Selected Reference Points Research Articles

Evaluation of Lithology Variations in Layered Red Beds with Depth: An Example of the Yellow River Guxian Dam, NW China

Abstract Lithology variations, which are recognized as rock type differences, significantly affect the physical properties of rock masses in red beds. In this paper, we introduce a statistical method for quantitatively evaluating the degree of lithology variations in layered red beds with depth. The core of this method is to use borehole logs as random variables for statistical analysis to calculate the percentage of a specified lithology at a given elevation, which involves seven steps of attitude calculation, reference point selection, distance calculation, elevation modification, data discretization, data statistics, and curve plotting. The Yellow River Guxian Dam is chosen as a field case study. We classify rock types of feldspar sandstone, fine sandstone, and conglomerate into hard rocks and that rock types of calcareous siltstone, argillaceous siltstone, and mudstone into soft rocks. Borehole logs recorded during the geological investigation are used to plot the percentage curve of hard rocks. We find that the degree of lithology variations for each lithology group differs greatly, the general behaviors of lithology variations on two sides of the Guxian Dam riverbed are quite similar but still with some differences, and that some thick lithology groups can be finely divided into several subgroups. On the basis of the hard rock percentage curve, we introduce a lithology variation index to quantitatively characterize the degree of lithology variations, which can be used as an important index to supplement the traditional methods when performing rock mass classifications in red beds. We also plot the trilithology percentage curve of sandstone, calcareous siltstone, and argillaceous siltstone, which serves for the determination of physical parameters of the dam foundation rock mass, the identification of the potential shear sliding surface, and the search for an impervious grouting bottom. Moreover, we find that the crest and trough, which are local high and low points in the hard rock percentage curve, can be used to show some characteristics of shear zones. The locations of shear zones are well represented in the form of troughs and that the development of shear zones has a good linear relationship with the hard rock percentage of the corresponding crest. The method proposed in this paper can be promoted and applied in similar projects or studies.

Optimization and Mechanism of the Wicket Gate Closing Law for High-Head Pumped Storage Power Stations

The high-head pumped storage power station (PSPS) has complex working conditions and severe transient processes. Under load rejection conditions, the turbine speed and the flow channel pressure will threaten the unit. By adjusting the wicket gate closing law (WGCL), we can effectively alleviate the adverse effects of the transient process. In this study, a full flow channel refined model of a high-head PSPS was constructed, and the influence mechanism of load rejection conditions on key parameters was analyzed by tracking the operating trajectory on the S characteristic curves and simulating the transient flow field inside the pumped turbine by three-dimensional computational fluid dynamics (3D-CFD). Given the contradiction between different parameters in the wicket gate closing process, a third-generation non-dominated genetic algorithm based on reference point selection (NSGA-III) was introduced, and a high-dimensional multi-objective WGCL optimization model was constructed. We compared parameter changes in the two-phase and three-phase WGCL optimized elite solutions and explained the rationality of adopting the three-phase WGCL in high-head PSPSs. By proposing an improved three-phase WGCL, a new scheme—the most suitable WGCL under load rejection—was obtained through precise optimization. The research embodied the excellent effect of the heuristic multi-objective (MO) optimization algorithm based on the Pareto strategy in solving the operation problem of the large fluctuation transient process of hydraulic machinery. It revealed the theoretical basis of engineering adjustment for the safe production and operation of hydropower.

A Modified Manta Ray Foraging Optimization for Global Optimization Problems

The Manta ray foraging optimization (MRFO) is a novel swarm-based metaheuristic optimizer. It is mainly modeled by simulating three foraging behaviors of the Manta rays, which has a good performance. However, several drawbacks of MRFO have been noticed by analyzing its mathematical model. Random selection of reference points in the early iterations weakens the exploitation capability of MRFO. Chain foraging tends to lead the algorithm into local optimum. In addition, the algorithm suffers from the deficiency of decreasing population diversity in the late iteration. To address these shortcomings, a modified MRFO using three strategies, called m-MRFO, is proposed in this paper. An elite search pool (ESP) is established in this paper to enhance exploitation capability. By using adaptive control parameter strategies (ACP), we expand the range of MRFO’s exploration in the early iterations and enhance the accuracy of exploitation in the later iterations, balancing exploiting and exploring capabilities. Furthermore, we use a distribution estimation strategy (DES) to adjust the evolutionary direction using the dominant population information to promote convergence. The m-MRFO performance was verified by selecting 23 classical test functions and CEC2017 test suite. The significance of the results was also verified by Friedman test, Wilcoxon test and Iman-Davenport test. Moreover, we have confirmed the potential of m-MRFO to solve real-world problems by solving three engineering design problems. The simulation results show that the improvement strategy proposed in this paper can effectively improve the performance of MRFO. m-MRFO is highly competitive.

