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Artículos de revistas sobre el tema "Information storage and retrieval systems"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 29 de julio de 2024

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1

Azubuike, Abraham A., and Jackson S. Umoh. "Computerized information storage and retrieval systems." International Library Review 20, no. 1 (January 1988): 101–10. http://dx.doi.org/10.1016/0020-7837(88)90046-5.

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2

Korfhage, Robert. "Book review: information storage and retrieval systems." XRDS: Crossroads, The ACM Magazine for Students 6, no. 5 (July 15, 2000): 4. http://dx.doi.org/10.1145/345107.345115.

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3

Arunarani, Ar, and D. Manjula Perkinian. "Intelligent Techniques for Providing Effective Security to Cloud Databases." International Journal of Intelligent Information Technologies 14, no. 1 (January 2018): 1–16. http://dx.doi.org/10.4018/ijiit.2018010101.

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Cloud databases have been used in a spate of web-based applications in recent years owing to their capacity to store big data efficiently. In such a scenario, access control techniques implemented in relational databases are so modified as to suit cloud databases. The querying features of cloud databases are designed with facilities to retrieve encrypted data. The performance with respect to retrieval and security needs further improvements to ensure a secured retrieval process. In order to provide an efficient secured retrieval mechanism, a rule- and agent-based intelligent secured retrieval

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4

Yang, Heecheol, Wonjae Shin, and Jungwoo Lee. "Private Information Retrieval for Secure Distributed Storage Systems." IEEE Transactions on Information Forensics and Security 13, no. 12 (December 2018): 2953–64. http://dx.doi.org/10.1109/tifs.2018.2833050.

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5

Park, Laurence A. F., and Kotagiri Ramamohanarao. "Efficient storage and retrieval of probabilistic latent semantic information for information retrieval." VLDB Journal 18, no. 1 (February 28, 2008): 141–55. http://dx.doi.org/10.1007/s00778-008-0093-2.

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6

Tian, Chao, Hua Sun, and Jun Chen. "A Shannon-Theoretic Approach to the Storage–Retrieval Trade-Off in PIR Systems." Information 14, no. 1 (January 11, 2023): 44. http://dx.doi.org/10.3390/info14010044.

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We consider the storage–retrieval rate trade-off in private information retrieval (PIR) systems using a Shannon-theoretic approach. Our focus is mostly on the canonical two-message two-database case, for which a coding scheme based on random codebook generation and the binning technique is proposed. This coding scheme reveals a hidden connection between PIR and the classic multiple description source coding problem. We first show that when the retrieval rate is kept optimal, the proposed non-linear scheme can achieve better performance over any linear scheme. Moreover, a non-trivial storage-re

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7

Guo, Tao, Ruida Zhou, and Chao Tian. "New Results on the Storage-Retrieval Tradeoff in Private Information Retrieval Systems." IEEE Journal on Selected Areas in Information Theory 2, no. 1 (March 2021): 403–14. http://dx.doi.org/10.1109/jsait.2021.3053217.

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8

Kovalcik, Justin, and Mike Villalobos. "Automated Storage & Retrieval System." Information Technology and Libraries 38, no. 4 (December 16, 2019): 114–24. http://dx.doi.org/10.6017/ital.v38i4.11273.

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The California State University, Northridge (CSUN) Oviatt Library was the first library in the world to integrate an automated storage and retrieval system (AS/RS) into its operations. The AS/RS continues to provide efficient space management for the library. However, added value has been identified in materials security and inventory as well as customer service. The concept of library as space, paired with improved services and efficiencies, has resulted in the AS/RS becoming a critical component of library operations and future strategy. Staffing, service, and security opportunities paired w

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9

Mitev, Nathalie N. "Information Storage and Retrieval Systems: Origin, Development and Applications." Journal of Information Technology 4, no. 4 (December 1989): 242–43. http://dx.doi.org/10.1057/jit.1989.39.

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10

Ellis, D. "Information storage and retrieval systems: Origin, development and applications." International Journal of Information Management 10, no. 2 (June 1990): 157–58. http://dx.doi.org/10.1016/0268-4012(90)90011-g.

