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Relevant bibliographies by topics / Point and Range Queries

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Academic literature on the topic 'Point and Range Queries'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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Journal articles on the topic "Point and Range Queries"

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Lai, Ying Kit, Chung Keung Poon, and Benyun Shi. "Approximate colored range and point enclosure queries." Journal of Discrete Algorithms 6, no. 3 (September 2008): 420–32. http://dx.doi.org/10.1016/j.jda.2007.10.001.

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Ghosh, Esha, Olga Ohrimenko, and Roberto Tamassia. "Efficient Verifiable Range and Closest Point Queries in Zero-Knowledge." Proceedings on Privacy Enhancing Technologies 2016, no. 4 (October 1, 2016): 373–88. http://dx.doi.org/10.1515/popets-2016-0045.

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AbstractWe present an efficient method for answering one-dimensional range and closest-point queries in a verifiable and privacy-preserving manner. We consider a model where a data owner outsources a dataset of key-value pairs to a server, who answers range and closest-point queries issued by a client and provides proofs of the answers. The client verifies the correctness of the answers while learning nothing about the dataset besides the answers to the current and previous queries. Our work yields for the first time a zero-knowledge privacy assurance to authenticated range and closest-point queries. Previous work leaked the size of the dataset and used an inefficient proof protocol. Our construction is based on hierarchical identity-based encryption. We prove its security and analyze its efficiency both theoretically and with experiments on synthetic and real data (Enron email and Boston taxi datasets).

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Watve, Alok, Sakti Pramanik, Sungwon Jung, and Chae Yong Lim. "Data-independent vantage point selection for range queries." Journal of Supercomputing 75, no. 12 (April 21, 2018): 7952–78. http://dx.doi.org/10.1007/s11227-018-2384-8.

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MYERS, YONATAN, and LEO JOSKOWICZ. "POINT SET DISTANCE AND ORTHOGONAL RANGE PROBLEMS WITH DEPENDENT GEOMETRIC UNCERTAINTIES." International Journal of Computational Geometry & Applications 22, no. 06 (December 2012): 517–41. http://dx.doi.org/10.1142/s0218195912500148.

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Classical computational geometry algorithms handle geometric constructs whose shapes and locations are exact. However, many real-world applications require modeling and computing with geometric uncertainties, which are often coupled and mutually dependent. In this paper we address the relative position of points, point set distance problems, and orthogonal range queries in the plane in the presence of geometric uncertainty. The uncertainty can be in the locations of the points, in the query range, or both, and is possibly coupled. Point coordinates and range uncertainties are modeled with the Linear Parametric Geometric Uncertainty Model (LPGUM), a general and computationally efficient worst-case, first-order linear approximation of geometric uncertainty that supports dependence among uncertainties. We present efficient algorithms for relative points orientation, minimum and maximum pairwise distance, closest pair, diameter, and efficient algorithms for uncertain range queries: uncertain range/nominal points, nominal range/uncertain points, uncertain range/uncertain points, with independent/dependent uncertainties. In most cases, the added complexity is sub-quadratic in the number of parameters and points, with higher complexities for dependent point uncertainties.

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Sun, Ping, Caimei Liang, Guohui Li, and Ling Yuan. "Researching Why-Not Questions in Skyline Query Based on Orthogonal Range." Electronics 9, no. 3 (March 18, 2020): 500. http://dx.doi.org/10.3390/electronics9030500.

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This paper aims to answer “why-not” questions in skyline queries based on the orthogonal query range (i.e., ORSQ). These queries retrieve skyline points within a rectangular query range, which improves query efficiency. Answering why-not questions in ORSQ can help users analyze query results and make decisions. We discuss the causes of why-not questions in ORSQ. Then, we outline how to modify the why-not point and the orthogonal query range so that the why-not point is included in the result of the skyline query based on the orthogonal range. When the why-not point is in the orthogonal range, we show how to modify the why-not point and narrow the orthogonal range. We also present how to expand the orthogonal range when the why-not point is not in the orthogonal range. We effectively combine query refinement and data modification techniques to produce meaningful answers. The experimental results demonstrate that the proposed algorithms have high-quality explanations for why-not questions in ORSQ in the real and synthetic datasets.