An Improved Weighted K-Nearest Neighbor Algorithm for Indoor Localization

The weighted K-nearest neighbor (WKNN) algorithm is the most commonly used algorithm for indoor localization. Traditional WKNN algorithms adopt received signal strength (RSS) spatial distance (usually Euclidean distance and Manhattan distance) to select reference points (RPs) for position determination. It may lead to inaccurate position estimation because the relationship of received signal strength and distance is exponential. To improve the position accuracy, this paper proposes an improved weighted K-nearest neighbor algorithm. The spatial distance and physical distance of RSS are used for RP selection, and a fusion weighted algorithm based on these two distances is used for position calculation. The experimental results demonstrate that the proposed algorithm outperforms traditional algorithms, such as K-nearest neighbor (KNN), Euclidean distance-based WKNN (E-WKNN), and physical distance-based WKNN (P-WKNN). Compared with the KNN, E-WKNN, and P-WKNN algorithms, the positioning accuracy of the proposed method is improved by about 29.4%, 23.5%, and 20.7%, respectively. Compared with some recently improved WKNN algorithms, our proposed algorithm can also obtain a better positioning performance.

Near-to-node modal identification using multiple related response models

Experimental modal analysis (EMA) is a well-established procedure for determining the modal parameters of a structure. Typically, a point-force is used to excite the structure and the translational response is measured. When performing an EMA, problems with a reliable modal-parameter estimation can arise whenever a selected reference point is located in the proximity of a node for any mode shape in interest. This problem can be addressed by performing multi-reference measurements; however, a non-coincidental position with respect to the remaining nodes cannot be guaranteed. In this research a novel modal-identification method, based on multiple related experimental response models at a single reference point, is proposed as an alternative to the established multi-reference measurement. The idea is to combine multiple response models of the same structure, acquired by different types of sensors (e.g., translational and rotational) for which the nodes of the response-related modal shapes do not coincide. The Least-Squares Frequency-Domain (LSFD) method is modified by considering the mutual relations of the acquired response models. The proposed methodology is experimentally validated on a homogeneous aluminum beam. The proposed method shows both a successful modal identification and an increased consistency of the identified modal constants, despite the proximity of the nodes to the selected reference point.

Fast calculation of high-definition depth-added computer-generated holographic stereogram by spectrum-domain look-up table [Invited

High-definition depth-added computer-generated holographic stereogram (DA-CGHS) is superior in its high quality, easy realization, and auto-shading effect. However, its computing cost is extremely high because numerous scenes together with depth information must be calculated. Here, we proposed a fast calculation scheme of DA-CGHS by the spectrum-domain look-up table (SDLUT) method. In SDLUT, diffraction fields on the hogel plane of selected reference points in the object space are calculated. Subsequently, the fields are Fourier transformed to the spectrum domain. Because the signal energy always concentrates in a small spectrum region, these regions are cropped as the elemental tables. In the computing of the hogels, the field superposition is conducted in the spectrum domain by using the elemental tables. In our demonstration, the table size of SDLUT is only 0.44% that of the look-up table (LUT). Because the table size is very small, the computing time of SDLUT method can be nearly 80 times faster than that of conventional LUTs in the spatial domain, while the image quality is comparable.