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11

Travis, Irene. "From "Storage and Retrieval Systems" to "Search Engines": Text Retrieval in Evolution." Bulletin of the American Society for Information Science and Technology 24, no. 4 (January 31, 2005): 6. http://dx.doi.org/10.1002/bult.88.

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12

Wei, Yi-Peng, Batuhan Arasli, Karim Banawan, and Sennur Ulukus. "The Capacity of Private Information Retrieval from Decentralized Uncoded Caching Databases." Information 10, no. 12 (November 28, 2019): 372. http://dx.doi.org/10.3390/info10120372.

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We consider the private information retrieval (PIR) problem from decentralized uncoded caching databases. There are two phases in our problem setting, a caching phase, and a retrieval phase. In the caching phase, a data center containing all the K files, where each file is of size L bits, and several databases with storage size constraint μ K L bits exist in the system. Each database independently chooses μ K L bits out of the total K L bits from the data center to cache through the same probability distribution in a decentralized manner. In the retrieval phase, a user (retriever) accesses N d

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13

Riad, Khaled, and Lishan Ke. "Secure Storage and Retrieval of IoT Data Based on Private Information Retrieval." Wireless Communications and Mobile Computing 2018 (November 18, 2018): 1–8. http://dx.doi.org/10.1155/2018/5452463.

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The fast growth of Internet-of-Things (IoT) strategies has actually presented the generation of huge quantities of information. There should exist a method to conveniently gather, save, refine, and also provide such information. On the other hand, IoT data is sensitive and private information; it must not be available to potential attackers. We propose a robust scheme to guarantee both secure IoT data storage and retrieval from the untrusted cloud servers. The proposed scheme is based on Private Information Retrieval (PIR). It stores the data onto different servers and retrieves the requested

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14

Kiskani, Mohsen Karimzadeh, and Hamid R. Sadjadpour. "Secure and Private Information Retrieval (SAPIR) in Cloud Storage Systems." IEEE Transactions on Vehicular Technology 67, no. 12 (December 2018): 12302–12. http://dx.doi.org/10.1109/tvt.2018.2876683.

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15

Shirato, Linda, Sarah Cogan, and Sandra Yee. "The impact of an automated storage and retrieval system on public services." Reference Services Review 29, no. 3 (September 1, 2001): 253–61. http://dx.doi.org/10.1108/eum0000000006545.

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In June 1998, the Bruce T. Halle Library opened on Eastern Michigan University’s campus and began using an automated storage and retrieval system for low‐use books and periodicals. Approximately one third of the library’s total collection was placed into this storage system, freeing floor space for many new activities in the library. This system, linked to the library’s online catalog, could retrieve items requested by a patron in less than ten minutes. While the Automated storage/retrieval systems (AS/RS) performed well, other start‐up problems of a new building and public perceptions of the

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16

Sun, Hua, and Syed Ali Jafar. "Multiround Private Information Retrieval: Capacity and Storage Overhead." IEEE Transactions on Information Theory 64, no. 8 (August 2018): 5743–54. http://dx.doi.org/10.1109/tit.2018.2789426.

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17

Tian, Chao. "On the Storage Cost of Private Information Retrieval." IEEE Transactions on Information Theory 66, no. 12 (December 2020): 7539–49. http://dx.doi.org/10.1109/tit.2020.3015818.

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18

Pillay, Karan Ravindran, and Omkar Upendra Khadilkar. "The Scalable Image Retrieval Systems and Applications." International Journal of Engineering and Computer Science 7, ``11 (November 13, 2018): 24406–8. http://dx.doi.org/10.18535/ijecs/v7i11.03.

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Advances in information storage and image acquisition technologies have enabled the creation of enormous image datasets. during this situation, it's necessary to develop applicable data systems to with efficiency manage these collections. the most typical approaches use the supposed Content-Based Image Retrieval (CBIR) systems. Basically, these systems attempt to retrieve pictures like a user-defined specification or pattern (e.g., form sketch, image example). Their goal is to support image retrieval supported content properties (e.g., shape, color, texture), typically encoded into feature vec

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19

Minhas-Khan, Aamir, Morteza Ghafar-Zadeh, Tina Shaffaf, Saghi Forouhi, Anthony Scime, Sebastian Magierowski, and Ebrahim Ghafar-Zadeh. "UV-Vis Spectrophotometric Analysis of DNA Retrieval for DNA Storage Applications." Actuators 10, no. 10 (September 24, 2021): 246. http://dx.doi.org/10.3390/act10100246.

