Index Structure Research Articles

FogLBS: Utilizing fog computing for providing mobile Location-Based Services to mobile customers

The growth of Location-Based Services (LBSs) has been made possible by the widespread use of GPS-enabled devices. Some important LBSs require the ability to quickly process moving spatial-keyword queries over moving objects, such as when a moving customer is looking for a nearby mobile fuel delivery service. While there have been solutions proposed for scenarios where either the queries or the objects being queried are moving, there is still a need for solutions that can handle scenarios where both are in motion. This research focuses on the application of fog computing to provide real-time processing of moving spatial-keyword queries for LBSs. Specifically, the research proposes a new model, FogLBS, designed to efficiently process moving continuous top-k spatial-keyword queries over moving objects in a directed streets network, with a particular emphasis on the use case of a mobile service provider. FogLBS computes queries’ answer sets for time intervals and incrementally updates them using novel optimization techniques and indexing structures. By implementing FogLBS in a fog computing architecture, the model is able to meet the real-time requirements of the service provider application and other similar LBSs. The results of extensive experiments demonstrate the effectiveness of the proposed model in terms of efficiency, scalability, and accuracy, making it a valuable contribution to the field of fog computing in LBSs.

Structure and Analysis of the Smart Court Construction Evaluation Index Based on Principal Component Analysis for Different Regions

<p>In this paper, the principal component analysis method is mainly used to analyze that the construction level of Smart Court in different regions. The construction level of Smart Court consists of three main components. The result of Smart Court construction level in different regions is calculated. It is concluded that the construction level of Smart Court varies in different regions. It is necessary to make great efforts to solve the problem of unbalanced regional development. It is suggested that the construction of Smart Court in the future should focus on the publicity business such as online cases. And more and more new generation information technology such as artificial intelligence should be applied.</p> <p> </p>

Comparison of Environmental Costs in Divisions with Different Geographical Action and their Significance in Environmental Management

Abstract The relevance of the decision of this scientific research is related to the requirements of Industry 4.0. orientated to environmental sustainability. This article summarizes the scientific discussion on the issue of the comparison of environmental costs in various divisions such as Slovakia, Italy, Brazil, Mexico, China. The main goal of this article is to compare costs in divisions of the parent company with different geographical working. The object of the research was the parent company EMBRACO. Methods of research were focused on using economic analysis with indicators of the cost function, chain index, and cost structure. The results of the research show environmental costs of the divisions are at the level of €1.9-€3.1 million. The total state of the environmental costs by individual country represents the lowest value in Italy and Slovakia. The lowest environmental costs are for the category of air costs for all divisions and the second category of costs with low values are other environmental costs, while Brazil and Mexico do not record this category of costs in the accounting. The key category for minimizing environmental costs is water costs for Slovakia and China and other waste costs for Italy, Brazil, and Mexico. The hazardous waste category represents (0.9-32%). Based on these results, the parent company can decide on the possibilities of positioning its divisions in terms of strategic business.

Orbital angular momentum shift-keying communication through atmospheric turbulence and high scattering channel using a deep learning decoder

To increase the data rate and the channel capacity, orbital angular momentum shift keying (OAM-SK) has been studied extensively for free space optical (FSO) communication. However, the beams carrying OAM are disturbed into speckle patterns via the atmospheric turbulence (AT) and high scattering (HS) channel, which causes difficulty in decoding. Herein, we propose an AT and HS channel model to simulate the propagation of OAM beams, showing that the formed speckle size depends on the topological charge l of the OAM mode, which means the OAM mode can be recognized from the receiving speckle patterns. Proof-of-concept​ experiments of an OAM-SK system using a deep learning decoder are implemented. The results show that under dynamic AT with the refractive index structure constant (the AT strength, Cn2=1×10−16K2m−2/3) and static HS (a ground glass), we achieve a hybrid eight-mode OAM-SK, where the decoding accuracy of the encoding set l=1,2,3,4,5,6,7,8 reaches >0.95 within a 500 m transmission distance. Moreover, increasing the encoding mode interval can improve the decoding accuracy; when the AT strength increases to Cn2=1×10−14K2m−2/3 and the scattering media becomes dynamic, the accuracy of the encoding set l=1,4,7,10,13,16,19,22 with a mode interval of 3 can still achieve >0.94 at 100 m. Furthermore, error-free image transmission can be achieved in the OAM-SK system under AT strengths of Cn2=1×10−16K2m−2/3 and 1×10−15K2m−2/3 and HS at 100 m. This work provides a potential approach for FSO communication based on OAM modes under harsh AT and HS channels.