Variation Of Rotation In Chaos Game By Modifying The Rules

<span>The core concept of fractals is the process of rearranging identical components that have a large amount of self-similarity. One example of fractals is the Sierpinski trianglecan be generated using the chaos game method. This method is a form of play in drawing points on triangles that have certain rules and are repeated iteratively. This research will modify the rules of chaos game triangle with the addition of various rotationswith the center of rotation at one, two, three, four, and five reference points. The visual results obtained are in the form of fractals because they have self-similarity properties and a collection of new points formed experiences rotation with the center of rotation based on the selected reference point with the direction of rotation based on the rules. The visual results of the rotation </span><span>θ</span><span> angle are visually symmetrical about the axis-y with the visual results of the rotation 360</span><span>⁰</span><span>-</span><span>θ</span><span> angle at one, three, four, and five reference points as the center of rotation. At two reference points as the center of rotation it is obtained that there are two parts that are visually symmetrical about a certain line. Visual results of rotation 360</span><span>⁰</span><span> angles at one, two, three reference points as the center of rotation have a shape similar to the Sierpinski triangle. Whereas at four and five points of reference as the center of rotation has a shape similar to the Sierpinski triangle.</span>

Technological Features of Forming Flat Tool for Processing Axicons

It has been substantiated that in order to control the process of forming flat surfaces while using a free grinding method it is advisable to choose such machine setup parameters as a tool diameter and its rotation frequency, an amplitude of the reciprocating movement of the part along the tool (or vice versa) and frequency of this movement, as well as the value of the working force. Mathematical modeling of patterns for abrasive processing of flat surfaces in the conditions of free grinding on lever machines has been carried out in the paper. A formula has been obtained for calculating a sliding speed at selected reference points on the surface to be treated while taking into account the pressure in their vicinity. Patterns of the part operation have been determined, for which a correct plate is used in the proposed axicon production technology with due account of the combination and size of the selected setup parameters for processing equipment. Self-organization of the processing process has been substantiated while using a free grinding method. Sensitivity of a kinematic response to a change in processing modes and efficiency of these modes in terms of process performance have been determined in the paper. It has been noted that an increase in a tool diameter, as one of the effective adjustment parameters for controlling the shaping process, is difficult to implement in practice, since this requires replacement of tools, each of which must be pre-configured while using a special rather time-consuming technique. The paper reveals that with an increase in the tool rotation frequency and an amplitude of its oscillatory movements, there is an increased removal of material on the periphery of the surface being machined, and with an increase in vibrational movements, on the contrary, the central zone of the part is more intensively activated.

Assessment on ecological integrity of typical lakes, reservoirs and wetlands in Tianjin, China

The ecological health assessment of lakes, reservoirs and wetlands can provide decision-making basis for ecosystem restoration and management. We selected 20 typical lakes, reservoirs and wetlands sampling points in Tianjin, based on physical, chemical, and biological community indicators data (zooplankton, phytoplankton, benthos, fish, large aquatic plants, riparian plants) obtained during the survey from August to September 2018. We constructed an index of ecological integrity (IEI) including physical integrity, chemical integrity, and biological integrity to evaluate their ecological health. The reference points were selected based on three aspects using standardized methods: habitat environmental quality index (QHEI), water quality status, and disturbance of human activities. The analytic hierarchy process was used to calculate the weight of the three indicators. The evaluation results of the ecological integrity of typical lakes, reservoirs and wetlands in Tianjin were finally obtained. The results showed that: 1) Among all the samples, "healthy" points accounted for 5.0%, "good" points accounted for 20.0%, "general" points accounted for 35.0%, "worse" points accounted for 30.0%, and "poor" points accounted for 10.0%. Ecological health status of typical lakes, reservoirs and wetlands in Tianjin was at a general level, with a trend that the west was better than the east with significant spatial differences. 2) Reference points were selected based on the combination of habitat score, water quality conditions, and human activity disturbance. Water quality indicators could reduce subjectivity when selecting reference points and promote the application of ecological integrity evaluation. 3) The applicability verification results showed that IEI could better characterize the health status of each point, and the discrimination efficiency was obvious, which was suitable for evaluating the ecological health of lakes, reservoirs and wetlands.

