Index Structure Research Articles

Seeing and turbulence profile simulations over complex terrain at the Thai National Observatory using a chemistry-coupled regional forecasting model

Abstract This study utilized advanced numerical simulations with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to predict anticipated astronomical seeing conditions at the Thai National Observatory (TNO). The study evaluated the effects of both gas-phase and aerosol-phase chemical processes in the Earth’s atmosphere, along with the impact of spatial and temporal resolution on model performance. These simulations were validated against measurements from the Differential Image Motion Monitor (DIMM) and the Slope Detection and Ranging (SLODAR) technique. Due to the inherent temporal variability of the DIMM observations, a 24-h moving average window was applied to both DIMM data and WRF-Chem model outputs. This reduced the percentage root-mean-square error in the comparison between the two data sets from 23 per cent to 11 per cent and increased the correlation coefficient from 0.21 to 0.59. Chemistry played a minor role during the study period, contributing 3.49 per cent to astronomical seeing. However, it did affect the model’s accuracy. Additionally, the study revealed that higher spatial and temporal resolution simulations did not necessarily improve the model’s accuracy. When compared to SLODAR observations of the refractive index structure constant (Cn2dh), the simulations captured altitude variations within ±25 per cent above 5 km and 25–50 per cent below 5 km. Dome seeing also played a role, contributing to around 90 per cent or more in the lowest altitude layer. The results emphasized the significance of seeing predictions in providing valuable insights into complex atmospheric phenomena and how to mitigate the effects of atmospheric turbulence on telescopes.

EXPERIMENTING TIN DATA STRUCTURE FOR REPRESENTING PLANE SURFACE AND SUBSURFACE SPATIAL OBJECTS - PRELIMINARY WORK

Abstract. Understanding and analyzing complex spatial objects involves the integration of surface, terrain, and subsurface data into 3D spatial models. However, describing and efficiently analyzing the connections between these data model is particularly challenging. This study aims to generate TIN data structure that enable the 3D representation of surface terrain subsurface integration. Furthermore, to ensure accurate representation within a unified 3D model, spatial relationships between the TIN data model could be obtained. Consequently, three – dimensional Triangular Irregular Networks (3D TIN) mesh of spatial objects representations and indexing structures were created. The integration of spatial objects, encompassing surface, terrain, and subsurface elements, is realized through a unified model. This synergy is achieved by combining the distinct 2D and 3D topology structures of each component. The resulting comprehensive model captures the intricate relationships and interactions within the spatial environment. This study provides additional insight into the representation and analysis of surface, terrain, and subsurface management in 3D spatial models. Hence, better decision making, resource management, underground utility installations, and evaluation of spatial objects will be made possible in our future work.

Equalization system of low differential mode delay few-mode fibers based on the neural network MIMO algorithm.

In recent years, with the development of information networks, higher requirements for transmission capacity have been recommended. Yet, at the same time, the capacity of single-mode fiber is rapidly approaching the theoretical limit. The multidimensional multiplexing technique is an effective way to solve this problem. Since the high differential mode delay (DMD) of transmission fiber increases the complexity of demultiplexing in equalization algorithms, we use an intelligent design method to optimize the trench-assisted gradient refractive index structure in this paper. The maximum DMD of the optimized optical fiber structure is 19.6 ps/km. A least mean squares-feedforward neural network constant modulus algorithm (LMS-FNNCMA) is also designed by using the theory of the least mean squares (LMS), constant modulus algorithm (CMA), and the multiple input multiple output (MIMO) neural networks. In order to verify the accuracy of the algorithm, a polarization division multiplexing-wavelength division multiplexing-mode division multiplexing (PDM-WDM-MDM) optical transmission system is constructed through simulation. The algorithm successfully realizes the de-crosstalk over a transmission distance of 1200 km at a rate of 1.2 Tbps under simulation conditions.