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Cho, Hyung-Ju, and Rize Jin. "Efficient Processing of Movingk-Range Nearest Neighbor Queries in Directed and Dynamic Spatial Networks." Mobile Information Systems 2016 (2016): 1–17. http://dx.doi.org/10.1155/2016/2406142.

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Ak-range nearest neighbor (kRNN) query in a spatial network finds thekclosest objects to each point in the query region. The essential nature of thekRNN query is significant in location-based services (LBSs), where location-aware queries with query regions such askRNN queries are frequently used because of the issue of location privacy and the imprecision of the associated positioning techniques. Existing studies focus on reducing computation costs at the server side while processingkRNN queries. They also consider snapshot queries that are evaluated once and terminated, as opposed to moving queries that require constant updating of their results. However, little attention has been paid to evaluating movingkRNN queries in directed and dynamic spatial networks where every edge is directed and its weight changes in accordance with the traffic conditions. In this paper, we propose an efficient algorithm called MORAN that evaluates movingk-range nearest neighbor (MkRNN) queries in directed and dynamic spatial networks. The results of a simulation conducted using real-life roadmaps indicate that MORAN is more effective than a competitive method based on a shared execution approach.

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El-Mahgary, Sami, Juho-Pekka Virtanen, and Hannu Hyyppä. "A Simple Semantic-Based Data Storage Layout for Querying Point Clouds." ISPRS International Journal of Geo-Information 9, no. 2 (January 22, 2020): 72. http://dx.doi.org/10.3390/ijgi9020072.

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The importance of being able to separate the semantics from the actual (X,Y,Z) coordinates in a point cloud has been actively brought up in recent research. However, there is still no widely used or accepted data layout paradigm on how to efficiently store and manage such semantic point cloud data. In this paper, we present a simple data layout that makes use the semantics and that allows for quick queries. The underlying idea is especially suited for a programming approach (e.g., queries programmed via Python) but we also present an even simpler implementation of the underlying technique on a well known relational database management system (RDBMS), namely, PostgreSQL. The obtained query results suggest that the presented approach can be successfully used to handle point and range queries on large points clouds.

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R. Brisaboa, Nieves, Guillermo De Bernardo, Roberto Konow, Gonzalo Navarro, and Diego Seco. "Aggregated 2D range queries on clustered points." Information Systems 60 (August 2016): 34–49. http://dx.doi.org/10.1016/j.is.2016.03.004.

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EPPSTEIN, DAVID, MICHAEL T. GOODRICH, and JONATHAN Z. SUN. "SKIP QUADTREES: DYNAMIC DATA STRUCTURES FOR MULTIDIMENSIONAL POINT SETS." International Journal of Computational Geometry & Applications 18, no. 01n02 (April 2008): 131–60. http://dx.doi.org/10.1142/s0218195908002568.

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We present a new multi-dimensional data structure, which we call the skip quadtree (for point data in R2) or the skip octree (for point data in Rd, with constant d > 2). Our data structure combines the best features of two well-known data structures, in that it has the well-defined “box”-shaped regions of region quadtrees and the logarithmic-height search and update hierarchical structure of skip lists. Indeed, the bottom level of our structure is exactly a region quadtree (or octree for higher dimensional data). We describe efficient algorithms for inserting and deleting points in a skip quadtree, as well as fast methods for performing point location, approximate range, and approximate nearest neighbor queries.

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Shen, Jun Hong, Ye In Chang, Chen Chang Wu, and Ta Wei Liu. "A Forward Moving Method for Continuous Nearest Neighbor Queries." Applied Mechanics and Materials 284-287 (January 2013): 2965–69. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2965.