Impact of Implementing a Deodorization System on the Functioning of a Waste Management Plant

This article is an analysis of the impact of implementing technical and technological solutions in the form of a deodorization system, which was carried out on the basis of a case study in the years 2015 and 2019 of an existing waste management plant named located in the region of Lower Silesia. The method for determining the impact was based on an analytical method for estimating changes in plant operation parameters in relation to the emission of odor compounds, determined at selected reference points, during a period of normal operation before and directly after the implementation of the deodorization system. The purpose of this work is the evaluation of the impact of the deodorization system on the parameters determining the functioning of the plant—a mechanical-biological waste treatment facility in order to determine sustainability factors and their relative changes.

An Improved Fingerprint Algorithm with Access Point Selection and Reference Point Selection Strategies for Indoor Positioning

The fingerprint positioning (FP) algorithm has been investigated extensively owing to the fact that it can provide a relatively ideal indoor positioning result. However, the effectiveness of the fingerprint algorithm relies on the size of fingerprint database, which prevents the algorithm from being widely applied in practical applications. In this paper, an improved fingerprint algorithm with access point (AP) selection strategy and reference point (RP) selection strategy is proposed to reduce the size of the fingerprint database and improve the positioning accuracy. The experimental results show that the proposed algorithm can reduce the storage size of the fingerprint database by more than 42·64%. Moreover, compared with the FP algorithm, the fingerprint algorithm with segment characteristic distance (FP-SCD) and the fingerprint algorithm with RP selection strategy (FP-RPSS), the average positioning error of the proposed algorithm is reduced by 20·15%, 10·83% and 11·57%, respectively. Therefore, the proposed algorithm has a good application in real positioning scenarios.

A new perspective for Minimal Learning Machines: A lightweight approach

This paper introduces a new procedure to train Minimal Learning Machines (MLM) for regression tasks. Besides that, we propose a new prediction process in MLM. A well-known drawback concerning the (original) MLM model formulation is the lack of sparseness.The most recent efforts on this problem strongly rely on the selection of reference points before training and prediction steps in MLM, all based on some supposition regarding the data. In the opposite direction, here, we explore another formulation of MLM in which we do not rely on any assumption regarding the data for prior selection. Instead, our proposal, named Lightweight Minimal Learning Machine (LW-MLM), builds a regularized system that imposes sparseness. We thrive in such a sparse criterion, not by selection but instead using a piece of weighted information into the model. We validate the contributions of this paper through four types of experiments to evaluate different aspects of our proposal: the prediction error performance, the goodness-of-fit of estimated vs. measured values, the norm values which are related to the sparsity, and finally, the prediction error in high dimensional settings. Based on the results, we show that LW-MLM is a valid alternative since achieved similar or higher accuracy rates against other variants being all seen as statistically equivalent.

The Potential Use of Ground Conductivity Meters to Identify the Location of Seepages—Case Study of the Maniów Levee near Krakow, Poland

This paper presents an assessment of the potential usefulness of the Ground Conductivity Meter (GCM) method to locate seepage pathways in the Maniow levee zone near Kraków, Poland. We have realized this aim through geological recognition of the study area, which requires the implementation of GCM data inversion measured in the sounding version. The GCM measurements were performed along with the net of profiles using combined data from CMD Mini Explorer and CMD Explorer equipment. The methodology of the one-dimensional (1D) inversion of the GCM soundings located along profiles is presented in the article. The legitimacy of the inversion and the relationship of the results obtained in the form of conductivity sections along profiles with geology have been verified in detail. The inversion procedures were tested on the synthetic GCM soundings obtained from modeling processes, by using the electrical conductivity and thicknesses, known from the drilled formations and additionally based on DC-R sounding data. These soundings were performed at some selected reference points in the levee zone. We have used our software and IX1D Interpex software to calculate the forward modeling. Quantitative interpretation processed along the profiles has been proceeded by 1D inversion of GCM data at several referential points located close to boreholes and DC soundings. It was done to verify the correctness of the quantitative interpretation. The geoelectrical models, obtained in a section form, were correlated with the borehole lithology data, providing a reference geological structure in some places. As a result of the work mentioned above, the potential seepage zones were located on the conductivity sections. The thickness of the cohesive silty clay layer, lying near to the surface, in the seepage zones, was thin enough and less than a meter. When the water level in the Vistula river was high enough, water can flow in the noncohesive gravel layer occurring directly below the silty clays and lead to flooding on the landward side of the dams in the Maniow region.