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Informational Deoxyribonucleic Acid (iDNA) has gained the attention of many researchers and pioneer companies for the development of novel storage systems for the long-term and high-density storing of information. This research focuses on the physical storage of iDNA strands to address some of the current challenges by evaluating the accuracy of the process of iDNA retrieval from the surface after the dehydration process. For this aim, a UV-Vis spectrophotometric technique was used to measure the concentration of the DNA samples. Although spectroscopy has been widely employed for the evaluatio

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20

Bergman, Ofer, Steve Whittaker, and Yaron Frishman. "Let’s get personal: the little nudge that improves document retrieval in the Cloud." Journal of Documentation 75, no. 2 (March 6, 2019): 379–96. http://dx.doi.org/10.1108/jd-06-2018-0098.

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Purpose State-of-the-art cloud applications are problematic for collaborative document management; their current design does not encourage active personal folder categorization. Cloud applications such as Google Drive and Microsoft’s OneDrive store documents automatically, so at no point are users directed to categorize them by placing them in folders. To encourage active categorization and promote effective retrieval of cloud documents, the authors designed an add-on “nudge” called Personal Organizer which prompts Google Drive users to categorize by storing cloud documents in personal folders

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21

Tajeddine, Razane, Oliver W. Gnilke, and Salim El Rouayheb. "Private Information Retrieval From MDS Coded Data in Distributed Storage Systems." IEEE Transactions on Information Theory 64, no. 11 (November 2018): 7081–93. http://dx.doi.org/10.1109/tit.2018.2815607.

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22

Mitev, Nathalie N. "Book Review: Information Storage and Retrieval Systems: Origin, Development and Applications." Journal of Information Technology 4, no. 4 (December 1989): 242–43. http://dx.doi.org/10.1177/026839628900400408.

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23

Wheeler, William J. "Book Review: A History of Information Storage and Retrieval." Library Resources & Technical Services 48, no. 1 (January 1, 2004): 87–88. http://dx.doi.org/10.5860/lrts.48n1.87.

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24

Sieverts, E. G., M. Hofstede, Ph H. Haak, P. Nieuwenhuysen, G. A. M. Scheepsma, L. Veeger, and G. C. Vis. "Software for information storage and retrieval tested, evaluated and compared Part II — Classical retrieval systems." Electronic Library 9, no. 6 (June 1991): 301–16. http://dx.doi.org/10.1108/eb045091.

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25

Volk, Daniel. "On the Phase Transition of Hopfield Networks — Another Monte Carlo Study." International Journal of Modern Physics C 09, no. 05 (July 1998): 693–700. http://dx.doi.org/10.1142/s0129183198000595.

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A Hopfield-type neural network has content addressable memory which emerges from its collective properties. I reinvestigate the controversial question of its critical storage capacity at zero temperature. To locate the discontinuous transition from good retrieval to bad retrieval in infinite systems the decreasing average quality of retrieved information is traced until it falls below a threshold. The cutoff points found for different system sizes are extrapolated towards infinity and yield αc=0.143±0.002.

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26

Shirazi, Ehsan, and Mohammad Zolghadr. "An Item Retrieval Algorithm in Flexible High-Density Puzzle Storage Systems." Applied System Innovation 4, no. 2 (June 11, 2021): 38. http://dx.doi.org/10.3390/asi4020038.

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This paper studies a design of a puzzle-based storage system. We developed an item retrieval algorithm for our system which has three advantages over the previous counterparts in the literature: (i) we can retrieve items from all sides of our storage system; (ii) the existence of only one empty cell in our system is sufficient to retrieve an item; and (iii) our algorithm never ends in deadlocks. The main feature of our algorithm is to prefer three moves to five moves in the process of moving the seized empty cell toward the optimal side of the requested item. The conventional view in the liter

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27

Lima, Gercina, and Maria Campos. "Information Storage and Retrieval System: an analysis of the impact of variables and measures aimed at the organization and retrieval of information centered on the user." RDBCI: Revista Digital de Biblioteconomia e Ciência da Informação 20, no. 2022 (January 11, 2022): 1–22. http://dx.doi.org/10.20396/rdbci.v20i00.8667925/28663.

