Academic literature on the topic 'Key-value database'

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Journal articles on the topic "Key-value database"

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Osemwegie, Omoruyi, Kennedy Okokpujie, Nsikan Nkordeh, Charles Ndujiuba, Samuel John, and Uzairue Stanley. "Performance Benchmarking of Key-Value Store NoSQL Databases." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 5333. http://dx.doi.org/10.11591/ijece.v8i6.pp5333-5341.

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<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given va
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Zhou, Peng, Mei Li, Jing Huang, and Hua Fang. "Research on Database Schema Comparison of Relational Databases and Key-Value Stores." Advanced Materials Research 1049-1050 (October 2014): 1860–63. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1860.

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With the rapid development of Internet technology, the management capacity of traditional relational databases becomes relatively inefficient when facing the access and processing of big data. As a kind of non-relational databases, the key-value stores, with its high scalability, provide an efficient solution to the problem. This article introduces the concept and features of Key-Value stores, and followed by the comparison with the traditional relational databases, and an example is illustrated to explain its typical application and finally the existing problems of Key-Value stores are summar
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Iliakis, Konstantinos, Konstantina Koliogeorgi, Antonios Litke, Theodora Varvarigou, and Dimitrios Soudris. "GPU accelerated blockchain over key‐value database transactions." IET Blockchain 2, no. 1 (2022): 1–12. http://dx.doi.org/10.1049/blc2.12011.

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Dourhri, Ahmed, Mohamed Hanine, and Hassan Ouahmane. "KVMod—A Novel Approach to Design Key-Value NoSQL Databases." Information 14, no. 10 (2023): 563. http://dx.doi.org/10.3390/info14100563.

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The growth of structured, semi-structured, and unstructured data produced by the new applications is a result of the development and expansion of social networks, the Internet of Things, web technology, mobile devices, and other technologies. However, as traditional databases became less suitable to manage the rapidly growing quantity of data and variety of data structures, a new class of database management systems named NoSQL was required to satisfy the new requirements. Although NoSQL databases are generally schema-less, significant research has been conducted on their design. A literature
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송경태 and Sanghyun Park. "A Recent Trend of Database for Big Data Handling using Key-value database." Journal of Knowledge Information Technology and Systems 12, no. 1 (2017): 47–57. http://dx.doi.org/10.34163/jkits.2017.12.1.005.

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Wang, Jiangning, Congtian Lin, Yan Han, and Liqiang Ji. "Discussion of the Method for Constructing Animal Traits." Biodiversity Information Science and Standards 2 (April 25, 2018): e26168. https://doi.org/10.3897/biss.2.26168.

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Trait data in biology can be extracted from text and structured for reuse within and across taxa. For example, body length is one trait applicable to many species and "body length is about 170 cm" is one trait data point for the human species. Trait data can be used in more detailed analyses to describe species evolution and development processes, so it has begun to be valued by more than taxonomists. The EOL (Encyclopedia of Life) TraitBank provides an example of a trait database. Current trait databases are in their infancy. Most are based on morphological data such as shape, color, structur
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Liu, Qian. "A High Performance Memory Key-Value Database Based on Redis." Journal of Computers 14, no. 3 (2019): 170–83. http://dx.doi.org/10.17706/jcp.14.3.170-183.

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Kelly, Terence. "Crashproofing the Original NoSQL Key-Value Store." Queue 19, no. 4 (2021): 5–18. http://dx.doi.org/10.1145/3487019.3487353.

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This episode of Drill Bits unveils a new crash-tolerance mechanism that vaults the venerable gdbm database into the league of transactional NoSQL data stores. We'll motivate this upgrade by tracing gdbm's history. We'll survey the subtle science of crashproofing, navigating a minefield of traps for the unwary. We'll arrive at a compact and rugged design that leverages modern file-system features, and we'll tour the production-ready implementation of this design and its ergonomic interface.
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Fruth, Michael, and Stefanie Scherzinger. "Live Patching for Distributed In-Memory Key-Value Stores." Proceedings of the ACM on Management of Data 2, no. 6 (2024): 1–26. https://doi.org/10.1145/3698816.