Profile optimization of the impeller blade of a low-speed centrifugal pump using surrogate modeling

This article presents an alternative approach to optimizing the profile of the impeller blade of a centrifugal pump. The researches were carried out using modern methods of computational fluid dynamics and the ANSYS CFX software package. The target of optimization is to maximize hydraulic efficiency and head. The calculated variables were selected using the Bezier biquadratic curve, and calculation experiments were used to select reference points from the projected space. Particular attention is paid to the construction of a surrogate RSA model, which is used in numerical simulation. To study the optimal points, the NSGA-II genetic algorithm was used. In a process of processing the results, a standard response surface with a second-order polynomial was formed to predict integral parameters. It is concluded that the main problem associated with the optimization of design based on a surrogate model is the accuracy of modeling the approximation functions. Also, the use of several surrogates can increase the reliability of optimization with minimal computational costs.

Robust Tracking for Small Target Groups With Dynamic Outlines

Low altitude small target group has the special motion characteristics of orderly as a whole and flexibly as individuals. The performances of traditional target tracking algorithms (such as centroid tracking, geometric centre tracking, etc.) decrease obviously when the group outline changes. Hence in this paper, a robust tracking algorithm for target group with dynamic outline is studied. Aiming at the two key issues of group division and equivalent tracking point estimation, a robust group division algorithm, which can maintain the stability of group division results under any reference point selection, is firstly introduced. Then, on this basis, a new optimal tracking point estimation method is proposed by introducing the group structure into the likelihood function. The simulation results show that this proposed method can effectively improve the robustness of low altitude small target group tracking in the scene of group merging and group splitting.

Finding K Most Significant Motifs in Big Time Series Data

Abstract An efficient discovery algorithm of frequently occurring patterns, called motifs, in a time series would be useful as a tool for summarizing and visualizing big time series databases. In this paper, we propose an efficient approximate algorithm, called DiscMotifs, to discover the K most significant (KMS) motifs from time series. First, the proposed algorithm transforms the time series into a SAX representation and then the algorithm divides the SAX representation into subsequences. Next, these subsequences are linearized by projecting them into a one-dimensional space based on their distances form a randomly selected reference point, or a subsequence. By utilizing the linear ordering of subsequences, DiscMotifs efficiently discovers the KMS motifs. DiscMotifs algorithm requires a storage space linear to the number of subsequences. We demonstrate the feasibility of this approach on several synthetic and real application datasets.

Impact of reference point selection on DXA-based measurement of forearm bone mineral density.

Forearm fractures are clinically important outcomes from the perspective of morbidity, health care costs, and interruption of work. BMD of the forearm, as derived by dual-energy x-ray absorptiometry (DXA), is a better predictor of fracture at the forearm compared with BMD measured at other sites. However, very few studies have evaluated the technical aspects of selecting the ROI for forearm BMD measurement. This study aimed to compare the BMD values measured at the 1/3 radius site using three different reference points: the ulnar styloid process, the radial endplate, and the bifurcation of the ulna and radius. Healthy Chinese patients participating in the control group of an ongoing study at Zhejiang Provincial People's Hospital were recruited for this study. For each patient, a DXA scan (GE Lunar Prodigy) of the forearm was performed and BMD values were separately calculated using each of the three reference points to identify the ROI. Pearson correlation coefficients were calculated to examine the correlation between the BMD measures derived from each reference point. The F test and independent t test were applied for more robust analysis of the differences in the variances and means. Sixty-eight healthy Chinese volunteers agreed to participate in this study. The root mean square standard deviation (RMS-SD) percentages of BMD values measured at the 1/3 radius site were 2.19%, 2.23%, and 2.20% when using the ulnar styloid process, radial endplate, and the bifurcation of the ulna and radius as the reference points, respectively. Pearson's correlation coefficients for all pairwise comparisons among these three groups were greater than 0.99. F tests and independent t tests showed p values ranging from 0.92 to 0.99. However, we observed that among 10% of patients, choosing an ROI at the ulnar styloid process led to an inability to accurately determine the BMD at the ultra-distal radius. Given equal ability to determine BMD at the 1/3 radius accurately, the radial endplate or the bifurcation of the ulna and radius should be preferentially selected as the reference point for routine forearm BMD measurements in order to avoid situations in which the ultra-distal radius BMD cannot be determined.