Linear-time computation of DAWGs, symmetric indexing structures, and MAWs for integer alphabets

The directed acyclic word graph (DAWG) of a string y of length n is the smallest (partial) DFA which recognizes all suffixes of y with only O(n) nodes and edges. In this paper, we show how to construct the DAWG for the input string y from the suffix tree for y, in O(n) time for integer alphabets of polynomial size in n. In so doing, we first describe a folklore algorithm which, given the suffix tree for y, constructs the DAWG for the reversed string yˆ in O(n) time. Then, we present our algorithm that builds the DAWG for y in O(n) time for integer alphabets, from the suffix tree for y. We also show that a straightforward modification to our DAWG construction algorithm leads to the first O(n)-time algorithm for constructing the affix tree of a given string y over an integer alphabet. Affix trees are a text indexing structure supporting bidirectional pattern searches. We then discuss how our constructions can lead to linear-time algorithms for building other text indexing structures, such as linear-size suffix tries and symmetric CDAWGs in linear time in the case of integer alphabets. As a further application to our O(n)-time DAWG construction algorithm, we show that the set MAW(y) of all minimal absent words (MAWs) of y can be computed in optimal, input- and output-sensitive O(n+|MAW(y)|) time and O(n) working space for integer alphabets.

Protective effects of scutellaria-coptis herb couple against non-alcoholic steatohepatitis via activating NRF2 and FXR pathways in vivo and in vitro

Ethnopharmacological relevanceScutellaria-coptis herb couple (SC) is a classic herbal pair used in many Traditional Chinese Medicine (TCM) formulations in the treatment of endocrine and metabolic deseases. Diabetes mellitus and non-alcoholic steatohepatitis (NASH) are both endocrine and metabolic diseases. Previous studies have shown that SC has anti-diabetic effects. However, the effect and mechanism of SC against NASH remains unclear. Aim of the studyThis study aimed to demonstrate the effect and mechanism of SC against NASH through the nuclear factor-erythroid 2-related factor 2 (Nrf2) and farnesoid X receptor (FXR) dual signaling pathways in vivo and in vitro. Materials and methodsThe high fat diet-fed rat model, and HepG2 and RAW264.7 cell models were used. Serum biochemical indexes and liver histopathological changes were examined. Metabolomics, transcriptomics, and flow cytometry were performed. RT-qPCR and western blot analysis were performed to provide expression of NRF2 and FXR pathway signal molecules during SC's anti-NASH treatment in vivo and in vitro. ResultsSC had anti-NASH effects in vivo with significantly improvement of serum NASH biochemical index and hepatopathological structure; meanwhile, SC significantly elevated the expression levels of FXR protein in liver and intestinal tissues, and cholesterol 7a-hydroxylase (CYP7A1) protein in liver. The mRNA expression levels of Takeda G protein receptor 5 (TGR5), CYP7A1, fibroblast growth factor receptor-4 (FGFR4), FXR, small heterodimer partner (SHP), fibroblast growth factor 15/19 (FGF15/19) and glucagon-like peptide-1 (GLP-1) were significantly elevated by SC. SC reduced the levels of NorCA, isoLCA and α-MCA in the feces of NAFLD rats. In vitro, SC-containing serum (SC-CS) was found to significantly reduce intracellular lipid deposition, inhibit ROS production, reduce intracellular Malondialdehyde (MDA) and IL-1β levels, and enhance the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px). Six differential genes closely related to oxidative stress and Nrf2 were identified by transcriptomic analysis. SC-CS up-regulated the expression of NRF2, and reduced the expression of TXNIP and Caspase-1 genes in RAW264.7 cells. In addition, SC-CS reduced the expression of Keap1 and NF-κB, and up-regulated the expression of Nrf2, heme oxygenase-1 (HO-1), quinone oxidoreductase 1 (NQO1), and SOD; SC-CS elevated the protein level of NRF2, and reduced the protein level of TXNIP in HepG2 cells. Conclusionsthe mechanisms of SC action against NASH was closely related to the simultaneous activations of both NRF2 and FXR signaling pathways. These findings provide a new insight into the anti-NASH application of SC in clinical settings and demonstrate the potential of SC in the treatment of NASH.