Single star SCIDAR: Atmospheric parameters profiling using the power spectrum of scintillation

Optical parameters of atmospheric turbulence have a significant impact on high angular resolution, adaptive optics, and site testing. The single star SCIDAR technique provides vertical profiles of these parameters, including the refractive index structure constant Cn2(h). Its is based on the analysis of single stars scintillation. This study introduces a new approach for real-time measurement of atmospheric parameters using the Single Star SCIDAR. The key element of this approach is the utilization of a modified power spectrum of atmospheric speckles, that have more significant variation with altitude. By using that modified power spectrum, an objective function is computed, and the minimization process is performed using the Active-Set algorithm. With this approach, we successfully obtained real-time vertical profiles of Cn2(h) with good accuracy. The processing takes approximately 3 s per profile, and the recovery rate (i.e. sum of Cn2(h)) is about 95%. The reliability of this approach is validated through simulation results and a comparison with data obtained from sounding balloons. These validations confirm the accuracy and credibility of this method, which can be useful in many practical applications.

A fast DBSCAN algorithm using a bi-directional HNSW index structure for big data

A fast DBSCAN algorithm using a bi-directional HNSW index structure for big data

Combining Cn2 models to forecast the optical turbulence at Paranal

ABSTRACT We applied a combination of models to improve the forecasts of refractive index structure coefficient ($C^{2}_{n}$) profiles and seeing at Paranal using high-temporal and spatial resolution simulations with the Weather Research and Forecasting model. We assessed our method with Stereo−SCIntillation Detection And Ranging observations from several nights between 2016 and 2018. The combined approach consists of the turbulent kinetic energy-based model to estimate the $C^{2}_{n}$ profile within the boundary layer and another model for the free atmosphere. We tested the Dewan, Jackson−Dewan, and Gladstone models. The implementation of the combined method gives better results than those obtained using each model separately for the whole atmospheric column. However, a much better agreement with observations is obtained when we use a calibration method to improve the results. Calibrated seeing forecasts at Paranal showed a root mean squared error of 0.30 arcsec and a bias around −0.1 arcsec for all the nights of 2017 and 2018, which are similar to previous results obtained at Paranal during the same nights. Due to its performance and rapid execution, the proposed methodology could be implemented as an operational tool to forecast the $C^{2}_{n}$ profiles and the seeing at Paranal and potentially over other astronomical sites around the world.

Development and validation of the adolescent behavioural change Counselling Assessment Tool in Indonesia

BackgroundPrimary care provides an important context to engage adolescents and their families in healthy lifestyles with the goal of reducing future behaviour-related health problems. Developing a valid tool to assess health professionals’ skills in behavioural change counselling is integral to improving the quality of clinical care provided to adolescents in Indonesia.MethodsThis work was nested within a project to develop a training program to enhance the behaviour-change counselling of adolescents and their parents by Indonesian primary care professionals. Initial item development was based on the content of the training module and the domain structure of the Behavioral Change Counselling Index (BECCI), a commonly used tool to assess counselling quality in healthcare settings. Expert panels were used to test content validity, while face validity was assessed by a group of trained psychologists. Inter-rater agreement was calculated prior to tests of construct validity and reliability, which involved psychologists rating 125 audio-taped counselling sessions between the health professional and adolescent patients, together with a parent.ResultsAn initial 13-item tool was developed using a 1–5 Likert scale. Validity and reliability testing resulted in the decision to use a 14-item tool with a 0–3 Likert scale. The scale was found to have a Cronbach’s α coefficient of 0.839 (internal consistency), and there was strong inter-rater agreement (0.931).ConclusionThe assessment tool known as the Adolescent Behavioural Change Counselling Assessment Tool, is a valid and reliable instrument to measure Indonesian health professionals’ behavioural-change counselling skills with adolescent patients. The tool provides an evaluation framework for future interventions that aim to improve health professionals’ skills in addressing adolescent behaviour-related health problems.

Azerbaijani adaptation of the WHO-5 wellbeing index: investigating its relationship with psychological distress, resilience, and life satisfaction.