Reference points for the length-based indicator Lmax5% for use in the assessment of data-limited stocks

Abstract In the absence of abundance indices from scientific surveys or commercial sources, reliable length frequency data from sampled commercial catches can be used to provide an indirect assessment of fishing mortality. Length-based indicators are simple metrics which describe length frequency distributions. The length-based indicator Lmax5%, the mean length of the largest 5% of individuals in the catch, combined with appropriately selected reference points, can be used to evaluate the presence of very large individuals in the catch and hence determine exploitation level. Using analytical per-recruit models, we derive reference points consistent with a spawning potential ratio of 40%. The reference points depend on the life history parameters for natural mortality, maturity, and growth (M, Lmat, L∞, k, CVL∞). Using available simulation tools, we investigate the sensitivity of the reference points to errors in these parameters and explore the usefulness of particular reference points for management purposes for stocks with different life histories. The proposed reference points are robust to uncertainty in length at first capture, Lc, and take into account the maturation schedule of a species. For those stocks with high M/k ratios (>1), Lmax5%, combined with the appropriate reference point, can be used to provide a data-limited stock assessment.

Boundary shapes guide selection of reference points in goal localization.

In this study, we contrasted two hypotheses theorizing the role of the global shape of a boundary in object location memory: People might differentiate reference points based on the global shape extracted from the environment configuration and choose appropriate parts for encoding a specific location, or, alternatively, only the number of reference points provided by a shape might be important for accurate encoding. We designed a location memory task in an immersive virtual environment in order to examine these two hypotheses. Participants first learned four target locations with a circular wall and a landmark array. During testing, participants recalled the locations with either one entire cue or part of one cue removed. Location memory was impaired when the testing cues did not form a circle, but it was not impaired when the testing configuration retained the circular shape. In Experiment 2, the circle formed by a landmark array and the circular wall did not share the same center during learning. Memory performance decreased when either the wall or the landmark array was removed during testing. These results indicated that participants might segment the shape of the circular wall into parts (similar to segmenting a clock face into 12 hours) and encode target locations relative to the differentiated parts. When such segmentation could be recovered from the testing configuration, object location memory was retained. Otherwise, impairment occurred during testing. These findings suggest that although the individual reference points on a boundary are important for encoding specific target locations, the global shape of the boundary nonetheless affects segmentation and the selection of individual reference points.

The effects of cue placement on the relative dominance of boundaries and landmark arrays in goal localization.

Two types of visual features are identified as reference points used by individuals to encode locations: surface-based boundaries and discrete-object-based landmarks. Previous research show that learning locations relative to a boundary can overshadow learning relative to a landmark, but not vice versa, suggesting that environmental boundaries play a privileged role in representing individual locations. However, other research has revealed that a less accurate cognitive map is derived from boundary-related learning than from landmark-related learning, suggesting that a boundary is less privileged in representing inter-location spatial relations. The current study aims to reconcile these inconsistent findings. Experiment 1, using both a cue-competition paradigm and a cognitive mapping task, replicated the finding that participants preferred a circular boundary to a four-landmark array for encoding four locations (1A), but that the cognitive maps of the locations derived from the landmark array were more accurate (1B). Using the cue-competition paradigm, Experiments 2-4 manipulated the placement and distinctiveness of the two cues. The results showed that manipulating the placement of the landmark array effectively modulated the relative reliance upon the boundary/landmark-array in encoding individual location. Whereas increasing the distinctiveness of the landmark-array alone is not sufficient to eliminate the boundary advantage in localization. We propose that the boundary privilege occurs in selecting reference points for encoding locations due to its relative peripheral placement in the environment, whereas the landmark advantage occurs in inferring inter-location spatial relations due to the common reference point provided by the single landmark.