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A continuous nearest neighbor (CNN) query retrieves the nearest neighbor of every point on a line segment and indicates its valid segments. Zheng et al. have proposed a Hilbert-curve index for the CNN query. This method contains two phases, searching candidates in the approximate search range, and filtering the candidates to get the final answer. However, it may determine a wide search range in the first phase based on this method, resulting in the decrease of the accuracy and the increase of the processing time. Therefore, in this paper, to avoid this disadvantage, we propose a forward moving method to efficiently support the CNN queries. The proposed method locally expands the search range along the query line segment to find the neighbors. Experimental results show that our method outperforms Zheng et al.’s method in terms of the accuracy and the processing time.

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Dissertations / Theses on the topic "Point and Range Queries"

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Apaydin, Tan. "Query Support for Multi-Dimensional and Dynamic Databases." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1221842826.

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Suryanarayanan, Vinoth. "Synchronised range queries." Thesis, University of Birmingham, 2012. http://etheses.bham.ac.uk//id/eprint/3768/.

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Computer simulations have been used more than ever before to embark on developing and understanding complex systems such as Multi-Agent Systems (MAS). As simulation systems become larger and more complex, scalability becomes an important issue for their successful deployment. PDES-MAS (Parallel and Discrete Event Simulations for Multi-Agent Systems) framework is, implemented based on distributed shared memory architecture, a parallel and discrete event simulation kernel to distribute and run parallel simulation of Multi-Agent Systems (MAS). There are several issues within such system and this thesis presents a notion of logical time synchronised range queries to address the issue of data access. Accessing data efficiently in a latency-sensitive and large scale network overlay is a vital requirement for the scalability of the system. So, this thesis presents a notion of synchronised range queries with algorithms to manage distributed data structures consistently and in a time ordered fashion across the system. To localise data access in such a large scale simulation system, algorithms are provided to distribute shared state such that the distribution reflects access patterns of simulating nodes. The algorithms are evaluated within the implementation of PDES-MAS framework using various agent based simulation traces.

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Bernagozzi, Stefano. "Range Queries on an encrypted outsourced database." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10907/.

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This project is about retrieving data in range without allowing the server to read it, when the database is stored in the server. Basically, our goal is to build a database that allows the client to maintain the confidentiality of the data stored, despite all the data is stored in a different location from the client's hard disk. This means that all the information written on the hard disk can be easily read by another person who can do anything with it. Given that, we need to encrypt that data from eavesdroppers or other people. This is because they could sell it or log into accounts and use them for stealing money or identities. In order to achieve this, we need to encrypt the data stored in the hard drive, so that only the possessor of the key can easily read the information stored, while all the others are going to read only encrypted data. Obviously, according to that, all the data management must be done by the client, otherwise any malicious person can easily retrieve it and use it for any malicious intention. All the methods analysed here relies on encrypting data in transit. In the end of this project we analyse 2 theoretical and practical methods for the creation of the above databases and then we tests them with 3 datasets and with 10, 100 and 1000 queries. The scope of this work is to retrieve a trend that can be useful for future works based on this project.

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Kennedy, W. Brett. "Declustering spatial data for range and join queries." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0004/MQ45949.pdf.

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Sprenger, Stefan. "Efficient Processing of Range Queries in Main Memory." Doctoral thesis, Humboldt-Universität zu Berlin, 2019. http://dx.doi.org/10.18452/19786.