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Introduction:The effective performance of an Information Retrieval System depends on the quality with which the organization of information is performed, which will imply a retrieval of the most relevant and pertinent information, since these procedures are conditioned to each other, creating a bridge between input and output of information. Objective:To evaluate the impact of the exhaustiveness and specificity variables and the recall and precision measures, as well as the concepts of relevance and pertinence, in Information Retrieval Systems. Methodology:It is characterized as a descriptive

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28

Bidve, Vijaykumar, Kiran Kakakde, Pakiriswamy Sarasu, Shailesh Kediya, Pradip Tamkhade, and Suprakash Sudarsanan Nair. "Patient data management using blockchain technology." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 3 (December 1, 2023): 1746. http://dx.doi.org/10.11591/ijeecs.v32.i3.pp1746-1754.

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<span>The patient data management is an essential component of healthcare systems, the secure and efficient data processing is important for the medical data. Data security, interoperability and privacy are the key requirements of data storage systems of healthcare organizations. The electronic medical records have become a key technique to maintain patient information in hospitals due to the technology revolution. Some hospital systems are also using server-based patient detail management systems, they require considerable storage to record all of the patient's medical reports, limiting

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29

Gerhold, Henry, Kim Steiner, and C. J. Sacksteder. "Management Information Systems for Urban Trees." Arboriculture & Urban Forestry 13, no. 10 (October 1, 1987): 243–49. http://dx.doi.org/10.48044/jauf.1987.051.

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The concept and applications of computerized information systems for the management of urban trees are reviewed. Among their uses are landscape planning, choosing species to be planted, organizing work on trees, departmental planning and evaluation, and public relations. Five types of data required for these purposes pertain to the location of trees, tree characteristics, site characteristics, actions recommended, and work completed. Methods for handling data are reviewed including collection, processing, storage retrieval, and updating. Computer equipment and software options are discussed, p

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30

Ohe, K., T. Sakurai, T. Nagase, S. Kaihara, and C. Wang. "Object-oriented Analysis and Design of an ECG Storage and Retrieval System Integrated with an HIS." Methods of Information in Medicine 35, no. 01 (January 1996): 35–40. http://dx.doi.org/10.1055/s-0038-1634636.

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AbstractFor a hospital information system, object-oriented methodology plays an increasingly important role, especially for the management of digitized data, e.g., the electrocardiogram, electroencephalogram, electromyogram, spirogram, X-ray, CT and histopathological images, which are not yet computerized in most hospitals. As a first step in an object-oriented approach to hospital information management and storing medical data in an object-oriented database, we connected electrocardiographs to a hospital network and established the integration of ECG storage and retrieval systems with a hosp

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31

Han, Yan. "Cloud storage for digital preservation: optimal uses of Amazon S3 and Glacier." Library Hi Tech 33, no. 2 (June 15, 2015): 261–71. http://dx.doi.org/10.1108/lht-12-2014-0118.

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Purpose – The purpose of this paper is to use cloud storage in digital preservation by analyzing the pricing and data retrieval models. The author recommends strategies to minimize the costs and believes cloud storage is worthy of serious consideration. Design/methodology/approach – Few articles have been published to show the uses of cloud storage in libraries. The cost is the main concern. An overview of cloud storage pricing shows a price drop once every one or one-and-a-half years. The author emphasize the data transfer-out costs and demonstrate a case study. Comparisons and analysis of S3

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32

Haslam, Michaelyn. "The Lied Library Automated Storage and Retrieval (LASR) Unit." Library Hi Tech 23, no. 3 (September 2005): 306–12. http://dx.doi.org/10.1108/07378830510621720.

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33

Abburu, Sunitha, and Nitant Dube. "Satellite Parametric Description to Ontology Concepts and Semantic Classification of Satellite Data." International Journal on Semantic Web and Information Systems 12, no. 2 (April 2016): 53–75. http://dx.doi.org/10.4018/ijswis.2016040103.