IESDB – the Iberian Evaporite Structure Database

Abstract. Evaporites flow in the solid state under relatively low differential stress and have unique mechanical properties compared to other sedimentary rocks. Worldwide, they control the structural and stratigraphical architecture of many basins and orogens in ancient and active tectonic settings. Moreover, they host mineral deposits and play a key role in petroleum systems because they typically act as seals due to their low permeability, and their ability to flow results in the formation of structural hydrocarbon traps such as folds and faults in their encasing rocks. Additionally, evaporite structures can be used as subsurface storage sites for geo-energy applications and nuclear waste. The systematic characterisation of subsurface evaporite structures is thus key for the development of geoscience-based technologies to address societal challenges. Owing to their value, massive amounts of surface and subsurface information about (among others) the stratigraphy, structure, geochemistry, and petrophysical properties of evaporite structures and their surrounding rocks have been acquired by Earth scientists, petroleum and mining exploration companies, and geological surveys. However, the data often appear segregated (i.e. in the form of database fragments, scientific articles, and unpublished reports), are not systematically organised, and are sometimes not fully accessible. This contribution presents the Iberian Evaporite Structure Database (IESDB), the first comprehensive assessment that focuses on evaporite structures carried out in any region of the world. The IESDB includes information and figures for 150 evaporite structures and their surrounding rocks inventoried in Spain and Portugal and is sourced from other six thematic databases and more than 1500 published and unpublished scientific documents. The database targets undeformed to slightly deformed evaporite successions, outcropping and buried diapirs, evaporite-cored anticlines, evaporite-detached thrusts, and allochthonous evaporite bodies. Collated data include information about the structure, stratigraphy, event chronology, surface and subsurface data availability, mining activity, and key bibliographic references. The IESDB follows the FAIR principles of database management (Findable, Accessible, Interoperable, and Reusable) and is presented as an interactive web page and an open-access database, where indexed structures can easily be selected from a map or browser and filtered by a search engine. The IESDB intends to be a useful resource for teaching (i.e. pointing out examples of exceptional evaporite outcrops), academic and industry research (i.e. identifying knowledge deficits on specific structures or tectonic settings), and for the sustainable exploration and appraisal of mineral resources and geo-energy applications (i.e. representing a terminus a quo for site selection and suitability assessment). The framework provided by the IESDB is an opportunity to enhance the scientific research on Iberian evaporite structures in Spain and Portugal and to take advantage of their scientific and economic potential to tackle important societal challenges faced by these countries. The IESDB is freely available at https://iesdb.eu (last access: 15 June 2023) and the datasets can be downloaded from https://doi.org/10.20350/digitalCSIC/14586 (González-Esvertit et al., 2022).

Effect of data spatial vertical resolution on the estimation of vertical profiles of the refractive index structure constant.

The vertical profile of optical turbulence is a key factor in the performance design of astronomical telescopes and adaptive optics instruments. As site-testing campaigns are extremely expensive, the selection of appropriate spatial resolution data and estimation methods is extremely important. This study investigated the effect of using different methods (Dewan, HMNSP99, Thorpe method) to estimate the refractive index structure constant (C n2) using different resolution data (5 m, 25 m, ERA5 data) in Huaihua, Hunan. Compared with Dewan, HMNSP99 for estimating C n2 using 5 m and 25 m resolution data, the Thorpe method almost always shows the best performance, with RXY above 0.75 and lower RMSE and MRE between estimated and measured C n2. The results of C n2 estimation using HMNSP99 at different resolution data varied widely, indicating that HMNSP99 is more sensitive to the data resolution and the temperature gradient is more sensitive to the resolution. Using ERA5 data, the two methods of estimating C n2 using Dewan and HMNSP99 have close results. It indicates that the wind shear is the main factor when the spatial resolution of the data is reduced to a certain degree, and the contribution of temperature gradient is small in the high altitude turbulence.

Diversity, distribution and conservation status of mangrove species in Pulias Bay, Indonesia