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Datenbanksysteme verwenden Indexstrukturen, um Suchanfragen zu beschleunigen. Im Laufe der letzten Jahre haben Forscher verschiedene Ansätze zur Indexierung von Datenbanktabellen im Hauptspeicher entworfen. Hauptspeicherindexstrukturen versuchen möglichst häufig Daten zu verwenden, die bereits im Zwischenspeicher der CPU vorrätig sind, anstatt, wie bei traditionellen Datenbanksystemen, die Zugriffe auf den externen Speicher zu optimieren. Die meisten vorgeschlagenen Indexstrukturen für den Hauptspeicher beschränken sich jedoch auf Punktabfragen und vernachlässigen die ebenso wichtigen Bereichsabfragen, die in zahlreichen Anwendungen, wie in der Analyse von Genomdaten, Sensornetzwerken, oder analytischen Datenbanksystemen, zum Einsatz kommen. Diese Dissertation verfolgt als Hauptziel die Fähigkeiten von modernen Hauptspeicherdatenbanksystemen im Ausführen von Bereichsabfragen zu verbessern. Dazu schlagen wir zunächst die Cache-Sensitive Skip List, eine neue aktualisierbare Hauptspeicherindexstruktur, vor, die für die Zwischenspeicher moderner Prozessoren optimiert ist und das Ausführen von Bereichsabfragen auf einzelnen Datenbankspalten ermöglicht. Im zweiten Abschnitt analysieren wir die Performanz von multidimensionalen Bereichsabfragen auf modernen Serverarchitekturen, bei denen Daten im Hauptspeicher hinterlegt sind und Prozessoren über SIMD-Instruktionen und Multithreading verfügen. Um die Relevanz unserer Experimente für praktische Anwendungen zu erhöhen, schlagen wir zudem einen realistischen Benchmark für multidimensionale Bereichsabfragen vor, der auf echten Genomdaten ausgeführt wird. Im letzten Abschnitt der Dissertation präsentieren wir den BB-Tree als neue, hochperformante und speichereffziente Hauptspeicherindexstruktur. Der BB-Tree ermöglicht das Ausführen von multidimensionalen Bereichs- und Punktabfragen und verfügt über einen parallelen Suchoperator, der mehrere Threads verwenden kann, um die Performanz von Suchanfragen zu erhöhen.
Database systems employ index structures as means to accelerate search queries. Over the last years, the research community has proposed many different in-memory approaches that optimize cache misses instead of disk I/O, as opposed to disk-based systems, and make use of the grown parallel capabilities of modern CPUs. However, these techniques mainly focus on single-key lookups, but neglect equally important range queries. Range queries are an ubiquitous operator in data management commonly used in numerous domains, such as genomic analysis, sensor networks, or online analytical processing. The main goal of this dissertation is thus to improve the capabilities of main-memory database systems with regard to executing range queries. To this end, we first propose a cache-optimized, updateable main-memory index structure, the cache-sensitive skip list, which targets the execution of range queries on single database columns. Second, we study the performance of multidimensional range queries on modern hardware, where data are stored in main memory and processors support SIMD instructions and multi-threading. We re-evaluate a previous rule of thumb suggesting that, on disk-based systems, scans outperform index structures for selectivities of approximately 15-20% or more. To increase the practical relevance of our analysis, we also contribute a novel benchmark consisting of several realistic multidimensional range queries applied to real- world genomic data. Third, based on the outcomes of our experimental analysis, we devise a novel, fast and space-effcient, main-memory based index structure, the BB- Tree, which supports multidimensional range and point queries and provides a parallel search operator that leverages the multi-threading capabilities of modern CPUs.

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Avoodaiappan, Murugiah. "Performance evaluation of hierarchical datacubes for range-sum queries /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1559859531&sid=11&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Norelius, Jenny, and Antonello Tacchi. "Evaluating data structures for range queries in brain simulations." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229767.