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Providers of high-availability data stores need to roll out software updates without causing noticeable downtimes. For distributed data stores like Redis Cluster, the state-of-the-art is a rolling update, where the nodes are restarted in sequence. This requires preserving, restoring, and resynchronizing the database state, which can significantly prolong updates for larger memory states, and thus delay critical security fixes. In this article, we propose applying software updates directly in memory without restarting any nodes. We present the first fully operational live patching solution for
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Malykh, Mikhail D., Anton L. Sevastianov, and Leonid A. Sevastianov. "About Symbolic Integration in the Course of Mathematical Analysis." Computer tools in education, no. 4 (December 28, 2019): 94–106. http://dx.doi.org/10.32603/2071-2340-2019-4-94-106.

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The work of transforming a database from one format periodically appears in different organizations for various reasons. Today, the mechanism for changing the format of relational databases is well developed. But with the advent of new types of database such as NoSQL, this problem was exacerbated due to the radical difference in the way data was organized. This article discusses a formalized method based on set theory, at the choice of the number and composition of collections for a key-value type database. The initial data are the properties of the objects, information about which is stored i
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Dissertations / Theses on the topic "Key-value database"

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Rose, Kyle R. (Kyle Robert) 1976. "Asynchronous generic key/value database." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86633.

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Hsiue, Kevin D. "FPGA-based hardware acceleration for a key-value store database." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91829.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 89-90).<br>As the modern world processes larger amounts of data and demand increases for better transaction performance, a growing number of innovative solutions in the field of database technologies have been discovered and implemented. In software and systems design, the development and deployment of the NoSQL (Not Only SQL) database challenged yesterday's relational database and answere
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Jansson, Jens, Alexandar Vukosavljevic, and Ismet Catovic. "Performance comparison between multi-model, key-value and documental NoSQL database management systems." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19857.

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This study conducted an experiment that compares the multi-model NoSQL DBMS ArangoDB with other NoSQL DBMS, in terms of the average response time of queries. The DBMS compared in this experiment are the following: Redis, MongoDB, Couchbase, and OrientDB. The hypothesis that is answered in this study is the following: “There is a significant difference between ArangoDB, OrientDB, Couchbase, Redis, MongoDB in terms of the average response time of queries”. This is examined by comparing the average response time of 1 000, 100 000, and 1 000 000 queries between these database systems. The results
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Klapač, Milan. "Výhody a nevýhody relačních a nerelačních (noSQL) databází pro analytické úlohy." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-193931.

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This work focuses on NoSQL databases, their use for analytical tasks and on comparison of NoSQL databases with relational and OLAP databases. The aim is to analyse the benefits of NoSQL databases and their use for analytical purposes. The first part presents the basic principles of Business Intelligence, Data Warehousing, and Big Data. The second part deals with the key features of relational and NoSQL databases. The last part of the thesis describes the properties of four basic types of NoSQL databases, analyses their advantages, disadvantages and areas of application. The end of this part in
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Balmau, Oana Maria. "Redesigning Persistent Key-Value Stores for Future Workloads, Hardware, and Performance Requirements." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/22913.

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Cloud storage stacks are being challenged by new workloads, new hardware, and new performance requirements. First, workloads evolved from following a read-heavy pattern (e.g., a static web-page) to a write-heavy profile where the read:write ratio is closer to 1:1 (e.g., as in the Internet of Things). Second, the hardware is undergoing rapid changes. The divide between fine-grained volatile memory and slow block-level storage is rapidly being bridged by the emerging byte-addressable non-volatile memory devices and the fast block-addressable NVMe SSDs (e.g., Intel Optane NVMe SSDs). Third, perf
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Zhu, Sainan. "Creating a NoSQL database for the Internet of Things : Creating a key-value store on the SensibleThings platform." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25525.

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Due to the requirements of the Web 2.0 applications and the relational databaseshave a limitation in horizontal scalability. NoSQL databases have become moreand more popular in recent years. However, it is not easy to select a databasethat is suitable for a specific use. This thesis describes the detailed design, im plementation and final performance evaluation of a key-value NoSQL databasefor the SensibleThings platform, which is an Internet of Things platform. Thethesis starts by comparing the different types of NoSQL databases to select themost appropriate one. During the implementation of
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Smailji, Liridon. "Performance comparison of differentNoSQL structure orientations." Thesis, Högskolan Kristianstad, Fakulteten för naturvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-20971.