As an ecosystem, the mangrove ecosystem serves various purposes. The objectives of this study are to (1) identify the community structure of the important value index; and (2) evaluate the importance of the mangrove species diversity index in Pulias Bay in Ogodeide District, Tolitoli Regency. The study was conducted in 2021 using a quantitative descriptive methodology and survey method. The number of discovered species will be used to establish the species composition. The structure of the mangrove communities is being evaluated by calculating the relative density (RD) and frequency (FR). The data is tabulated to calculate the Important Value Index (IVI) value according to the Shannon-Wiener formula. There were 18 different species of mangroves discovered, including Rhizophora apiculata, Rh. mucronata, Rh. stylosa, Bruguiera parviflora, B. gymnorrhiza, Ceriops tagal, C. decandra, Sonneratia alba, S. caseolaris, S. ovata, Avicennia lanata, Xylocarpus moluccensis, Acrostichum aureum, Nypa fruticans, and Pemphis acidula. The Rhizophoraceae family predominated at each observation station, according to the findings of the vegetation analysis. Meanwhile the most rarely found species of mangrove were Acrostichum aureum, Sonneratia casiolaris, and Xylocarpus moluccensis, each with two specimens. The community structure reveals that X. moluccensis has the lowest IVI value of 12.7%, while Rhizophora mucronata has an IVI value of 101.3%. The mangrove Diversity Index (H') has a value of 2.48 and meets the standards for moderate diversity. Physical and chemical parameter measurements often indicate that the four stations or sites where the data was collected have similar conditions. Interestingly, we also found Avicennia lanata, a mangrove species that falls under the Vulnerable category. The collected information can be used to manage the mangrove forest in Pulias Bay in the Ogodeide Sub-District of the Tolitoli Regency and serve as a database for efforts to conserve mangroves and mitigate the effects of global warming.

Relationship between ODI and sleep structure of obstructive sleep apnea andcardiac remodeling.

The purpose of the study was to evaluate the quantitative relationship between Oxygen Desaturation Index (ODI) and sleep structure of obstructive sleep apnea (OSA)and cardiac remodeling. In this study, patients were enrolled from January 2015 to October 2022, and were divided into 3 groups according to AHI: patients with AHI < 15, patients with 15 ≤ AHI < 30, and 260 patients with AHI ≥ 30. Stratified linear regression was used to analyze independent risk factors for cardiac remodeling in OSA. A total of 479 patients were enrolled.We found that compared with AHI < 15 group(n= 120), the group with AHI > 30 (n= 260)had increased left atrial anteroposterior diameter, left ventricular end-diastolic internal diameter, left ventricular posterior wall thickness, right ventricular anteroposterior diameter, and interventricular septal thickness (P < 0.05). The group with 15 ≤ AHI ≤ 30 (n= 99)had increased left atrial anteroposterior diameter (P < 0.05). Multivariate linear regression revealed that N2 sleep was an independent risk factor for left ventricular posterior wall thickness, with positive correlation (p < 0.05).N3 sleep was an independent risk factor for transverse right atrial diameter and right ventricular anteroposterior diameter, with negative correlation (P < 0.05).ODI was an independent risk factor for interventricular septal thickness, with positive correlation (P < 0.05).The arousal index was an independent risk factor for increased left atrial anteroposterior diameter, with positive correlation (P < 0.05). Increased ODI is an independent risk factor for interventricular septal thickness, while decreased slow wave sleep is an independent risk factor for right heart remodeling in OSA.

Genome assembly composition of the String "ACGT" array: a review of data structure accuracy and performance challenges.

The development of sequencing technology increases the number of genomes being sequenced. However, obtaining a quality genome sequence remains a challenge in genome assembly by assembling a massive number of short strings (reads) with the presence of repetitive sequences (repeats). Computer algorithms for genome assembly construct the entire genome from reads in two approaches. The de novo approach concatenates the reads based on the exact match between their suffix-prefix (overlapping). Reference-guided approach orders the reads based on their offsets in a well-known reference genome (reads alignment). The presence of repeats extends the technical ambiguity, making the algorithm unable to distinguish the reads resulting in misassembly and affecting the assembly approach accuracy. On the other hand, the massive number of reads causes a big assembly performance challenge. The repeat identification method was introduced for misassembly by prior identification of repetitive sequences, creating a repeat knowledge base to reduce ambiguity during the assembly process, thus enhancing the accuracy of the assembled genome. Also, hybridization between assembly approaches resulted in a lower misassembly degree with the aid of the reference genome. The assembly performance is optimized through data structure indexing and parallelization. This article's primary aim and contribution are to support the researchers through an extensive review to ease other researchers' search for genome assembly studies. The study also, highlighted the most recent developments and limitations in genome assembly accuracy and performance optimization. Our findings show the limitations of the repeat identification methods available, which only allow to detect of specific lengths of the repeat, and may not perform well when various types of repeats are present in a genome. We also found that most of the hybrid assembly approaches, either starting with de novo or reference-guided, have some limitations in handling repetitive sequences as it is more computationally costly and time intensive. Although the hybrid approach was found to outperform individual assembly approaches, optimizing its performance remains a challenge. Also, the usage of parallelization in overlapping and reads alignment for genome assembly is yet to be fully implemented in the hybrid assembly approach. We suggest combining multiple repeat identification methods to enhance the accuracy of identifying the repeats as an initial step to the hybrid assembly approach and combining genome indexing with parallelization for better optimization of its performance.