The WHO-5 Wellbeing Index is a widely used tool for assessing psychological well-being. Despite its global application, its adaptation and validation for the Azerbaijani population had not been previously explored. This study aims to fill this gap by adapting the WHO-5 Wellbeing Index for Azerbaijani adults and examining its relationship with psychological distress, resilience, and life satisfaction. A sample of 875 Azerbaijani adults aged 18 to 89 (mean age = 29.13, SD = 10.98) participated in this study. The adaptation process included confirmatory factor analysis to test the original 5-item structure of the index in the Azerbaijani context. Additionally, item response theory analysis was employed to evaluate the discriminative values of the items. Reliability was assessed through various methods, including Cronbach's alpha, McDonald's omega, and Guttmann's lambda. Confirmatory factor analysis supported the original 5-item structure of the WHO-5 Wellbeing Index for the Azerbaijani sample, demonstrating alignment with the index's original version. All items showed acceptable discriminative values in item response theory analysis. The index also exhibited sufficient reliability, as evidenced by Cronbach's alpha, McDonald's omega, and Guttmann's lambda. Correlation and network analyses indicated significant associations of the WHO-5 Wellbeing Index with psychological distress, resilience, and life satisfaction. Specifically, the index was negatively correlated with depression, anxiety, and stress, and positively correlated with resilience and life satisfaction. The findings suggest that the WHO-5 Wellbeing Index is a valid and reliable tool for assessing psychological well-being in the Azerbaijani population. Its significant associations with psychological distress, resilience, and life satisfaction further affirm its utility in this cultural context.

MnO2-based dual channel surface plasmon resonance fiber sensor for trace glutathione and refractive index detection.

Glutathione (GSH) plays vital role in human biological systems, so its rapid and sensitive detection is necessary for health condition monitoring. In this work, a simple structure for dual channel GSH and refractive index (RI) detection is proposed. By introducing Au-MnO2 thin film coating on the fiber surface for the first time, GSH solution would lead to the dissolution of MnO2, the change in GSH levels could be monitored over a short period in channel 2. For channel 1, ITO-Ag thin film is applied for RI change detection. After optimization, the GSH detection sensitivity reached about -2.361 nm/mM in the range of 0.005-50 mM, and the RI sensitivity reached 1704.252 nm/RIU in the range of 1.331-1.3895 RIU. Channel 1 could also put into GSH detection in the high concentration scale to enlarge the sensor's range and 0.095 nm/mM of sensitivity is acquired within the range of 50-600 mM. With the presence of MnO2 film, the detection sensitivity increased 25.663 times. Neither channel interferes with the operation of the other. Proposed sensor provides stability, high selectivity and elevation in GSH detection sensitivity, which shows great potential for environmental and biological detection field and their applications.

Perseid: A Secondary Indexing Mechanism for LSM-Based Storage Systems

LSM-based storage systems are widely used for superior write performance on block devices. However, they currently fail to efficiently support secondary indexing, since a secondary index query operation usually needs to retrieve multiple small values, which scatter in multiple LSM components. In this work, we revisit secondary indexing in LSM-based storage systems with byte-addressable persistent memory (PM). Existing PM-based indexes are not directly competent for efficient secondary indexing. We propose Perseid , an efficient PM-based secondary indexing mechanism for LSM-based storage systems, which takes into account both characteristics of PM and secondary indexing. Perseid consists of (1) a specifically designed secondary index structure that achieves high-performance insertion and query, (2) a lightweight hybrid PM-DRAM and hash-based validation approach to filter out obsolete values with subtle overhead, and (3) two adapted optimizations on primary table searching issued from secondary indexes to accelerate non-index-only queries. Our evaluation shows that Perseid outperforms existing PM-based indexes by 3–7× and achieves about two orders of magnitude performance of state-of-the-art LSM-based secondary indexing techniques even if on PM instead of disks.

Ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)

Abstract. Statistical bias adjustment is commonly applied to climate models before using their results in impact studies. However, different methods based on a distributional mapping between observational and model data can change the simulated trends as well as the spatiotemporal and inter-variable consistency of the model, and are prone to misuse if not evaluated thoroughly. Despite the importance of these fundamental issues, researchers who apply bias adjustment currently do not have the tools at hand to compare different methods or evaluate the results sufficiently to detect possible distortions. Because of this, widespread practice in statistical bias adjustment is not aligned with recommendations from the academic literature. To address the practical issues impeding this, we introduce ibicus, an open-source Python package for the implementation of eight different peer-reviewed and widely used bias adjustment methods in a common framework and their comprehensive evaluation. The evaluation framework introduced in ibicus allows the user to analyse changes to the marginal, spatiotemporal and inter-variable structure of user-defined climate indices and distributional properties as well as any alteration of the climate change trend simulated in the model. Applying ibicus in a case study over the Mediterranean region using seven CMIP6 global circulation models, this study finds that the most appropriate bias adjustment method depends on the variable and impact studied, and that even methods that aim to preserve the climate change trend can modify it. These findings highlight the importance of use-case-specific selection of the method and the need for a rigorous evaluation of results when applying statistical bias adjustment.

