Drought Assessment Based on Fused Satellite and Station Precipitation Data: An Example from the Chengbi River Basin, China

Drought poses a significant constraint on economic development. Drought assessment using the standardized precipitation index (SPI) uses only precipitation data, eliminating other redundant and complex calculation processes. However, the sparse stations in southwest China and the lack of information on actual precipitation measurements make drought assessment highly dependent on satellite precipitation data whose accuracy cannot be guaranteed. Fortunately, the Chengbi River Basin in Baise City is rich in station precipitation data. In this paper, based on the evaluation of the accuracy of IMERG precipitation data, geographically weighted regression (GWR), geographic difference analysis (GDA), and cumulative distribution function (CDF) are used to fuse station precipitation data and IMERG precipitation data, and finally, the fused precipitation data with the highest accuracy are selected to evaluate the drought situation. The results indicate that the accuracy of IMERG precipitation data needs to be improved, and the quality of CDF-fused precipitation data is higher than the other two. The drought analysis indicated that the Chengbi River Basin is in a cyclical drought and flood situation, and from October to December 2014, the SPI was basically between +1 and −1, showing a spatial pattern of slight flooding, normal conditions, and slight drought.

Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm

In this paper, a new method in forecasting the horizontal displacement of diaphragm wall (D.W.) for high-rise buildings is introduced. A new stochastic optimizer, called Planet Optimization Algorithm (P.O.A.), is employed to assess how proper finite element (F.E.) simulation is against field data. The process is adopted for a real phased excavation measured at the field. To automatically run the iterative optimization tasks, a source code is constructed directly in the Geotechnical Engineering Software (PLAXIS) by using Python to ensure that the operation between optimization algorithm and F.E. simulations are smooth to guarantee the accuracy of the complex calculation for the soil problem. The proposed process consists of two steps. (1) The parameters will be optimized at the early phases of the excavation. (2) The responses of D.W. displacements are forecasted at the subsequent phases. The aim of the process is to predict the displacements of D.W. of the building from the result of the nearby excavation or to provide early warning about the risks of excavation that may happen under vital phases. The proposed procedure also provides an effective method for optimization-based soil parameters updating in real engineering practice.

A Biometric Recognition Method Using Deep CNN

Face is perhaps the first biometric trait of a person that catches one’s eye and it remains in memory for a long due to its uniqueness created by almighty. Recognizing a person using his/her face, is very natural to us and we do not need any special training for identification. But computers are programmed for analyzing things and making predictions almost in similar fashion that our brain does. Then, the recognition takes place by using some techniques and trainings. The recognition system which uses biometric properties is itself a secure and trusted technique but use of neural networks make it highly accurate and add more worth to it. A CNN model works in a fully supervised or guided environment and performs all the tasks in a robotic manner. The convolutional layer which lies in CNN model performs the complex calculation and extracts all the unique and useful features without any human involvement. I preferred to adopt Transfer learning in my work, by importing a pre-trained CNN model and I found 97.5% accuracy in recognition when I tested the model with my test samples. Keywords: Biometrics, Convolution, AlexNet, Feature Extraction, Transfer Learning

An Improved Estimation Algorithm of Space Targets Pose Based on Multi-Modal Feature Fusion

The traditional estimation methods of space targets pose are based on artificial features to match the transformation relationship between the image and the object model. With the explosion of deep learning technology, the approach based on deep neural networks (DNN) has significantly improved the performance of pose estimation. However, the current methods still have problems such as complex calculation, low accuracy, and poor real-time performance. Therefore, a new pose estimation algorithm is proposed in this paper. Firstly, the mask image of the target is obtained by the instance segmentation algorithm, and its point cloud image is obtained based on a depth map combined with camera parameters. Finally, the correlation among points is established to realize the prediction of pose based on multi-modal feature fusion. Experimental results in the YCB-Video dataset show that the proposed algorithm can recognize complex images at a speed of about 24 images per second with an accuracy of more than 80%. In conclusion, the proposed algorithm can realize fast pose estimation for complex stacked objects and has strong stability for different objects.