A Robust Coverless Image Steganography Based on an End-to-End Hash Generation Model

Recently, coverless steganography algorithms have attracted increased research attention due to their ability to completely resist steganalysis algorithms. However, the existing algorithms do not attain the same robust balance against geometric and non-geometric attacks. In addition, most of the existing methods need to transmit some auxiliary information along with the stego-images, which increases the cost of the hidden information. In this paper, a robust coverless image steganography algorithm based on a hash generation model is proposed. Different from the existing methods, the hash sequences are generated by an end-to-end CNN model, where the input is the original images, and the output is the corresponding hash sequences. Therefore, no auxiliary information needs to be transmitted when hiding the secret information. Moreover, the attention mechanism and adversarial training are introduced to improve the robustness of the model. The loss function is redesigned to accommodate these operations. Finally, an index structure is built to enhance the mapping efficiency. The experimental results show that the proposed method possesses better robustness and security compared with the state-of-the-art coverless image steganography algorithms.

Practical and Dynamic Attribute-Based Keyword Search Supporting Numeric Comparisons Over Encrypted Cloud Data

The attribute-based keyword search (ABKS), which simultaneously achieves searching and fine-grained access control over encrypted data, is frequently applied in cloud computing environments characterized by data storage and sharing. Recently, inspired by attribute-based encryption (ABE) and searchable encryption (SE) primitives, several ABKS schemes have been presented. However, almost all existing ABKS schemes actually only provide an attribute-based keyword equality match function and do not have a structural index to support practical search efficiency and dynamic data updates in real-world applications. To the best of our knowledge, this study is the first to realize an attribute-based keyword search construction supporting numerical comparison expressions with the practical search efficient and dynamic data update capacity (ABKS-NICEST), based on our proposed attribute-based keyword secure search scheme supporting numerical comparison expressions (ABKS-NICE) and an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">exclusive OR-chain</i> -based inverted index structure. To the best of our knowledge, ABKS-NICEST is the first attributed-based keyword search scheme with practical search efficiency and dynamic data update capacity. In addition, numerical values are an important and common attribute, so providing comparison expressions among numerical values can greatly enhance the expressivity of access policy. Therefore, we use the prefix membership verification technique to design a method to support any numeric comparison expression in a flexible and uniform manner. Through theoretical and experimental evaluations, we determine that ABKS-NICEST is the most efficient ABKS scheme.

Fast Search-by-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests

The vast amounts of data collected in various domains pose great challenges to modern data exploration and analysis. To find "interesting" objects in large databases, users typically define a query using positive and negative example objects and train a classification model to identify the objects of interest in the entire data catalog. However, this approach requires a scan of all the data to apply the classification model to each instance in the data catalog, making this method prohibitively expensive to be employed in large-scale databases serving many users and queries interactively. In this work, we propose a novel framework for such search-by-classification scenarios that allows users to interactively search for target objects by specifying queries through a small set of positive and negative examples. Unlike previous approaches, our framework can rapidly answer such queries at low cost without scanning the entire database. Our framework is based on an index-aware construction scheme for decision trees and random forests that transforms the inference phase of these classification models into a set of range queries, which in turn can be efficiently executed by leveraging multidimensional indexing structures. Our experiments show that queries over large data catalogs with hundreds of millions of objects can be processed in a few seconds using a single server, compared to hours needed by classical scanning-based approaches.

Privacy-Preserving Multi-Range Queries for Secure Data Outsourcing Services

Encrypted range query schemes that enable range-based searches over encrypted data have become an effective solution for secure data outsourcing services. However, existing schemes are still inadequate on desired functionality and security. Specifically, supporting efficient multi-range queries while hiding the data ordering leakage remains a challenging research problem. Existing works on order-hiding query schemes only work for encrypted single-range search and incur significant computational overhead due to the protection of the ordering information. In this paper, we present a privacy-preserving multi-range query scheme that can address the above problems simultaneously. It not only enables efficient multi-range queries over encrypted data but also guarantees the privacy of ordering information. To protect the ordering leakage, our design adopts an Order-hiding Encoding (OHE) scheme to support multi-range obfuscation. In addition, a novel order-hiding KD-tree index structure is designed as the core technique underlying our scheme, which accelerates efficient multi-range queries and obfuscates ordering information of encrypted values. Finally, the formal security analysis confirms that our proposed multi-range query scheme is secure in the random oracle model. The extensive experimental results conducted on real-world datasets demonstrate the practicality of our design.