Advancing the path to in-vivo imaging in freely moving mice via multimode-multicore fiber based holographic endoscopy.

Hair-thin multimode optical fiber-based holographic endoscopes have gained considerable interest in modern neuroscience for their ability to achieve cellular and even subcellular resolution during in-vivo deep brain imaging. However, the application of multimode fibers in freely moving animals presents a persistent challenge as it is difficult to maintain optimal imaging performance while the fiber undergoes deformations. We propose a fiber solution for challenging in-vivo applications with the capability of deep brain high spatial resolution imaging and neuronal activity monitoring in anesthetized as well as awake behaving mice. We used our previously developed multimode-multicore fiber to record fluorescently labeled neurons in anesthetized mice. Our exhibits a cascaded refractive index structure, enabling two distinct regimes of light transport that imitate either a multimode or a multicore fiber. The has been specifically designed for use in the initial phase of an in-vivo experiment, allowing for the navigation of the endoscope's distal end toward the targeted brain structure. The multicore regime enables the transfer of light to and from each individual neuron within the field of view. For chronic experiments in awake behaving mice, it is crucial to allow for disconnecting the fiber and the animal between experiments. Therefore, we provide here an effective solution and establish a protocol for reconnection of two segments of with hexagonally arranged corelets. We successfully utilized the to image neurons in anaesthetized transgenic mice expressing enhanced green fluorescent protein. Additionally, we compared imaging results obtained with the with larger numerical aperture (NA) fibers in fixed whole-brain tissue. This study focuses on addressing challenges and providing insights into the use of multimode-multicore fibers as imaging solutions for in-vivo applications. We suggest that the upcoming version of the increases the overall NA between the two cladding layers to allow for access to high resolution spatial imaging. As the NA increases in the multimode regime, the fiber diameter and ring structure must be reduced to minimize the computational burden and invasiveness.

Identifying similar-bicliques in bipartite graphs

Bipartite graphs have been widely used to model the relationship between entities of different types, where vertices are partitioned into two disjoint sets/sides. Finding dense subgraphs in a bipartite graph is of great significance and encompasses many applications. However, none of the existing dense bipartite subgraph models consider similarity between vertices from the same side, and as a result, the identified results may include vertices that are not similar to each other. In this work, we formulate the notion of similar-biclique which is a special kind of biclique where all vertices from a designated side are similar to each other and aim to enumerate all similar-bicliques. The naive approach of first enumerating all maximal bicliques and then extracting all maximal similar-bicliques from them is inefficient, as enumerating maximal bicliques is already time consuming. We propose a backtracking algorithm MSBE\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf{MSBE}$$\\end{document} to directly enumerate maximal similar-bicliques and power it by vertex reduction and optimization techniques. In addition, we design a novel index structure to speed up a time-critical operation of MSBE\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf{MSBE}$$\\end{document}, as well as to speed up vertex reduction. Efficient index construction algorithms are developed. To handle dynamic graph updates, we also propose algorithms and optimization techniques for maintaining our index. Finally, we parallelize our index construction algorithms to exploit multiple CPU cores. Extensive experiments on 17 bipartite graphs as well as case studies are conducted to demonstrate the effectiveness and efficiency of our model and algorithms.

Analysis of the Convergence of Manufacturing Industry Structure in the Three Provinces of Northeast China

At present, China's economic development is in an important stage of transformation towards high-quality development. Realizing industrial structure adjustment, promoting rational regional industrial layout, and collaborative division of labor play an important role in promoting high-quality economic development. Therefore, conducting research on the convergence of regional industrial structure is of great practical significance for promoting sustainable economic development. This article takes the manufacturing industry in the three northeastern provinces as the research object, and analyzes the problem of industrial structure convergence in the manufacturing industry from multiple perspectives. By measuring the similarity coefficient of industrial structure, location entropy, and regional division of labor index, it was found that the manufacturing industry in the three northeastern provinces of China has intensified industrial homogeneity while the convergence of industrial structure is not obvious. Policy suggestions are proposed to address this phenomenon.