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Our brain and nervous system is a vital organ to us, since it is from there our thoughts, personalities, and other mental capacities originate. Within this field of neuroscience a common method of study is to build and run large scale brain simulations where up to hundred thousand neurons are used to produce a model of a brain in three dimensional space. To find all neurites within a specific area is to perform a range query. A vast number of range queries are required when running brain simulations which makes it important that the data structure used to store the simulated neurons is efficient. This study evaluate three common data structures, also called spatial index; the R-tree, Quadtree and R*-tree (Rstar-tree). We test their performance for range queries with regards to execution time, incurred reads, build time, size of data and density of data. The data used is models of a typical neuron so that the characteristics of the data set is preserved. The results show that the R*-tree outperforms the other indices by being significantly more efficient compared to the others, with the R-tree having slightly worse performance than the Quadtree. The time it takes to build the index is to be almost identical for all implementations.
Vår hjärna och nervsystem är ett grundläggande organ för oss. Det är där ifrån våra tankar, personligheter och mentala kapaciteter kommer ifrån. Inom neurovetenskap är en vanlig forskningsmetod att köra storskaliga hjärnsimuleringar där hundratusentals neuroner används för att skapa en modell av hjärnan i 3D. För att hitta alla neuroner inom en viss area används en så kallad intervallfråga. En stor mängd intervallfrågor behövs för hjärnsimuleringar vilket gör det viktigt att datastrukturerna som används för detta är kostnadseffektiva. Denna studie har som mål att jämföra tre stycken vanliga datastrukturer som används för intervallfrågor. Dessa är R-tree, Quadtree och R*-tree. Deras prestanda testas för exekveringstid, antal läsningar, konstruktionstid, samt storlek och densitet på neuroner. För att skapa hjärnsimuleringen används en typisk neuron som standard sådant att dess karakteristiska egenskaper bevaras. Resultaten från studien visar att R*-tree hade den tydligt bästa prestandan för de givna kriterierna, och att Quadtree har en något bättre prestanda än R-tree. Tiden det tar att mata in neuronerna i datastrukturerna är i stort sett densamma.

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Lamoureux, Michael G. "Dynamic data structures for generalized range queries on orthogonal data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0021/NQ54595.pdf.

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Wong, Wing Sing. "K-nearest-neighbor queries with non-spatial predicates on range attributes /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?COMP%202005%20WONGW.

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Norberg, Jesper. "Generating geospatial heatmaps : Optimizing point-region quadtrees for window queries." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172815.

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This study aims to investigate and identify how to effectively generate blurred geospatial heatmaps for use in geo-spatial map engines. We focus on how to store the points in a way that facilitates efficient window querying, with support for zoom-level handling. We decide on primarily using a Morton-ordered variant of the point-region quadtree, which we name a HeatMap Quadtree (HMQ). The nodes of the HMQ each have access to the points they contain, through storing the number of points and the lower bound of where to look at in the input point set, which we also store in Morton order. The HMQ also has the functionality to allow for window querying at different levels of detail. We parallelize the generation of the HMQ as well as the Gaussian blurring of the raster resulting from the window query using CUDA, and compare this implementation with that of two naive solutions as well as a linear point-region quadtree. In conclusion we find that the HMQ provides a significant improvement in window querying time, at the cost of additional construction time.
Denna studie avser att undersöka och identifiera hur man effektivt kan generera Gaussiskt oskarpa geospatiala värmekartor för användning i geospatiala kartmotorer. Vi fokuserar på hur man ska lagra punkterna på ett sätt som underlättar effektiv `window querying', med stöd för zoomnivå-hantering. Vi bestämmer oss för att huvudsakligen använda oss av en Morton-ordnad variant av ett `point-region quadtree', vilket vi döper till `HeatMap Quadtree' (HMQ). Noderna i vårt HMQ har alla tillgång till punkterna dom innehåller, genom att lagra antalet punkter och den lägre gränsen för var man ska leta efter punkterna i den ursprunliga punktlistan, som vi också lagrar i Morton-ordning. Vårt HMQ har också funktionaliteten att tillåta `window querying' på olika detaljnivåer. Vi parallelliserar genererandet av vårt HMQ samt uträknandet av den Gaussiska oskärpan på rastret som resulterar från vår `window query' med hjälp av CUDA, och jämför denna implementation med två naiva lösningar samt ett linjärt `point-region quadtree'. Vår slutsats är att vårt HMQ ger en signifikant förbättring i `window query'-tid, till en kostnad av extra konstruktionstid.