Asymptotically Better Query Optimization Using Indexed Algebra

Query optimization is essential for the efficient execution of queries. The necessary analysis, if we can and should apply optimizations and transform the query plan, is already challenging. Traditional techniques focus on the availability of columns at individual operators, which does not scale for analysis of data flow through the query. Tracking available columns per operator takes quadratic space, which can result in multi-second optimization time for deep algebra trees. Instead, we need to re-think the naïve algebra representation to efficiently support data flow analysis. In this paper, we introduce Indexed Algebra , a novel representation of relational algebra that makes common optimization tasks efficient. Indexed Algebra enables efficient reasoning with an auxiliary index structure based on link/cut trees that support dynamic updates and queries in O (log n ). This approach not only improves the asymptotic complexity, but also allows elegant and concise formulations for the data flow questions needed for query optimization. While large queries see theoretically unbounded improvements, Indexed Algebra also improves optimization time of the relatively harmless queries of TPC-H and TPC-DS by more than 1.8×.

A refractive index sensor based on the MIM waveguide with a semi-elliptical and a rectangular ring resonant cavity

In this paper, a novel nanosensor comprising the metal–insulator–metal (MIM) plasmonics waveguide with a semi-elliptical and rectangular ring resonant cavity is designed. In near-infrared waveband, the propagation properties of electromagnetic waves in the structure are studied using the finite-difference time-domain (FDTD) method. The results show that, based on the coupling between the semi-elliptical and the rectangular ring resonant cavity, the transmission spectrum of the structure exhibits a sharp Fano resonance shape. Next, the influence of the refractive index and sensor structure parameters on performance is systematically investigated. The simulation results show that the sensor structure has the best sensitivity of 1384[Formula: see text]nm/RIU (refractive index unit), and the figure of merit (FOM) is 28.4. The simple MIM structure could be applied to sensitive plasmonic sensors.

Research on the Visualization of Railway Signal Operation and Maintenance Based on BIM + GIS

To adapt to the “fine” and “extensive” management characteristics of railway signal equipment operation and maintenance, achieving real-time and interactive monitoring of signal equipment operation status, and developing an integrated approach to equipment operation and maintenance, this paper takes a comprehensive management perspective. To create a lightweight BIM model, the Garland folding algorithm is utilized to simplify the IFC file format. Building on this approach, the data are divided based on building component division standards to obtain separate files containing geometric information and semantic attributes. The geometric information files are converted to a 3D Tiles format, combining BIM semantic attributes with semantic attribute files through an intermediate format. Dynamic data management is achieved by setting the octree space index structure in combination with a view-frustum culling algorithm. Then, the 3D Tiles target file is imported into the Cesium platform, and Node.js is used to achieve three-dimensional visualization of railway signal operation and maintenance. The proposed method is verified using an inbound signal as an example to assess its feasibility. The results demonstrate the potential of the proposed method to achieve stable integration between BIM equipment full lifecycle maintenance and GIS geographical space display. Railway signal equipment is endowed with comprehensive one-click information query functions for equipment positioning and spatial analysis, improving the efficiency and scientific decision-making level of equipment operation and maintenance.

Generating Encrypted Document Index Structure Using Tree Browser

Generating Encrypted Document Index Structure Using Tree Browser

Distance, Origin and Category Constrained Paths

Recommending a Point of Interest (PoI) or a sequence of PoIs to visit based on user’s preferences and geo-locations has been one of the most popular applications of Location-Based Services (LBS). Variants have also been considered which take other factors into consideration, such as broader (implicit or explicit) semantic constraints as well as the limitations on the length of the trip. In this work, we present an efficient algorithmic solution to a novel query – PaDOC (Paths with Distance, Origin, and Category constraints) – which combines the generation of a path that (a) can be traversed within a user-specified budget (e.g., limit on distance), (b) starts at one of the user-specified origin locations (e.g., a hotel), and (c) contains PoIs from a user-specified list of PoI categories. We show that the problem of deciding whether such a path exists is an NP-hard problem. Based on a novel indexing structure, we propose two efficient algorithms for approximate PaDOC query processing based on both conservative and progressive distance estimations. We conducted extensive experiments over real, publicly available datasets, demonstrating the benefits of the proposed methodologies over straightforward solutions.