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Current satellite data retrieval systems retrieves data using latitude, longitude, date, time and sensor parameters like wind, cloud etc. To achieve concept based satellite data retrieval like Storm, Hurricane, Overcast and Frost etc., requires ontological concept descriptions using satellite observation parameters and concept based classification of satellite data. The current research work has designed and implemented a two phase methodology to achieve this. The phase 1 defines ontology concepts through satellite observation parameters and phase 2 describes ontology concept based satellite d

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34

Ping, Yuan, Wei Song, Zhili Zhang, Weiping Wang, and Baocang Wang. "A Multi-Keyword Searchable Encryption Scheme Based on Probability Trapdoor over Encryption Cloud Data." Information 11, no. 8 (August 12, 2020): 394. http://dx.doi.org/10.3390/info11080394.

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With the rapid development of cloud computing, massive data are transferred to cloud servers for storage and management savings. For privacy concerns, data should be encrypted before being uploaded. In the encrypted-domain (ED), however, many data computing methods working in the plain-domain are no longer applicable. Data retrieval has become a significant obstacle to cloud storage services. To break through this limitation, we propose a multi-keyword searchable encryption scheme by introducing probability trapdoors. Firstly, a keywords probability trapdoor is established to ensure that the s

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35

Deutsch, E. S. "A Review of Some Electronic Text-Document Handling, Storage and Retrieval Systems." Journal of Information Technology 1, no. 2 (June 1986): 39–45. http://dx.doi.org/10.1177/026839628600100209.

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This paper investigates some of the currently available optical disk storage and retrieval systems, image manipulation systems and OCR systems. Future developments are presented and an attempt at outlining a longer term trend is made. The main conclusions of the paper are as follows: 1. Optical disk systems which are currently available are costly and are accompanied by excessive software and hardware capabilities which might be beyond the needs of the straightforward document storage and retrieval application. A tailor-made system to suit a specific application might be the route to follow pr

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36

Pozzi, María. "Btmex." Terminology 3, no. 1 (January 1, 1996): 111–24. http://dx.doi.org/10.1075/term.3.1.06poz.

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Term banks of recent creation are characterised by being user-friendly and by providing their users with new features that facilitate the information-retrieval operation, thus making them more efficient. This paper describes BTMEX, the Term Bank of Mexico, as one of these systems. Although it shares with most term banks the storage of the same basic units of information, it offers a wide range of possibilities to retrieve this information, making it one of the most flexible term banks available.

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37

Xu, Rui, Yafang Tuo, Huimin Chen, and Jinxue Xu. "Scheduling Parallel Cranes for Unit-Load Automated Storage and Retrieval Systems with Shared Storage." Systems 12, no. 1 (December 20, 2023): 3. http://dx.doi.org/10.3390/systems12010003.

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Motivated by observing real-world instances of multi-aisle automated storage and retrieval systems (AS/RSs) with shared storage, we introduced a new optimization problem called the parallel crane scheduling (PCS) problem. Unlike the single crane scheduling (SCS) problem, the decisions of the PCS problem include not only the request sequencing and storage/retrieval location selection, but also assigning requests to cranes. The PCS problem better reflects the real-life situation, but it is more complex, since these three decisions are interrelated and interact with one another. In this study, si

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38

Chen, Li, Zhen Zhang, Jianjun Wu, Xiang Wei, and Wenyuan Bai. "Dynamic Retrieval Model of Quantitative Data of Power Grid Resources Based on 3D Geographic Information Systems (GIS)." Journal of Nanoelectronics and Optoelectronics 17, no. 2 (February 1, 2022): 344–50. http://dx.doi.org/10.1166/jno.2022.3204.

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In order to improve the efficiency of the quantitative data retrieval of power grid resources, a dynamic retrieval model of the quantitative data of power grid resources based on a three-dimensional GIS system is designed. First, the retrieval model architecture is designed based on the 3D GIS system, which is mainly composed of application architecture, technical architecture, data architecture and physical architecture. The technical architecture includes core technologies such as 3D GIS engine, index storage and retrieval applications. Secondly, the real-time daemon mode in the distributed

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39

Nieuwenhuysen, Paul. "Computerised storage and retrieval of structured text information: CDS/ISIS Version." Program 25, no. 1 (January 1991): 1–18. http://dx.doi.org/10.1108/eb047073.