The influence of bottom-up anchors pre-tension optimization on the prediction of pit walls rockfall displacements

Introduction. Currently in Russia, innovations in urban subsoil facilities construction are among the key factors of economic development. To improve the efficiency of holding a pit wall in restraint urban conditions and prevent soil loosening around the pit, it is proposed to optimize the pre-tension forces of the bottom-up anchors. It has been determined that the pre-tension forces of the active anchors create extra retention forces in the sliding wedge and, in some specified sense, reinforce the walled soil. Research methodology. When modeling the complex calculation of a pit wall, 4 main stages of the pit excavation and 3 stages of preliminary level tensions of anchor ties were preset. The numerical solution of the beam bending problem is the basic method of calculating the walling strength; the beam laying on the elastoplastic base and retained by the anchors as bonds. The bottom-up anchor structure is modeled in the operating environment of GeoWall software. The values of bottom-up anchors pre-tension are set following the ordinates of forces in the anchors, obtained from the walling stability calculation by the deterministic approach. Experimental research was carried out of the impact made by pit opening stages on the walling stress strained state. Results. Analysis and discussion. The efficiency of bottom-up anchors optimal pre-tension, according to the research results, is obtained by constructing the diagrams reflecting the correlation dependence between the anchors loading and the walling displacement. An obvious advantage of the software is the opportunity to calculate walling and retaining structures stage by stage ignoring their construction technologies. Experimental calculation in GeoWall has shown a high bearing capacity of the bottom-up anchor support. Summary. The nature of the obtained dependence between the anchor longitudinal forces and the pit walling horizontal displacement reflects the actual situation. Thus, for a quiet expectable value of horizontal displacement, it is required to correct the optimal value of pre-tension using the empiricalformula dependences.

Reliability analysis method for redundancy systems based on GO methodology and the universal generation function

In this study, Goal-Oriented (GO) methodology, as an important technique for reliability analysis, is used in multi-state redundancy systems. However, traditional GO operation is usually not sufficiently effective for such multi-state redundancy systems because of the complex computational problem. To solve this problem, an efficient UGF-based GO operation that combines the advantages of GO methodology and the universal generation function (UGF) is proposed. The algorithm can avoid the complex calculation process caused by the algorithm-based GO operation of traditional probability formulas, and can simplify the correction of the shared signal by regarding it as the system’s conditional probability. In addition, the further correction problem in which some dependent shared signals with a common failure are caused by other shared signals is also considered. Some application examples are presented to illustrate the proposed UGF-based GO methodology, as well as its effectiveness and practicability.

Analytical model for estimating the production and composition of gas resulted through gasification

For the modelling of gasification processes, several models have been developed over the years. It is remarked that gasification calculation models of very high complexity entail some complications. Therefore, simpler mathematical representations of gasification characteristics and process behavior are required as a first step in addressing such systems. The preliminary calculation simplicity is needed form two perspectives: First – the pre-sizing of gasification installations, and second – the estimation of experimental or functional results. For this kind of topics, an adequate simplified model should be defined. Further, to validate the results it will be necessary to use complex calculation models. The model proposed in this paper addresses gasification with distributive air in the air distribution current, considering general concurrent flow of air fuel. Previous successful investigations, conducted by the present research team, are taken into account within model definition stages. Thus, the work presented here provides useful advances in the field of mathematical modeling of gasification processes. The originality of the model consists in its easy computational accessibility, which allows the approach of technological optimizations, such as the variation of excess air and fuel composition.

Development of NRU MPEI active energy complex calculation model

Implementation of AEC on the basis of the Moscow Power Engineering Institute is being solved. The paper considered the technical and economic conditions for the creation of AEC in the retail electricity (power) markets. Technological, organizational and economic systems of interaction between AEC participants formed on the grounds of the MPEI CHPP. To form a business model of AEC NRU MPEI functioning, an analysis of the energy consumption balance for consumers connected to the distribution networks of the MPEI CHPP was carried out as well as analysis of the technical and economic indicators of the MPEI CHPP operation. Through the research the possibilities of the AEC of NRU MPEI for payments to the unified energy system and economic efficiency of the AEC organization were assessed.

Performance Evaluation of Offline Motion Preparation Approaches on the Example of a Non-Linear Kinematics

In motion control, the generation of motion profiles for non-linear kinematics is usually computationally complex. In order to minimize the workload on the machine’s control system, the approach pursued is outsourcing complex calculation tasks to the offline area. In this offline motion preparation, predefined criteria have to be taken into account to guarantee process stability on the real machine. During the motion preparation, a high performance is desired, characterized by less data generated and at the same time little computing effort. The evaluation will use the example of a motion specification, which is characterized by a large amount of data compared to conventional motion specifications. Thus, the demands on performance become even higher. This paper examines the performance of different motion preparation approaches known from literature. On the one hand, selected spline-based algorithms are discussed and compared. A recursive algorithm based on monomial splines is recommended for use in the example. On the other hand, a very simple approach based on the linearization of the non-linear workspace of the mechanism is presented and applied on the algorithms. With this, the performance increased significantly again.