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Books on the topic "Point and Range Queries"

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Guibas, Leonidas. Ray shooting, implicit point location, and related queries in arrangements of segments. New York: Courant Institute of Mathematical Sciences, New York University, 1989.

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E, Mitchell John. Robustness of the point-line method for monitoring basal cover. Fort Collins, Colo: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1994.

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E, Mitchell John. Robustness of the point-line method for monitoring basal cover. Fort Collins, Colo: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1994.

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Mitchell, John E. Robustness of the point-line method for monitoring basal cover. Fort Collins, Colo: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1994.

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E, Mitchell John. Robustness of the point-line method for monitoring basal cover. Fort Collins, Colo: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1994.

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E, Mitchell John. Robustness of the point-line method for monitoring basal cover. Fort Collins, Colo: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1994.

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Buckley, Winston Hamlett. An integration, long range planning, and migration guide for the stock point logistics integrated communications project. Monterey, Calif: Naval Postgraduate School, 1986.

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Williams, William A. Preserving range and airspace access for the Air Force mission: Striving for a strategic vantage point. Santa Monica, CA: RAND, 2011.

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Muchoki, C. H. K. A preliminary survey of the efficiency of three methods used in studying rangeland vegetation: The quadrat, point centre quarter, and line transect methods. [Nairobi]: Dept. of Resource Surveys and Remote Sensing (KREMU), Ministry of Planning and National Development, Kenya, 1988.

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Saribun, Daud S. Hubungan kandungan mineral-mineral ordo kisaran pendek (short range order minerals) dengan muatan titik nol (zero point of charge) pada andisol: Laporan penelitian. [Jatinangor]: Fakultas Pertanian, Universitas Padjadjaran, 1997.

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Book chapters on the topic "Point and Range Queries"

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Lee, Guanling, Yi-Chun Chen, and Chung Chi Lee. "Supporting Similarity Range Queries Efficiently by Using Reference Points in Structured P2P Overlays." In Advances in Intelligent Systems and Applications - Volume 1, 645–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35452-6_65.

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Laaksonen, Antti. "Range Queries." In Undergraduate Topics in Computer Science, 119–29. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-72547-5_9.

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Laaksonen, Antti. "Range Queries." In Undergraduate Topics in Computer Science, 127–37. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39357-1_9.

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Raman, Rajeev. "Range Extremum Queries." In Lecture Notes in Computer Science, 280–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35926-2_30.

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Skala, Matthew. "Array Range Queries." In Lecture Notes in Computer Science, 333–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40273-9_21.

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Kerschbaum, Florian. "Private Range Queries." In Encyclopedia of Cryptography, Security and Privacy, 1–3. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27739-9_1475-1.

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Patil, Manish, Rahul Shah, and Sharma V. Thankachan. "Faster Range LCP Queries." In String Processing and Information Retrieval, 263–70. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02432-5_29.

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Lai, Ying Kit, Chung Keung Poon, and Benyun Shi. "Approximate Colored Range Queries." In Algorithms and Computation, 360–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11602613_37.

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Jo, Seungbum, Shay Mozes, and Oren Weimann. "Compressed Range Minimum Queries." In String Processing and Information Retrieval, 206–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00479-8_17.

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Külekci, M. Oğuzhan. "Inverse Range Selection Queries." In String Processing and Information Retrieval, 166–77. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46049-9_17.

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Conference papers on the topic "Point and Range Queries"

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Mathioudakis, Michael, Dimitris Sacharidis, and Timos Sellis. "A study on workload-aware wavelet synopses for point and range-sum queries." In the 9th ACM international workshop. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1183512.1183519.

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Alam, Maksudul, Srikanth B. Yoginath, and Kalyan S. Perumalla. "Performance of Point and Range Queries for In-memory Databases Using Radix Trees on GPUs." In 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2016. http://dx.doi.org/10.1109/hpcc-smartcity-dss.2016.0212.

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Ttito, Josue Joel, Renato Marroquin, and Sergio Lifschitz. "Query co-planning for shared execution in Key-Value Stores." In XXXV Simpósio Brasileiro de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/sbbd.2020.13643.