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This study proposes a performance comparison between the different structures of NoSQL databases; document, key-value, column and graph. A second study is also conducted, when looking at performance comparison between three different NoSQL databases, all of the same structure; document based, the databases that are tested here are; MongoDB, OrientDB and Couchbase. Performance tests are conducted using a benchmarking tool YCSB (Yahoo! Cloud Serving Benchmark), and by looking at time to execute and throughput (operations/ second). Beside benchmarking literature reviews are conducted to be able t
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Mormone, Giovanni. "Sistemi NoSQL:motivazioni, tecnologie e possibili impieghi." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15724/.

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Per oltre quarant'anni il modello relazionale è stato il punto di riferimento per la gestione dei dati all'interno dei sistemi informatici. Con lo sviluppo di internet ed il successivo avvento del web 2.0, è cresciuta esponenzialmente la necessità di gestire grandi moli di dati in rete, in un ambiente dinamico ed in cui ogni utente diventa, oltre che fruitore, anche generatore di contenuti. Le richieste di flessibilità e indipendenza dagli schemi, favorite dalla mancanza di struttura e coerenza dei dati generati in rete hanno messo a nudo le difficoltà, che saranno approfondite nel corso di qu
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Persson, Ragnvald. "NoSQL-databaser i socialt nätverk." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20692.

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Syftet med studien är att göra en fördjupning inom NoSQL-databaser och undersöka vilka uppgifter som de olika NoSQL-grupperna passar bäst till i ett socialt nätverk, som t.ex. Facebook och Twitter. Det finns fyra olika typer av NoSQL-databaser: kolumndatabaser, grafdatabaser, nyckelvärdedatabaser och dokumentdatabaser. Frågan är vilken NoSQL-databas ska man välja till en viss uppgift i ett givet socialt nätverk. När man ska utveckla ett socialt nätverk, som kräver lagring av data, är det viktigt att känna till vilken typ av databas som bör användas till en vis typ av uppgift. För att få svar p
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Toney, Ethan. "Improving Table Scans for Trie Indexed Databases." UKnowledge, 2018. https://uknowledge.uky.edu/cs_etds/76.

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We consider a class of problems characterized by the need for a string based identifier that reflect the ontology of the application domain. We present rules for string-based identifier schemas that facilitate fast filtering in databases used for this class of problems. We provide runtime analysis of our schema and experimentally compare it with another solution. We also discuss performance in our solution to a game engine. The string-based identifier schema can be used in addition scenarios such as cloud computing. An identifier schema adds metadata about an element. So the solution hinges on
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Books on the topic "Key-value database"

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Xu, Chen, and Aoying Zhou. Quality-Aware Scheduling for Key-value Data Stores. Springer London, Limited, 2015.

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Quality-aware Scheduling for Key-value Data Stores. Springer, 2015.

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Book chapters on the topic "Key-value database"

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Sacco, Andres. "Redis: Key/Value Database." In Beginning Spring Data. Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8764-4_7.

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Xu, Chen, Mohamed A. Sharaf, Minqi Zhou, Aoying Zhou, and Xiaofang Zhou. "Adaptive Query Scheduling in Key-Value Data Stores." In Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37487-6_9.

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Ooley, Nathan, Nick Tichawa, and Brian Miller. "Basic Setup of iCloud and Key-Value Storage." In Beginning iOS Cloud and Database Development. Apress, 2014. http://dx.doi.org/10.1007/978-1-4302-4114-0_4.

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Takeuchi, Susumu, Jun Shinomiya, Toru Shiraki, et al. "A Large Scale Key-Value Store Based on Range-Key Skip Graph and Its Applications." In Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12098-5_43.

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Li, Jiaoyang, Yinliang Yue, and Weiping Wang. "GHStore: A High Performance Global Hash Based Key-Value Store." In Database Systems for Advanced Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-00123-9_39.

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Li, Jiaoyang, Yinliang Yue, and Weiping Wang. "GHStore: A High Performance Global Hash Based Key-Value Store." In Database Systems for Advanced Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-00123-9_39.

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Zhao, Zihao, Chuan Hu, Zhihong Shen, Along Mao, and Hao Ren. "A Key-Value Based Approach to Scalable Graph Database." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39847-6_26.

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Chang, Dong, Yanfeng Zhang, and Ge Yu. "MaiterStore: A Hot-Aware, High-Performance Key-Value Store for Graph Processing." In Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43984-5_9.

