monodon from the Mekong River Delta (MRD), and the South Key Economic Zone (SKEZ), South Vietnam. The general tendency in most trace element concentrations among different tissues were hepatopancreas>exoskeleton>muscle. Comparisons of trace element levels in tissues between the two regions showed that concentrations of Se in muscle and As in all three tissues were higher in SKEZ; whereas in MRD, the higher concentrations of most elements such as Mn, Cu, Cd, Ba, Hg, were observed in tissues. These geographical variations in trace element levels may reflect the differences in human activities between the two regions of South Vietnam. The target hazard quotient (THQ) values for trace elements (<1) indicate that local residents are not exposed to potential health risks via the consumption of shrimp.     

Influence of synoptic processes on the vietnamese current (the South China Sea) Dynamics during the Winter–Summer 1999 transition period

Demonstrated is an influence of synoptic processes on the seasonal dynamics of the Vietnamese Current in the South China Sea varying its direction under the influence of the monsoon. The spring season of 1999 is used as an example of the transition from the winter to summer. In winter, under the influence of the northeastern monsoon, the current is directed from north to south and in the summer, at the southwestern monsoon, in the opposite direction. In the spring, two zones of different water modification are formed: an impact is observed of both the leaving winter monsoon and the coming summer monsoon. Considered is an atmospheric process of low-gradient field type, when the pressure field is characterized by the low pressure gradient over the whole South China Sea. It is revealed that the Vietnamese Current moves in the summer regime (from south to north) in the northern and southern parts and keeps the winter regime (from north to south) in the central part.     

Hyper-parameter optimization of gradient boosters for flood susceptibility analysis

Properly choosing hyper-parameters improves machine learning models' performance and reduces training time and resource requirements. In this study, we investigated the uses of the Bayesian optimization algorithm for hyper-parameter searches of two classifiers, namely LightGBM and XGBoost. The models were verified with a dataset from Vietnam, including historical flood locations from satellite images and survey data, and 11 features from three groups, namely physical, hydrological, and human-related factors. The models' performance was evaluated using Area under Receiver Operating Characteristic curves (AUC-ROC). Several strategies were applied to avoid over-fitting, and the results show that two tuned Gradient boosters reached considerably high AUC values (approximately 0.98) compared with the previous study with a similar dataset. The model interpretation was also implemented using the Shapley (SHAP) values to understand better how models work and the interactions between features. The search for optimal hyper-parameters is worth investigating in the future, particularly when there is growing work for novel optimization algorithms. The verification of such an approach is scientifically sound, and the models can be used as an alternative solution for natural hazard analysis in countries prone to hazards.     

Distribution of eruptive volcanic basalt in the South China Sea and adjacent areas by interpreting gravity,magnetic and seismic data

Volcanic basalt eruption activity in the South China Sea and adjacent areas occurred strongly in Cenozoic E ra. However, it is difficult to define their ranges and spatial locations.This paper presents the methods of reduction to the magnetic equator in low latitudes to bring out a better correlation between magnetic anomalies and their causing-sources; high-frequency filtering is to separate gravity and magnetic anomalies as well as information about the volcanic basalts in the upper part of the Earth’s crust; 3D total gradient is to define the spatial location of high density and magnetic bodies. The distribution of eruptive volcanic basalt is determined by multi-dimensional correlation analysis between high frequency gravity and magnetic anomalies with weighted total gradient 3D.The results from the above-mentioned methods have shown that the distribution of the eruptive volcanic basalt is mainly concentrated along the South China Sea’s sea floor-spreading axis, transitional crust, Manila trench and some large faults zone. These results are improved by existing boreholes and seismic data in the study area.