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40

Ma, Yung-Cheng, Chung-Ping Chung, and Tien-Fu Chen. "Load and storage balanced posting file partitioning for parallel information retrieval." Journal of Systems and Software 84, no. 5 (May 2011): 864–84. http://dx.doi.org/10.1016/j.jss.2011.01.028.

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41

Rexwhite Enakrire, Tega, and E. Emmanuel Baro. "Patterns of Information Storage and Retrieval in University Libraries in Nigeria." Library Hi Tech News 25, no. 1 (January 25, 2008): 19–26. http://dx.doi.org/10.1108/07419050810877526.

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42

Deutsch, E. S. "A Review of Some Electronic Text-Document Handling, Storage and Retrieval Systems." Journal of Information Technology 1, no. 2 (June 1986): 39–45. http://dx.doi.org/10.1057/jit.1986.22.

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43

Wei, Yi-Peng, and Sennur Ulukus. "The Capacity of Private Information Retrieval With Private Side Information Under Storage Constraints." IEEE Transactions on Information Theory 66, no. 4 (April 2020): 2023–31. http://dx.doi.org/10.1109/tit.2019.2953883.

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44

Tajeddine, Razane, Oliver W. Gnilke, David Karpuk, Ragnar Freij-Hollanti, and Camilla Hollanti. "Private Information Retrieval From Coded Storage Systems With Colluding, Byzantine, and Unresponsive Servers." IEEE Transactions on Information Theory 65, no. 6 (June 2019): 3898–906. http://dx.doi.org/10.1109/tit.2018.2890285.

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45

Abburu, Sunitha, and Suresh Babu Golla. "Ontology Storage Models and Tools: An Authentic Survey." Journal of Intelligent Systems 25, no. 4 (October 1, 2016): 539–53. http://dx.doi.org/10.1515/jisys-2014-0167.

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AbstractOntology is a formal, explicit specification of a shared conceptualization. Ontology provides domain vocabulary, domain knowledge, common understanding, shareability, information interoperability, reusability, concept hierarchy, and relationships that support semantic information retrieval. Ontology improves performance of the system by addressing interoperability issues due to semantic and syntactic heterogeneity. Vast numbers of application domain experts are using ontologies in diverse applications. Use of effective and efficient ontology storage system results improved performance

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46

Imanbekova, A. N. "Development of an information system of a medical institution." Mechanics and Technologies, no. 4 (December 30, 2023): 140–48. http://dx.doi.org/10.55956/zcgt6039.

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This article discusses the issues about Information technology (IT) is the research, design, development, implementation, maintenance or management of Computer Information Systems, in particular software applications and computer hardware. Information Technology Association. It deals with the use of electronic computers and computer software tools for the safe Conversion, Storage, Protection, processing, transmission and retrieval of information.

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47

Rahmawati, Yuli. "Digital Preservation of Photo Journalism (Case Study of the Kompas Daily)." Record and Library Journal 1, no. 2 (January 2, 2017): 183. http://dx.doi.org/10.20473/rlj.v1i2.1170.

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Newspaper provides many information from politics, economics, cultures, and sports for society. Newspaper reports important events in the world. Besides the news, there also some pictures portraying those events. So readers will easilly to see what happen visually. According to the journalistic concept, photos has comply as a reference source. Kompas daily, firstly published on 1965, and published many historical photos both paper and digital format. The digitize process is done by kompas information center, through scanning, indexing, and syncronizing. Two most important issues are standardiz

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48

Kanet, John J., and Richard Gonzalo Ramirez. "Optimal stock picking decisions in automatic storage and retrieval systems." Omega 14, no. 3 (January 1986): 239–44. http://dx.doi.org/10.1016/0305-0483(86)90043-5.

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49

Hessler, David. "InfoStation: A Low‐Cost Electronic Document Storage, Retrieval, and Transmission System." Library Hi Tech 5, no. 1 (January 1987): 81–86. http://dx.doi.org/10.1108/eb047682.

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50

Chou, Shih-Wei. "Knowledge creation: absorptive capacity, organizational mechanisms, and knowledge storage/retrieval capabilities." Journal of Information Science 31, no. 6 (December 2005): 453–65. http://dx.doi.org/10.1177/0165551505057005.

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