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Wang, Jiangtao, Zhiliang Guo, and Xiaofeng Meng. "SASS: A High-Performance Key-Value Store Design for Massive Hybrid Storage." In Database Systems for Advanced Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18120-2_9.

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Huang, Chenchen, Huiqi Hu, Xuecheng Qi, Xuan Zhou, and Aoying Zhou. "RS-store: A SkipList-Based Key-Value Store with Remote Direct Memory Access." In Database Systems for Advanced Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59410-7_22.

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Conference papers on the topic "Key-value database"

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Piyawarapong, Piraboon, and Somchart Fugkeaw. "Optimizing Database Image Retrieval with In-Memory Key-Value Store, Image Compression, and Smart Cache Updater Algorithm." In 2025 17th International Conference on Knowledge and Smart Technology (KST). IEEE, 2025. https://doi.org/10.1109/kst65016.2025.11003319.

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Hu, Hao, Kai Lu, Gen Li, Xiaoping Wang, and Tianye Xu. "CAAC: A Key-Value Database Performance Boosting Algorithm." In 2012 Fourth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccis.2012.97.

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Moreno, Julio, Eduardo B. Fernandez, Eduardo Fernandez-Medina, and Manuel A. Serrano. "A Security Pattern for Key-Value NoSQL Database Authorization." In EuroPLoP '18: 23rd European Conference on Pattern Languages of Programs. ACM, 2018. http://dx.doi.org/10.1145/3282308.3282321.

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Polyakov, Artem Y., Alexandr V. Efimov, Konstantin E. Kramarenko, and Kirill V. Pavsky. "Key-Value Database Access Optimization For PMIx Standard Implementation." In 2021 IEEE Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). IEEE, 2021. http://dx.doi.org/10.1109/usbereit51232.2021.9455075.

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Thanh, Ta Minh, Nguyen Huu Thuy, and Ngoc-Tu Huynh. "Key-value based data hiding method for NoSQL database." In 2018 10th International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2018. http://dx.doi.org/10.1109/kse.2018.8573334.

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Hui-jun, Wu, Lu Kai, Jiang Jing-fei, and Wang Shuang-xi. "Agent-Based Fault Tolerance Mechanism for Distributed Key-Value Database." In 2014 5th International Conference on Digital Home (ICDH). IEEE, 2014. http://dx.doi.org/10.1109/icdh.2014.58.

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Zhao, Xin, Kai Lu, Xiao-Ping Wang, and Gen Li. "GSkiplist: A GPU-method to accelerate key-value database search." In International Conference on Computer Science, Technology and Application (CSTA2016). WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813200449_0045.

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Puangsaijai, Wittawat, and Sutheera Puntheeranurak. "A comparative study of relational database and key-value database for big data applications." In 2017 International Electrical Engineering Congress (iEECON). IEEE, 2017. http://dx.doi.org/10.1109/ieecon.2017.8075813.

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Alami, Alae El, Mohamed Bahaj, and Younes Khourdifi. "Supply of a key value database redis in-memory by data from a relational database." In 2018 19th IEEE Mediterranean Electrotechnical Conference (MELECON). IEEE, 2018. http://dx.doi.org/10.1109/melcon.2018.8379066.

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Kruber, Nico, Florian Schintke, and Michael Berlin. "A relational database schema on the transactional key-value store scalaris." In 2014 IEEE International Conference on Big Data (Big Data). IEEE, 2014. http://dx.doi.org/10.1109/bigdata.2014.7004441.

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Reports on the topic "Key-value database"

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Cogan, Dan, and Dan Cogan. Vegetation mapping inventory project: Death Valley National Park. National Park Service, 2024. https://doi.org/10.36967/2306941.

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This study presents a comprehensive vegetation mapping inventory project undertaken in Death Valley National Park (DEVA) within the National Park Service?s Mojave Desert Network (MOJN). Spanning 3.4 million acres across California and Nevada, DEVA is the largest national park in the contiguous United States. Renowned for its harsh environment?characterized by intense heat, aridity, and low elevation?DEVA encompasses a variety of landscapes, including playas, alluvial fans, sand dunes, and mountain ranges. Despite its desolate appearance, the park harbors a diverse array of vegetation, with pla
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Iammarino, Simona, Sumontheany MUTH, and Kosal NITH. 20 Years of FDI in Cambodia: Towards Upper Middle-Income Status and Beyond. Cambodia Development Resource Institute, 2024. https://doi.org/10.64202/wp.149.202410.