The Crimean Tatar Ethnic Group in the Socio-Economic and Ethnopolitical Processes of the Republic of Crimea

The article examines the specifics of the manifestation of the Crimean Tatar ethnos in the socio-economic and ethnopolitical processes of the Republic of Crimea. It is noted that the socio-economic factor in some cases can act as an additional factor in the destabilization of ethnopolitical processes. Within the framework of the study, the index of the level of socio-economic development is calculated, as well as the index of the level of ethnopolitical instability in the municipalities of the Republic of Crimea is calculated. It is concluded that in 66% of municipalities with the largest share of the Crimean Tatar ethnic group in the population structure, either high or maximum values of the ethnopolitical tension index are recorded. In four municipalities with the largest share of the Crimean Tatar ethnic group in the population structure, a minimum and low quantitative indicator of the level of socio-economic development is recorded (Belogorsky, Dzhankoy, Sovetsky and Pervomaisky districts), and in four more districts (Bakhchisarai, Kirovsky, Simferopol and Krasnogvardeysky), average values of the index can be observed. The exception is the Sudak city district, where a high quantitative indicator of the level of socio-economic development is recorded. Another conclusion is that in the Belogorsky, Sovetsky and Pervomaisky districts there is a high probability of the influence of a socio-economic factor on the destabilization of ethnopolitical processes. At the same time, the socio-economic factor can have almost no effect on the deterioration of ethnopolitical stability in the Krasnogvardeysky district and the Sudak city district.

Groundwater Chemical Status Assessment in the Area of the Waste Landfill in Chorzów—Southern Poland

In this study, the spatiotemporal variation of water pollution near a municipal solid waste landfill in Chorzow (southern Poland) was investigated. For this purpose, analyses of electrolytic conductivity, sulfates, chlorides, nitrates, ammonium ion, and boron were performed. The landfill water pollution index (LWPI) and Nemerow Pollution Index (NPI) were calculated on the basis of groundwater monitoring results for the study area. The results indicated very high pollution in each piezometer. The value of the LWPI index for the piezometer located at the groundwater outflow from the landfill exceeded 320, and values exceeding five indicate a high risk to groundwater. In the case of the NPI index, the value reached nearly 44, which also indicates a high risk. The structure of both indices allows for the assessment of the level of threat to groundwater in areas of pollution sources. However, the NPI index highlights the contribution of parameters other than main ions to total water pollution. The use of indexes in assessing the quality of groundwater around pollution hotspots is very helpful in waste management, as it allows for determining the degree of threat to water, and thus can help in implementing additional preventive solutions.

Evaluation of Heart Substructures as a Function of Dose and Radiation-Induced Toxicities in Left-Sided Breast Cancer Radiotherapy

Background. A group of cardiopathies (ischemic, arrhythmic, and pericardial cardiac events) were shown to be associated with doses received by heart substructures following radiotherapy, alerting about the importance of dosimetric evaluation of cardiac structures besides the heart. The aim of this study was to assess the dosimetry of heart and heart substructures of left-sided breast cancer radiotherapy to evaluate possible radiation-induced complications. Methods and Materials. The study enrolled 20 patients treated with 3D-conformal radiotherapy (3DCRT), while intensity-modulated (IMRT) and volumetric-modulated arc radiotherapy (VMAT) plans were simulated for comparative purposes. The organs at risk (OARs) of interest were the heart, ascending aorta, descending aorta, left ventricle, left atrium, right ventricle, right atrium, superior vena cava, inferior vena cava, and pulmonary artery. Results. The percentage of left ventricle included in the radiation field was >5% for all plans (8.92% 3DCRT, 8.30% IMRT, and 6.84% VMAT). A strong correlation between mean heart dose and the percentage of left ventricle overlapping with the radiation fields was observed in 3DCRT (r = 0.784) and IMRT (r = 0.755) plans, and a moderate correlation was shown between tumor volume and the percentage of left ventricle included in the radiation field for all plans. A moderate correlation was observed between body mass index and cardiac structures for the mean dose to the right ventricle (r = 0.640) in conformal plans and V5 of heart (r = 0.528) and left ventricle (r = 0.669) in volumetric-modulated plans. Additionally, moderate to strong correlations were found between maximum heart distance and heart dose in both conformal and modulated plans. Conclusions. Considering possible occurrences of cardiac events during or postradiotherapy, monitoring the heart and its substructures and setting dosimetric thresholds for healthy tissues must be a priority to achieve a personalized and effective treatment.