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Key-value stores propose a very simple yet powerful data model. Data is modeled using key-value pairs where values can be arbitrary objects and can be written/read using the key associated with it. In addition to their simple interface, such data stores also provide read operations such as full and range scans. However, due to the simplicity of its interface, trying to optimize data accesses becomes challenging. This work aims to enable the shared execution of concurrent range and point queries on key-value stores. Thus, reducing the overall data movement when executing a complete workload. To accomplish this, we analyze different possible data structures and propose our variation of a segment tree, Updatable Interval Tree. This data structure helps us co-planning and co-executing multiple range queries together, as we show in our evaluation.

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Xirouchakis, Paul C. "Constrained Structural Design Databases." In ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium collocated with the ASME 1995 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/edm1995-0852.

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Abstract The technology of constrained databases (CDBs) is employed in the design of structural design databases. To illustrate the application of CDBs in structural design, the following example is considered in some detail: the design of a database for combined stiffener-plate sectional properties. A major drawback of relational database technology (RDBs) for engineering applications is that constraints cannot be processed within the data model. Another major drawback of the relational data model for engineering applications is that it only can incorporate attributes with discrete value set i.e. it cannot represent effectively variables with a continuous range. To remedy this situation, we propose the use of CDBs which are extended RDBs (so that they retain the advantages of RDBs) that can process arithmetic constraints in both relations and queries. CDBs can represent infinite point sets through the respective constraints on variables with a continuous range. We provide the database schema specification and specification for a number of typical queries for the example problem of combined stiffener-plate sectional properties database. We also specify constraints in the data models that model structural stability and manufacturing constraints.

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Suryanarayanan, Vinoth, Rob Minson, and Georgios K. Theodoropoulus. "Synchronised Range Queries." In 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications. IEEE, 2009. http://dx.doi.org/10.1109/ds-rt.2009.31.

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Stougiannis, Alexandros, Farhan Tauheed, Thomas Heinis, and Anastasia Ailamaki. "Accelerating spatial range queries." In the 16th International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2452376.2452461.

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Ferrada, Hector, and Gonzalo Navarro. "Improved Range Minimum Queries." In 2016 Data Compression Conference (DCC). IEEE, 2016. http://dx.doi.org/10.1109/dcc.2016.42.

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Patil, Manish, Sharma V. Thankachan, Rahul Shah, Yakov Nekrich, and Jeffrey Scott Vitter. "Categorical range maxima queries." In SIGMOD/PODS'14: International Conference on Management of Data. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2594538.2594557.

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Pagel, Bernd-Uwe, and Hans-Werner Six. "Are window queries representative for arbitrary range queries?" In the fifteenth ACM SIGACT-SIGMOD-SIGART symposium. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/237661.237704.

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Yung, Duncan, Eric Lo, and Man Lung Yiu. "Authentication of moving range queries." In the 21st ACM international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2396761.2398441.

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Reports on the topic "Point and Range Queries"

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Kipnis, Shlomo. Three Methods for Range Queries in Computational Geometry. Fort Belvoir, VA: Defense Technical Information Center, March 1989. http://dx.doi.org/10.21236/ada210830.

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Koski, William R., John W. Lawson, Denis H. Thomson, and W. Richardson. Point Mugu Sea Range Marine Mammal Technical Report. Fort Belvoir, VA: Defense Technical Information Center, December 1998. http://dx.doi.org/10.21236/ada413894.

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DOE. Corrective Action Decision Document for Corrective Action Unit 423: Building 03-60 Underground Discharge Point, Tonopah Test Range, Nevada. Office of Scientific and Technical Information (OSTI), June 1999. http://dx.doi.org/10.2172/9595.

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Bechtel Nevada. Corrective Action Plan for Corrective Action Unit 423: Area 3 Building 03-60 Underground Discharge Point, Tonopah Test Range, Nevada. Office of Scientific and Technical Information (OSTI), October 1998. http://dx.doi.org/10.2172/4606.