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Although Cambodia has a strong ambition to become an upper middle-income nation by 2030 and a high income by 2050, it faces various challenges in achieving these goals. This study investigates Cambodia’s progress and potential in this regard by analysing its position and trajectory relative to Greenfield Foreign Direct Investment (FDI) inflows and outflows – where foreign firms establish new operations in Cambodia and Cambodian investors set up businesses abroad. This study also provides preliminary insights on Cambodia's integration into Global and Regional Value Chains (GVCs), always using F
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LaBonte, Don, Etan Pressman, Nurit Firon, and Arthur Villordon. Molecular and Anatomical Characterization of Sweetpotato Storage Root Formation. United States Department of Agriculture, 2011. http://dx.doi.org/10.32747/2011.7592648.bard.

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Original objectives: Anatomical study of storage root initiation and formation. Induction of storage root formation. Isolation and characterization of genes involved in storage root formation. During the normal course of storage root development. Following stress-induced storage root formation. Background:Sweetpotato is a high value vegetable crop in Israel and the U.S. and acreage is expanding in both countries and the research herein represents an important backstop to improving quality, consistency, and yield. This research has two broad objectives, both relating to sweetpotato storage root
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Langlais, Pierre-Carl. Open Scientific Data. Comité pour la science ouverte, 2023. https://doi.org/10.52949/69.

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Not opening scientific data is costly. It has been estimated that a significant share of scientific knowledge disappears every year. In a 2014 study less than half of biological datasets from the 1990s have been recovered and when possible the recovery has necessitated significant time and efforts. In comparison, 98% of datasets published on PLOS with unique identifiers (data DOIs) are still available for future research. Open scientific data are fundamental resources for a large variety of scientific activities: meta-analysis, replication of research results or accessibility to primary source
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Burak, Leonid Ch, and Nataliya L. Ovsyannikova. Modern methods of storage and packaging of garden strawberries (Fragaria × ananassa Duch.) (review). Contemporary horticulture, 2024. https://doi.org/10.12731/2312-6701-266171.

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Postharvest treatment of garden strawberries and the development of effective storage methods are crucial to increase the shelf life and preserve its quality until consumption. Although some reviews on certain treatment technologies have been published, we have not found studies that considered and compared common and advanced methods of storing garden strawberries. Therefore, the goal of this study is to review modern postharvest methods of strawberry storage (Fragaria × ananassa Duch). The review includes reports published in English and Russian in 2014—2024. PubMed, Scopus, Web of Science,
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Downes, Jane, ed. Chalcolithic and Bronze Age Scotland: ScARF Panel Report. Society for Antiquaries of Scotland, 2012. http://dx.doi.org/10.9750/scarf.09.2012.184.

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The main recommendations of the panel report can be summarised under five key headings:  Building the Scottish Bronze Age: Narratives should be developed to account for the regional and chronological trends and diversity within Scotland at this time. A chronology Bronze Age Scotland: ScARF Panel Report iv based upon Scottish as well as external evidence, combining absolute dating (and the statistical modelling thereof) with re-examined typologies based on a variety of sources – material cultural, funerary, settlement, and environmental evidence – is required to construct a robust and up to da
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Rankin, Nicole, Deborah McGregor, Candice Donnelly, et al. Lung cancer screening using low-dose computed tomography for high risk populations: Investigating effectiveness and screening program implementation considerations: An Evidence Check rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for the Cancer Institute NSW. The Sax Institute, 2019. http://dx.doi.org/10.57022/clzt5093.

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Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asy
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Honey authenticity: collaborative data sharing feasibility study. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.fbt231.

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According to the UN,1 there are more than 90 million managed beehives around the world producing about 1.9 million tonnes of honey worth more than £5 billion a year. That honey will then be packaged, as single origin or a blend of honey from different sources, and sold for consumption. Given the size of the market and the immense environmental benefits of beekeeping – three out of four crops depend on pollination by bees – it is an industry on which both livelihoods and lives depend. Target for adulteration As a labour-intensive, high-value expensive product with an often complex supply chain,
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