Flan: An Expressive and Efficient Datalog Compiler for Program Analysis

Datalog has gained prominence in program analysis due to its expressiveness and ease of use. Its generic fixpoint resolution algorithm over relational domains simplifies the expression of many complex analyses. The performance and scalability issues of early Datalog approaches have been addressed by tools such as Soufflé through specialized code generation. Still, while pure Datalog is expressive enough to support a wide range of analyses, there is a growing need for extensions to accommodate increasingly complex analyses. This has led to the development of various extensions, such as Flix, Datafun, and Formulog, which enhance Datalog with features like arbitrary lattices and SMT constraints. Most of these extensions recognize the need for full interoperability between Datalog and a full-fledged programming language, a functionality that high-performance systems like Soufflé lack. Specifically, in most cases, they construct languages from scratch with first-class Datalog support, allowing greater flexibility. However, this flexibility often comes at the cost of performance due to the conflicting requirements of prioritizing modularity and abstraction over efficiency. Consequently, achieving both flexibility and compilation to highly-performant specialized code poses a significant challenge. In this work, we reconcile the competing demands of expressiveness and performance with Flan, a Datalog compiler fully embedded in Scala that leverages multi-stage programming to generate specialized code for enhanced performance. Our approach combines the flexibility of Flix with Soufflé’s performance, offering seamless integration with the host language that enables the addition of powerful extensions while generating specialized code for the entire computation. Flan’s simple operator interface allows the addition of an extensive set of features, including arbitrary aggregates, user-defined functions, and lattices, with multiple execution strategies such as binary and multi-way joins, supported by different indexing structures like specialized trees and hash tables, with minimal effort. We evaluate our system on a variety of benchmarks and compare it to established Datalog engines. Our results demonstrate competitive performance and speedups in the range of 1.4× to 12.5× compared to state-of-the-art systems for workloads of practical importance.

A deep-learning approach for turbulence correction in free space optical communication with Laguerre–Gaussian modes

Free space optical communication has become increasingly popular in the past decade due to its terahertz bandwidth, unlicensed spectrum, and enhanced security features. This technology has been attracting significant interest from the network community due to its broad applications in future military and civilian protocols. Recently, the use of orthogonal spatial states of the light field, including those with nonzero orbital angular momentum, has increased communication system capacities and bit-transfer rates per photon. However, atmospheric turbulence disrupts the orthogonal spatial modes over propagation. We present a novel deep learning architecture, cGULnet, to mitigate the effects of atmospheric turbulence on spatial multiplexing of Laguerre–Gaussian structured light modes. The model predicts the phase correction patterns required for an adaptive optical system. It is a U-shaped architecture trained adversarially to a patch discriminator similar to conditional generative adversarial neural-networks. The network is trained for exact phase recovery systems without approximating Zernike polynomials, enabling its use in highly phase-sensitive but high-speed spatial multiplexed communication systems. The proposed architecture can predict the successive three frames in a single shot using the previous ten frames. The method was evaluated for a wide range of beam waist sizes in a simulated Laguerre–Gaussian spatial mode multiplexed 1 km free space optical communication link. We have considered 20 dB optical signal-to-noise ratio, with turbulence conditions parameterized by the refractive index structure parameter of Cn2≤5×10−15m−23. It was found to reduce the bit error rate to the International Telecommunication Union recommended forward error correction limit of 3.8×10−3 under high turbulence conditions.

Development of Algorithm and Data Structure for 2D Regions Discrete Model Elements Accelerated Search

This paper is devoted to improving the search request processing productivity for planar discrete models used in engineering software. A data structure has been developed to accelerate the search for discretization elements based on a hierarchical triangular mesh. The developed indexing structure is built by a downward iterative algorithm, which constructs each new level of the hierarchy based on the previous level or indexed triangulation by simplifying it, which ensures that the morphology of the triangulation mesh is preserved throughout all levels of the hierarchical indexing structure. The developed building algorithm ensures the presence of tree-like connections between the levels of the hierarchical triangulation mesh, which allows downward navigation between geometrically close triangles. Search acceleration is achieved by performing a directed search in the top level of the indexing structure and then navigating between levels using downward links until the indexed triangle is found. The program implementation was carried out using C++17, and visualization of triangulation grids and isolines was carried out using the ObjectARX library. Based on the software implementation, an executive library was created.