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DOE. Corrective Action Investigation Plan for Corrective Action Unit No. 423: Building 03-60 Underground Discharge Point, Tonopah Test Range, Nevada. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/16838.

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Kidman, Lynn. Addendum to the Closure Report for Corrective Action Unit 423: Area 3 Building 03-60 Underground Discharge Point, Tonopah Test Range, Nevada, Revision 0. Office of Scientific and Technical Information (OSTI), October 2008. http://dx.doi.org/10.2172/945280.

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Anderson, A. V. Geologic map and cross-sections: Headwaters of the Kongakut and Aichilik rivers, Demarcation Point (A-4) and Table Mountain (D-4) quadrangles, eastern Brooks Range, Alaska. Alaska Division of Geological & Geophysical Surveys, 1991. http://dx.doi.org/10.14509/1470.

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Bechtel Nevada. Record of Technical Change for Closure Report for Corrective Action Unit 423: Area 3 Building 03-60 Underground Discharge Point, Tonopah Test Range, Nevada (July 1999, DOE/NV/11718--319). Office of Scientific and Technical Information (OSTI), June 2005. http://dx.doi.org/10.2172/841186.

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Rodier, Caroline, Andrea Broaddus, Miguel Jaller, Jeffery Song, Joschka Bischoff, and Yunwan Zhang. Cost-Benefit Analysis of Novel Access Modes: A Case Study in the San Francisco Bay Area. Mineta Transportation Institute, November 2020. http://dx.doi.org/10.31979/mti.2020.1816.

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The first-mile, last-mile problem is a significant deterrent for potential transit riders, especially in suburban neighborhoods with low density. Transit agencies have typically sought to solve this problem by adding parking spaces near transit stations and adding stops to connect riders to fixed-route transit. However, these measures are often only short-term solutions. In the last few years, transit agencies have tested whether new mobility services, such as ridehailing, ridesharing, and microtransit, can offer fast, reliable connections to and from transit stations. However, there is limited research that evaluates the potential impacts of these projects. Concurrently, there is growing interest in the future of automated vehicles (AVs) and the potential of AVs to solve this first-mile problem by reducing the cost of providing these new mobility services to promote access to transit. This paper expands upon existing research to model the simulate the travel and revenue impacts of a fleet of automated vehicles that provide transit access services in the San Francisco Bay Area offered over a range of fares. The model simulates a fleet of AVs for first-mile transit access at different price points for three different service models (door-to-door ridehailing and ridesharing and meeting point ridesharing services). These service models include home-based drop-off and pick-up for single passenger service (e.g., Uber and Lyft), home-based drop-off and pick-up for multi-passenger service (e.g., microtransit), and meeting point multi-passenger service (e.g., Via).

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Slater, Anne-Michelle. Passport to the oceans of the future: delivering marine energy with science linked to policy. Marine Alliance for Science and Technology for Scotland (MASTS), July 2021. http://dx.doi.org/10.15664/10023.23980.

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In February 2021, a group from MASTS, Environmental Interactions of Marine Renewables (EIMR) and Marine Scotland began exploring options for a joint event on marine energy science and policy development. The original concept was to bridge the gap between events that each group would normally arrange ‘in person’ and the virtual world in which we were all currently existing. Encouraged by the online support and experience available from MASTS, a steering group decided to arrange a workshop. In order to straddle our interests, the starting point was the capacity of the North Sea to deliver renewable energy. We wanted to include emerging science and the timing of the review of Scotland’s National Marine Plan provided an excellent context. We sought to deliver a wide range of content but encourage participant conversation. We aimed for a range of speakers delivering 7-minute recorded talks. Talks included findings from funded research, ongoing projects, and some emerging thinking across the science policy interface for marine planning. Marine energy was interpreted in the widest of senses, but the main focus was on offshore wind in UK waters, with particular detail about Scotland.

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